Volume 10 | Issue 12 |

 Abstract

To generate electricity, solar cells use either photovoltaic effects or chemical reactions to transform solar energy into heat or chemical power. Solar panels are made up of cell configurations that are used to create solar modules that gather energy from the sun. Processes for large-scale production that can be scaled up A flexible, semi-transparent, and low-cost organic solar cell (OSC) is a promising alternative to traditional photovoltaic cells. The effect of solar-cell thinness and doping concentration on the cell characteristics of TiO2 and GaAs photovoltaic cells was investigated with the use of SCAPS. However, these cells' performance of power transmission remains modest. We ran simulations of n-TiO2/p-GaAs using the SCAPS-1D software. Thin-film solar cells made of n-TiO2/p-GaAs. We assessed a few certain n-TiO2/p-GaAs thermal impact, phase density at the interface, metal work function and other heterojunction factors and Cross-section of electron and hole capture. Our findings demonstrate that raising the density of states of p-type GaAs layers and decreasing user's metal casting functionality can improve the performance of n-TiO2/p-GaAs solar cells. Our findings also show that the best design includes TiO2 as a buffer layer, GaAs as an absorber, and thicknesses of x = 2?m, 4?m, 6?m, 8?m, 10?m, 12?m, 14?m, 16?m and 18?m doped with a concentration of 1.00E+17 cm-3 for all compositions. These solar-cells have a performance of 24.99 %, which is potentially higher than what was previously achieved in the Solar-cell research.

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 Keywords

TiO2/GaAs solar cells, Thin film solar cell, SCAPS-1D, Simulation

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 Abstract

Synthesis and characterization of one-dimensional nanostructures have attracted attention primarily due to their potential myriad applications in different fields including magnetic, electronic and optical devices. There are various techniques used in the fabrication of one-dimensional structures but template synthesis is an elegant, versatile and economic method for synthesizing variety of these one dimensional nanostructures, and so on. Highly ordered Ag2S nanowires each having 100 nm diameters were synthesised into the pores of anodic alumina membrane (AAM) template by using direct chemical deposition method. The nanowires were deposited using silver nitrate as a Ag+ ion source and sodium sulphide as S2- ion source . The nanowires were characterized by Scanning Electron Microscope (SEM) and UV-Vis spectrophotometer to see surface morphology and optical band gap respectively. The as- deposited Ag2S nanowires embedded in AAM are black in colour and having optical band gap 0.95 eV.

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 Keywords

Ag2S nanowires; Anodic Alumina Membrane; Optical band gap

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Khaled Hosseini 's novel The Kite Runner gives a vivid picture of diasporic sensibility. This paper first gives a brief introduction to diaspora and then describes how it impacts people. In the novel, The Kite Runner, the main cause of displacement is the war and violence in the country. This paper seeks how cultural factors affect the lives of immigrants. They miss their homeland in the host country, but for the sake of betterment, they face all the hurdles. They have to deal with issues such as social stratification, cultural crises, rootlessness and nostalgia etc. They also suffer from mental trauma; they think that if they adopt the new culture of the host country, they will lose their own culture as well as their identity, so they always spend their lives in a dilemma of whether to be or not to be.

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 Keywords

Diasporic Sensibility, immigrants, social stratification, cultural crisis, rootlessness, mental trauma

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Creative Commons Attribution 4.0 and The Open Definition

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Over the last few decades, historians and researchers have been increasingly inclined to conduct research on the regional history. From that sence, the interest in knowing the history of Manbhum's freedom struggle has been increased. In 1833, Manbhum district was formed through various setbacks. It was one of the largest districts of India and can be said to be one of the areas of the anti-British war of independence. Many leaderships were emerged at the local, regional, as well as at the national level through this anti-British freedom movement. Their dedication, self-sacrifice, sense of responsibility, taking risk of life was no less than the national leaders. Stapping out beyond the boundaries of the four walls, women also joined the anti-British freedom struggle along with men, whose entire history still remained in darkness. Lavanya Prabha Ghosh, who later became famous as Manbhum Janani, was one of the women leaders who came forward to organize and lead the organization of the women of Manbhum in the anti-British war of independence. The article highlights her role in freedom struggle of Manbhum district.

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 Keywords

Manbhum, Movement, Freedom, Satyagraha, Lavanyaprabha, Shilpashram, British, National, Women, etc.

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Eco-consciousness. Eco-criticism, Temsula Ao, Northeast literature

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Creative Commons Attribution 4.0 and The Open Definition

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With the rapid growth of document storage in modern society, handwritten character recognition has become an important research branch in the field of machine learning and pattern recognition. Meanwhile, how to effectively extract and store the information from documents plays a critical role in the document digitization system, especially in terms of ancient literature storage. However, handwritten characters vary with the writers and writing materials, even handwritten texts with the same content may have many differences, which brings challenges to the establishment of a high reliability recognition system. This project seeks to classify an individual handwritten word so that handwritten text can be translated to a digital form. We used two main approaches to accomplish this task: classifying words directly and character segmentation. For the former, we use Convolution Neural Network (CNN) with various architectures to train a model that can accurately classify words. For the latter, we use Long Short Term Memory networks (LSTM) with convolution to construct bounding boxes for each character. We then pass the segmented characters to a CNN for classification, and then reconstruct each word according to the results of classification and segmentation. This work aims to implement a segmentation strategy in the context of handwritten multi-digit string recognition. The LSTM model is built to be evaluated and benchmarked, also research about the effect of the different training sets on model performance is carried out. Finally, the text can be converted to digits, alphabet, and Tamil characters.

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 Keywords

Deep Learning, Hand Writing Recognition

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

For the easy and flexible management of large scale networks, Software-Defined Networking (SDN) is a strong candidate technology that offers centralisation and programmable interfaces for making complex decisions in a dynamic and seamless manner. On the one hand, there are opportunities for individuals and businesses to build and improve services and applications based on their requirements in the SDN. On the other hand, SDN poses a new array of privacy and security threats, such as Distributed Denial of Service (DDoS) attacks. For detecting and mitigating potential threats, Machine Learning (ML) is an effective approach that has a quick response to anomalies. In this article, we analyse and compare the performance, using different ML techniques, to detect DDoS attacks in SDN, where both experimental datasets and self-generated traffic data are evaluated. Moreover, we propose a simple supervised learning (SL) model to detect flooding DDoS attacks against the SDN controller via the fluctuation of flows. We verify the outcome through simulations and measurements over a real testbed. Our main goal is to find a lightweight SL model to detect DDoS attacks with data and features that can be easily obtained. In this study, DDoS attacks in SDN were detected using machine learning-based models. First, specific features were obtained from SDN for the dataset in normal conditions and under DDoS attack traffic. Then, a new dataset was created using feature selection methods on the existing dataset. Feature selection methods were preferred to simplify the models, facilitate their interpretation, and provide a shorter training time. Both datasets, created with and without feature selection methods, were trained and tested with K-Nearest Neighbors (KNN) classification models. The test results showed that the use of the wrapper feature selection with a KNN classifier achieved the highest accuracy rate Our results show that SL is able to detect DDoS attacks with a single feature. The performance of the analysed SL algorithms is influenced by the size of training set and parameters used. The accuracy of prediction using the same SL model could be entirely different depending on the training set. This project is developed using PYTHON, PyCharm as IDE, Kaggle dataset.

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 Keywords

Software Defined Network, Machine Learning

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Consumers are said to be the main components of the Kerala economy. Using products that are not harmful to nature is essential for the development of Kerala. Change the existing environmental awareness in Kerala and highlight the environmental responsibilities of the society is essential . Water pollution, air pollution and noise pollution are the main problems that Kerala is facing in today's era. This study shows how knowledgeable the people of Kerala are about environmental products. This study is also a journey to answer the question whether the public in Kerala is reluctant to buy green products or not. This study also tries to find out whether consumers are making interventions in Kerala society in such a way as to promote green products. Through this study green products are studied which are acceptable to consumers in Kerala.

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Consumption behaviour, green product, sustainable goods, environmental awareness, environmental friendly goods

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Creative Commons Attribution 4.0 and The Open Definition

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Compacting of concrete is one of the major concepts in civil construction in day-to-day life. The main factors effecting due to improper compacting concrete causes leakages, corrosion which finally leads disintegration of the structure in order to encounter this conflict we prefer good compacting as also compaction plays prominent role in any civil constructions. based on availability resources and type of construction different methods in compaction is preferred. So based on some critical areas and places where human and machine involvement is restricted in those areas we can go prefer for Self-compacting concrete. This is what my thesis completely talks about the process and requirements that necessary to make the study successful.

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 Keywords

Compacting, Admixtures, Filling ability, Passing ability

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In hilly terrains VANET high speed is the real characteristics which leads frequent breakdown, interference, high noise ratio etc. that further leads to more drainage of the battery. Researchers have elaborated several routing protocols that possess different performance levels. In this paper we studied various Ad hoc routing protocols, Reactive, Proactive & Hybrid, taking in to consideration various VANET parameters like Speed, Altitude etc. in Real traffic Scenario taking battery drainage at the altitude of 1500m. The AODV and DYMO (Reactive), OLSR (Proactive) and ZRP (hybrid) protocols are compared for battery model Panasonic AAA standard using Qualnet as a Simulation tool. Since Energy conservation is main focus area nowadays. Hence performance of the protocols with various battery models counts and helps to make a right selection. Varying parameters of VANET shows that in the real traffic scenarios proactive protocol performs more efficiently for energy conservation leads to minimum drainage.

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 Keywords

VANET, Routing Protocols, Battery model, Qualnet, Nodes.

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