Chennai Region Research Articles

Performance assessment of free standing and building integrated grid connected photovoltaic system for southern part of India

Photovoltaic (PV) system efficiency depends on the geographical location and the orientation of the building. Until installing the building structures, the integration of the PV module must be evaluated with ventilation and without ventilation effects. This work optimises the performance of the 250 kWp grid-connected photovoltaic (GPV) for community buildings in the southern part of India. This simulation is carried out to evaluate the system efficiency of the GPV system under various ventilation conditions, such as free-standing PV (FSPV), building integrated photovoltaic ventilated (BIPV_V) and Building Integrated Photovoltaic without ventilation (BIPV). The PVsyst simulation tool is used to simulate and optimise the performance of the system with FSPV, BIPV and BIPV_V for the region of Chennai (13.2789° N, 80.2623° E), Tamilnadu, India. An annual system energy production is 446 MWh, 409 MWh and 428 MWh of FSPV, BIPV and BIPV_V system respectively. while electrical efficiency for the FSPV, BIPV_V, BIPV system is 15.45%. 15.25% and 14.75% respectively. Practical application: Integrating the grid connected photovoltaic system on the building reduces the energy consumption in the building. The integration of the PV on the roof or semi integrated on the roof is need to be investigated before installing on the buildings. The need for installation of the BIPV with ventilation is explored. This study will assist architects and wider community to design buildings roofs with GPV system which are more aesthetic and account for noise protection and thermal insulation in the region of equatorial climate zones.

The recent trend in mycobacterial strain diversity among extra pulmonary lymph node tuberculosis and their association with drug resistance and the host immunological response in South India

BackgroundTuberculosis (TB) though primarily affects the lungs it may also affect the other parts of the body and referred as extra pulmonary (EPTB). This study is focused on understanding the genetic diversity and molecular epidemiology of Mycobacterium tuberculosis (M.tb) among tuberculous lymphadenitis (TBL), a form of EPTB patients identified in Chennai, Tamil Nadu.MethodsThe genetic diversity was identified by performing spoligotyping on the M.tb clinical isolates that were recovered from lymph node samples. A total of 71 M.tb isolates were recovered from extra pulmonary lymph node samples and subjected to Drug susceptibility testing and spoligotyping was carried out. In addition, immunological characterization from blood of same individuals from whom M.tb was isolated was carried out between the two major lineages groups East African Indian 3 (EAI3) and non-EAI3 strains by ELISA. The results of spoligotyping patterns were compared with the world Spoligotyping Database of Institute Pasteur de Guadeloupe (SpolDB4).ResultsWe found 41 spoligotype patterns and their associated lineages. Out of 41 spoligotype pattern, only 22 patterns are available in the spoldB4 database with Spoligotype international Type (SIT) number and remaining patterns were orphan strains without SIT number. The most predominant spoligotype lineage that was found in lymph node sample in this region of India was EAI (36), followed by central Asian strain (CAS) (6), T1 (5), Beijing (3), Latin American & Mediterranean (LAM) (2), U (1), X2 (1) and orphan (22). In addition to EAI, CAS and Beijing, our study identified the presence of orphan and unique spoligotyping patterns in Chennai region. We observed six drug resistant isolates. Out of six drug resistant isolates, four were resistant to isoniazid drug and associated with EAI family. Moreover, we observed increased levels of type 2 and type 17 cytokine profiles between EAI3 and non-EAI family, infected individuals.ConclusionsThe study confirms that EAI lineage to be the most predominant lineages in EPTB patients with lymphadenitis and were found to have increased type 1 and type 17 proinflammatory cytokine profiles.

Correlating unsoaked CBR with UCC strength for SC and SP soil

Most of the civil engineering structures are constructed on the ground and are supported by soil strata or rock strata present at the site. As soil is heterogeneous, its properties vary from one place to another within a distance of few meters. Thus it is tough to predict the behavior of soil without studying its engineering properties in detail. One of the important laboratory test that is generally conducted for the flexible pavement design is California Bearing Ratio (CBR) test. CBR test is a laborious and time consuming process and may lead to delay in execution of construction projects and thus cause increase in construction costs. Thus an effort has been made to correlate unsoaked CBR value of soil with the UCC strength of soil by Simple Linear Regression Analysis (SLRA) so that based on the UCC strength of soil unsoaked CBR value of soil can be predicted. In this project, 2 types of disturbed soil samples were collected from in and around Chennai region and were classified as Clayey Sand (SC) and Poorly Graded Sand (SP) based on the index properties of each soil. Unconfined Compression (UCC) test and unsoaked CBR test were conducted on the two soil samples by varying the moisture content (MC), to determine whether the maximum strength gain was observed on the dry side or wet side of optimum moisture content (OMC) and to study the extent of increase in UCC and CBR strength compared to control specimen (CS) prepared at OMC. From the results, it was observed that maximum strength gain was attained on the dry side of optimum.

Influence of the biological age of the investor on decision-making in the secondary equity market

PurposeDecision-making in the equity market has been a challenging task for investors belonging to all age groups. This study aims to find linkages between the decision-making techniques in the equity market and the biological age of the investor.Design/methodology/approachThis is an exploratory study and by surveying a sample of 436 secondary equity investors residing in the Chennai region of India, the study measured the decision-making techniques. Using the ANOVA test, the decision-making technique mostly used by investors belonging to an age category was determined. Further, the linkages were investigated in isolation for the male and female investors. By using regression analysis, a model was developed to predict the actual equity return. The financial characteristics of the various age groups were also analyzed using cross-tabulation.FindingsThe results of the study show that the age of the investor plays an important role in the choice of decision-making technique used. The younger investors, who earn the lowest returns were less likely to use industry analysis but more likely to use technical analysis and advocate’s recommendation. Specifically, the younger male investors were less likely to use industry analysis and more likely to use the advocate’s recommendation. The younger female investors were also less likely to use industry analysis. The middle-aged respondents, who earn the highest return were less likely to use technical analysis and advocate’s recommendation owing to lower means. Specifically, the middle-aged male investors were less likely to use the advocate’s recommendation and technical analysis. Then, middle-aged female investors were more likely to use industry analysis.Originality/valueThe findings would be beneficial for financial advisors and wealth managers to suggest age-appropriate strategies for the various investor groups. This age-based profiling of investors would make investors aware of their decision-making techniques and encourage them to make more rational decisions.

Physico-chemical analysis of selected industrial effluents and its treatment using novel biocarbon

In the present research work, Industrial effluents from a sugar industry, thermal power plant and a leather industry wastewater are collected in selected locations in Chennai region during January 2018 to December 2019. In the present research work, the following essential physico-chemical parameters such as colour, pH, electrical conductivity, TDS, TSS, TH, DO, BOD, COD and metals such as calcium and magnesium, anions of chloride, sulphate and nitrate was determined. In addition, selected heavy metals for instance Cu, Cd, Pb, Ni and Cr which are commonly found in the industrial wastewater is quantified for assessing the level of pollution load in the wastewater. In the present research work, the removal of heavy metal pollutants and the organic load was carried out using AIBC as adsorbent and the results indicates that, in sugar, thermal power plant and leather industry wastewater, the percent removal of Cu is 91.23, 90.32 and 81.12 and Cd is 92.34, 94.64 and 92.20, Pb is 93.64, 95.15 and 90.74, Ni is 90.59, 94.79 and 82.31 and Cr is 93.85, 92.38 and 84.95 respectively. In the present investigation, the use of biocarbon produced from the leaves of Lawsonia inermis and interfaced with alumina as support material was used as an effective, low-cost and inexpensive material for the removal of heavy metals Cu, Cd, Pb, Ni and Cr from selected industrial effluent for the treatment of wastewater.

Rainfall Forecasting Based on Surface Data of Chennai Region Using Artificial Neural Networks

In this study, we developed user friendly rainfall forecasting system based on Back propagation Neural Network using MATLAB 7.10 to forecast Hourly rainfall in Chennai region. The dataset of 31488 samples has been collected from Nungambakkam Meteorological Station, Chennai for the period of 2005 to 2015. The data was organized into day-wise hourly recordings as well as day-wise, maximum, minimum, average data of Relative Humidity (RH), Temperature, Pressure and Wind Speed along with Rainfall data. The collected dataset has been used both for training and for testing the data. The developed system gives more accuracy of 94.8197% when the training data set is 55% and the testing data set is 45% with least Mean Squared Error (MSE) value 0.012437.

Knowledge and Awareness about the Mode of Transmission of Vector Borne Diseases among General Public

Vector borne diseases account for more than 17% of other contagious diseases and can be caused either by parasites, bacteria or viruses. Malaria is a parasitic infection caused by female Anopheles mosquitoes. It causes millions of cases globally and most deaths occur in children. Dengue is another vector disease caused by Aedes mosquito and also affects millions of people, also causing more deaths. Other vector diseases may include yellow fever, zika fever, west nile fever, chikungunya, elephantiasis etc. The aim of the study was to assess the knowledge and awareness about the mode of transmission of vector borne disease among the general public and also to analyse the correlation between gender and the level of awareness about vector borne disease among them. A cross sectional questionnaire survey was conducted among people in the region of Chennai. A set of 15 questions including questions on knowledge and awareness on the mode of transmission of vector borne diseases among the general population. It included questions like examples of vector borne diseases, mode of transmission of disease, preventive measures etc. The people of age group between 25-45 years were involved in the survey. There were 100 responses to the survey. The duration of the study was about 7 days. It is clear that the population was aware about the vector borne diseases but not very clear about the preventive measures to be taken to prevent the spread of vector borne diseases.

Investigating the Factors Influence Adoption of Internet Banking in Chennai: Adopters Perspective

The remarkable boom in the usage of the internet has made all banking institutions to make use of the internet for serving their customers retain and benefits, banks delivering all financial services through an online platform through Internet Banking. The track to embrace new technology to gain an advantage in the market gives the bank a new shape called the online Bank. The increased internet usage has made banks influence over the internet to gain a competitive advantage in the sector. This paper focus on the factors that influence the adoption of internet banking by customer”. In this study, descriptive research is used. The study is conducted to obtain data on the adoption of internet banking in Chennai. The study is conducted in the Chennai region. A sample size of 100 was selected using convenience sampling. The study reveals that perceived usefulness and perceived ease of use are the key factors to influence customer adoption of Internet Banking.

Study on Job Autonomy and Job Proficiency of Private School Primary Teachers in Chennai Region

In earlier days, employers felt the job satisfaction component is the only avenue to make employees happy. A lot of research studies proved that internal motivation/drive is also needed for improving employees, thereby giving way for enrichment avenues. One such enrichment avenue is autonomy given in job areas. This study focuses on job enrichment aspects for school-level teachers concentrating primary level teachers in the Chennai region. The enrichment tool analyzed in this paper is job autonomy for teachers that can have a significant effect on task crafting and curriculum analysis. The job proficiency level is compared after skill set improvement. This study is carried out to check the job level independence given to teachers and certain decentralization areas based on interest level. The study is also done to identify the related factors of the job proficiency level of teachers. The method used for collecting data is a convenient sampling method using a well-designed questionnaire. Two hundred samples are collected that are used for the data analysis section. Data analysis is done using statistical methods using Statistical Package for the Social Sciences (SPSS) software and analysis of a moment structures (AMOS) software. Statistical techniques used for this study are linear regression and confirmatory factor output used to check the model fit. Research findings are teacher’s work-based competency levels that significantly affect students’ creativity using mind-mapping techniques. Task autonomy has a significant relationship with curriculum analysis and task crafting. This study recommends analyzing hidden factors of learner’s behavior to improve reflective teaching, leading to the teachers’ proficiency level in their job.

Customer Preferences towards Premium Category Super Food Products in Modern Trade Outlets

The super-food competition in Indian consumer industry is very demanding. Indian consumers have shown growing interest in nutritious and quality food items with high nourishing value, environmental sustainability and food safety. A person with a positive attitude towards the food product of this type is more likely to make a purchase; this makes a marketer's analysis of consumer preference highly important. The primary purpose of this analysis was to examine consumer expectations for quality and safe super food items. The target demographic of this research includes consumers in Chennai region. 173 respondents were chosen using the convenience sampling method. The results of the research study have shown that factors such as ethnicity, monthly income and family status, level of intake, brand knowledge and health issues are linked to customer demand for super-food items. The Structured Equation Modeling methodology was used to define determinants that may describe consumers' propensity for purchasing these groups of food stuffs. Consumers choose food products of this type due to safety considerations, quality issues and environmental concerns, as well as to qualities such as nutritional benefit, taste satisfaction, freshness and attractiveness of organic food items that matter a lot to consumers. This work may be used into further study into the application of various marketing campaigns by advertisers and the examination of other variables.

Spatio-temporal distribution of negative emotions on Twitter during floods in Chennai, India, in 2015: a post hoc analysis

BackgroundNatural disasters are known to take their psychological toll immediately, and over the long term, on those living through them. Messages posted on Twitter provide an insight into the state of mind of citizens affected by such disasters and provide useful data on the emotional impact on groups of people. In 2015, Chennai, the capital city of Tamil Nadu state in southern India, experienced unprecedented flooding, which subsequently triggered economic losses and had considerable psychological impact on citizens. The objectives of this study are to (i) mine posts to Twitter to extract negative emotions of those posting tweets before, during and after the floods; (ii) examine the spatial and temporal variations of negative emotions across Chennai city via tweets; and (iii) analyse associations in the posts between the emotions observed before, during and after the disaster.MethodsUsing Twitter’s application programming interface, tweets posted at the time of floods were aggregated for detailed categorisation and analysis. The different emotions were extracted and classified by using the National Research Council emotion lexicon. Both an analysis of variance (ANOVA) and mixed-effect analysis were performed to assess the temporal variations in negative emotion rates. Global and local Moran’s I statistic were used to understand the spatial distribution and clusters of negative emotions across the Chennai region. Spatial regression was used to analyse over time the association in negative emotion rates from the tweets.ResultsIn the 5696 tweets analysed around the time of the floods, negative emotions were in evidence 17.02% before, 29.45% during and 11.39% after the floods. The rates of negative emotions showed significant variation between tweets sent before, during and after the disaster. Negative emotions were highest at the time of disaster’s peak and reduced considerably post disaster in all wards of Chennai. Spatial clusters of wards with high negative emotion rates were identified.ConclusionsSpatial analysis of emotions expressed on Twitter during disasters helps to identify geographic areas with high negative emotions and areas needing immediate emotional support. Analysing emotions temporally provides insight into early identification of mental health issues, and their consequences, for those affected by disasters.

Employee Engagement and its Influencing Factors Among the Women Lecturers of Self-Financing Arts and Science Colleges in Chennai Region

Employee Engagement and its Influencing Factors Among the Women Lecturers of Self-Financing Arts and Science Colleges in Chennai Region

Monitoring and Intelligible Alert System to control Water Quality in Reverse Osmosis Plants

The classification of drinking water quality severity from RO production plant needs appropriate methods to provide intelligible alert to the operators who involve to carry out remedial action in pace with the production. The proposed technique finds more relevance to detect instantly the quality variations in plant through efficient classification system and drives to reduce the cumbersome of operators. In this paper, it is proposed a SVM based classification method to detect drinking water quality attributes temporally and then precisely classifying severity condition in order to correct quality derivations. A different control scheme is experimented to detect quality variables like pH, TDS, ORP and EC and to support production system. Thus this contributes an automated diagnosis of water quality in RO plant. For classification, SVM is trained with data obtained around 8 plants from West and North of Chennai region. This is demonstrated specifically for a top-level classification job on Quality. On the features extracted from 1280 data, the SVM is trained and achieves a sensitivity of 85% and an accuracy of 90%

An Effective Mechanism for Detecting Crime Rate in Chennai Location Using Supervised Machine Learning Approach

In the current era of digital world, the crime is the important challenge among the distinct user. People are applying various techniques to prevent and reduce the crime. But there is no specific solution is optimal for crime issues. It is need to be tracking the all sets of crimes which is managed and stored in the crime specific database. The proposed work brings the solution to identify the occurrences of the crime for Chennai region and also tracking the location and type of threats over the criem can be detected in the public user group. This mechanism will be achiened the effective outcomes by applying the supervised meachine learning approach.

Different Treatment Modalities followed by Dental Practitioners for Ellis Class 2 Fracture – A Questionnaire-based Survey

Introduction:Dental trauma is one of the most commonly seen injuries involving teeth and surrounding structures. The frequent causes of dental trauma are usually falls, traffic accidents, fights and sports injuries. Rapid treatment can prevent long-term damage to the orofacial structures and save the teeth. Ellis class 2 fracture is classified as the involvement of enamel and dentin excluding pulp. Dental practitioners are used to treating Ellis class 2 fracture very often in their dental practice and is usually considered as a dilemma among dental practitioners for the different treatment modalities followed for treatment of Ellis class 2 fracture. A survey is done among dental practitioners to assess the different treatment modalities followed by them in the case of Ellis class 2 fracture.Materials and Methods:A survey was done among 380 dental practitioners in the Chennai region in which 360 dental practitioners responded. The survey was distributed through electronic media and other means of communication. The survey data was collected, analysed and interpreted.Results:The results suggested that about 90% of dental practitioners had adequate knowledge and attitude towards the management of dental traumatic injuries. However, the practical application of the different treatment modalities was seen to be varied among dental practitioners. Based on this survey it was clear that majority of the dental practitioners in Chennai have good knowledge, attitude but there was a lack of clinical practice regarding the different treatment modalities followed by general practitioners for Ellis class 2 fracture.Conclusion:The survey shows that dental practitioners have a sound knowledge, attitude, but the practical application of the various treatment modalities available was seen to vary among various dental practitioners for Ellis class 2 fracture.

Is There a Difference in Etiology in the Liver Abscesses in South India?: A Clinical and Microbiological Study

Background: Liver abscesses in India are considered to be amoebic in origin. Studies for determining causative organism of liver abscesses in Southern India are limited in number. The present study was conducted to determine the etiology of these abscesses in the Chennai region. Methods: Twenty-three patients with a diagnosis of liver abscess were prospectively studied with full blood profile. Ultrasound-guided pus was aspirated and sent for culture. Amoebic serology was performed. The abscesses were classified as pyogenic, amoebic and indeterminate. Results: Sixteen patients (69.6%) were diagnosed as pyogenic, three (13%) as amoebic and four (17.4%) as indeterminate. Fifteen (5.2%) abscesses were single and 12 (52.3%) affected the right lobe. Escherichia coli (42.85%) and Staphylococcus aureus (35.71%) remained the most common causative organisms grown on pyogenic culture. Conclusion: In this study of a small group of patients from South India, liver abscesses were found to be predominantly single and pyogenic in origin with an equal propensity of gram-positive and gram-negative organisms.

Deep learning-based production assists water quality warning system for reverse osmosis plants

Abstract Classifying water quality irregularities in reverse osmosis (RO) production plants requires suitable systems to provide intelligent warnings to the operators or supervisors who are engaged in executing corrective procedures applicable to production. The suggested deep learning methods are of utmost importance to identify at once variations in water quality irregularities in plants through competent classification methods, thereby enabling a reduction of burden for operators. In this paper, two types of LSTM-CNN based classification techniques are suggested to classify water quality features temporally into grades based on corrective actions that classify irregularity conditions of water quality on the basis of corrections. Distinct control methods are used for experiments to find water quality irregularities from variables, namely, pH, TDS, ORP, and EC, which aim to assist the production line. This proposed method enables automatic diagnosis and warning systems about water quality in RO plants. For classification, LSTM-CNN was trained with data recorded from eight plants of west and north parts of Chennai region. This research is meant to demonstrate particularly the top-level classification job for quality alerts. The features obtained from 4,096 time series array data using LSTM-CNNs achieved sensitivity to 97% and accuracy to 98%.

Relationship of Emotional Intelligence, Workplace Spirituality and Performance

The main objective of this research is to examine the influence of emotional and spiritual intelligence on the performance of selected IT employees working in Chennai city. Spiritual intelligence also makes every individual more concerned with other and the accepted surroundings. Self-Awareness, Self-Regulation and Self-Competence are the construct under Emotional Intelligence. The study population comprised the employee of IT sector at Chennai region. The required sample size was initially arrived by conduction pilot survey. From the pilot study the sample size estimated was 381 and which was collected through stratified random sampling method. The Analysis of Confirmatory Factor was conducted to acquire a measurement model for the research and also to confirm the factor structure identified in the EFA analysis in view to simplify the relationship between observed measures and latent variables. The result indicated that there is no effect between the self-regulatory and self-competence and workplace spirituality and self-awareness on work performance. The results of the study indicate that the spiritual intelligence in IT employees affect the increase or decrease in the job performance of their work place.

Mineralogical influence over the presence of primordial radionuclide along the industrial corridor of northern coastal region of Chennai

The present study focuses on the correspondence between the natural radioactivity and geological parameters such as the textural nature and mineralogical variation of the sediment. The activity concentration of the primordial radionuclide varied in correspondence with the variation in the heavy mineral accumulation along the coastal stretch and the coal ash deposition along the hinterland region. XRD analysis on heavy minerals confirms the presence of heavy mineral—Ilmenite to be present predominantly in the heavy minerals fraction of the samples. The magnetic susceptibility values confirm, the correspondence between the magnetic minerals and materials and the activity concentration of 238U and 232Th in the sediments.

An Experiment in Weather Prediction for North East and South West Monsoon Over Chennai

There is a growing demand for spot specific forecast. Presently this has to be extracted from the regional forecast based on synoptic models. Synoptic models require input from various observatories of regions or the country and the central analysis centre is required for generating the synoptic charts. But recently the authors have established the potential of local data alone as a continuous time scale for use in effective local forecast using data mining techniques. Following the same association rule mining and classifier approach is tried for the forecast of wet and dog days on North East Monsoon and South West Monsoon months for the Chennai region with Latitude 13°11' N and Longitude 80°11' E, a coastal station over Bay of Bengal in South India and results are presented.