International Journal on Recent and Innovation Trends in Computing and Communication
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Skin Cancer Detection in Deep Learning Using Restnet-50 Model
Get PDFPore and skin cancers are one of the riskiest types of cancer. DNA is a type of nucleic acid. Breaks in skin cells that do non get fixed cause genetic flaws or mutations in the skin, which is how skin malignancies develop. Pores and skin cancers have the inclination to step by step spread over different bits components, so i curable in initial ranges, which is why it's far more peasant to detect at early ranges. Due to the increased prevalence of skin cancer, its high mortality rate, and the high price of medical treatments, it is crucial to understand the early warning studies signs of skin cancer. Due to the importance of these issues, researchers take created a variety of primary detection techniques for skin and pore cancers. The characteristics of a lesion include its symmetry, colouring, duration, form, and so on. Are used to discover most cancers and differentiate benign pores and skin cancers from most cancers. This paper gives an in-depth systematic overview of deep studying techniques for detecting pores and skin cancer early. Study papers posted popular nicely-reputed periodicals, appropriate toward the problem of pores and pores and skin most cancers diagnosis had been analysed. Study results are provided in equipment, charts, stands, strategies, as well as models for higher data
An Automated Irrigation System for Smart Agriculture Using the Internet of Things
Get PDFWater is a valuable but limited agriculture resource, and it is becoming harder to manage it efficiently. This paper discusses a system of an automated irrigation that integrates the cloud computing, tools, and IoT (Internet of Things) for optimization in order to reduce water usage in the agriculture. Low-cost sensors have been utilized by the automated irrigation system to monitor important factors like soil type, pH, soil moisture, and meteorological conditions. For information storage & analysis, the data is kept in the Thing speak cloud service. The field data is sent to the cloud by utilizing the networks of GSM cellular as well as a Wi-Fi modem. Subsequently, using an optimization model, the ideal irrigation rate is determined. This rate would then be automated by utilizing a solenoid valve & regulated by an ARM controller (WEMOS D1). The essential variables are available to farmers as a cloud-based service. When the recommended approach is used in a pilot-scale agricultural operation, our findings show a decrease a water use, a rise in the amount of data available, and better imagining
An Intelligent Controller for the Signal Generation of Solar Energy and Battery Storage Supported Multi-Level UPQC
Get PDFThis study examines, the solar power and battery energy storage associated diode clamped five-level unified Power quality conditioner (5L-UPQC) to handle the PQ related problems. To eliminate the requirement of the complex transformations like abc, dq0, ?? , the ANN based control scheme with LMBP training method is adopted for the 5L-UPQC to produce the necessary reference signals for the voltage source converters (VSC’s). The prime goal of the proposed scheme is to maintain stable DLCV during load shifting, reduction of THD. In addition, the grid voltage distortions like sag, disturbance and swell were eliminated. The suggested method was demonstrated on two cases with several permutations of loads. However, to reveal the performance of the developed method, the comparison is carried out with the PIC and SMC
Design a New Neural Network Architecture Using a Layer of Neurons
Get PDFNowadays there are many different models of artificial neural networks. The difference between these models lies in the learning methods only, that is, in the rules for changing the parameters of the algorithm tuning, with or without links and side comments. While studying the general framework of network models, we see that the rules for obtaining the result and the mechanism for calculating the error can differ. For example, a multilayer realization might produce a threshold function when used as a classifier, or a linear function if used as an internal typeface.
Where this research came to discuss the possibilities of the standard representation of some models of artificial neural networks, which clarify and treat some of the characteristics of that representation. Which can be considered an essential element in the process of typical representation of these networks, where a new proposal is made during this representation by using a “layer” of neurons, in other words, using a group of neurons that work in parallel and perform the same functions for which they were set
Emerging Therapies in Retinal Diseases: From Gene Therapy to Stem Cell Interventions
Get PDFRetinal disorders pose a serious threat to eye health as they frequently result in blindness and reduced vision. There is hope that the treatment of many illnesses will be revolutionised by emerging medicines, especially gene therapy and stem cell approaches. This study explores the current state of these innovative therapies and how they could affect retinal disorders. By replacing or repairing damaged genes, gene therapy, which uses precise genetic modification, shows promise in treating hereditary retinal problems. Clinical trials have yielded promising results, including improvements in visual function and optimism for patients with illnesses such as choroideremia and Leber congenital amaurosis. Regenerative approaches are provided by stem cell therapies, which restore damaged retinal tissues. Numerous stem cell varieties, including as embryonic and induced pluripotent stem cells, show promise in preclinical research and early-stage clinical trials, suggesting that cell replacement techniques may be a viable means of recovering vision. On the other hand, effective delivery, long-term safety, and ethical issues provide obstacles on the path to clinical application. To fully realise the transformational potential of these medicines, it is imperative to address these obstacles. There is potential for improved visual outcomes, targeted therapies, and personalised care as gene therapy and stem cell interventions advance. These developments highlight the promising future of treating retinal illnesses
Liquid Biopsies in Oncology: Revolutionizing Cancer Diagnosis and Monitoring
Get PDFOncology has been transformed by liquid biopsies, which offer non-invasive techniques for cancer detection and tracking. This article examines how circulating tumour cells (CTCs), extracellular vesicles (EVs), cell-free DNA (cfDNA), circulating microRNAs (miRNAs), and their therapeutic uses might revolutionise cancer therapy. CTCs provide information on tumour heterogeneity and metastatic potential since they are excreted from primary or metastatic tumours. Released by necrotic or apoptotic tumour cells, cfDNA is a genetically altered material that helps track the effectiveness of therapy. EVs, which are made up of microvesicles and exosomes, are capable of carrying cancer biomarkers and transferring biomolecules. Stable in circulation, miRNAs show dysregulation in cancer and are therefore useful indicators for both diagnosis and prognosis.
Clinical uses include tracking illness development, evaluating treatment response, and early identification. Early therapies are made possible by the diagnosis of minimal residual illness by liquid biopsies. Therapeutic decisions are guided by real-time monitoring of treatment response, and dynamic evaluations facilitate the development of individualised treatment plans.
Technical difficulties, problems with standardisation, concerns with cost-effectiveness, and difficulties interpreting data are among the challenges. The development of technology, its incorporation into clinical practice, personalised medicine, the identification of biomarkers, and cooperative efforts to overcome obstacles are the main focuses of future directions
Updates in Dermatopathology: Emerging Trends in Diagnosis and Classification
Get PDFDevelopments in dermatopathology are transforming clinical practice profoundly by constantly changing disease categorization and diagnostic methods. This review highlights key developments that have shaped modern dermatopathology, including the use of digital pathology, artificial intelligence (AI) applications, changing categorization schemes, and molecular profiling. By using methods such as next-generation sequencing, molecular profiling clarifies complex genetic changes that underlie skin conditions, enabling accurate diagnosis and focused treatment plans. Digital pathology systems are transforming the field of diagnostics through the provision of remote consultations, cooperation, and improved diagnosis accuracy. Artificial intelligence (AI) applications show promise in automating picture processing, improving diagnosis accuracy, and optimising workflow. Molecular, histological, and clinical data are integrated via evolving classification systems, which improve disease categorization and prognostication. The synergy of knowledge created by interdisciplinary interactions between dermatologists, pathologists, technologists, and molecular biologists promotes holistic approaches to patient treatment and disease understanding. When taken as a whole, these discoveries represent a paradigm change in dermatopathology, opening the door to applications in precision medicine and individualised patient care
Evaluation of Lung Function by Spirometry in Textile Mill Workers
Get PDFBackground: In present scenario industrialization is growing at a faster rate throughout the world in developed as well as developing countries. Occupational lung disease is becoming one of the major problem in occupational health. Many environmental problems are associated with textile industry such as water pollution, noise pollution, soil pollution and air pollution. Out of these different pollutions air pollution resulting from cotton dust is the most important factor affecting health of the workers. Various studies in India and outside have been carried out in cotton mill workers with different results. So present study was planned to evaluate the lung function of cotton mill workers by spirometry in this part of country.
Material & methods: The study was carried out in 55 participants who were exposed to cotton dust directly. 55 controls were also selected from the workers of same mill but not exposed directly to cotton dust. Spirometry findings were compared between two groups.
Results: The values of most of the PFT parameters were significantly reduced in subject group compared to control group (p<0.05). However there was no any significant difference in the values of FEV1/FVC ratio between the groups (p>0.05).
Conclusion: From our study we conclude that workers in the cotton mills are exposed to cotton dust and various types of other air pollutants. And the chronic exposure results in decline in pulmonary functio
A Novel Approach for Detecting Outliers by Using Isolation Forest with Reducing Under Fitting Issue
Get PDFThe effectiveness of machine learning for a particular activity depends on a variety of parameters. The incident database's description and validity come first and primary. Information retrieval even during the training cycle is more challenging if there is a lot of repetitious, unimportant information or incomplete information available. It is good knowledge that running time for ML tasks is significantly impacted by conditions as follows and sorting stages. To increase the accuracy of any model data cleansing is essential. Without sufficient data scrubbing, no predictive model accuracy can begin. EDA, or exploratory data analysis, is the name of this procedure. In this study, we discussed outlier identification, one of many EDA processes for complete perfect data. In this research, we attempted to use the isolation forest approach to calculate the outlier factor. Then a model known as an outlier finding model is created. The problem of outlier detection leads to a collection of connected supervised learning for binary classification. We carry out in-depth tests on various datasets and demonstrate that in our latest outlier finding technique compare with the old way. Our approach yields superior outcomes in terms of accuracy, precision, recall & F-1 score. Additionally, we successfully lowered the machine learning algorithms' under fitting issue
Analysis on Security Vulnerabilities of the Modern Internet of Things (IOT) Systems
Get PDFThe IoT, or Internet of Things, has quickly grown in popularity as a means to collect data in real-time from any and all linked devices. These networked physical objects can exchange data with one another via their respective sensor technologies and have their own unique identifiers. Insightful data analytics applied to the obtained information also presents a substantial possibility for many organisations. Embedded devices, authentication, and trust management are all areas where the Internet of Things has shown a significant security hole. This study delves into the problems with the Internet of Things (IoT), covering topics such as its privacy and security, its vulnerability, its analytics at the moment, the impending ownership threat, trust management, IoT models, its roadmap, and its security issues. It then offers solutions to these problems