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Study of the diffuse ultraviolet background radiation at high galactic latitudes
The diffuse background radiation is observed throughout the whole sky and across every wavelength of the electromagnetic spectrum. The study of this background is of great importance as it contains photons coming from a va- riety of astrophysical environments, traveling over the time scales of a few hundred light years to the age of the universe itself. After the discovery of the cosmic microwave background, the diffuse sky in all the other wave- lengths was studied with great interest as they could provide useful insights into the formation history of the universe. In the work outlined in this the- sis, I will be describing this diffuse background radiation observed in the ultraviolet (UV) region. Over more than three decades of observations of the diffuse sky in the UV has revealed our lack of understanding of all the components that con- tribute to the observed background sky in this wavelength region. Initial studies arrived at controversial conclusions with one group suggesting that most of the observed diffuse surface brightness is due to the dust scat- tered starlight while another group suggested contribution from an exotic component along with the dust scattered component. We will explore this background sky in detail by trying to identify individual components and quantify its contribution at various regions in the sky. We have started our analysis at the Galactic pole regions with |b| > 80 using the data from Galaxy Evolution Explorer (GALEX) in the ultravio- let band. A major Galactic component of the diffuse sky in the UV is the starlight scattered by interstellar dust (also called Diffuse Galactic Light: DGL). We chose to study the Galactic poles due to the low dust environ- ment in these regions and easier modeling of the DGL component. We found consistent offsets in the UV data at a level of 230 290 photons s?1 cm?2 sr?1 1 (hereafter photon units) in the far-UV (FUV: 1539 and 480 580 photon units in the near-UV (NUV: 2316 when the UV surface brightness was compared with Galactic tracers like E(B-V) and the infrared surface brightness. These offsets represent the UV brightness at zero column densities. Part of this offset comes from the extragalactic background light (EBL) originating in background galaxies, Quasi-Stellar Objects (QSOs), etc. After careful estimation of this EBL component, we found a residual UV surface brightness of about 120 180 photon units in the FUV and 300 400 photon units in the NUV. The DGL component came to be about 120 photon units in these regions. We also found evidence for contribution from molecular hydrogen fluorescence at a column density of log NH > 20.2 (NH is in cm?2). We conclude that this contribution from H2 is from the cirrus features present at high Galactic latitudes. We further confirmed our findings at the north and south Galactic poles by studying the region between latitudes 70< b < 80 where we found similar offsets and the fluorescence contribution from H2 at the same levels as in the NGP. We proposed a possible contribution to the observed residual surface brightness coming from Hawking evaporation of Primordial Black Holes. But the level of this radiation was not sufficient to account for the entirety of the observed excess. The failure of this explanation only further deepens the mystery of the source of the excess surface brightness of the UV sky. -
Martian Habitats: A Review
Establishing colonies in Lunar and Martian environments is the major task of our primary means to become a multi-planetary civilization. The Space Exploration Initiative (SEI), administered by President George H.W. Bush in 1989, was the first spark that ignited humanity's vision to establish space settlements beyond low Earth orbit (LEO) (Marc M. Cohen, 2015). At present, private space companies (like SpaceX and Blue Origin) are competing to be the first ones to colonise space. From the late 1980s to the present space race, many space habitat designs to suit human factors, ensure protection from space radiation, and be capable of regulating our day-to-day activities have been proposed for both lunar and martian settlements, respectively. In this paper, only Martian settlements are focused, and the reason for that follows next. While the moon is closer to Earth than Mars, Mars has several other advantages that make it an equal, if not a better candidate for colonisation. Some of the reasons why martian colonisation is preferred over lunar colonization include the presence of an atmosphere on Mars, its resource-rich nature, and its rotation period being closer to Earth's rotation period (Mars has 24.5 hours per day, while the moon has 28-day days) (Kamrun Narher Tithi, 2017). Another added advantage is its proximity to the main belt asteroids, which will further increase the potential for space mining in the future. So this paper will be a review of the various Martian habitat designs proposed over the last one and a half decades in terms of their designs, construction and challenges. To do so, it is assumed that every step associated with delivering the habitats to the Martian environment is achievable. These steps include the following: propulsion systems for long-term spaceflights; launch vehicles capable of lifting the habitats and fitting the habitat modules within them (Marc M. Cohen, 2015). Copyright 2023 by the International Astronautical Federation (IAF). All rights reserved. -
Effects of supply chain integration on firms performance: a study on micro, small and medium enterprises in India
The cooperation in the supply chain assumes an adequate job for enhancing an organisation's performance and increasing competitive advantage. Supply Chain Integration (SCI) affects organisational performance. This paper studies the impact of the integration of supply chain procedures and practices on organisational performance and explores the effect of SCI on organisational performance at Micro, Small and Medium Enterprises (MSMEs) in Madurai District, Tamilnadu, India. A questionnaire is developed with validated measurement scales from previous studies and empirical data are collected through a survey questionnaire from 250 randomly selected MSMEs. This research provides sound recommendations to MSMEs in Madurai District, Tamilnadu, India, and maybe used for different industries and decision making policies. Finally, the study will contribute to the scientific field by providing some future studies. 2020 by the authors; licensee Growing Science, Canada. -
Causality and volatility spillovers of banks' stock price returns on BSE Bankex returns
This paper investigates the causal relationships and volatility spillovers between the BSE Bankex index and the stock prices of five major Indian banks (Axis Bank, HDFC Bank, ICICI Bank, Kotak Bank, and SBI). Daily data from January 2, 2018 to March 8, 2023 are used, and statistical techniques such as descriptive statistics, Unit Root test, Cointegration test, Ganger Causality test, OLS regression, and GARCH model are employed. The study finds bidirectional causal relationships between the bank stocks and BSE Bankex returns, suggesting that the movement of the bank stocks significantly affects the overall market returns and vice versa. The study also finds significant volatility spillovers between the bank stocks and BSE Bankex returns, implying that the shocks in the bank stocks affect the market returns and vice versa. The study's outcomes have practical implications for investors and policymakers. Investors can use the results to make informed investment decisions in the Indian stock market, while policymakers can use the findings to monitor the financial stability of the banking sector and design appropriate policy interventions to address any potential financial crises. Overall, the study's findings suggest that policymakers should proactively monitor and manage market risks to safeguard overall financial stability. 2023 Wiley Periodicals LLC. -
Enhancing business capabilities through digital transformation, upscaling, and upskilling in the era of Industry 5.0: A literature review
This literature review aims to understand the recent developments in the field of upscaling and upskilling in the digital transformation of business, from an Industry 5.0 prospective. It used a comprehensive search of relevant peer-reviewed journal articles, industry reports, and online sources to gather the relevant data. The findings indicate that upscaling is essential for industry 5.0, and that businesses should invest in upskilling and upscaling programs to meet the changing demands of the digital economy. This literature review provides a comprehensive analysis of the current state of upscaling and upskilling in the digital transformation of business and provides insights into the future direction of this field. It also highlights the importance of collaboration between businesses, governments, and educational institutions to ensure that the workforce is prepared for the future of work. 2024, IGI Global. All rights reserved. -
Sale and transplantation of human organs in india critical evaluation of the legal framework
The demand for the organ transplantation far exceeds the availability of organs or donors. This leads to unfair trade and commerce in human organs. Though India has a legal framework to regulate various aspects of organ transplantation the same does not seemed to have addressed the issue either adequately or comprehensively. The supply of donated organs has been inadequate for years. Current methods of obtaining organs and tissues have not provided an adequate supply of organs for use in transplantation. Obviously, the problem of scarcity is acute newlinefor the individuals who require organ transplants.Organ Transplantation is a lifesaving method.But, still it is unclear whether existing law is adequate to curb the organ sale and regulate organ transplantation. Although the general field of transplantation is still in a state of change and growth, there have been recent developments in legislation, especially giving priority to the genuine consent of the donor. Although the majority of legislation has been written for cadaver organ donation, slowly, regulation is developing for living organ donation as well.The advantages of cadaver transplantation are obvious: the dead donor encounters no risk in the performance of the transplantation operation. At present this is the only way that a vital organ newlinecan be replaced. The donor, once pronounced dead, is not exposed to any of the hazards which face the live donor. The laws of different countries allow either the potential organ donor to consent or dissent to the donation during his life time, or his relatives to consent or dissent after newlinehis death. Due to these different legislative possibilities, the number of donations per million people varies substantially in different countries. In most countries with the dissent solutions, newlinethere is no waiting list for donations, or the list is short, while most countries with consent solutions have substantial organ shortages. -
Studies on the Culture Conditions, Nutritional Value of the Black Soldier Fly, Hermetia illucens (Diptera : Stratiomyid) and its Suitability as Aquaculture Feed
The Black Soldier Fly (BSF), Hermetia illucens, has emerged as a promising newlinesolution in aquaculture due to its remarkable ability to convert organic waste into newlineprotein-rich biomass. This has garnered interest among aquaculturists seeking costeffective and sustainable alternative ingredients for aqua feed. However, fully newlineharnessing the potential of this insect requires a deeper understanding of its life cycle and nutritional composition. A key challenge in utilising BSF larvae (BSFL) for newlineaquafeed production is the lack of standardized culture systems. This study addresses this gap by establishing a comprehensive culture system using two common organic wastes, fruit waste (FW) and vegetable waste (VW), as rearing substrates. By evaluating the growth performance of BSFL reared on these substrates, the research sheds light on optimal conditions for large-scale BSF production. The study investigated the impact of FW and VW substrates on BSFL growth through a thorough analysis of growth performance, morphometric measurements and newlineScanning Electron Microscopy (SEM). Results showed that BSFL reared on FW exhibited better growth (40 days) than those reared on VW (46 days). Morphometric analysis and SEM identified five larval stages and the prepupa, pupa, and adult stages. Additionally, the study analysed the nutritional composition of BSFL at different newlinedevelopmental stages, such as Instar 3 through instar 5, prepupa and pupa, including newlineprotein, carbohydrate, lipid, amino acids and fatty acids. This provided insights into newlinehow variations in substrate impact the nutritional quality of BSFL at different stages, which is crucial for ensuring that BSFL-derived feed meets the dietary requirements of target aquaculture species. Significant differences were found in the proximate composition of the substrates (FW and VW), resulting in significant variations in BSFL nutrition. BSFL reared on FW exhibited higher nutritional content especially crude newlineprotein (54.160.64%), than those reared on VW, except for crude lipids (2.200.01%). -
Stress mindset as a mediator between self-efficacy and coping styles
Stress mindset is a lens through which one views stress and its consequences as beneficial or harmful for them. It is a distinct variable that differs from frequency, amount, and intensity of stress. The literature review indicated that stress mindset could mediate the link between self-efficacy and coping style, which was previously not tested. Hence, the study aimed; 1) to examine the relationship between self-efficacy, stress mindset, and coping style; 2) to investigate the influence of stress mindset and self-efficacy on coping styles; 3) to find whether stress mindset mediates the association between self-efficacy and coping styles. The study employed a correlational research design, whereby through multi-phase sampling recruited 727 participants (male = 300, female = 427, mean age = 16.26) studying in 11th and 12th standard. The researchers administered validated stress mindset, self-efficacy, and coping style and performed a multiple correlational and regression analysis. They computed mediation analysis using Hayes model 4 in Process Macro. The finding indicated that the association between self-efficacy and self-controlling coping style is mediated by stress mindset. Furthermore, it mediated the connection between some sub-domains of self-efficacy and coping styles. The data were evident to infer that individual with high self-efficacy can interpret social stressors as beneficial and improve their coping skills. 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Efficiency Enhancement using Least Significant Bits Method in Image Steganography
Over the years, there has been a tremendous growth in the field of steganography. Steganography is a technique of hidden message passing i.e. transferring a message which is not visible to human eyes, through some media such as an image, music, games etc. In this particular article we focus on Image steganography which has its own advantages and has undergone a lot of improvements in the past years. The most basic image steganography can be achieved by changing the LSBs (Least Significant Bits) of the image pixels. These bits can usually be called the redundant bits. However, changing a large numbers of LSBs of an image can distort the image to an extent where it would be easily noticeable that the image maybe carrying a hidden message rendering it useless. These LSBs are changed according to the message bits allowing the person to hide their data which can be decoded later by reading the LSBs of image pixels. This paper introduces and explains a method to improve the efficiency of LSB method. 2022 IEEE -
Role of Marital Status of Parents on Self-esteem, Happiness and Academic-achievement among Adolescents
Adolescence is that development period of human life where the adolescent learns the knowledge of reasoning, critical thinking, problem solving behavior, emotional intelligence, and managing relationships. In today???s society, divorce has become a common affair. A child perception of divorce will be largely determined by age and gender. The purpose of the current study was to find out the role of marital status of parents and gender in self-esteem, happiness and academic achievement of adolescents. Four CBSE schools from Bhubanseswar, Odisha were contacted for the data collection. Total number of samples was 60 students of separated family and 60 students from intact family were selected randomly for the study of happiness, selfesteem and academic achievement. Among each 60 sample 30 were female and 30 were male to check the effect of gender on happiness, self-esteem and academic achievement of adolescents. The result of the study shown that adolescents with divorced parents has less happiness score, low self-esteem and less academic achievement in comparison to adolescents with both parents. On gender basis it was found out that female adolescents have less happiness score and low selfesteem in comparison to male adolescents. But female adolescents have shown high academic achievement in comparison to male adolescents. Adolescence is the vulnerable time period of a human???s life span. The adolescents need to get proper love, affection, attention from parents and society. Parents play a vital role in adolescents??? life. According to the current study the adolescents with divorced parents need to get proper support, love and counseling if necessary. -
A Narrative Review on Experience and Expression of Anger Among Infertile Women
Infertility is stressful among women though there are several technological advancements in treating infertility. Anger is a powerful emotion resulting due to stigma and oppression due to infertility, especially among women. Studies have also proven that women have a poor quality of life in the context of infertility. Women are prone to suppressing anger rather than dealing with anger in the present. Psychosocial intervention and psychoeducation help women manage anger and maintain healthy quality of life. Springer Nature Switzerland AG 2023. -
Statistical Analysis of Ecological Mathematical Model Based on Data Warehouse
Persistence of ecosystems, existence and stability of periodic and almost periodic solutions, and global attractiveness are important research contents in ecological mathematical theory. This article takes the ocean as an example to illustrate. The marine ecological model management system integrates marine technology, Internet technology and database technology. The purpose is to collect, organize and analyze mathematical models related to marine ecosystems, integrate them according to certain classification principles, and store them in the form of text. In the database, the query of the database according to the important parameters in the mathematical model or the classification of the mathematical model is provided on the Internet, and the queried mathematical model is displayed on the screen through the browser. This paper adopts the method of data warehouse. How to effectively use resources is an important aspect of whether to take the initiative in competition. Data warehouse can play the characteristics of information processing and has broad application prospects in the face of competition in the field of telecommunications. 2023 IEEE. -
Predicting Wind Energy: Machine Learning from Daily Wind Data
This paper offers a comprehensive review of the advancements in the realm of renewable energy, specifically focusing on solid oxide fuel cells and electrolysers for green hydrogen production. The review delves into the significance of wind energy as a pivotal renewable energy source and underscores the importance of precise forecasting for efficient energy management and distribution. The integration of machine learning-based approaches, such as Support Vector Regression and Random Forest Regression, has shown promising results in enhancing the accuracy of wind energy production forecasts. Furthermore, the paper explores the broader landscape of renewable energy generation forecasting, emphasizing the rising prominence of machine learning and deep learning techniques. As the penetration of renewable energy sources into the electricity grid intensifies, the need for accurate forecasting becomes paramount. Traditional methods, while valuable, have encountered limitations, paving the way for advanced algorithms capable of deciphering intricate data relationships. The review also touches upon the inherent challenges and prospective research avenues in the domain, including addressing uncertainties in renewable energy generation, ensuring data availability, and enhancing model interpretability. The overarching goal remains the seamless integration of renewable sources into the grid, propelling us towards a greener future. The Authors, published by EDP Sciences, 2024. -
Stress Level Detection in Continuous Speech Using CNNs and a Hybrid Attention Layer
This paper mainly targets stress detection by analyzing the audio signals obtained from human beings. Deep learning is used to model the levels of stress pertaining to this whole paper followed by an analysis of the Mel spectrogram of the audio signals is done. A hybrid attention model helps us achieve the required result. The dataset that has been used for this article is the DAIC-WOZ dataset containing continuous speech files of conversations between a patient and a virtual assistant who is controlled by a human counselor from another room. The best results obtained were a 78.7% accuracy on the classification of the stress levels. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024. -
Lane Detection using Kalman Filtering
Autonomous vehicles are the future of transportation. Modern high-tech vehicles use a sequence of cameras and sensors and in order to assess their atmosphere and aid to the driver by generating various alerts. While driving, it is always a challenging task for drivers to notice lane lines on the road, especially at night time, it becomes more difficult. This research proposes a novel way to recognize lanes in a variety of environments, including day and night. First various pre-processing techniques are used to improve and filter out the noise present in the video frames. Then, a sequence of procedure with respect to lane detection is performed. This stable lane detection is achieved by Kalman filter, by removing offset errors and predict future lane lines. 2023 Elsevier B.V.. All rights reserved. -
COVID-19 Effects on Learning Behaviour of Tourism Students for Sustainable Education: The Malaysian Context
According to the World Health Organization (WHO), the alarming spread of coronavirus (COVID-19) began to shock the world on 31 December 2019, and it was first detected in Wuhan, Hubei, in China when a patient presented with pneumonia. To date, the virus has recorded over 2,088,663 cases worldwide. The impact of COVID-19 would be precisely worrying as it aggravated not only tourism but also the learning behaviour of tourism students. What are the effects of the COVID-19 pandemic on the learning behaviour of tourism students? What lessons could be learned to make it more sustainable for the students? And finally, what would be the suggested resilient strategies for the tourism students in the post-pandemic era? There is no original study conducted to focalise investigation on revealing the negative characteristics of COVID-19 and the learning curve of university students in Malaysia. However, the main objectives of this chapter are to provide an overview of the effects of COVID-19 in the learning behaviour of tourism students for sustainable education and the factors that distress students minds and how these helped students to share the positive aspects with others. It is gradually visible that the effects of COVID-19 on learning behaviour and dangers to university students in Malaysia and their significance on students emotional change or learning behaviours are not well perceived. This chapter recommends that educational institutions produce studies to proliferate and document the pandemics impact on the educational system. It is crucial for tourism students for sustainable education in the current time. 2023 Priyakrushna Mohanty, Anukrati Sharma, James Kennell and Azizul Hassan. -
Diversifying investor's portfolio using bitcoin: An econometric analysis
Rational investors look into maximizing returns with minimal risk. Since this is highly unlikely, optimizing risk and return is a practical solution. Bitcoin is a new financial product that can be included in an investment portfolio. This paper looks at Bitcoins as a separate asset class and attempts to capture the volatility using the Exponential GARCH (E-GARCH) as well as to check if Bitcoins can be used as an optimal tool to hedge using the Dynamic Conditional Correlation GARCH against four traditional asset classes in the U.S. economy which includes the stock market (S&P 500 index), Bonds (U.S. Aggregate Bond Index), Gold and Crude Oil. The period of study is a little over 7 years. The results suggest that Bitcoin stands as a highly speculative class of asset with extremely high volatility and with respect to hedging, Bitcoin stands as a possible tool of hedge with the U.S. Aggregate Bond index and to a certain extent against Gold but fails to be an optimal hedge against the S&P 500 and Crude Oil in the U.S. economy between April 29, 2013 and October 31, 2019 due to its highly volatile nature. 2020 John Wiley & Sons, Ltd. -
KMSBOT: enhancing educational institutions with an AI-powered semantic search engine and graph database
In the rapidly evolving field of education, a semantic search engine is essential to efficiently retrieve knowledge experts data. Universities and colleges continuously generate a vast amount of educational and research data. A semantic search engine can assist students and staff in efficiently searching for required information in such a big data pool. The existing systems have limitations in providing personalized recommendations that align with the individual learning objectives of students and scholars, thus hindering their educational experience. To address this, this paper proposed a KMSBOT. This novel recommendation system effectively summarizes academic data and provides tailored information for students, research scholars, and faculty, enhancing educational experiences. This paper meticulously details the development of KMSBOT, which comprises a neo4j-based knowledge graph technique, the NLP method for data structuring, and the KNN machine learning model for classification. The system employs a three-module approach, utilizing data structuring, NLP processing, and semantic search engine integration. By leveraging Neo4j, NLTK, and BERT in Python, this proposed work ensures optimal performance metrics such as time, accuracy, and loss value. The proposed solution addresses traditional recommendation systems limitations and contributes to a brighter future, improving user satisfaction and engagement in academic environments. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
Smart Skin Cancer Diagnosis: Integrating SCA-RELM Method for Enhanced Accuracy
One out of three cancers now is skin cancer, a figure that has exploded in the previous several decades. Melanoma is the worst kind of skin cancer and occurs in 4% of cases. It is also the most aggressive type. The health and economic impact of skin cancer is substantial, especially given its rising incidence and fatality rates. However, with early detection and treatment, the 5-year survival rate for skin cancer patients is much improved. As a result, a lot of money has gone into studying the disease and developing methods for early diagnosis in the hopes of stopping the rising tide of cancer cases and deaths, particularly melanoma. In order to enhance non-invasive skin cancer diagnosis, this research examines a range of optical modalities that have been utilized in recent years. The suggested system uses image processing to identify, remove, and categorize lesions from dermoscopy images; this system will greatly aid in the detection of melanoma, a type of skin cancer. A median filter is employed for preprocessing. Using watershed and clever edge detector, it can segment objects. The BOF plus SURF method is employed for feature extraction. It employs SCA-RELM, which performs better than the other two conventional approaches, to train the model. 2024 IEEE. -
Melanoma Skin Cancer Detection using a CNN-Regularized Extreme Learning Machine (RELM) based Model
Recent years have brought a heightened awareness of skin cancer as a potentially fatal type of human disease. While all three forms of skin cancer - Melanoma, Basal, and Squamous are terrifying, Melanoma is the most erratic. Melanoma cancer is curable if caught at an early stage. Multiple current systems have demonstrated that computer vision can play a significant role in medical image diagnosis. This study suggests a new approach to picture categorization that can help convolutional neural networks train more quickly (CNN). CNN has seen widespread use in multiclass image classification datasets, but its poor learning performance for huge volumes of data has limited its usefulness. On the other hand, whereas Regularized Extreme Learning Machine (RELM) are capable of rapid learning and have strong generalizability to improve their recognized accuracy quickly. This study introduces a novel CNN-RELM, a novel classifier that integrates convolutional neural networks with regularized extreme learning machines. CNN-RELM begins by training a Convolutional Neural Network (CNN) through the gradient descent technique until the desired learning and target accuracy is achieved. This approach outperforms the CNN and RELM model with an accuracy of around 98.6%. 2023 IEEE.