Sentiment Analysis and Classification on Amazon Products using Improved Support Vector Machine for Multiclass Classification

There is a huge increase in number of peoples who have been accessing many social networking sites especially user post or reviews for a specific product, company, brand, individual, forums and movies etc. These reviews are helpful in judging customer perception on certain thing. The development of algorithms that could automate the categorization of distinct comments based on feedback from consumers became an analyst project, and this automated classification process is known as sentiment analysis. This research main goal is to analyze Amazon product reviews using an approach to Machine Learning (ML) built around TF-IDF and then employ the Support Vector Machine (SVM) algorithm to categorize the sentiment scores and sentences. SVM can handle binomial classification but the customer reviews is mostly classified into positive, negative and neutral and in some applications, it is fine grained into star ratings such 1-5 or sometimes 1-10. Also, in some applications features or attributes are high in number in which some are irrelevant. Hence, this work applies feature subset algorithm and improves the existing SVM to handle multiclass classification. The Sentiment analysis, Rapidminer tool is considered for classification and the results are visualized, assessed with suitable classification metrics

A correlation of clinical, hormonal and ultrasonography features of polycystic ovarian syndrome among adolescent and reproductive age group women attending OPD in Navodaya medical college

Background: Polycystic ovarian syndrome is the most common complex endocrine disorder in women of reproductive age. It is characterized by an array of clinical, endocrinal and metabolic manifestation. Aim of this study was to examine the correlation between clinical, hormonal and ultrasonography features in women diagnosed as polycystic ovarian syndrome. Methods: A cross sectional study of 100 reproductive age group women who had irregular cycles and polycystic ovarian morphology on ultrasound. Data about the menstrual history and anthropometric measurements were collected. Clinical observations were like hirsuitism and acanthosis nigricans was noted. Results: In all 100 PCOS women were studied and analysed. The mean age was 24.27(±5.64), mean BMI was 26(±4.8). Among the PCOS women 82% had oligo menorrhoea, 38% had hirsuitism and LH:FSH ratio deranged in 37% cases. The association between women having oligomenorrhoea and obesity with PCO morphology on scan was statistically significant. Conclusions: Young women who are diagnosed as dysregulated PCO are at a high risk to develop PCOD and long term sequel such as diabetes, hypertension and infertility. Lifestyle modification is advisable for managing symptoms and preventing long term complications and have a quality life

Influence of different types of soils on the growth and yield of Quinoa (Chenopodium quinoa Wild.)

Quinoa is a resilient high-yielding pseudo cereal, gaining attention because of its high nutritional value, strong growth potential, and tremendous source of essential amino acids, micronutrients, vitamins, phenolic compounds, and minerals. The main aim of this investigation was to find the best suitable soil type for maximizing the growth and yield of Quinoa. The pot study was undertaken at the Department of Agronomy, Tamil Nadu Agricultural University, Coimbatore, during the Kharif 2022 season. Eight soil samples (clay loam soils of wetlands of TNAU, sandy loam soils of eastern block of TNAU, sandy loam soils of Mettupalayam, sandy clay loam soils of 36 B eastern block of TNAU, sandy clay loam soils of 37 B eastern block of TNAU, clay loam soils of Ooty, sandy clay loam soils of Govindanaickenpalayam and sandy clay loam soils of Annur) were collected round Coimbatore in Tamil Nadu and tested in a complete randomized design with three replications. The pot study results revealed that growth parameters viz. Plant height (81.5 cm), number of leaves plant-1 (164.8), leaf area (317.7 cm2), number of branches plant-1 (38.0) and dry matter production (22.78 g) were significantly higher in the clay loam soils of Ooty than all other soil types. Similarly, yield attributes such as the number of panicles plant-1 (21.7), panicle length (13.08 cm), number of grains panicle-1 (3050) and grain yield plant-1 (9.60 g) of Quinoa were also higher in the same clay loam soils followed by that in sandy clay loam soils of Govindanaickenpalayam. Red soils of Mettupalayam had shown the lowest growth, yield and yield attributes of Quinoa. Based on the above results, it was concluded that the clay loam soil of Ooty was the best suited for cultivating Quinoa crops

Effect of hydrogen bonding and solvent polarity on the fluorescence quenching and dipole moment of 2-methoxypyridin-3-yl-3-boronic acid

Two photophysical properties namely, fluorescence quenching and dipole moment (both ground state and excited state) of 2-methoxypyridin-3-yl-3-boronic acid (2MPBA) have been investigated in alcohol environment using steady state fluorescence technique at 300 K. In quenching studies, a rare but not unusual observation; negative Stern-Volmer (S-V) deviation has been noticed. It has been explained using the concept of solute’s conformational changes in the ground state due to inter-molecular and intra-molecular hydrogen bonding in alcohol environment. The spectroscopic data has been processed using Lehrer equation and thereby Stern-Volmer constant (KSV) has been evaluated. It has been found to be above 100 for most of the solvents used. The data related to dipole moment has been examined using different solvent polarity functions. Theoretical calculation of dipole moment in the ground state has been done using Gaussian software. The general solute–solvent interactions and hydrogen bond interactions have been found to be operative. An appreciable red shift of about 25 nm in the emission spectra has been identified with the rise in solvent polarity and decrease in molar mass of alcohols. It confirms the π→π* transition as well as the possibility of intra-molecular charge transfer (ICT) character in the emitting singlet state of 2MPBA

Wifi Infrastructure Security System from Vulnerable Attacks

Abstract Wi-Fi is a very popular wireless technology which is powerful core for the global digital infrastructure. A device connected using Wi-Fi can access the network resource such as the Internet via a wireless network access point. Recent discoveries and initiatives highlight a simple fact that the core is just as vulnerable as the edge. Wi-Fi can be less secure than wired connections because an intruder does not need a physical connection. Though security threats are imminent due to the open nature of communication, there are certain ways to protect the infrastructure of a network.In this paper, we examine the vulnerabilities of Wi-Fi network and this includes the intrusion detection in the security architecture of that network. We have shown such mechanism to solve arrival of intruders by Man-in -the-middle attack on a Wi-Fi network. Also, provide the steps to eliminate hackers from the Wi-Fi network and descriptions regarding the operations performed by different tools to avoid attackers from network. There are several holes in the wireless environment through which the attacks enter the network. In future those holes may be blocked completely by eliminating hackers from all attacks through which they enter. We also discuss a number of available solutions for controlling those threats

Thyroid pathology in canine parvoviral infection

The hypothalamic-pituitary-thyroid axis is suppressed by pro-inflammatory mediators in systemic disease, which affects the thyroid hormone level. Canine parvovirus is one of the important infectious diseases which causes profound morbidity as well as mortality in dogs. It is found that canine parvovirus infection can result in non-thyroidal sickness syndrome. The relation between thyroid pathology and canine parvovirus infection will pave the way for therapeutic and preventive measures for this infectious disease. This study was conducted on 61 dog carcasses brought to the Department of Veterinary Pathology, College of Veterinary and Animal Sciences, Pookode during one year period. Among 61 cases, nine were found to be positive for canine parvovirus which constitutes an incidence of 14.75 per cent. Analysis of gross and histopathological lesions in canine parvovirus positive cases was the goal of this investigation. The gross lesions observed were paleness and nodular growth and histopathological lesions encountered were lymphocytic thyroiditis, colloidal goiter, c cell hyperplasia, severe fibrotic changes and neoplastic lesions. Further research is required to understand the pathophysiology of the euthyroid sick syndrome in canine parvoviral infection

Revolutionizing Crop Production: The Imperative of Speed Breeding Technology in Modern Crop Improvement

Speed breeding (SB) technology is an innovative solution to shorten the breeding cycle and accelerate crop improvement. The key factors of plant growth and development, including photoperiod, light intensity and quality, temperature, relative humidity, planting density and plant nutrition are manipulated in such a way as to stimulate flowering and seed set under controlled conditions. The development of SB technology may be challenging as crops tend to vary in their response to physiological manipulations. Therefore, crop-specific optimization is highly critical to developing successful SB technology in crops. The SB technology can also be synergistically integrated with cutting edge genomics and marker-assisted selection technologies to enhance genetic gain in crop breeding programmes. In this review, various aspects concerning the science and techniques underpinning SB technology, the successful implementation of SB technology in different crops, the inherent challenges faced, and the potential opportunities to integrate SB technology with cutting-edge genomics technologies towards accelerating crop improvement are discussed

Application of Linear Discriminant Analysis in Dimensionality Reduction for Hand Motion Classification

The classification of upper-limb movements based on surface electromyography (EMG) signals is an important issue in the control of assistive devices and rehabilitation systems. Increasing the number of EMG channels and features in order to increase the number of control commands can yield a high dimensional feature vector. To cope with the accuracy and computation problems associated with high dimensionality, it is commonplace to apply a processing step that transforms the data to a space of significantly lower dimensions with only a limited loss of useful information. Linear discriminant analysis (LDA) has been successfully applied as an EMG feature projection method. Recently, a number of extended LDA-based algorithms have been proposed, which are more competitive in terms of both classification accuracy and computational costs/times with classical LDA. This paper presents the findings of a comparative study of classical LDA and five extended LDA methods. From a quantitative comparison based on seven multi-feature sets, three extended LDA-based algorithms, consisting of uncorrelated LDA, orthogonal LDA and orthogonal fuzzy neighborhood discriminant analysis, produce better class separability when compared with a baseline system (without feature projection), principle component analysis (PCA), and classical LDA. Based on a 7-dimension time domain and time-scale feature vectors, these methods achieved respectively 95.2% and 93.2% classification accuracy by using a linear discriminant classifier

Myoelectric control of prosthetic hands: state-of-the-art review

Purushothaman Geethanjali School of Electrical Engineering Department of Control and Automation VIT University, Vellore, Tamil Nadu, India Abstract: Myoelectric signals (MES) have been used in various applications, in particular, for identification of user intention to potentially control assistive devices for amputees, orthotic devices, and exoskeleton in order to augment capability of the user. MES are also used to estimate force and, hence, torque to actuate the assistive device. The application of MES is not limited to assistive devices, and they also find potential applications in teleoperation of robots, haptic devices, virtual reality, and so on. The myoelectric control-based prosthetic hand aids to restore activities of daily living of amputees in order to improve the self-esteem of the user. All myoelectric control-based prosthetic hands may not have similar operations and exhibit variation in sensing input, deciphering the signals, and actuating prosthetic hand. Researchers are focusing on improving the functionality of prosthetic hand in order to suit the user requirement with the different operating features. The myoelectric control differs in operation to accommodate various external factors. This article reviews the state of the art of myoelectric prosthetic hand, giving description of each control strategy. Keywords: EMG, assistive device, amputee, myoelectric control, electric powered, body ­powered, bioelectric signal contro

A study on lignin degrading fungi isolated from the litter of evergreen forests of Kodagu (D), Karnataka

ABSTRACT Litter forms the major portion of the net primary production in natural ecosystems and in most managed forests and grasslands. Litter is the surface layer of the forest floor consisting of freshly fallen leaves, needles, twigs, stems, bark and fruits. Litter biota varies with depth and with stage of decay. Litter contain about 20-50% lignin. Because of the size and complexity of lignin, its decomposition rate is slow. Fungi especially Basidiomycetes are generally recognized as the major group responsible for lignin degradation. The lignolytic enzymes are being used in food, textile, paper industries and in the degradation of lignin rich agro-waste. In the present work lignin degrading fungi were isolated from the litter of evergreen forest of Kodagu D. About 58% of the total fungi isolated were found to be potential lignin degraders. The isolates were tested for enzyme activity and those showing maximum activity were tested for their efficiency to degrade areca and coffee husk. The Chaetomium sp, Penicillium sp, Aspergillus sp and Trichoderma sp were found to degrade areca and coffee husk effectively