International Research Journal on Advanced Science Hub

Crack formation is a very common phenomenon in concrete structures which allows the water and chemicals through the cracks and decreases the durability and strength. For repairing the cracks developed in the concrete, it requires maintenance and special type of treatment. So, to overcome this problem an autonomous self healing mechanism is introduced into the concrete which helps to repair the cracks with the help of Bacillus bacteria by producing calcium carbonate crystals which seals the micro cracks and pores in the concrete. For the isolation of bacteria nearly eighty soil samples were collected from soils of extreme environments and cultured in three different media. A total of two thousand seventy colonies were observed and fifty five Bacillus colonies were isolated and identified by Gram staining and different biochemical tests.

Development of smart homes is the recent trend all over the world. For cooking purpose LPG is predominantly used while using this leakage may lead to disaster. This paper focuses the regular issue occur in routine life that gas level detection in domestic LPG cylinder by using IOT concept and helps to book another cylinder at the time of low gas level. To detect the gas in LPG, MQ2 sensor is used, and any gas leakage arises the sensor detects by making an alert with buzzer. The sensor output is fed to Atmega8 microcontroller. To know the cylinder heaviness, load cell utilized which helps to booking new LPG incorporated with IOT. The ESP8266 WIFI component transmits the statistics to end user through text message as well as booking is automatically accepted in record gasoline numeral. This methodology is helpful to shield the human life and thereby preventing LPG blast disaster in particular area.

The idea behind the word “Green Cloud Computing” is to minimize the energy consumed by the hardware that are used in the process of Cloud Computing. It not only achieves efficient processing but also utilizes the computing architecture and also minimizes energy consumption. This concept of going green ensures that growth of cloud computing in the future doesn't affect the environment in a big scale. There has been an enormous increase in energy consumption by data centres and other infrastructure. The aim of this paper is to call attention to some of the effective ways to attain Green Cloud Computing that include Virtualization, installing solar PV arrays and some energy saving techniques. Despite its positive impacts, green cloud computing still faces challenges which are also discussed. This paper also concentrates on the solutions that can be opted for greener clouds.

Fiber metal laminate (FML) belongs to metallic materials class consisting of layers of metal and fiber composite laminates which bonded together. This permits the structure to behave as very simple metal structure with affordable properties such as good resistance to corrosion, high strength to weight ratio, good resistance to fire, better fatigue properties. For the last few decades, the Fiber Metal laminates (FML) which yields high performance as a light weight material and accordingly its increasing demand in aircraft industry have a strong basement towards the development of refined fiber laminated structures. As a hybrid composites these FML’s is a composition of fibers reinforced material bonded with thin metal layers. The most common types of FMLs are CARALL (carbon reinforced aluminum laminate), GLARE (glass reinforced aluminum laminate), ARALL (aramid reinforced aluminum laminate), CentrAl, that bounded by a GLARE core and layers of aluminum. These hybrid composites which have two key constituents namely aluminum metals and fiber-reinforced laminate, offer numerous advantages such as resist fatigue failure and overcome the crack growth mostly in aircraft applications.Glare composed of thin aluminium sheets that are bonded together using an epoxy adhesive film in which glass fibers are embedded. The presence of the epoxy layers causes the attention has to be given to moisture ingress, which can occur during the aircraft service life.An important parameter that might influence the material properties is the service temperature. During the day time the ambient temperature changes from - 40^o to 55^o C. The in-service temperature of the airplane changes from -55^o C to 70^oC. Especially the increased or elevated temperatures could affect the material properties of the epoxy and thus the glare properties. Hence this study mainly focused on temperature influences on glare material when the laminate thickness is considered as variable and total heat flux is calculated for the temperature differences.

In this paper the effect of arc oscillation and pulsed current of gas tungsten arc welding (GTAW)on the microstructure and mechanical properties of aluminium alloy 2219 was studied. Microstructural characterisation of the weld region was carried out using optical micros copy and Electron probe micro analysis (EPMA). Hardness measurements were carried out using Vickers hardness tester to evaluate the hardness in the base metal and weld zone. The microstructures of Arc oscillation and pulsed current (AOPC) welds and continuous current (CC) welds were compared and their hardness were correlated. It was observed that arc oscillation and pulsed current weld resulted in fine equiaxed grain structure whereas continuous current welds resulted in columnar structure. The significant improvement in mechanical properties of arc oscillation and pulsed current welds may be attributed to the discrete copper segregation. Post weld deformation has improved the mechanical properties of arc oscillation and pulsed current welds significantly. Aging can be carried out at lower temperature with prior deformation to improve the mechanical properties of the weld

Drought is a natural and gradual threat, with many devastating consequences for all aspects of human life. Accurate drought forecasting is a promising step to help decision-makers develop strategies to manage drought risks. To achieve this goal, choosing a suitable model plays a vital role in the forecasting method. Various artificial neural network (ANN) models are used to predict short-term and long-term droughts on different time scales using the Standardized Precipitation Index (SPI), including 3, 6, 12, 24, and 48 months in Rajasthan and Gujarat. Due to the frequent danger of drought, people Today are facing many environmental challenges. It affects the environment of the country, community and industry. Some of the adverse effects of the drought threat persist in Pakistan, including other threats. However, early measurement and identification of drought can guide for water resources management to use drought-resistant strategies. In this article, we use the Multilayer Perceptron Neural Network (MLPNN) algorithm to predict drought. 17 weather stations in Daman and Diu.

Network Management Systems (NMSs) are the innovative products used by telecommunication companies to monitor, control, analyze and manage telecommunication networks. Base Transceiver Station (BTS) is a network element which facilitate wireless communication between user equipment and network. BTSs can be integrated with NMS and all related applications available in NMS can be used over BTS. One such application is software upgrade or downgrade in BTS which is termed here as BTS commissioning. This BTS commissioning process involves multiple steps to be performed for successful software upgrade or downgrade in BTS manually through NMS. In this paper methodology to implement end to end automation of BTS commissioning using python is discussed. GUI is developed using JavaScript, jQuery, Flask, Python, HTML and CSS. The reason for using Python for this website is because it is powerful, simple and has many libraries. Developed feature is tested by integrating a test BTS with Nokia’s NMS named NetAct.

Basically, Big Data means large volumes of data that can be used to solve problems. It has piqued people’s attention over the past two decades because of the enormous potential it holds. Big data is generated, stored, and analyzed by a variety of  public  and  private  sector  industries  in  order to enhance the services they provide. Hospital reports, patient medical records, medical test outcomes, and internet of things applications are all examples of big data outlets in the healthcare industry. Biomedical research often produces a large amount of big data that is pertinent to public health. To extract useful information from this data, it must be properly managed and analyzed. Otherwise, finding solutions by analyzing big data quickly becomes impossible. The ability to identify trends and transform large amounts of data into actionable information for precision , medicine and decision makers is at the heart of Big Data’s potential in healthcare. In a variety of areas, the use of Big Data in healthcare is now offering solutions for optimizing patient care and creating value in healthcare organizations. In this paper, some big data solutions are provided for healthcare. Big Data Analytics strategies to mitigate covid-19 health disparities are provided. Finally we analyse some of the challenges with big data in healthcare.

Today people, exchanging their thoughts through online web forums, blogs, and different platforms for social media. In online shopping, they are giving reviews and opinions on other various products, brands, and services. Their thoughts towards a product are do not only purchase decisions of the consumers but also improves the product quality about their requirements and find out the product's particular problem and get an excellent solution on that product. The present system concentrate on the peer-reviewed review model (User-generated review) and global qualification i.e., rating and, tries to classify the semantic aspect and emotions at the time aspect level from the data to investigate general sense feel of the reviews. SJASM represents each review document in the format of opinion pairs and, along with simulating the terms of appearance and the corresponding opinion words of the study, consideration for the hidden aspect and the sentiment detection. The current system is designed as a recommendation system Physiological Language Processing (NLP) Technique to read reviews and using Naïve Baye's Classification automatically. We have also extracted the thoughts of the product characteristics. Here admin can analyze the opinion pair that actually what is defect in the finished product so in future the market of that product will increase. This system to extract product aspects and corresponding opinions from consumer ratings on the internet. Different machine learning algorithms are discussed in Naïve Bayes is considered in order to classify of sentiments, and variables such as precision, recall, F-score, and accuracy are used to assess a classifier's performance.

The present study attempts to find the relationship between assistive technology and cognitive, psychomotor and social performance of students with Intellectual Disability. Assistive Technology Scale, Cognitive Performance Scale, Psychomotor Performance scale and social performance scale developed by the researcher were used to collect data. 200 Samples were drawn from special educators working at an intellectual disability school in Bangalore District. The statistical analysis was done by computing Pearson’s Product Moment Coefficient of Correlation. The study showed a significant relationship between assistive technology and cognitive, psychomotor and social performance of students with intellectual disability.

The new kind of applications known as social electronic applications (or "social e- app's") aid with networking, other applications, known as social networking apps (or "social networking apps" or "SNApp's") and social networking sites (or "SNS's") have become widely used as resources in academics during pandemic. Students have been accustomed to using SNApp and hence participate in non-academic activities on a regular basis. This study examines the impact of widespread use of SNApps on students' academic achievement as well as how these SNApps influenced their commitment to their studies post lockdown after the widespread of “Covid-19”. Because the use of SNApp daily has may harm their performance, it is critical to encourage students to adopt comparable technologies that are solely used to supplement classroom work. SNApp began as a networking communication tool, but it has evolved into much more. "How much time the kids spent on social media" and "How many hours, minutes, and seconds they spent reading messages or going through all of their followers' photographs on these Apps" are never realized. The study examines how the social App influences students' academic performance, focusing on a KKU (Saudi Arabia) students. The study proves that “Covid-19” has forced the students globally to use social networking apps for academic activities. Even if COVID-19 numbers are decreasing, some of the emerging tendencies have remained consistent over time. To get insight into emerging patterns that will have a long-term influence during COVID-19.

This study examines relationship between emotional intelligence, social intelligence and creativity among young adults with high education and the problem of the study is stated as “Psychosocial correlates of young adult students”. The sample size was determined by purposive sampling method (n=100). In this study three standard questionnaires of emotional intelligence, social intelligence and creativity respectively were used. The reliability and validity of these three instruments were reported to be significant in different studies. The findings indicated that there was a significant moderate and negative correlation between emotional intelligence and social intelligence, no significant correlation between emotional intelligence and creativity, and significant moderate positive correlation between social intelligence and creativity of the participants. 

Air Purification is considered to be the vital function to implement in our society for effective and healthy environment. Today, most of the countries are suffering from air pollution which may be caused by Industrial Exhaust, Agricultural activities, Mining operations, Transportations, etc. In these causes, the majority of the pollution occurred in Urban and rural areas are mainly because of Vehicles. To fulfil our daily basic needs, we are all dependent on the transportations. So the pollution caused by the vehicles is inevitable. It is the hardest Challenges to the government to overcome these situations. There are so many technologies for monitoring the air pollution level caused by vehicles and also to control pollution. Still, there is a problem for society which in evoking everyday as because of air pollution. Government is in search for better system for handling and controlling this problem. Here The Proposed System is to target the minimizing level of air pollution, which is caused by the vehicles. 

Brinjal or eggplant is a very important crop (vegetable) of sub-tropics and tropics of India. This plant is highly infested by, Henosepilachna vigintioctopunctata (Coleoptera: Coccinellidae). It is a polyphagous pest in nature, the adult and grub stages cause severe damage to the plants by feeding on its leaves, flowers and vegetables and create a heavy economic loss. Though the beetles could be controlled using synthetic pesticides, indiscriminate use of pesticide in the field causes problems such as pest resistance, environmental and health hazards etc. These pave way for the development of effective ecofriendly pest control measures. Plant based essential oils are used against these insect pests, as they constitute a rich source of bioactive components and reported to have many biological properties. Recently, essential oils were formulated as nanoemulsion and was developed for their effectiveness and eco-friendly nature. In this study, the oil in water (O/W) nanoemulsion of Mentha piperita were prepared by ultrasonication method at different concentrations and examined for the stability study. The stable nanoemulsion was characterized by DLS and was reported to consist with a mean droplet size of 10.84 nm, PDI was 0.1 and zeta potential was -45 mv which proved the good stability of the nanoemulsion. To assess the efficacy of the formulated nanoemulsion, and bulkemulsion, it was screened against the adult beetles, Henosepilachna vigintioctopunctata at different concentrations for 96 hours and the resulted LC₅₀ value of nanoemulsion was 15.84 % which was found to be very effective than the LC₅₀ value of bulkemulsion, which was 60.25 %. Hence from the results obtained, Mentha piperita nanoemulsion may be used as an organic pesticide because of its higher efficacy against the adult beetles, Henosepilachna vigintioctopunctata.

An experiment was conducted on observing the influence of season and growing environment on the performance of leafy coriander var. CO (CR)4. Institute of Agriculture under Tamil Nadu Agricultural University located at Kumulur, Trichy district of Tamilnadu was the experimental station. The experimental design was split plot design with two factors and three replications. Leafy coriander of Rabi season performed well and recorded significantly maximum values in parameters such as  germination percentage (63.36 %), plant height (27.18 cm), number of leaves per plant (36.16), plant height (6.76 g) and yield per hectare (7.29 t/ha) than kharif crop. Similarly coriander under polyhouse recorded maximum germination percentage (62.55 %), plant  height (26.52 cm), number of branches (4.50), number of leaves per plant (36.40), plant height (7.57 g) and yield per hectare (7.99 t/ha). The interaction effect has more influence especially in polyhouse condition during rabi season. The result of the experiment on cultivating coriander under polyhouse during kharif and rabi as well as under shadenet during rabi season will be economically notable.

COVID-19 is a disease caused by coronavirus. 'CO' stands for corona, 'VI' for virus, and 'D' for disease. Formerly, this disease was referred to as '2019 novel coronavirus. The data mining is the best tools for analyzing and predicting the hidden information with the help of pre-existing dataset. The covid analysis and prediction for consider different related parameters namely name of the states, total cases, today cases, active cases, discharged cases, today discharged cases, overall death and today deaths. In this paper, taking consideration into analyzing and predicting covid dataset using statistical techniques namely regression model. Numerical illustrations also provide to prove the results and discussions.

The study based on the conception of green accounting. We all know that in India green accounting is turning around the national and international level. It has an important role in social responsibility of business. It acts as a scanner of the effects of the organization on the environment, society and the economy of the nation. Green accounting provides value management and a combination of accounting and environment through which it facilitates the balance between the growth of both environment and economy. Responsibility regarding environmental development has turned out to be the most important area of responsibility towards society. This paper aims to analyze the effects in reference to the guidelines of green accounting and for implementing the approach of environmental design for upgrade the product. The findings can refer arrangements of green trends for the enterprises in the economy.

Packaging, today, is one of the most important element in the food network, guaranteeing food safety and maintenance of freshness among food products from the factories to the plates. There has been tremendous development in technology in the food sector which offers high quality products, increases the shelf life and also therefore safeguards the food security. Our motivation and the main objective of this review paper is to bring out the fact of how food packaging plays a role in assuring the quality and standards of food and to showcase how intellectual property rights can be used in protecting food packaging. The review paper also focuses on some of the new packaging technologies that have transformed the food sector to meet today’s needs and the impact of food packaging on our environment. Further, this research paper also highlights the regulations governing the packaging and judicial decision.

Semantic Hashing technique wraps the meaning of short texts into compressed binary codes. So, to find out that whether two short texts are alike or not in their meaning, their binary codes need to be matched. A deep neural network is used for encoding. Bag-of-words representation of texts is used to train the neural network. Unfortunately, the fundamental semantics are not sufficiently captured by the above mentioned form of representation for short texts such as titles, tweets, or queries. We propose adding additional semantic signals to better group short texts using their meaning. More specifically, we procure the co-occurring terms and concepts of every term in the short text via a knowledge database to further enhance the short text. Additionally, we use a k-Nearest Neighbor based approach id for hashing. Multiple experiments provide evidence that by increasing the number of semantic signals, our neural network is better capable to capture the meaning of short texts, which enables various uses like retrieving information, classifying data, and processing of short texts.

Sales forecasting plays a significant role in the development and success of consumer-oriented companies. Sales forecasting without high accuracy generates massive losses to the companies. To avoid losses, the company should focus on the factors which are affecting the sales forecasting. Nowadays people prefer e-commerce websites for purchasing products and they give online reviews and ratings about the products. These online reviews are used for computing the sentiment index which is necessary for sales forecasting. This paper surveys the different state-of-the-art sales forecasting techniques with different approaches. This survey also focused the sentiment analysis to predict sales forecasting.  

Aerodynamic efficiency is defined as a ratio of co-efficient of lift to co-efficient of drag.  Reduction of aerodynamic efficiency is a result of wing tip vortices which attributes to induced drag. These vortices are formed due to the difference in pressure between the top and bottom surfaces of the wing. Winglets can be used to improve overall aerodynamic efficiency of a wing. In this study, we will compare the effect of different configurations of winglets – Canted, Fenced, Raked and Spiroid on the aerodynamic efficiency of the wing. A GOE767-il aerofoil wing made of aluminium is modelled and retro-fitted with the above mentioned winglet configurations. CFD analysis for the wing and winglets will be done in three flight conditions – Take-off, Cruise and Landing, to calculate co-efficient of lift and drag. This computational analysis will be done on Ansys Fluent using Spalart – Allmaras turbulence model. The CFD results obtained will be compared based on the efficiency to determine the best winglet configuration for said aerofoil structure and wing parameters. 

Suicides are on the rise all across the world, and depression is a prevalent cause. As a result, effective diagnosis and therapy are required to lessen the symptoms of depression and anxiety. An electroencephalogram (EEG) is a device that measures and records electrical activity from the brain. It can be used to generate a precise assessment on the severity of depression and anxiety. Previous research has shown that EEG data and deep learning (DL) models can be used to diagnose various psychiatric disorders. As a result, this paper offers DeepNet, a DL-based convolutional neural network (CNN) for identifying EEG data from depressed, anxiety and healthy people. This study examines DeepNet's performance in two trials, namely the subject wise split and the record wise split. DeepNet's results have an accuracy of 0.9837, and when record wise split data is used, the area under the receiver operating characteristic curve (AUC) is 0.989.

Cloud computing is one of the widely used technology in the 20^th century. Cloud has become an essential part in our day-to-day life, because the data are stored in the cloud in any one form such as Gmail, Google Drive etc. As the users store sensitive information in the cloud, the Cloud Service Providers need to provide proper data security for data stored in the cloud. There are many issues in Cloud Computing Security. This paper discussed about various issues in the Cloud Computing environment and the future work directions have identified for the Cloud Computing Security.

Design Thinking (DT) has been applied to the corporate world with elan, and organizations have made DT their mainstay.  Tourism in its Sustainable avatar can be seen in Community Based Ecotourism (CBE) which has brought to the forefront the Community who live in the forest fringes to adopt to business opportunities with support from the Government, primarily the Forest Departments (FD) across various states in India, and helped in the creation of special purpose vehicles (SPV) which have provided for livelihood options, income generating opportunities at the same point in time to preserve and conserve the ecology, environment, the flora and fauna, which is the mandate of the FD.  The researcher paper talks about the efforts of applying DT to community-based business activities and with a population which may not be able to appreciate the larger nuances of business, as we seen in the modern contemporary term.  The adoption of DT to businesses and organization, was easily juxtaposed on account of the understanding the associates/employees already had about DT.  But when it came to the community helping them to understand the facets was tough, but once they understand that this is for their betterment, they have never looked back. We realized that the experiences provided by the communities were not short of the corporate world and look forward to implement this further as best practices.