Volume 8 | Issue 8 |

 Abstract

Abstract: Background- Medical interns undergo huge amount of pressure. They tend to reduce their amount of sleep and develop altered sleep pattern in an effort to adjust and cope with their workload and stressful environment. Thus, the above situation leads to deprivation of sleep quality. Objectives: To observe sleep quality assessed by Pittsburgh Sleep Quality Index (PSQI) and to study factors associated with it among study population. Aim: To determine factors associated with poor sleep quality. Materials and Methods- This is a cross sectional self-administered questionnaire based study among the 100 medical interns. Data is analysed statistically by MS-Excel 2016 using Chi-square test Results- out of 100 interns, the majority were having poor sleep quality (53%). Female counterparts were found to be good sleepers (56.90%). Maximum students with sleeping arrangement of sleeping alone in a room were having good sleep quality (70.15%). Most of them having sleep duration of 7-8 hours (65.79%) or more (71.43%) were good sleepers. But those having habit of Coffee intake (62.26%) and regular smoking (92%) were found to be having poor sleep quality. Majority of those doing regular exercises were good sleepers (52.94%).Students spending time on electronic media like mobile or laptop for less than one hour were mostly good sleepers (71.43%).All of the above study factors had P value of <0.05. Among those consuming alcohol on regular basis most of them were having poor sleep quality (97.05%), but there was no statistical significance between interns consuming alcohol and those who did not with P value marginally >0.05. Conclusion: As there were statistical differences found in gender, sleeping arrangement, sleep duration, coffee intake, smoking habit, regular exercises and use of electronic devices, these factors are related with the sleep quality of study population.

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Sleep quality, Medical interns, Pittsburgh Sleep Quality Index (PSQI).

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CDMA, GPRS, GSM, UTMS

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In the era of knowledge, it is important to look at education; huge data is getting accumulated for educational purposes. It is the need of time to look at the data figure out patterns and check if the system needs any improvisation. To see useful trends in data, data will have to be clustered. To achieve this, various clustering techniques are used all over the world. This paper presents a comparative study of two such techniques; k-mean and Clustering by fast search and finding density peaks - heat diffusion (CFSFDP-HD). K-Mean, which has been used for a long time; is a robust algorithm and useful when the data is small. This is an iterative algorithm, by changing centroids in each iteration, this will give us a proper and optimum number of clusters. CFSFDP-HD algorithm follows a different and adaptive approach to cluster data where centroids are selected based on the density of data around them. We observed CFSFDP-HD be more efficient and robust as without too many iterations it gives proper clusters.

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Data Mining, Clustering, K-mean, Clustering by fast search, and finding density peaks - heat diffusion.

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The major cause of frailty in older and overweight people is Osteoarthritis. It is a joint illness that generally influences the ligament that could be principally affects the cartilage. Cartilage is a smooth elastic tissue which makes the bones move easily, stabilizes the joint and prevents them from abrading one another. The protective cartilage in Osteoarthritis is ruptured and makes the bones rub one another, inflicting joint stiffness and excessive pain. The current system for the assessment of Osteoarthritis incorporates clinical examination and restorative imaging methods. In this project, by utilizing profound features and medical images we need to recognize and classify OA affected in knee. This can impact on the detection and classification of target area in images and cause of it the irrelevant features could be selected from the medical images. This article will moreover center on dealing the colossal quantity of image information by using high speed computing. This paper also discovers the Magnetic Resonance Imaging (MRI) techniques for detection and classification of Osteoarthritis in descriptive and comparative manner.

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MRI, Osteoarthritis, OA detection, Classification, Machine Learning, Deep learning.

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Investments have gained momentum over the years since it is believed that merely earning money is not enough. One feels the need for a sense of social security in case of unforeseen happenings. The ultimate goal is to boost one�s passive income so as to live a cushy life. Due to the prevalence of this mindset among investors, companies in India were able to raise 114.1 billion USD in 2019. Also, assets managed by mutual funds reached 26.94 trillion USD. To facilitate the hike in one�s passive income, one�s awareness levels with regard to investment should be stimulated from a tender age and one�s mind should be conditioned towards risks associated with the same. In view of the above mentioned scenario, a comprehensive research has been conducted. This research has been conducted to analyse the levels of awareness with regard to the concerned subject, analyse one�s behaviour towards market trends and ascertain the road ahead. From the point of view of those who do not maintain investment portfolios, we wish to ascertain their understanding of the investment market and the financial literacy of both those who invest and also those who do not. Thereby, we wish to point out gaps in one�s knowledge and establish a scope of improvement of awareness levels towards the same. To facilitate the same, a primary research has been conducted to collate Quantitative Data and conduct a Descriptive Research. Under the banner of Descriptive Research, a Single-Cross Sectional Study has been conducted on students across Mumbai ranging from 16 to 25 years of age. The reason for the same is to delve deep into just 1 section of society and develop the necessary findings in a comprehensive manner. The results drawn have shown poor results which range from a low level of investment among students (16 to 25 years of age), which has been attributed to low levels of awareness of investment products and a significantly low level of financial literacy even among those who maintain investment portfolios, to a greater reliance on convenient sources of information to make investment decisions such as family and friends rather than company financial statement analysis or market trend analysis. An increase in the awareness levels of students with regard to traditional investment products such as Mutual Funds, Equity shares, Fixed Deposits and Insurance is advocated with a special focus on Derivatives. Family and friends are encouraged to inculcate the habit of financial statement and market trend analysis in youth around the age of 16 years to facilitate an increase in short and long term investments by students in order to secure the latter�s future.

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Investment, Students, Investment Behaviour, Factors affecting Investment, Significance of Factors, Investment Holding Period, Financial Literacy.

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Hiring academic leader and maintaining qualities in higher education is always challenge in India and eles where. But in India as per guidelines given by UGC at least ten year experience of professorship with good academic and research back ground is needed for VC and NAAC and several governments rating agencies play big role to make Private Universities robust and dynamic. Present study is based on secondary and primary data by close ended question asked to 150 stakeholder of higher education from UP ,UK and ,Bihar . Simple statistics with simple hypothesis are taken into consideration . To know the truth about most burning issue of academia with convection and confidence.

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Academic, Challenge, Professorship, secondary, Convection

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The Internet of Things (IoT) is a key driver for smart city initiatives, making it necessary to have an IT infrastructure that can take advantage of the many benefits that IoT can provide. The Cloudlet is a new infrastructure model that offers cloud-computing capabilities at the edge of the mobile network. This environment is characterized by low latency and high bandwidth, constituting a novel ecosystem where network operators can open their network edge to third parties, allowing them to flexibly and rapidly deploy innovative applications and services towards mobile subscribers. In this paper, we present a cloudlet architecture that leverages edge computing to provide a platform for IoT devices on top of which many smart city applications can be deployed. We first provide an overview of existing challenges and requirements in IoT systems development. Next, we analyse existing cloudlet solutions. Finally, we present our cloudlet architecture for IoT, including design and a prototype solution. For our cloudlet prototype, we focused on a micro-scale emission model to calculate the CO2 emissions per individual trip of a vehicle, and implemented the functionality that allows us to read CO2 data from CO2 sensors. The location data is obtained from an Android smartphone and is processed in the cloudlet. Finally, we conclude with a performance evaluation.

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Cloud Computing, Cloudlet Architecture, Server & Benefits, Internet of Things (IoT).

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Aim and objectives : To estimate the epidemiological profile of acute poisoning patients admitted in Agartala Government Medical College and GBP Hospital. Materials and Methods: This observational study was conducted in Medicine Department of Agartala Government Medical College & GBP hospital between January 2020 to June 2020. Patients admitted to this hospital with a clinical diagnosis of any acute poisoning with drugs or chemicals were the study participants irrespective of age and sex. Results: Overall female (54%) preponderance was observed compared to males(46%). Most of the poisoning cases were from the age group 18 to 24 years (35.8%) followed by age group 25 to 39 years (28.6%). Most common substance for poisoning was Organophosphorus (40%), followed by drugs (23.4%), oleander (17.8%) rodenticide (9.8%), corrosives (7.3%). Home was the most common place where 95% of incidence took place. This study reported that 62% of study population was married while 38 % were unmarried. In the present study, Organophosphorus poisoning was found more among rural population (80%) and the proportion was higher among males (58%). Corrosive ingestion cases were mostly found in adolescent and young adult males in tribal population (93%) and seen more in rural areas (75%). Among the drug abusers, proportion of females were higher (91%). The drugs commonly used are benzodiazepines , nsaids, etc. Oleander poisoning mostly found in males (58%) and in rural areas. In rodenticide poisoning, female proportion is higher (55%), mostly seen in non tribal population (79%) and in rural areas (75%). Among the rodenticide ingestion cases mortality was found to be higher with paste ingestion (95%) than cake (5%). Overall mortality was found to be higher among corrosive(42%) cases. Conclusion: Most of poisoning cases were observed among females though incidence among males not less . Incidence was quite high among married young adults & home was the most common location. Domestic violence was one of the factor behind this suicidal attempts. Organophosphorus compounds, one of the most commonly used poison, was found more in rural areas may be due to its indiscriminate use in farming practices. Corrosive ingestion cases were mostly among tribals may be due to easy availability of corrosives in the villages. The present study raises the epidemiology of different poisons. Large case-control studies are needed to evaluate in details of psychological & economical factors among vulnerable young adults.

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An observational study on acute poisoning in a tertiary care hospital in Tripura

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The global pandemic �COVID-19 hit almost every country and disrupted the economy very hard. As we know to prevent the spread of this virus, the government has taken several steps and this has impacted the retail business of the country. Most Stores except the essentials stores has been shut, and these essentials store is given a certain period to allow them to open, still facing a huge loss as they are not allowed to sell non-essential items and facing inventory loss issues because of the inefficiency of supply chain management. Citizens are being afraid of coming out of the houses and have started doing panic buying looking at the lockdown for several days and thinking they won�t be able to buy in the coming days. We took a survey of 100+ consumers and find out the factors that are affecting or impacting the FMCG sector. Looking at the situation by our eyes itself we researched how this pandemic is impacting the FMCG sector and what was the buying be like before and during the COVID.

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Consumer Behavior, FMCG industry, Retail Industry, Covid19, Pandemic situation, Lockdown, Purchase decision, Grocery, Online purchase, Economic crisis, E-commerce, Disposable income, Essential goods, Bulk buying, Health conscious.

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Abstract To satisfy the demand for ever-increasing data rates in the mobile networks, and that the high demands for the future applications in the 5G system require more capacity. In the microwave band below 6?GHz, most of the available bands are occupied; hence, the microwave band above 6?GHz and mmWave band can be used for the 5G system to cover the bandwidth required for all 5G applications. In this paper, the propagation characteristics at three different bands above 6?GHz (19, 28, and 38?GHz) are investigated in an indoor corridor environment for line of sight (LOS) and non-LOS (NLOS) scenarios. Five different path loss models are studied for this environment, namely, close-in (CI) free space path loss, floating-intercept (FI), frequency attenuation (FA) path loss, alpha-beta-gamma (ABG), and close-in free space reference distance with frequency weighting (CIF) models. Important statistical properties, such as power delay profile (PDP), root mean square (RMS) delay spread, and azimuth angle spread, are obtained and compared for different bands. The paper studied and discusses the comparative propagation model below and above 6 GHz characteristics for 5G wireless networks channels at two different frequency bands. In which two different wireless networks models have been proposed and analyzed to study the loss due to the diffraction from wall edge and the loss of high frequency band. The wideband measurements were summarized and conducted at 3.5 GHz and 28 GHz using a 5G channel sounder including the gains of antennas, with a high chip rate of 1000 Mcps. All the key system parameters are summarized for path loss; excess delay and power delay profile were calculated. The frequency response of the entire system and signal loss due to the edge shadow and high frequency was monitored, investigated and discussed accordingly. Two separate models have been proposed to study and calculate the loss due to the diffraction from wall edge and the loss of high frequency band/ antennas. The wideband including waveguide horn antenna measurements were conducted and calculated at 3.5 GHz and 28 GHz using a 5G channel sounder including the gains of antennas with a high chip rate of 1000 Mcps. The 5G channel parameters for path loss, excess delay and power delay profile were investigated, summarized and calculated. The signal loss due to the edge shadow and high frequency was also investigated.

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 Keywords

Keywords: 5G Networks, Propagation Model Below 6GHz, Propagation Model Above 6GHz, 5G Wireless Networks, frequency bands.

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