Volume 12 | Issue 1 |

 Abstract

This survey study examines malware detection methods and focuses on a particular project that employs machine learning to find potentially hazardous URLs and identify infected files. Malware is any software that carries out harmful operations, such data theft or espionage. In Kaspersky Labs' definition from 2017, malware is "a type of computer programme designed to infect a legitimate user's computer and cause harm in various ways." The several polymorphic layers present in contemporary malware apps make it increasingly challenging to identify malware using conventional signature-based techniques. Since these layers either conceal from view or update themselves automatically on a regular basis, antivirus software finds it difficult to identify them. Machine learning provides the answer by teaching models to recognise both positive and negative file attributes. This feature allows malware to be detected independent of previous experience by enabling the recognition of hazardous patterns. The study that is being presented makes use of a Random Forest classifier for PE-header-based malware detection and Logistic Regression to discover potentially harmful URLs.

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 Keywords

Malware detection, Machine learning in cybersecurity, Polymorphic malware, Signature-based detection limitations, Cybersecurity threats, Random Forest classifier, Logistic Regression, PE-header-based detection, Hazardous URLs detection, Contemporary malware challenges, Antivirus software limitations, Malware identification techniques, Cyber threat intelligence, Data theft prevention, Cybersecurity defense mechanisms

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Original Research Article: STUDY OF EXPRESSION OF VARIOUS IMMUNOHISTOCHEMICAL MARKERS IN THE INVASIVE DUCTAL CARCINOMA OF BREAST (IDC). Authors: Dr. Jeel Sheth1, Dr. Rajvee Jadeja2 , Dr. Jasmin Jasani3, Dr. Yesha Chauhan4, Dr. Devansh Sheth5 1Resident, Department of Pathology, Shrimati Bhikhiben Kanjibhai Shah Medical Institute and Research Centre, Sumandeep Vidyapeeth. 2Resident, Department of Pathology, Shrimati Bhikhiben Kanjibhai Shah Medical Institute and Research Centre, Sumandeep Vidyapeeth. 3 Professor, Department of Pathology, Shrimati Bhikhiben Kanjibhai Shah Medical Institute and Research Centre, Sumandeep Vidyapeeth. 4 Resident, Department of Pathology, Shrimati Bhikhiben Kanjibhai Shah Medical Institute and Research Centre, Sumandeep Vidyapeeth.. 5 Third year MBBS student, B.J.Medical College, Gujarat University Ahmedabad ABSTRACT: INTRODUCTION: Breast cancer is the most frequent cancer in women worldwide, affecting one out of every eight women.(1) It accounts for 25% of all invasive cancers in females and 16% of all female malignancies. (2) The World Health Organization (WHO) reports that 685,000 women died from breast cancer in 2020, with an estimated 2.3 million women receiving a diagnosis worldwide. Breast cancer occurs in every country of the world in women at any age after puberty but with increasing rates in later life. (3) If detected at an early stage, breast cancer is curable. Prognostic factors are those that affect a patient's overall prognosis, such as the likelihood of recurrence following treatment. These variables aid in choosing the right patients for a certain treatment. (6) Tumor size, tumour grade, and axillary lymph node metastases are examples of conventional morphological prognostic variables. As a result of the fact that a considerable proportion of patients with early-stage breast cancer already have microscopic metastases when they are diagnosed, biological molecular prognostic markers are being given more weight.(7) The most relevant clinical biomarkers that are widely used in managing breast cancer cases according to stage are hormone receptors (ER and PR) and human epidermal growth factor receptor-2 (HER-2).(7) Making management decisions and plans for breast cancer management requires an understanding of hormone receptors and HER-2 expressions. (8) In treatment of breast cancer, prognostic and predictive factors are used. Predictive factors assess the likelihood of benefit from a certain treatment. ER, PR, and HER2/neu are prognostic as well as predictive variables. (6) METHOD: This present study, entitled "IMMUNOHISTOCHEMICAL (IHC) EXPRESSION OF ESTROGEN RECEPTOR (ER), PROGESTERONE RECEPTOR (PR) AND HUMAN EPIDERMAL GROWTH FACTOR RECEPTOR-2 (HER2/NEU) IN INVASIVE DUCTAL CARCINOMA OF BREAST: A CLINICOPATHOLOGICAL STUDY" is conducted in the Department of Pathology at Dhiraj hospital from 1st February 2023 to 31st August 2023. o The recorded data of IHC of patients who were diagnosed as invasive ductal carcinoma of breast that received in the department of pathology at Dhiraj hospital from 1st February 2023 to 31st August 2023. RESULT: The present study was undertaken to evaluate the various IHC markers expression in invasive ductal carcinoma of breast. Total of sixty cases who met the inclusion criteria were taken into the study. CONCLUSION: The present study reported maximum number of cases in the age group of 51-60 years. Majority of cases were in grade II followed by grade III and grade I. The highest proportion of positive ER (18.33%), and PR (16.67%) expressions were observed in the age group 51-60 years. The highest proportion of positive HER/2neu (10%) expression was observed in the age group 51-60 & 61-70 years.

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KEY WORDS: ER, PR, HER/2neu

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This study analyzed the familiarity in use of electronic resources by the library users of Tamil Nadu Agricultural University. 30.9% respondents are spend less than an hour for using internet per day. 41.1% of the respondents opined that use the internet for subject knowledge. 28.3% of the respondents opined that the using for E-Journals. 39.6% respondents use the Electronic sources every day. 43% respondents have learning electronic resources by guidance from friends. 35.5% of the respondents opined that the lack of facilities is the main problem for using the electronic resources. 39.1% respondents agree that they are satisfied with the quality of electronic resources.

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Internet, Electronic Resources, Information Communication Technology, Digital Library, e-learning databases.

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Severe hyperbilirubinemia; Acute bilirubin encephalopathy; kernictus; Direct Coombs test.

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A person's everyday life, social relationships, and general well-being are all negatively impacted by a visual handicap. This essay examines the many facets of vision impairment, discussing the difficulties experienced by those with visual impairments, looking at the problem from a variety of angles, and suggesting creative fixes to improve their quality of life. The difficulties include a broad spectrum of topics, such as obstacles to accessibility in the built environment, restrictions on career and educational options, and the effect on mental health. Medical, social, and technical paradigms are used to analyze perspectives on vision impairment, illuminating the complexity of this illness. The study also explores current treatments and solutions, such as advocacy campaigns, instructional plans, and assistive technology. It also looks at how new technologies like augmented reality and artificial intelligence could be used to meet the special requirements of people who are blind or visually impaired. To sum up, this article highlights the need to adopt a comprehensive strategy that integrates medical, social, and technological treatments to provide a more welcoming and supportive atmosphere for those with visual impairments. Through comprehension of the obstacles, evaluation of many viewpoints, and application of creative resolutions, the community may endeavor to create a future that is fairer and easily accessible for people with visual impairments.

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Visual disability, accessibility barriers, educational opportunities, employment opportunities, mental health, social paradigm, assistive technologies, artificial intelligence, equity

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The chimney structures are tall and generally placed in regions of high gust. The design of chimney has significant effect on wind load bearing characteristics of chimney. The research is intended to investigate the effect of wind load on structural characteristics of chimney. The wind load analysis of chimney structure is conducted using techniques of Computational Fluid Dynamics. The CAD modeling and CFD simulation of chimney is conducted using ANSYS CFX software. The lateral deformation and induced pressure is evaluated for different chimneys. The edge treatment on tapered chimney has significant effect on magnitude of induced pressure and drag force on chimney. By changing the sharp edged chimney to filleted edge chimney the drag force and shear stress reduced significantly.

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Chimney, wind load

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Bronchial asthma is a serious global health problem. 5% to 10% of persons of all ages suffer from this chronic airway disorder. This review article presents homeopathic medicines and treatment of bronchial asthma .Cases summary: This is a case of patients suffering from bronchial asthma having the complaints of cough shortness of breath , wheezing along with itching all over the body . The patients were prescribed indicated constitutional Homeopathic medicines and at the end of treatment showed reasonable improvement in disease as well as in the quality of life.

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HAMSA HOMEOPATHY MEDICAL COLLEGE, HOSPITAL & RESEARCH CENTRE

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The skin is the largest organ in the body, and fungus infections are among the many conditions that affect it. Skin disorders are common worldwide. According to Ayurveda, all skin diseases are categorised under the term Kushtha. In Ayurveda Dadru and Pama is one of the common skin diseases mentioned in Ayurveda. Ayurveda has described 'Samshodhana' (Bio-purification), 'Samshamana' (Pacification) and 'NidanParivarjana' (Avoiding causative factors) as main therapy for many diseases including skin disorders.

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Kushtha, Dadru, Pama, Skin diseases

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: This paper presents a system that embodies the essence of sonic detective work. Like a musician, it first extracts certain features from the sound, identifies individual instruments, checks the notes or sounds they play, and then synchronizes the notes with the music. The end result is like a beautiful piece of music that takes the messy sounds and organizes them into something pleasant. It could be a new music mix or music score. People can listen to it and have a great time enjoying the music. This project is designed for listening to polyphonic music played by a variety of instruments together, and it does a lot of things well. For the purpose to advance the musical field we are developing the system that is capable of identifying instruments from polyphonic instrument sound from the feature extracted using Kernel PCA (Probabilistic Component Analysis) ,the classification is performed using SVM (Support Vector Machine).This allows system to efficiently identify the instruments. Then the pitch is detected from the instruments identified using Cepstrum method which is capable of detecting pitches from detected instruments. The detected pitches are then synchronized to provide a synthesized audio file as output using HMM (Hidden Markov Model) and DTW (Dynamic Time Wrapping).

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Machine Learning, Kernel PCA, Kernel Probabilistic Component Analysis, Support Vector Machine, Hidden Markov Model, Cepstrum, Dynamic Time Wrapping, Tune Detection, Instrument Recognition, Pitch Detection, Synchronization, Classification , Feature Extraction, Audio Preprocessing, Synthesized Audio Generation

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Considering the enormous difficulties that the globe is experiencing in providing food for an ever-increasing population, the incorporation of technology into agricultural practices has become an absolute need. Climate-controlled agricultural facilities, such as greenhouses and hydroponic systems, provide methods of food production that are both effective and environmentally friendly. It is essential to have the capacity to monitor and control plant health in order to get optimal results while optimizing these habitats. The purpose of this study is to investigate the use of machine learning techniques for the categorization of plants in controlled agricultural situations with the intention of improving precision agriculture operations. One of the most important components of a plant is water. Along these lines, the development of plants is extremely dependent on the changes that occur in the amount of water that is contained within the plant. There have been a lot of different approaches that have been developed in order to enhance plant development in times of water scarcity and dry period pressure. The purpose of this study is to organize and construct an intelligent framework that will promote plant development in a constrained water environment. This framework will be based on Support Vector Machine (SVM) and machine vision. Shading, morphological, and textural highlights were finally isolated from a large number of photographs of turf grass, wheat, and rice plants that were taken under pressure circumstances that were typical of the dry season. At that point, an SVM and an ANN were utilized in order to supervise the process of information organization by using them. When the SVM was used as the classifier, the results showed that the general arrangement exactness of ANN was 92%, and greater correctness were obtained when the SVM was used. The general precision of the SVM was 98.00% for both fresh and wilted plant conditions.

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Classification, computer vision, controlled-environment agriculture, image compression, machine learning.

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