Volume 9 | Issue 7

 Abstract

In current days cloud has gotten one of the entrancing area so as to store and recover all the information from the distant machines rather from the neighborhood machines. With the notoriety of wearable gadgets, alongside the improvement of mists and cloud hand held innovation, there is a colossal increment for the clinical consideration so as to store and access the data distantly. Because of the rising innovation every single clinical organization attempt to store and access data inside the cloud worker, which leaves a way for the gatecrasher to hack the information un-approved way. So in this paper we attempt to recognize the gatecrasher who attempt to change or adjust the patient data illicitly during information stockpiling.

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 Keywords

emerging technology, cloud server, hack , unauthorized manner.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Internet of Things (IoT) is a domain wherein which the transfer of data is taking place every single second. The security of these data is a challenging task; however, security challenges can be overcome with cryptography and steganography techniques. These techniques are crucial when dealing with user authentication and data privacy. In the proposed work, the elliptic Galois cryptography protocol is introduced and discussed. In this protocol, a cryptography technique is used to encrypt confidential data that came from different medical sources. Here we try to encrypt the Image and send through network from sender to receiver.

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 Keywords

Internet of Things, cryptography, steganography, Image, Encryption, Decryption

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Now a days there is a huge demand and interest in using path identifiers (PIDs) for data communication .These PIDs act as a inter-domain routing objects to avoid distributed denial-of service (DDoS) attacks. As we all know that path identifer are designed earlier , those are static in nature and hence it is very easy for the attackers to create any attack on a fixed path. To address this issue, in this present application we try to design and implement a novel path identifiers for data communication like dynamic D-PID, a framework that is not at all implemented in any DTNs till today. In DPID, the PID of an inter-domain path connecting two domains is kept secret and changes dynamically, so there is no chance for any attacker to identify which path the data is travelling and he cant able to convert nodes into faulty state. We simulated our application using socket programming language along with java network package to verify the effectiveness and cost. The results from both simulations and experiments show that dynamic nature of identifying faulty nodes and providing alternate path for data transfer can effectively prevent DDoS attacks.

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INTRUSION DETECTION USING DANGER OR NORMAL MODE

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 Abstract

Nowadays almost all the users try to exchange their day to day updates in their life on online social networks like Facebook, Twitter, and a lot more. In general, the users want to tweet on some friend's tweets either in a positive manner or in a negative manner based on their original feelings. In a recent survey report, there are a lot of posts that are contained in shameful tweets with some shameful related comments and replies. These tweets may contain some times information about political, social, and financial life with some shameful related messages, hence there is no method to identify these types of tweets automatically and try to display these tweets separately. Hence in this proposed application, we try to design a new method that can able to identify the tweets and its inner meaning of those tweets and try to categorize the tweets into separate categories like positive, negative, and shameful. Here we try to use Feature Extraction Method along with SVM Classifier algorithm for classifying the shameful tweets and normal tweets individually.

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DETECT AND IDENTIFY THE SHAMEFUL TWEETS ON TWITTER SOCIAL NETWORK

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 Abstract

The Machine Learning (ML) field has gained its momentum in almost any domain of research and just recently has become a reliable tool in the medical domain. Identification of the plant diseases is the key to prevent the losses in the yield and quantity of the agricultural product. The studies of the plant diseases mean the study of visually observed patterns seen on the plant. Health monitoring and disease detection on the plant is very critical for the substantial growth. It is very difficult to identify the diseases on the plant manually and provide the treatment for that appropriate disease. It requires a tremendous amount of work experience and should be expertise in the plant diseases and also requires excessive time for processing. Here in this proposed application we try to find out the disease of the plant based on the inputs which we observe physically on any plant. For any plant there are 5 levels of disease occurrences: Stem Level, Leaves Level, Seed Level,Lessions Level, Plant Level. So any disease on the plant can be either of these five levels. We try to design an medical dictionary in which all the physical inputs are substituted according to any of the level and then try to detect which disease plant is suffered with and it will try to provide cure for that appropriate disease. Our evaluation results on the proposed method using ML approach for identifying diseases on plant able to identify the diseases accurately and try to provide a solution for the end users.

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 Keywords

Plant Diseases, Machine Learning, Medical Diseases

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Online shopping and opinion mining have gained more and more importance due to the emergence of the world wide web and a lot of e-commerce web sites. As we as a whole realize that clients are attempting to buy every single thing through online as opposed to visiting the shops legitimately for those things. Online business is becoming quicker than anticipated all things considered up over 98% analyzed before. As clients have the simplicity to purchase things without investing a lot of energy there are additionally a few hoodlums who attempt to extortion and get benefit in unlawful manners. As individuals are getting a charge out of the focal points from web based exchanging, programmers are additionally taking favorable circumstances to achieve criminal operations against certified clients so as to get deceptive benefit. In this paper we mainly design a online model which can able to detect and identify the user reviews in early manner based on users individual reviews and opinions for the products. Finally we show that this model can probably distinguish primitive e-commerce sites and current site and extensively decrease customer complaints which are based on real-world online fraud detection.

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 Keywords

Real World, Online Fraud Detection, Reviews, Early Reviews , Individual, Online Model,Pro-Active.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Heterogeneous web media consists of many visual concepts, such as objects, scenes and activities, that cannot be semantically decomposed. The task of learning fundamental visual concepts (FVCs) plays an important role in automatically understanding the elements that compose all visual media, as well as in applications of retrieval, annotation, etc.In this project we try to apply annotations for all the images which are uploaded in the online web by taking neighboring concept distributing (NCD) attribute ,in which those which are having some similar difference will be added with same type of annotation and then they are tagged.

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FUNDAMENTAL VISUAL CONCEPT LEARNING FROM CORRELATED IMAGES AND TEXT ANNOTATION

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 Abstract

GIVING BACK TO SOCIETY: CORPORATE SOCIAL RESPONSIBILITY AT NALCO AND IMFA

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GIVING BACK TO SOCIETY: CORPORATE SOCIAL RESPONSIBILITY AT NALCO AND IMFA

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Training is a learning experience, in that it seeks a relatively permanent change in an individual which will improve his (or) her ability to perform on the job. We typically say training can change the skill, knowledge, attitude and social behavior. It means changing what employees know, how they work, their attitude towards their work or their interaction with their co-workers or their supervisors.

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Perform, Interaction, Behavior, Leadership

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Creative Commons Attribution 4.0 and The Open Definition

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Now a days, creative advertisements plays very significant role to achieve the success among competitive advertising. Creative advertisements are helpful in generating a favourable response from consumers and build long term relationship with them. The purpose of this research is to identify the key factors of creative advertisements on customer loyalty in banking sector. This study will be beneficial to understand the perspective of consumers towards loyalty. The study is conducted among 147 individuals in the city of Indore to find out their perception towards creative advertisements. The study is based on primary data that were collected through closed ended questionnaire. The results were analysed with the help of factor analysis and regression analysis. Results of this study can help marketers, organizations and advertisers in formulating effective strategies to engage with the target market.

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Creative advertisements, Customer loyalty, Consumers, Organizations, Advertisers, Effective strategies

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Creative Commons Attribution 4.0 and The Open Definition

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The purpose of this study is to present an overview of how artificial intelligence (AI) might be utilized to solve health problems caused by autoimmune illnesses. More than 80 kinds of autoimmune disorders impact a wide array of areas of the body. Diagnosis may sometimes be challenging since these symptoms might mimic those of other more prevalent diseases. Autoimmune system diseases are characterized by either unusually low or excessive immune system activities [1]. When the immune system becomes too active, the body fights and destroys its tissues. Immune deficiency disorders weaken the body's capacity to combat intruders and make infection vulnerable. The immune system may produce antibodies in reaction to an unexpected cause, which targets their tissues rather than combat infection. In general, autoimmune disorders are treated by decreasing immune system activation [1]. In the last decade, the treatment plan for self-immune illnesses has changed significantly, leading mainly from precision medicine to precise health and from precise efforts in the healthcare system [1,2]. To comprehend and apply these methods pragmatically, the motivations, gaps, and limits of precision medicine need to be understood. The importance of earning the confidence of the people and patients cannot be overstated, but it is important to recognize that innovations like artificial intelligence still necessitate context, which can only be made available by human intervention, or what is known as augmented machine learning.

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 Keywords

Artificial Intelligence, Autoimmune diseases, Biomarkers, machine learning, genetics, genomes

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Feature Extraction,Random Forest Algorithm,Ada Boost Classifier,Decision Tree Algorithm, Gradient Boosting Algorithm, Decision Fusion

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Music is the best gifted art of nature. The character of music is pervasive in every particle of nature, which is experienced continuously through life. It is an integral part of human life. Even, every person in the society is associated with music in some way or the other. In ancient times, the main purpose of performing music was to worship God and to entertain the general public. In the present time, many changes are seen in the field of music, as a result of which music has emerged as a major role in various other financial dimensions, not being limited to entertainment and God worship. Since, the scope of our Indian Music is very wide, it also creates different dimensions of employment. In this article, we will discuss how many such dimensions of music are there, which help an artist to earn money.

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Stage Performance, Playback Singing, Drama, Music Therapist

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 Abstract

Blasting is a critical part of the mining process, and it necessitates the use of a lot of explosives. However, the blasting process and the use of explosives continue to pose a risk to both humans and the environment. According to various research, fragmentation contributes for only 20-30% of the overall kinetic force used. Ground vibration, fly rock, air overpressure, and noise are all ways that energy is lost. The human reaction to ground vibrations is the special difficulty linked with them. Vibrations from the blast may cause substantial damage to neighboring buildings or structures. This project involves conducting a blast vibration research and interpreting the results in light of the DGMS criteria. Geophones and the Blastmate8.0 programme were used in the research. First and foremost, blasting operations were observed using geophones placed at 100, 200, and 300 metres. The data from the instrument was analyzed by the Blastmate software, which produced a graphical representation. For each explosion, the maximum charge per delay, peak particle velocity (PPV), and air overpressure were measured. The numerous observations were then compared to the standards in order to arrive at a conclusion. When the appropriate quantity of charge per delay or safe charge per delay was utilized, the vibration level for the blasts was less than 5 mm/sec, according to the analysis of blast vibration at the mines. The measured air overpressure was between 114 and 127.6 decibels (L). The results determined from the project indicates that the peak particle velocity, air overpressure generated due to blasting were within the limits. The safe charge per delay for the blasting operation was determined from the study. The project's findings show that the peak particle velocity and air overpressure created by blasting were both within acceptable limits. The analysis found the safe charge per delay for the blasting operation

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Explosives, Blasting, Peak Particle, velocity, Vibrations, Fly rocks

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A modest investment in bar created substantial savings in illness-related prices. The agency recently free its final orders regarding the labeling of sun blocker. the ultimate treatise updates the tentative final treatise regarding over the counter (OTC) sun blocker merchandise. Among the labeling standards square measure removals of the term "sun block" inclusion of an announcement particularization the importance of sun blocker to stop harmful effects of the sun, three sun protection categories: minimum, moderate, high, a brand-new SPF class of 30+ for merchandise with SPF values larger than 30, uniform, and efficient labeling for all sunscreens.

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Sunscreen, SPF, Skin.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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KEYWORDS: Occupational Stress, Adapted Coping Strategies, Nursing Personnel, Shree Krishna Hospital.

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An exploratory study was conducted among 120 bakery workers working across various bakeries to evaluate the prevalence rate and potential risk factors associated with work-related musculoskeletal disorders and the discomfort they face. The specific objectives were to evaluate the risk factors to musculoskeletal discomfort experienced by the bakery workers. It was reported that the neck, upper back, lower back, right forearm, right wrist, hip, and lower legs were the places where the bakery workers reported of pains, aches, or discomforts. 97.5(81.2%) bakery workers reported of having pain in their neck, 96.6(80.5%) had pain in their upper back, 99.2(82.6%) had pain in their right forearm and right wrist, which was due to continuous movement while kneading and rolling dough, cleaning pans/trays, or working above their shoulder level. Almost, 99.2(82.6%) of the workers had pain in their lower back and hip region, which was due to lifting heavy loads and equipment repeatedly, bending and twisting while picking or placing loaded trays on the ground. Whereas, 99.2(82.6%) reported having pain in both of their lower legs due to standing for long working hours. Early detection and appropriate management such as consulting a doctor help in reducing the long-term discomfort, thus preventing the onset of a musculoskeletal disorder in the future. Muscles and tendons should be allowed to rest and recover at the first sign of pain; otherwise, the injury will become long-term and, in some cases, irreparable (https://www.ccohs.ca/oshanswers/diseases/rmirsi.html, n.d.). This paper focuses on and emphasizes the work-related musculoskeletal discomfort faced by bakery workers in their workplace, i.e., bakeries.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Bakery Workers, Ergonomics, Work-related, Musculoskeletal Discomfort, Postures.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Recent developments in cardiac simulation have presented the heart as the most highly integrated example of a virtual organ. Computational modeling of tissue, organ, cells allow to link genomic and periodic information to the integrated organ behavior. This helps to better understand the functioning of heart in both diseased and healthy conditions. Patient-specific modeling (PSM) is the development of computational models of human pathophysiology that are individualized to patient-specific data. PSM has its potential to improve diagnosis, optimize clinical treatment by predicting outcomes of therapies and surgical interventions, and inform the design of surgical training platforms. The goal of this paper is to more broadly illuminate recent work in PSM by providing a survey of current publications in the field and also on computational optimization techniques used in the field of cardiac electrophysiology.

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Computational Modeling, Patient-Specific Modeling, Pathophysiology, Computational Optimization, Cardiac Electrophysiology

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One of the important fields of Artificial Intelligence is Computer Vision. Computer Vision is the science of computers and software systems that can recognize and understand images and scenes. Computer Vision is also composed of various aspects such as image recognition, object detection, image generation, image super-resolution and more. Object detection is probably the most profound aspect of computer vision due the number practical use cases. Object detection refers to the capability of computer and software systems to locate objects in an image/scene and identify each object. Object detection has been widely used for face detection, vehicle detection, pedestrian counting, web images, security systems and driverless cars. There are many ways object detection can be used as well in many fields of practice. Like every other computer technology, a wide range of creative and amazing uses of object detection will definitely come from the efforts of computer programmers and software developers. Traffic sign recognition system (TSRS) is a significant portion of intelligent transportation system (ITS). Being able to identify traffic signs accurately and effectively can improve the driving safety. This project brings forward a traffic sign recognition technique on the strength of deep learning, which mainly aims at the recognition of circular signs. The detected road traffic signs are classified based on deep learning. In this project, a traffic sign detection and identification method on account of the image processing is proposed, which is combined with convolutional neural network (CNN) to sort traffic signs. On account of its high recognition rate, CNN can be used to realize various computer vision tasks. TensorFlow is used to implement CNN. In the German data sets, we are able to identify the circular symbol with more than 95% accuracy.

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 Keywords

Keras, OpenCV, Convolutional Neural Networks(CNN), Deep Learning, Traffic sign recognition

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Creative Commons Attribution 4.0 and The Open Definition