A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Background: Interleukine-2 is a multifunctional cytokine, considered a central regulator of host resistance against a variety of pathogens and has been recently demonstrated to exert an active role in the pathogenesis of periodontal diseases. The purpose of this study was to evaluate the effect of scaling and root planning on level of IL-2 in serum and saliva of patients with chronic generalized periodontitis, in relation to clinical parameters. Materials and Methods: A total of 50 subjects were enrolled, of which 25 had chronic generalized periodontitis and 25 periodontally healthy subjects as control. The clinical parameters included: gingival index, pocket probing depth, clinical attachment level and bleeding on probing. The level of

Background: overweight and obesity are the fifth leadingrisk for global deaths. At least 2.8 million adults die eachyear as a result of being overweight or obese. Numerousstudies show that weight loss, even if only 5-10%,significantly improves dyslipidemia, hypertension, diabetesmellitus, risk for osteoarthritis and its symptoms and risk forselected cancers.Objectives: is to evaluate the effect of diet and exerciseprogram on anthropometric and biochemical status of adultobese patients.Methods: descriptive study. 124 adult obese patientsattending Al Kindy obesity research and therapy unit duringDecember 2012 were included. Measurement of Wt, heightHt and WC performed and BMI was calculated. Laboratorytest analysis, on the fasting state, w

This research dealt with the modern dengue living in its linguistic meaning and where this dengue will be, and its cause and treatment, then concluded the talk about the search with the results envisaged from this research, has been shown that the main reason in living dengue: is after the slave of the book of God and the Sunnah of the Prophet peace be upon him Him.

Brachytherapy treatment is primarily used for the certain handling kinds of cancerous tumors. Using radionuclides for the study of tumors has been studied for a very long time, but the introduction of mathematical models or radiobiological models has made treatment planning easy. Using mathematical models helps to compute the survival probabilities of irradiated tissues and cancer cells. With the expansion of using HDR-High dose rate Brachytherapy and LDR-low dose rate Brachytherapy for the treatment of cancer, it requires fractionated does treatment plan to irradiate the tumor. In this paper, authors have discussed dose calculation algorithms that are used in Brachytherapy treatment planning. Precise and less time-consuming calculations

This study investigates the results of electrocoagulation (EC) using aluminum (Al) electrodes as anode and stainless steel (grade 316) as a cathode for removing silica, calcium, and magnesium ions from simulated cooling tower blowdown waters. The simulated water contains (50 mg/l silica, 508 mg/l calcium, and 292 mg/l magnesium). The influence of different experimental parameters, such as current density (0.5, 1, and 2 mA/cm²), initial pH(5,7, and 10), the temperature of the simulated solution(25⁰C and 35 ⁰C), and electrolysis time was studied. The highest removal efficiency of 80.183%, 99.21%, and 98.06% for calcium, silica, and magnesium ions, respectively, were obtained at a current de

Synthetic anti-TB drugs are being used to treat tuberculosis (TB) as they are effective, however, they are accompanied by many side effects. The disease has remained largely uncured till date. The use of plant extracts or phytochemicals along with the anti-TB drugs is a very attractive strategy to make the treatment more effective as phytochemicals have no side-effects, are much less toxic than synthetic anti-TB drugs, are safe to use and most importantly, do not produce resistant strains as opposed to synthetic anti-TB drugs. Approximately 420,000 plant species have been identified globally and among them only a few have been explored for their therapeutic potential. Traditional medicine in different parts of the world has employed crud

         This study was designed to show the advantages of using the combination of metformin and rosiglitazone over using each drug alone in treatment of women with polycystic ovary syndrome (PCOS).Forty four women with PCOS were classified into 3 groups , group 1 received rosiglitazone (4mg/day) for 3 months , group ΙΙ received metformin ( 1500 mg/day)for three months and groupΙΙΙ received the combination ( rosiglitazone 4mg/day + metformin 1500 mg/day) for the same period of treatment   . The blood samples were drawn before treatment and after 3 months of treatment . The fasting serum glucose , insulin , progesterone , testosterone , leutinizing hormone were measure