A Review on Skin Disease Classification and Detection Using Deep Learning Techniques

Skin cancer ranks among the most dangerous cancers. Skin cancers are commonly referred to as Melanoma. Melanoma is brought on by genetic faults or mutations on the skin, which are caused by Unrepaired Deoxyribonucleic Acid (DNA) in skin cells. It is essential to detect skin cancer in its infancy phase since it is more curable in its initial phases. Skin cancer typically progresses to other regions of the body. Owing to the disease's increased frequency, high mortality rate, and prohibitively high cost of medical treatments, early diagnosis of skin cancer signs is crucial. Due to the fact that how hazardous these disorders are, scholars have developed a number of early-detection techniques for melanoma. Lesion characteristics such as symmetry, colour, size, shape, and others are often utilised to detect skin cancer and distinguish benign skin cancer from melanoma. An in-depth investigation of deep learning techniques for melanoma's early detection is provided in this study. This study discusses the traditional feature extraction-based machine learning approaches for the segmentation and classification of skin lesions. Comparison-oriented research has been conducted to demonstrate the significance of various deep learning-based segmentation and classification approaches

Parallel Processing for Range Assignment Problem in Wireless Sensor Networks

Wireless sensor network is a collection of autonomous devices called sensor nodes which sense the environmental factors such as temperature, pressure, humidity, moisture, etc. The nodes sense the data, process it and transmit to the other nodes within their transmission range through radio propagation. Energy minimization in wireless sensor networks is a significant problem since the nodes are powered by a small battery of limited capacity. In case of networks with several thousand nodes, the simulation of algorithms can be very slow. The parallel computing model provides significantly faster simulation time for larger networks. Parallel processing involves executing the program instructions by dividing them among multiple processors with the objective of reducing the running time. So, we propose algorithms for the range assignment problem in wireless sensor networks using the parallel processing techniques. We also discuss the complexity of the proposed algorithms and significance of the parallel processing techniques in detail. The proposed techniques will be useful for implementing the distributed algorithms in WSNs

A novel validated RP-HPLC method for the estimation of canagliflozin in bulk and pharmaceutical dosage forms

The objective of the present study was to develop a simple, specific and accurate reverse phase high performance liquid chromatographic method for the determination of Canagliflozin in bulk and pharmaceutical dosage forms. The method is optimized on an inertsil ODS-3(250.6mm, 5) column with a mobile phase combination of 0.02% Formic acid: Acetonitrile (40:60) at a flow rate 1.2ml/min and the eluents were monitored at 230nm. Under these LC conditions Canagliflozin peak was eluted at 4.4 min. The developed method was validated as per ICH guidelines. The calibration curve was linear over a concentration range of 10-50g/ml (R 2 =0.999) and the mean percentage assay was found to be 98.2. The statistical data proved that proposed method is accurate, precise and reproducible. The method which is LC-MS compatible can be adopted in the routine analysis of Canagliflozin in bulk and pharmaceutical dosage forms

Antimicrobial Activity of Suaeda monoica (Forsst ex Geml) against Human and Plant Pathogens

ABSTRACT Antimicrobial activity of the halophyte Suaeda monoica (Forsst ex Geml) was studied using leaf and shoot extracts, on the various test microorganisms, including multiple antibiotic resistant bacteria and phytopathogens. Antimicrobial activity of the extracts was determined by the Well Diffusion Method. The experimental results concluded that the hexane, methanol and water extracts of S. monoica leaves have greater potential as antimicrobial compounds against microorganisms and they can be used in the treatment of infectious diseases caused by resistant pathogenic microorganisms

EVALUATION OF THE PROPHYLACTIC ROLE OF INDIAN SHRIMP IN ALUMINUM CHLORIDE-INDUCED ALZHEIMER’S DISEASE ON EXPERIMENTAL RATS

Objective: This work was aimed to investigate the prophylactic and therapeutic role of Indian shrimp in aluminum chloride-induced Alzheimer’s disease (AD) in rats. Methods: The male Wistar rats were selected and divided into six groups. Group I received distilled water, Group II received AlCl3 ( 100 mg/kg, p.o.), Group III received rivastigmine (1 mg/kg, p.o.), Group IV received AlCl3 + shrimp powder (200 mg/kg, p.o), and Group V received AlCl3 + shrimp powder (400 mg/kg, p.o) for 60 days. At the end of the study, various parameters such as behavioral and biochemical investigations were assessed. Results: The result of the study shows that the shrimp (400 mg/kg) has better effect on the treatment of aluminum chloride-induced AD in rats. It showed a remarkable improvement in the behavioral and biochemical parameters, and the result of histopathology study shows that the hippocampus region of brain tissue recovered as compared with control. Conclusion: From this study, it is evident that dietary intake of shrimp can help to inhibit oxidative stress produced due to the accumulation of AlCl3 in the brain and used as a prophylactic for AD

A CASE REPORT ON CHRONIC LEAD POISONING FROM OCCUPATIONAL EXPOSURE

The hazard to public health from lead continues to be a matter of concern. It is one of the most serious environmental poisons among the toxic heavy metals all over the world. Lead poisoning is seen in all age groups, especially in adults working in lead-based industries. We report the case of a 28-year-old man working in an unorganized lead-based manufacturing unit admitted with the complaints of giddiness, excessive tiredness, pain in the upper abdomen, decreased appetite, excessive body pains, increased sweating, and oliguria. Investigations carried out during the admission showed hemoglobin levels of 8.5 g/dl and blood lead level (BLL) of 115 μg/dl. The patient was subjected to chelation therapy. After repeated course of chelation therapy, he has shown the signs of improvement. The paucity of a safe workplace and awareness among workers results in high BLLs. Therefore, education and awareness related to lead hazards is considered necessary

Improved Mca Based Dos Attack Detection

A denial of service (DoS) attack is a malicious attempt to make a server or a network resource unavailable to users, usually by temporarily interrupting or suspending the services of a host connected to the Internet Interconnected systems, such as Web servers, database servers, cloud computing servers etc, are now under threads from network attackers. As one of most common and aggressive means, Denial-of-Service (DoS) attacks cause serious impact on these computing systems. In this paper, we present a DoS attack detection system that uses Multivariate Correlation Analysis (MCA) for accurate network traffic characterization by extracting the geometrical correlations between network traffic features. Our MCA-based DoS attack detection system employs the principle of anomaly-based detection in attack recognition. This makes our solution capable of detecting known and unknown DoS attacks effectively by learning the patterns of legitimate network traffic only. Furthermore, a triangle-area-based technique is proposed to enhance and to speed up the process of MCA. The effectiveness of our proposed detection system is evaluated using KDD Cup 99 dataset, and the influences of both non-normalized data and normalized data on the performance of the proposed detection system are examined. The results show that our system outperforms two other previously developed state-of-the-art approaches in terms of detection accuracy

Formulation, evaluation & comparison of traditional poly herbal shampoo powders with marketed formulation

The aim of present work is to formulate poly herbal powder by using different natural herbs like Aswagandha, Tulsi, Ginger, Hibiscus, Aloe vera, Amla and Soap nut to have safety and effectiveness which can avoid toxic effects by chemical ingredients and prepared formulations were compared with marketed poly herbal shampoo. Prepared formulation strengths hair growth, prevents hair fall, dandruff and also acts as antibacterial conditioner and foaming agent without affecting or damaging hair. All the herbs have been selected to formulate poly herbal traditional shampoo powder on the basis of traditional system with scientific modern uses of poly herbs. In this present work herbs like Aswagandha, Tulsi, Ginger, Hibiscus, Aloe vera, Amla and Soap nut were collected, dried, powdered and sieved by passing through sieve no.60, stored in an air tight container and used for further formulation. Then the powders were formulated into four different formulations namely F1, F2, F3, F4 and evaluated for their organoleptic properties like color, odor and texture etc., General powder characteristics like angle of repose, bulk density and true density etc. and physiochemical properties like pH, moisture content, total ash contents, acid insoluble ash, other parameters evaluated were dirt dispersion and foaming capacity. All the four formulations offered good results in all the evaluation tests. The organoleptic characteristics were found to be good, general powder characteristics results were in specified limits and physicochemical evaluation like pH, foaming action, Dirt dispersion were found to yield good satisfactory results. So, the present work successfully formulated poly herbal traditional shampoo powder which meets the modern uses of hair without causing any damage to both skin and hair. Further the Scope of work need to be extended to carry out the stability studies.  Keywords: Poly herbal, Traditiona