In this work, we discuss a third order of accuracy difference scheme for approximate solution of the elliptic overdeter-mined multi-point problem in the Hilbert space. Functional operator approach is used to study exi...
In this work, we discuss a third order of accuracy difference scheme for approximate solution of the elliptic overdeter-mined multi-point problem in the Hilbert space. Functional operator approach is used to study existence and uniqueness of solution of difference problem. Stability, almost coercive stability and coercive stability estimates for solution of difference scheme are established.
A stepped forward E-Passports with IoT devices assumes an essential element in momentum research. Additionally, getting the data, placed away on E-Passport is also an essential difficulty. In this paper, we've got...
A stepped forward E-Passports with IoT devices assumes an essential element in momentum research. Additionally, getting the data, placed away on E-Passport is also an essential difficulty. In this paper, we've got proposed a stepped forward far- off E-Visa framework with simple stage protection. The number one aim of this advanced system is to devise and foster an excessive stage tremendous far-off identity and Savvy card which conveys the identity subtleties and visa limits. Radio Frequency Identification (RFID) is a programmed ID innovation this is using Radio recurrence signals. Utilizing RFID labels as opposed to identity and visa information to conquer the paper works and document lacking difficulty with IoT devices improvements the superior protection highlights of an identity. Also, this advanced system provides high level security in customer information storage.
The authors would like to add one affiliation for two of the authors of the original version of the published article.1 Affiliation to the department of Physics
The authors would like to add one affiliation for two of the authors of the original version of the published article.1 Affiliation to the department of Physics
Several chemicals are dangerously injurious to the breathing system of human being and so, the exact diagnosis of the pernicious chemicals is essential. Therefore, we present a PCF sensor to detect these pernicious ch...
Several chemicals are dangerously injurious to the breathing system of human being and so, the exact diagnosis of the pernicious chemicals is essential. Therefore, we present a PCF sensor to detect these pernicious chemicals such as Sarin, Soman, Tabun and in this work, Zeonex is considered as bulk material. The COMSOL Multiphysics V-5.5 is used to design and analysis of the sensor model and the investigation of the proposed sensor’s performance is accomplished by shifting the terahertz frequency. We have found that relatively enhanced sensitivity (almost 90.93%, 92.39%, and 94.12 % for Sarin, Soman, and Tabun at 2.5 THz) with negligible light confinement loss (around 1.043e×10-14 cm-1, 7.62×10−15 cm−1, and 6.15×10-15 cm-1 for Sarin, Soman, and Tabun at 2.5 THz) is achieved by the sensor which the foremost requirement to provide the best performance by any biosensor or chemical sensor. Besides, the existing modern fabrication technologies can be applied to fabricate the sensor.
The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. The focus of this paper is on the role of the SCI...
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The cancer death in concern to lung cancer is increased compared to other cancers worldwide. The presence of nodules in the lung indicates the chances of getting lung cancer in the future. In this paper, an accurate C...
The cancer death in concern to lung cancer is increased compared to other cancers worldwide. The presence of nodules in the lung indicates the chances of getting lung cancer in the future. In this paper, an accurate computer-Aided Detection (CAD) system for lung nodules detection using computer Tomography (CT) images is proposed. It consists of four important modules such as preprocessing; Two-Successive Segmentation Process (TS2P), Rule-Based Refinement Pass (RBRP), and Detection Module (***). The lung C.T. CT image is de-noised using the Wiener filter in the preprocessing module. In the TS2P module, the right and left lungs are segmented at first, and in the next stage, the nodules and vessels are segmented. Then, the RBRP module is designed to remove the vessels with the help of geometrical features. Finally, the nodules are detected using a deep learning approach in the ***. The proposed method is validated on 888 lung *** images, and a mean average precision of 96.75% and sensitivity of 97% with 2 false positives per image were obtained.
Radioactive 137Cs has a great concern because of its long half-life (30.2 year) and its similarity to potassium which is an essential element for humans. It is well known that Cs is distributed in surface soils or spe...
Radioactive 137Cs has a great concern because of its long half-life (30.2 year) and its similarity to potassium which is an essential element for humans. It is well known that Cs is distributed in surface soils or specifically adsorbed on illicit clay minerals and finally enters to organisms. 137Cs is made through nuclear accidents and processes is an example of anthropogenic radionuclides. In the present work, 137Cs specific activity concentration is measured with a high efficiency gamma ray spectroscopy NaI(Tl) detector in fly ash samples from two thermal electric power stations in the south of Iraq (Al-Naserya and Al-Musaeb). The 137Cs specific activity concentration are founded with ranges from 20±4.8 Bq kg-1 to 120±27.6 Bq kg−1 at Al-Naserya and 17±4.4 Bq kg-1 to 86±19.8 Bq kg−1 at Al-Musaeb station. Some of these values are alerted us to take care about the received dose because these concentrations are higher than background and world-wide limit (37 Bq kg-1 From UNSCEAR). Also, the presented 137Cs specific activity concentration results point out an additional shot to the measured effective dose rate, which can be predicted to be the 137Cs and cosmic radiation. By accounting for the contribution of 137Cs in the estimated absorbed dose rate, applying the conversion coefficient 0.136 (nGy h−1 per Bq kg−1). If a human inhale the air every day for 70 years, the radiation dose must be less than the dose limit (1 mSv y−1). In case 137CS is present, the criterion is the activity of 137Cs /60≦1.
A brain tumor, the cause of more death rate among all cancers, is diagnosed using uncontrollable cell growth and abnormal brain cell partitioning. The recent progress in Deep Learning (DL) neural network technology ai...
A brain tumor, the cause of more death rate among all cancers, is diagnosed using uncontrollable cell growth and abnormal brain cell partitioning. The recent progress in Deep Learning (DL) neural network technology aids the health service department in medical imaging diagnose several death-causing diseases. The visual learning of image recognition manually may result in fault detection and can be overcome by the most prevalent task of machine learning. In our paper, the Convolutional Neural Network (CNN) model is designed with data augmentation and image processing techniques to identify the brain MRI scan images into cancerous or non-cancerous and classify various brain tumor types. The performance comparison of our proposed CNN model uses the Transfer Learning (TL) method. With a very small dataset, the experimental result shows that our model is very effective at low computational power with less complexity and achieves better accuracy compared to an existing model.
The newer avid-19 corona virus created havoc for patients with a variety of complications that prompted health practitioners around the world to develop new technologies and treatment plans. Technologies based on Mach...
The newer avid-19 corona virus created havoc for patients with a variety of complications that prompted health practitioners around the world to develop new technologies and treatment plans. Technologies based on Machine Learning (ML) have been a major factor in addressing complex issues and many businesses have been able to develop and adapt to the COVID-19 challenges. The diagnosis of illness can be used with different AI methods to monitor the present havoc. Since Machine Learning (ML) approaches have been commonly used in other domain fields, a great deal of demand is now being made for ML-supported diagnostic systems to screen, monitor, and forecast void-19 spread and find a cure. The article presents an overview of the role of ML to combat the virus so far, especially from the perspective of screening, prognosis, and vaccine.
This paper reviews the complex task problems which are out of reach for a simple machine. So, there is a need for a solution for such a problem, so the solution is Reinforcement Learning with deep Q-Network. Reinforce...
This paper reviews the complex task problems which are out of reach for a simple machine. So, there is a need for a solution for such a problem, so the solution is Reinforcement Learning with deep Q-Network. Reinforcement learning techniques are now being researched for their applicability in a wide range of situations. Perhaps because of the rising complexity and unpredictability in the generation and distribution sector of power systems, traditional approaches frequently encounter congestion while attempting to handle decision and control issues that are out of reach for a basic machine. Deep Reinforcement Learning (DRL) is one of these data-driven approaches that is considered true Artificial Intelligence (AI). DRL is a hybrid of Deep Learning (DL) and Reinforcement Learning (RL). Our study examines the fundamental concepts, models, methods, and approaches of DRL. It also presents power system applications such as smart grids, energy management, demand response, the electricity market, operational control, and many others. Furthermore, current advancements in DRL, the coupling of RL with other classical techniques, and the prospects and problems of its applications in the power system are explored.
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