Volume 10 | Issue 6

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Sentiment classification, Sentiment analysis, Machine Learning algorithms.

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Acute stroke, Respiratory PNF, Intercostal stretch, Anterior basal lift, Incentive spirometry

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With the rapid urbanisation, space restrictions are becoming increasingly important in the case of tall structures. The wind produces gusts that cause the building to be influenced not just along the wind direction but also across the wind direction. In recent years, several architects have begun to use floating columns in their designs to embellish the cultural perspective. Because of variations in ground height, the shape's tension is discontinuous at the gentle story level. This discontinuity may cause structural collapse of structures beneath the effects of wind. In this study, identical static analysis of 3-D building frames of G+9 tales with floating columns, as well as tender-tale outcomes and exceptional infill cloth, were performed. A total of 12 instances were evaluated. Aside from the preceding situations, a basic case is established in which no memories are smooth and no columns are floating. There were nine load combinations to examine. The equal ground heights have resulted in soft narratives. The STAAD.Pro software package was utilised for analysis. The results are summarised in terms of maximum node displacements (resultant), maximum moments, maximum shear force, and maximum axial force. The results are evaluated in order to draw technical conclusions.

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Wind Loads, Soft Storey, Floating columns, Infill material, Design wind speed,

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Safety Aspects

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MUJAFFARAPUR JILE MEIN MURAIL BLOCK KE RAJAKIY PRATHAMIK VIDHALAYO MEIN CHHATRO EVAN CHHATRAO KI VIDHALAY SAMBANDHI SAMASYAO KA ADHAYAYAN

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MUJAFFARAPUR JILE MEIN MURAIL BLOCK KE RAJAKIY PRATHAMIK VIDHALAYO MEIN CHHATRO EVAN CHHATRAO KI VIDHALAY SAMBANDHI SAMASYAO KA ADHAYAYAN

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The Structural components in metallic structures subjected to mechanical loading as well as Thermal loading in severe environmental conditions experiencesthe different range of Temperatures.So the Steel Structures are predominant thermalloading apart from mechanical loading at the interfaces of the different metallic components at severe environment conditions. Those structures must also be constructed to withstand thermal loads. In order to design the component, thermal loading must be converted to its equivalent mechanical stress. For that, an empirical model proposed for thermal equivalency to mechanical stress using a Finite Element analysis interfacial fracture mechanics technique. The study's major goal is to use material properties to assess the impact of these loads on bi material interfaces based on releasing rate of energy. By usage of FRANC 2D programmer, we suggested a simple model for Thermal equivalence to mechanical stress using the finite element approach.

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Franc 2D; Thermal Loading; Design Component; Thermal Equivalence;

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Financial performance of panasonic private limited for five years 2014-2019 using ratio analysis

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Panasonic private limited

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There is no doubt that data is the new oil in the 21st century. Just like oil, data grows in value when refined. It offers tremendous potential for unravelling the mysteries of any data set and drawing valuable insights from it. When correctly assessed & addressed, these insights can lead to positive results. The purpose of this paper is to describe the meaning and characteristics of big data, as well as analyse the characteristics of consumer behaviour within the context of big data analysis. Based on the results, external factors and internal perception are major factors that affect consumer decision making, while big data impacts consumer perception through external factors.

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Consumer behaviour, Big Data, Business, Technology

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As the world is growing towards Internet-based digitalization over the social media, millions of articles are uploaded every second, and the Internet users are more keep on social media applications such as WhatsApp, Meta, Instagram, Twitter and other online applications. The aim of the project is to detect the Fake or Real News in online available articles. There are many news channels online, who are publishing the daily news and more people read online media as it has many benefits such as paperless, fingertip availability of news, Attractive headlines and colorful titles. The recent advancement of the online social media platforms has impacted the daily life of civilization. The people who are using the above online news platform should not get the fake news regarding, we need to identify the challenging solution that can detect the fake news. The application of the Project is detecting the fake news using Machine Learning (ML) and Deep learning (DL). The project uses two major algorithms namely Passive Aggressive Classifier and Adaptive Boosting Classifier (ABC) and Long Short Term Memory (LSTM). We have made the strong analysis and visualization on the dataset supplied. Our models are providing 95% & above accuracy. Finally we have developed the Web Application for the prediction of Forged and Actual news.

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Passive Aggressive Classifier, LSTM, TF-IDF, BOW, Flask-Web Application.

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One of the most prevalent cancer forms, skin cancer has become more widespread in recent decades. It is critical to correctly diagnose skin lesions to distinguish between benign and malignant lesions in order to provide proper patient care. While there are various computerized approaches for classifying skin lesions, convolutional neural networks (CNNs) have been demonstrated to outperform traditional methods. We offer an hybrid CNN model for skin lesion categorization in this paper. We fuse an optimized pre-trained VGG-16 model with a pre-trained ResNet-50 CNN model to construct an hybrid model for skin lesion classification. In this work, we have used ISIC 2016-17 dermoscopic images to test the performance of the proposed hybrid CNN model. The proposed method achieves very good classification performance when tested on the ISIC Dataset, with an accuracy of 0.8565.

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Convolutional Neural Networks (CNN), Deep Learning (DL), ResNet-50, Skin Lesion, VGG-16.

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Valuation is the analytical process of determining the currents worth of an asset or a company. Simply, valuation is the technique of determining the current market value of the property such as industrial, residential, commercial, agricultural land. Value is determined on basis of its selling price and rent or income it can fetch. The purpose of this is to introduce people with general field practice of valuation. This study covers the methodology verified by the government approved valuer and concerned field expert. The finding of this study is likely to have important implications in the valuation profession. This study directly introduces users with actual practice of valuation carried out in the field so that they can compare the theories and actual methodology. This study will result in stimulating debate and a realization of a need for a theory which supports a validated process of valuation.

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Methodology, Industrial Property, Field practice, Valuer, Valuation, Market Value, Finance.

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Shvahs means breathing. Normally human being breathes fifteen times in an average in a minute including both - inhalation and exhalation. However, during the outburst of emotions or anxiety, the breathing rate increases to twenty to twenty five breaths per minute and may increase further in the intensity of the emotions. It is believed that rapid breathing is often harmful to the health and may disturb the blood circulation. Meditation (dhyana) becomes more effective in the above cases if it is built upon asana (physical posture), pranayama (breath control), pratyahara (control of the senses, moving the focus to the inside), and dharana (concentration). We know that during inhalation, the lungs get filled with the air and the diaphragm is lowered and in turn expands the abdomen. In contrast, during exhalation the lungs contract along with the abdominal muscles. If we add our attention with the breathing, we can see the breath as well as perceive our consciousness. Regular practice of perception of breathing imparts physical, psychological, and spiritual benefits to the practitioner.

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Shvash-Preksha, Perception of Breathing and Preksha Meditation

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Online purchase behaviour, Rural and urban consumers in Ranga Reddy and Karimnagar districts of Telangana State, E-tailers, Online shopping, Electronic commerce, Consumer expectations.

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Nowadays, brain signals are employed in various scientific and practical fields such as Medical Science, Cognitive Science, Neuroscience, and Brain Computer Interfaces. The brain signal analysis is faced with complex challenges including small sample size, high dimensionality and noisy signals. The detection of EEG brain signal in patient to distinguish between normal and abnormal which are tumor and epilepsy, therefore, a very demanding process that requires a detailed analysis of the entire length of the EEG data. This paper describes an automated classification of EEG signals for the detection of normal and abnormal using NSCT and ANN Classifier. Feature extracted from input EEG signals. The performance of the proposed algorithm has been evaluated using in EEG signals. The results showed that the proposed classifier has the ability of classifying EEG signals efficiently.

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EEG Signal, Artificial neural networks, non subsampled contourlet transform

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Now-a-days with the growing industries large amount of waste products are produced. Disposal of these waste materials are required as they cause harm to human and other life. For its disposal large area is covered. As the production of waste is increasing day by day, we need to find a substitute to overcome this problem. Fly ash is a waste product produced due to burning of coal in power generating plants. Concrete consists of cement, sand, fine and coarse aggregate. Production of cement emits large quantity of greenhouse gases. Due to increase in construction work, demand for cement will also increase. So, to avoid production of greenhouse gases and to produce environment friendly concrete, cement is replaced with certain percentage of fly ash. Replacement of cement with certain percentage of fly ash is to improve the strength of pavement concrete. The fly ash used in this study is from NTPC, Badarpur, Delhi and is of Class B. In the experimental study the replacement of OPC (Ordinary Portland Cement) with fly ash is done and to get the desired workability and strength. Polymer based superplasticizer is used for all grades of concrete. The compressive and flexural strength of PQC (Pavement Quality Concrete) with different percentage of fly ash has been studied for 3, 14 and 28 days. From the experimental results it has been noted that without superplasticizer the compressive strength of Pavement Concrete is less for both 7days and 28 days. With the use of superplasticizer, the desired compressive strength is achieved. But in case of flexural strength even without superplasticizer concrete attains the required strength and with superplasticizer the flexural strength of PQC achieve higher strength.

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EFFECT OF FLY ASH ON STRENGTH OF PAVEMENT QUALITY CONCRETE

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ON THE PAPER

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BHOOJAL,JALSTAR,KRISHI,SHINCHAI,JALAPURTI,KISAN,KHETI

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Recent studies show the potential of artificial intelligence (AI) as a screening tool to detect COVID-19 pneumonia based on chest x-ray (CXR) images. However, issues on the datasets and study designs from medical and technical perspectives, as well as questions on the vulnerability and robustness of AI algorithms have emerged. In this study, we address these issues with a more realistic development of AI-driven COVID-19 pneumonia detection models by generating our own data through a retrospective clinical study to augment the dataset aggregated from external sources. We optimized five deep learning architectures, implemented development strategies by manipulating data distribution to quantitatively compare study designs, and introduced several detection scenarios to evaluate the robustness and diagnostic performance of the models. At the current level of data availability, the performance of the detection model depends on the hyperparameter tuning and has less dependency on the quantity of data. InceptionV3 attained the highest performance in distinguishing pneumonia from normal CXR in two-class detection scenario with sensitivity (Sn), specificity (Sp), and positive predictive value (PPV) of 96%. The models attained higher general performance of 91-96% Sn, 94-98% Sp, and 90-96% PPV in three-class compared to four-class detection scenario. InceptionV3 has the highest general performance with accuracy, F1-score, and g-mean of 96% in the three-class detection scenario. For COVID-19 pneumonia detection, InceptionV3 attained the highest performance with 86% Sn, 99% Sp, and 91% PPV with an AUC of 0.99 in distinguishing pneumonia from normal CXR. Its capability of differentiating COVID-19 pneumonia from normal and non-COVID-19 pneumonia attained 0.98 AUC and a micro-average of 0.99 for other classes.

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To develop a novel method for COVID-19 pneumonia in lungs with generation of appointment

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Cardiovascular disease, aging.

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The paper tries to elucidate the relationship between spirituality and psychological well-being in young adult professionals of Chhattisgarh. The role of spirituality in enhancing mental health and well-being of an individual. It was hypothesized that spiritual working professionals will show better psychological well-being than non-spiritual working professionals. The sample includes 50 participants, 25 from spiritual community(performing meditation, journaling, and gratitude practices on regular basis), and 25 from non-spiritual community. The statistical analysis was done using independent t-test and a significant difference was found between two groups. The paper concluded that there is a difference between well-being of people who are involved in the spiritual activities than the people who are not. And that promoting spiritual practices can be beneficial in enhancing mental health of working people and it can be a cure to their psychological challenges

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SPIRITUALITY, NON-SPIRITUALITY, PSYCHOLOGICAL WELLBEING, PROFESSIONALS

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