The Improvement of Automatic Skin Cancer Detection Algorithm Based on CVQ technique

Nowadays, by increasing the number of deaths related to skin cancer, this kind of cancer has been converted as one of the important issues in humans' life. However, the main key is early detection of skin cancer in order to save the life of people. By considering this fact that there is a near similarity between cancer moles and normal ones, attention to artificial systems with the ability of distinguishing between these kinds of moles can be very important, undoubtedly. The accuracy of this kind of system must be considered in order to find better results, especially in the cases which are related to human‘s life. In this paper, with regard to the fact that the raising of a kind of skin cancer, Melanoma, has increasing, we have employed neural networks in the aim of function improvement of an approach based on compressed image technique, namely, Classified Vector Quantization (CVQ) technique. This suggested method has been examined on some images and the results show that this method is a proper way in order to automatic skin cancer detection

The Improvement of Automatic Skin Cancer Detection Algorithm Based on CVQ technique

Nowadays, by increasing the number of deaths related to skin cancer, this kind of cancer has been converted as one of the important issues in humans' life. However, the main key is early detection of skin cancer in order to save the life of people. By considering this fact that there is a near similarity between cancer moles and normal ones, attention to artificial systems with the ability of distinguishing between these kinds of moles can be very important, undoubtedly. The accuracy of this kind of system must be considered in order to find better results, especially in the cases which are related to human‘s life. In this paper, with regard to the fact that the raising of a kind of skin cancer, Melanoma, has increasing, we have employed neural networks in the aim of function improvement of an approach based on compressed image technique, namely, Classified Vector Quantization (CVQ) technique. This suggested method has been examined on some images and the results show that this method is a proper way in order to automatic skin cancer detection

Long and Short-term Metformin Consumption as a Potential Therapy to Prevent Complications of COVID-19

Purpose: The aim of the study is to evaluate the effect of metformin in complication improvement of hospitalized patients with COVID-19. Methods: This was a randomized clinical trial that involved 189 patients with confirmed COVID-19 infection. Patients in the intervention group received metformin-500 mg twice daily. Patients who received metformin before admission were excluded from the control group. Patients who were discharged before taking at least 2000 mg of metformin were excluded from the study. Primary outcomes were vital signs, need for ICU admission, need for intubation, and mortality. Results: Data showed that patients with diabetes with previous metformin in their regimen had lower percentages of ICU admission and death in comparison with patients without diabetes (11.3% vs. 26.1% (P=0.014) and 4.9% vs. 23.9% (P≤0.001), respectively). Admission time characteristics were the same for both groups except for diabetes and hyperlipidemia, which were significantly different between the two groups. Observations of naproxen consumption on endpoints, duration of hospitalization, and the levels of spO2 did not show any significant differences between the intervention and the control group. The adjusted OR for intubation in the intervention group versus the control group was 0.21 [95% CI, 0.04-0.99 (P=0.047)]. Conclusion: In this trial, metformin consumption had no effect on mortality and ICU admission rates in non-diabetic patients. However, metformin improved COVID-19 complications in diabetic patients who had been receiving metformin prior to COVID-19 infection, and it significantly lowered the intubation rates

Static and Fatigue Behaviour of Hybrid FRP-Concrete Bridge Truss Girder with Connections Reinforced with Double-Headed Bars

An innovative hybrid FRP-concrete bridge system for short- and medium-span bridges has been developed at the University of Calgary. This system is composed of concrete deck slabs composite with precast prestressed concrete truss girders, consisting of pre-tensioned top and bottom chords connected by vertical and diagonal truss members made of concrete-filled fiber-reinforced polymer tubes. The advantages of this system include reduced self-weight and enhanced durability. The objective of this research is to investigate the performance of the truss girder under static and fatigue loading. An experimental program including fabrication of ten full-scale truss girders with the number of panels varying from two to eight is presented. The effect of several parameters, such as the span-to-depth ratio and the amplitude of fatigue loading on the performance of the truss girder are investigated. The tests showed excellent performance of the girder system in terms of strength and stiffness.2 year

Reference-Free Response-Only Damage Identification in Bridges Using Relative Wavelet Entropy

Bridges are designed and built to be safe against failure and to perform satisfactorily over their service life. To ensure safety and serviceability, it is essential to evaluate the structural performance of bridges through identification of potential damage at the earliest time possible. A vibration-based damage identification technique (DIT) that can detect structural damage, determine its location, and estimate its severity has been investigated in this research. The technique combines discrete wavelet transform (DWT) – a powerful signal processing tool for decomposition of signals – and spectral entropy in a relative procedure to detect and quantify the damage-induced disturbances in the measured dynamic response of bridges under ambient vibration. This relative wavelet entropy (RWE)-based DIT is a practical means for damage identification in in-situ cases, where the normal operation of bridges cannot be interrupted to perform dynamic excitation tests, and the data obtained from a reference (undamaged) state of the bridges are not available for comparison with the data measured from their current (damaged) state. Through its relative procedure, the technique has the advantage of mitigating undesirable effects of varying operational and environmental conditions on the damage detection process. In this research, the theoretical bases of the technique are presented, and its efficacy has been experimentally validated against false damage indications under varying operational and environmental conditions, such as the location of input dynamic excitation, location and extent of damage, support conditions, and temperature levels. The technique has also been implemented in small- and large-scale bridge specimens of various structural systems tested under different loading conditions. The test specimens included push-off columns, reinforced concrete beams, strengthened beams, precast concrete truss girders, slab-on-truss girder bridges, and post-tensioned concrete girders. The RWE-based DIT showed successful performance in identifying a wide variety of test-induced damage, including fracture in shear reinforcement, concrete cracking/crushing, debonding of strengthening sheets, rupture of truss elements’ confining tubes, and failure in truss connections. The technique has also been used to investigate the effects of pre-stressing on the dynamic behaviour of post-tensioned concrete girders to address the disagreement in the research community about the effectiveness of vibration-based DITs in pre-stress force identification

Human-Robot Collaboration Using Fuzzy Adaptive Virtual Fixture Method for Dental Implant Surgery

The purpose of this work is to develop a methodology to improve human-robot collaboration for robot-aided dental implant placement. In this study, a human-robotic implant system (HRIS) is designed according to a hand-guiding control to increase the accuracy and stability of osteotomy drilling based on the surgeon's decision, and robot motion during the implant placement. The proposed method is able to guide the surgeon's hand according to the pose of the desired placement. To guide and modify the pose of the surgeon's hand, the virtual fixture method is used as the main control approach. To verify the performance of the introduced method, the KUKA MED robot is used to perform the dental implant placement using the presented approach on a phantom head with a 3D jaw bone model. Additionally, the results between free-hand drilling and HRIS controlled drilling according to the apical center and head center of the implant placement are compared to evaluate the performance of the introduced method