Abstract: | Cement industry ranks 2nd in energy consumption among the industries in India. It is one of the major emitter of CO2, due to combustion of fossil fuel and calcination process. As the huge amount of CO2 emissions cause severe environment problems, the efficient and effective utilization of energy is a major concern in Indian cement industry. The main objective of the research work is to assess the energy cosumption and energy conservation of the Indian cement industry and to predict future trends in cement production and reduction of CO2 emissions. In order to achieve this objective, a detailed energy and exergy analysis of a typical cement plant in Kerala was carried out. The data on fuel usage, electricity consumption, amount of clinker and cement production were also collected from a few selected cement industries in India for the period 2001 - 2010 and the CO2 emissions were estimated. A complete decomposition method was used for the analysis of change in CO2 emissions during the period 2001 - 2010 by categorising the cement industries according to the specific thermal energy consumption. A basic forecasting model for the cement production trend was developed by using the system dynamic approach and the model was validated with the data collected from the selected cement industries. The cement production and CO2 emissions from the industries were also predicted with the base year as 2010. The sensitivity analysis of the forecasting model was conducted and found satisfactory. The model was then modified for the total cement production in India to predict the cement production and CO2 emissions for the next 21 years under three different scenarios. The parmeters that influence CO2 emissions like population and GDP growth rate, demand of cement and its production, clinker consumption and energy utilization are incorporated in these scenarios. The existing growth rate of the population and cement production in the year 2010 were used in the baseline scenario. In the scenario-1 (S1) the growth rate of population was assumed to be gradually decreasing and finally reach zero by the year 2030, while in scenario-2 (S2) a faster decline in the growth rate was assumed such that zero growth rate is achieved in the year 2020. The mitigation strategiesfor the reduction of CO2 emissions from the cement production were identified and analyzed in the energy management scenarioThe energy and exergy analysis of the raw mill of the cement plant revealed that the exergy utilization was worse than energy utilization. The energy analysis of the kiln system showed that around 38% of heat energy is wasted through exhaust gases of the preheater and cooler of the kiln sysetm. This could be recovered by the waste heat recovery system. A secondary insulation shell was also recommended for the kiln in the plant in order to prevent heat loss and enhance the efficiency of the plant. The decomposition analysis of the change in CO2 emissions during 2001- 2010 showed that the activity effect was the main factor for CO2 emissions for the cement industries since it is directly dependent on economic growth of the country. The forecasting model showed that 15.22% and 29.44% of CO2 emissions reduction can be achieved by the year 2030 in scenario- (S1) and scenario-2 (S2) respectively. In analysing the energy management scenario, it was assumed that 25% of electrical energy supply to the cement plants is replaced by renewable energy. The analysis revealed that the recovery of waste heat and the use of renewable energy could lead to decline in CO2 emissions 7.1% for baseline scenario, 10.9 % in scenario-1 (S1) and 11.16% in scenario-2 (S2) in 2030. The combined scenario considering population stabilization by the year 2020, 25% of contribution from renewable energy sources of the cement industry and 38% thermal energy from the waste heat streams shows that CO2 emissions from Indian cement industry could be reduced by nearly 37% in the year 2030. This would reduce a substantial level of greenhouse gas load to the environment. The cement industry will remain one of the critical sectors for India to meet its CO2 emissions reduction target. India’s cement production will continue to grow in the near future due to its GDP growth. The control of population, improvement in plant efficiency and use of renewable energy are the important options for the mitigation of CO2 emissions from Indian cement industries |
Description: | Division of safety and Fire Engineering, School of Engineering, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/4727 |
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Dyuthi-T1833.pdf | (5.356Mb) |
Abstract: | The nearshore marine ecosystem is a dynamic environment impacted by many activities, especially the coastal waters and sediments contiguous to major urban areas. Although heavy metals are natural constituents of the marine environment, inputs are considered to be conservative pollutants and are potentially toxic, accumulate in the sediment, are bioconcentrated by organisms and may cause health problems to humans via the food chain. A variety of metals in trace amounts are essential for biological processes in all organisms, but excessive levels can be detrimental by acting as enzyme inhibitors. Discharge of industrial wastewater, agriculture runoff and untreated sewage pose a particularly serious threat to the coastal environment of Kerala, but there is a dearth of studies in documenting the contaminant metals. This study aimed principally to assess such contamination by examining the results of heavy metal (Cu, Pb, Cr, Ni, Zn, Cd and Hg) analysis in seawater, sediment and benthic biota from a survey of five transects along the central and northern coast of Kerala in 2008 covering a 10.0 km stretch of near shore environment in each transect. Trophic transfer of metal contaminants from aquatic invertebrates to its predators was also assessed, by employing a suitable benthic food chain model in order to understand which all metals are undergoing biotransference (transfer of metals from a food source to consumer).The study of present contamination levels will be useful for potential environmental remediation and ecosystem restoration at contaminated sites and provides a scientific basis for standards and protective measures for the coastal waters and sediments. The usefulness of biomonitor proposed in this study would allow identification of different bioavailable metals as well as provide an assessment of the magnitude of metal contamination in the coastal marine milieu. The increments in concentration of certain metals between the predator and prey discerned through benthic food chain can be interpreted as evidence of biotransference. |
Description: | School of Environmental Studies Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/3746 |
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Dyuthi-T1707.pdf | (8.182Mb) |
Abstract: | Microcosm studies were performed to evaluate the survival of Escherichia coli, Salmonella paratyphi and Vibrio parahaemolyticus in water and sediment collected from the freshwater region of Vembanad Lake (9 35◦N 76 25◦E) along the south west coast of India. All three test microorganisms showed significantly (p < 0.01) higher survival in sediment compared to overlying water. The survival in different sediment types with different particle size and organic carbon content revealed that sediment with small particle size and high organic carbon content could enhance their extended survival (p < 0.05). The results indicate that sediments of the Lake could act as a reservoir of pathogenic bacteria and exhibit a potential health hazard from possible resuspension and subsequent ingestion during recreational activities. Therefore, the assessment of bacterial concentration in freshwater Lake sediments used for contact and non contact recreation has of considerable significance for the proper assessment of microbial pollution of the overlying water, and for the management and protection of related health risk at specific recreational sites. Besides, assessment of the bacterial concentration in sediments can be used as a relatively stable indicator of long term mean bacterial concentration in the water column above |
Description: | International Journal of Hygiene and Environmental Health 214 (2011) 258– 264 |
URI: | http://dyuthi.cusat.ac.in/purl/3919 |
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An assessment o ... ated with the extended.pdf | (727.3Kb) |
URI: | http://dyuthi.cusat.ac.in/purl/5093 |
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Dyuthi- T 2159.pdf.pdf | (4.548Mb) |
Abstract: | The cumulative effects of global change, including climate change, increased population density and domestic waste disposal, effluent discharges from industrial processes, agriculture and aquaculture will likely continue and increases the process of eutrophication in estuarine environments. Eutrophication is one of the leading causes of degraded water quality, water column hypoxia/anoxia, harmful algal bloom (HAB) and loss of habitat and species diversity in the estuarine environment. The present study attempts to characterize the trophic condition of coastal estuary using a simple tool; trophic index (TRIX) based on a linear combination of the log of four state variables with supplementary index Efficiency Coefficient (Eff. Coeff.) as a discriminating tool. Numerically, the index TRIX is scaled from 0 to10, covering a wide range of trophic conditions from oligotrophic to eutrophic. Study area Kodungallur-Azhikode Estuary (KAE) was comparatively shallow in nature with average depth of 3.6±0.2 m. Dissolve oxygen regime in the water column was ranged from 4.7±1.3 mgL−1 in Station I to 5.9±1.4 mgL−1 in Station IV. The average nitrate-nitrogen (NO3-N) of KAE water was 470 mg m−3; values ranged from Av. 364.4 mg m−3 at Station II to Av. 626.6 mg m−3at Station VII. The mean ammonium-nitrogen (NH4 +-N) varied from 54.1 mg m−3 at Station VII to 101 mg m−3 at Station III. The average Chl-a for the seven stations of KAE was 6.42±3.91 mg m−3. Comparisons over different spatial and temporal scales in the KAE and study observed that, estuary experiencing high productivity by the influence of high degree of eutrophication; an annual average of 6.91 TRIX was noticed in the KAE and seasonal highest was observed during pre monsoon period (7.15) and lowest during post monsoon period (6.51). In the spatial scale station V showed high value 7.37 and comparatively low values in the station VI (6.93) and station VII (6.96) and which indicates eutrophication was predominant in land cover area with comparatively high water residence time. Eff. Coeff. values in the KAE ranges from −2.74 during monsoon period to the lowest of −1.98 in pre monsoon period. Present study revealed that trophic state of the estuary under severe stress and the restriction of autochthonous and allochthonous nutrient loading should be keystone in mitigate from eutrophication process |
Description: | Mitig Adapt Strateg Glob Change (2012) 17:837–847 |
URI: | http://dyuthi.cusat.ac.in/purl/4450 |
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Assessment of t ... hikode estuary, India).pdf | (288.9Kb) |
URI: | http://dyuthi.cusat.ac.in/purl/5328 |
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Dyuthi T-2364.pdf | (136.4Mb) |
Abstract: | Everywhere, on the coastal belt it is proved without doubt that the pristine ground water quality was severely deteriorated after the 26 December 2004 Indian Ocean Tsunami. But how far is more relevant, as it is decided by the so-called pre-tsunamic situation of the region. In water quality studies it is this reference finger print which earmarks regional ground water chemistry based on which the monthly variability could rationally be interpreted. This Ph D thesis comprises the testing and evaluation of the facts: whether there is any significant difference in the water quality parameters under study between stations and between months in Tsunami Affected Dug Wells (TADW). Whether the selected water quality parameters vary significantly from BIS and WHO standards. Whether the water quality index (WQI) differ significantly between Tsunami Affected Dug Wells (TADW) and Bore Wells (BW). Whether there is any significant difference in the water quality parameters during December 2005 and December 2008. Is there any significant change in the Water Quality Parameters before 2001 and after tsunami (2005) in TADW. |
Description: | School of Environmental Studies, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/3708 |
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Dyuthi-T1666.pdf | (13.18Mb) |
Abstract: | HINDI |
Description: | Dept. of Hindi Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/4807 |
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Dyuthi-T1904.pdf | (11.86Mb) |
Description: | Department of Hindi, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/2667 |
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Dyuthi-T0719.pdf | (4.588Mb) |
URI: | http://dyuthi.cusat.ac.in/purl/5599 |
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Dyuthi T-2640.pdf | (6.933Mb) |
Abstract: | Learning disability (LD) is a neurological condition that affects a child’s brain and impairs his ability to carry out one or many specific tasks. LD affects about 10% of children enrolled in schools. There is no cure for learning disabilities and they are lifelong. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. Just as there are many different types of LDs, there are a variety of tests that may be done to pinpoint the problem The information gained from an evaluation is crucial for finding out how the parents and the school authorities can provide the best possible learning environment for child. This paper proposes a new approach in artificial neural network (ANN) for identifying LD in children at early stages so as to solve the problems faced by them and to get the benefits to the students, their parents and school authorities. In this study, we propose a closest fit algorithm data preprocessing with ANN classification to handle missing attribute values. This algorithm imputes the missing values in the preprocessing stage. Ignoring of missing attribute values is a common trend in all classifying algorithms. But, in this paper, we use an algorithm in a systematic approach for classification, which gives a satisfactory result in the prediction of LD. It acts as a tool for predicting the LD accurately, and good information of the child is made available to the concerned |
Description: | Neural Comput & Applic (2012) 21:1757–1763 DOI 10.1007/s00521-011-0619-1 |
URI: | http://dyuthi.cusat.ac.in/purl/4206 |
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Attribute reduc ... learning disabilities.pdf | (286.9Kb) |
Abstract: | Author identification is the problem of identifying the author of an anonymous text or text whose authorship is in doubt from a given set of authors. The works by different authors are strongly distinguished by quantifiable features of the text. This paper deals with the attempts made on identifying the most likely author of a text in Malayalam from a list of authors. Malayalam is a Dravidian language with agglutinative nature and not much successful tools have been developed to extract syntactic & semantic features of texts in this language. We have done a detailed study on the various stylometric features that can be used to form an authors profile and have found that the frequencies of word collocations can be used to clearly distinguish an author in a highly inflectious language such as Malayalam. In our work we try to extract the word level and character level features present in the text for characterizing the style of an author. Our first step was towards creating a profile for each of the candidate authors whose texts were available with us, first from word n-gram frequencies and then by using variable length character n-gram frequencies. Profiles of the set of authors under consideration thus formed, was then compared with the features extracted from anonymous text, to suggest the most likely author. |
URI: | http://dyuthi.cusat.ac.in/purl/4103 |
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Author Identifi ... alayalam using n-grams.pdf | (388.1Kb) |
Abstract: | This paper presents a new approach to implement Reed-Muller Universal Logic Module (RM-ULM) networks with reduced delay and hardware for synthesizing logic functions given in Reed-Muller (RM) form. Replication of single control line RM-ULM is used as the only design unit for defining any logic function. An algorithm is proposed that does exhaustive branching to reduce the number of levels and modules required to implement any logic function in RM form. This approach attains a reduction in delay, and power over other implementations of functions having large number of variables. |
Description: | NORCHIP Conference, 2005. 23rd |
URI: | http://dyuthi.cusat.ac.in/purl/3883 |
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Automated synth ... logic module networks.pdf | (2.066Mb) |
Abstract: | Malayalam is one of the 22 scheduled languages in India with more than 130 million speakers. This paper presents a report on the development of a speaker independent, continuous transcription system for Malayalam. The system employs Hidden Markov Model (HMM) for acoustic modeling and Mel Frequency Cepstral Coefficient (MFCC) for feature extraction. It is trained with 21 male and female speakers in the age group ranging from 20 to 40 years. The system obtained a word recognition accuracy of 87.4% and a sentence recognition accuracy of 84%, when tested with a set of continuous speech data. |
Description: | International Journal of Computer Applications (0975 – 8887) Volume 19– No.5, April 2011 |
URI: | http://dyuthi.cusat.ac.in/purl/4200 |
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Automated Trans ... for Malayalam Language.pdf | (207.7Kb) |
URI: | http://dyuthi.cusat.ac.in/purl/5530 |
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Dyuthi T-2573.pdf | (1.638Mb) |
Abstract: | The characterization and grading of glioma tumors, via image derived features, for diagnosis, prognosis, and treatment response has been an active research area in medical image computing. This paper presents a novel method for automatic detection and classification of glioma from conventional T2 weighted MR images. Automatic detection of the tumor was established using newly developed method called Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA).Statistical Features were extracted from the detected tumor texture using first order statistics and gray level co-occurrence matrix (GLCM) based second order statistical methods. Statistical significance of the features was determined by t-test and its corresponding p-value. A decision system was developed for the grade detection of glioma using these selected features and its p-value. The detection performance of the decision system was validated using the receiver operating characteristic (ROC) curve. The diagnosis and grading of glioma using this non-invasive method can contribute promising results in medical image computing |
Description: | International Journal of Emerging Technologies in Computational and Applied Sciences, 7(1), December 2013- February, 2014, pp. 08-14 |
URI: | http://dyuthi.cusat.ac.in/purl/4579 |
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Automatic Detec ... g Statistical Features.pdf | (413.4Kb) |
Abstract: | In recent years there is an apparent shift in research from content based image retrieval (CBIR) to automatic image annotation in order to bridge the gap between low level features and high level semantics of images. Automatic Image Annotation (AIA) techniques facilitate extraction of high level semantic concepts from images by machine learning techniques. Many AIA techniques use feature analysis as the first step to identify the objects in the image. However, the high dimensional image features make the performance of the system worse. This paper describes and evaluates an automatic image annotation framework which uses SURF descriptors to select right number of features and right features for annotation. The proposed framework uses a hybrid approach in which k-means clustering is used in the training phase and fuzzy K-NN classification in the annotation phase. The performance of the system is evaluated using standard metrics. |
Description: | India Conference (INDICON), 2012 Annual IEEE |
URI: | http://dyuthi.cusat.ac.in/purl/4317 |
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Automatic Image ... Using SURF Descriptors.pdf | (714.0Kb) |
Abstract: | Efficient optic disc segmentation is an important task in automated retinal screening. For the same reason optic disc detection is fundamental for medical references and is important for the retinal image analysis application. The most difficult problem of optic disc extraction is to locate the region of interest. Moreover it is a time consuming task. This paper tries to overcome this barrier by presenting an automated method for optic disc boundary extraction using Fuzzy C Means combined with thresholding. The discs determined by the new method agree relatively well with those determined by the experts. The present method has been validated on a data set of 110 colour fundus images from DRION database, and has obtained promising results. The performance of the system is evaluated using the difference in horizontal and vertical diameters of the obtained disc boundary and that of the ground truth obtained from two expert ophthalmologists. For the 25 test images selected from the 110 colour fundus images, the Pearson correlation of the ground truth diameters with the detected diameters by the new method are 0.946 and 0.958 and, 0.94 and 0.974 respectively. From the scatter plot, it is shown that the ground truth and detected diameters have a high positive correlation. This computerized analysis of optic disc is very useful for the diagnosis of retinal diseases |
Description: | (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 5, No. 7, 2014 |
URI: | http://dyuthi.cusat.ac.in/purl/4580 |
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Automatic Optic ... om Color Fundus Images.pdf | (602.5Kb) |
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