Brain Tissue Classification from Multispectral MRI by Wavelet based Principal Component Analysis

In this paper, we propose a multispectral analysis system using wavelet based Principal Component Analysis (PCA), to improve the brain tissue classification from MRI images. Global transforms like PCA often neglects significant small abnormality details, while dealing with a massive amount of multispectral data. In order to resolve this issue, input dataset is expanded by detail coefficients from multisignal wavelet analysis. Then, PCA is applied on the new dataset to perform feature analysis. Finally, an unsupervised classification with Fuzzy C-Means clustering algorithm is used to measure the improvement in reproducibility and accuracy of the results. A detailed comparative analysis of classified tissues with those from conventional PCA is also carried out. Proposed method yielded good improvement in classification of small abnormalities with high sensitivity/accuracy values, 98.9/98.3, for clinical analysis. Experimental results from synthetic and clinical data recommend the new method as a promising approach in brain tissue analysis.

Assessment of Energy Conservation in Indian Cement Industry and Forecasting of Co2 Emissions

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

Development of Total Quality Management System in Seafood (Freezing) Industry in Kerala

Quality related problems have become dominant in the seafood processing industry in Kerala. This has resulted in the rejection of seafood sent from India to many destinations. The latest being the total block listing of seafood companies from India from being exported to Europe and partial block listing by the US. The quality systems prevailed in the seafood industry in India were outdated and no longer in use in the developed world. According to EC Directive discussed above all the seafood factories exporting to European countries have to adopt HACCP. Based on this, EIA has now made HACCP system mandatory in all the seafood processing factories in India. This transformation from a traditional product based inspection system to a process control system requires thorough changes in the various stages of production and quality management. This study is conducted by the author with to study the status of the existing infrastructure and quality control system in the seafood industry in Kerala with reference to the recent developments in the quality concepts in international markets and study the drawbacks, if any, of the existing quality management systems in force in the seafood factories in Kerala for introducing the mandatory HACCP concept. To assess the possibilities of introducing Total Quality Management system in the seafood industry in Kerala in order to effectively adopt the HACCP concept. This is also aimed at improving the quality of the products and productivity of the industry by sustaining the world markets in the long run.

An Extended Pearson System Useful In Reliability Analysis

In the present environment, industry should provide the products of high quality. Quality of products is judged by the period of time they can successfully perform their intended functions without failure. The cause of the failures can be ascertained through life testing experiments and the times to failure due to different cause are likely to follow different distributions. Knowledge of this distribution is essential to eliminate causes of failures and thereby to improve the quality and the reliability of products. The main accomplishment expected to the study is to develop statistical tools that could facilitate solution to lifetime data arising in such and similar contexts

Rotational analysis of the C1Π-X1 Σ+ system of indium monofluoride

Indium monofluoride was excited in a high-frequency discharge and the C-X system was photographed at a reciprocal dispersion of 0.3 AA mm-1 using a plane-grating spectrograph. Rotational analyses of the 0,0 1,0 2,2 3,3 4,4 2,4 3,5 4,6 and 5,7 bands have been carried out and the following molecular constants have been evaluated. Be'=0.2670(+or-3) cm-1, Be"=0.2628(+or-4) cm-1, alpha e'=0.0050(+or-4) cm-1, alpha e"=0.0020(+or-1) cm-1, De'=3.65(+or-5)*10-7 cm-1, De"=2.5(+or-3)*10-7 cm-1, beta e'=0.5(+or-2)*10-7 cm-1, beta e"=0.2(+or-1)*10-7 cm-1, re'=1.9672(+or-3) AA, re"=1.9853(+or-2) AA. The re" value agrees with the microwave absorption value 1.9854 AA.

Recurrence Quantification Analysis of System Signals for Detecting Tool and Chatter in Turning

In this thesis, the applications of the recurrence quantification analysis in metal cutting operation in a lathe, with specific objective to detect tool wear and chatter, are presented.This study is based on the discovery that process dynamics in a lathe is low dimensional chaotic. It implies that the machine dynamics is controllable using principles of chaos theory. This understanding is to revolutionize the feature extraction methodologies used in condition monitoring systems as conventional linear methods or models are incapable of capturing the critical and strange behaviors associated with the metal cutting process.As sensor based approaches provide an automated and cost effective way to monitor and control, an efficient feature extraction methodology based on nonlinear time series analysis is much more demanding. The task here is more complex when the information has to be deduced solely from sensor signals since traditional methods do not address the issue of how to treat noise present in real-world processes and its non-stationarity. In an effort to get over these two issues to the maximum possible, this thesis adopts the recurrence quantification analysis methodology in the study since this feature extraction technique is found to be robust against noise and stationarity in the signals.The work consists of two different sets of experiments in a lathe; set-I and set-2. The experiment, set-I, study the influence of tool wear on the RQA variables whereas the set-2 is carried out to identify the sensitive RQA variables to machine tool chatter followed by its validation in actual cutting. To obtain the bounds of the spectrum of the significant RQA variable values, in set-i, a fresh tool and a worn tool are used for cutting. The first part of the set-2 experiments uses a stepped shaft in order to create chatter at a known location. And the second part uses a conical section having a uniform taper along the axis for creating chatter to onset at some distance from the smaller end by gradually increasing the depth of cut while keeping the spindle speed and feed rate constant.The study concludes by revealing the dependence of certain RQA variables; percent determinism, percent recurrence and entropy, to tool wear and chatter unambiguously. The performances of the results establish this methodology to be viable for detection of tool wear and chatter in metal cutting operation in a lathe. The key reason is that the dynamics of the system under study have been nonlinear and the recurrence quantification analysis can characterize them adequately.This work establishes that principles and practice of machining can be considerably benefited and advanced from using nonlinear dynamics and chaos theory.

Permutation Entropy Based Analysis of Complex Signals for Characterising Change in System Dynamics

Timely detection of sudden change in dynamics that adversely affect the performance of systems and quality of products has great scientific relevance. This work focuses on effective detection of dynamical changes of real time signals from mechanical as well as biological systems using a fast and robust technique of permutation entropy (PE). The results are used in detecting chatter onset in machine turning and identifying vocal disorders from speech signal.Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. Here we propose the use of permutation entropy (PE), to detect the dynamical changes in two non linear processes, turning under mechanical system and speech under biological system.Effectiveness of PE in detecting the change in dynamics in turning process from the time series generated with samples of audio and current signals is studied. Experiments are carried out on a lathe machine for sudden increase in depth of cut and continuous increase in depth of cut on mild steel work pieces keeping the speed and feed rate constant. The results are applied to detect chatter onset in machining. These results are verified using frequency spectra of the signals and the non linear measure, normalized coarse-grained information rate (NCIR).PE analysis is carried out to investigate the variation in surface texture caused by chatter on the machined work piece. Statistical parameter from the optical grey level intensity histogram of laser speckle pattern recorded using a charge coupled device (CCD) camera is used to generate the time series required for PE analysis. Standard optical roughness parameter is used to confirm the results.Application of PE in identifying the vocal disorders is studied from speech signal recorded using microphone. Here analysis is carried out using speech signals of subjects with different pathological conditions and normal subjects, and the results are used for identifying vocal disorders. Standard linear technique of FFT is used to substantiate thc results.The results of PE analysis in all three cases clearly indicate that this complexity measure is sensitive to change in regularity of a signal and hence can suitably be used for detection of dynamical changes in real world systems. This work establishes the application of the simple, inexpensive and fast algorithm of PE for the benefit of advanced manufacturing process as well as clinical diagnosis in vocal disorders.

Development of Safety and Quality Management System in Shrimp Farming

Shrimp Aquaculture has provided tremendous opportunity for the economic and social upliftment of rural communities in the coastal areas of our country Over a hundred thousand farmers, of whom about 90% belong to the small and marginal category, are engaged in shrimp farming. Penaeus monodon is the most predominant cultured species in India which is mainly exported to highly sophisticated, quality and safety conscious world markets. Food safety has been of concem to humankind since the dawn of history and the concern about food safety resulted in the evolution of a cost effective, food safety assurance method, the Hazard Analysis Critical Control Point (HACCP). Considering the major contribution of cultured Penaeus monodon to the total shrimp production and the economic losses encountered due to disease outbreak and also because traditional methods of quality control and end point inspection cannot guarantee the safety of our cultured seafood products, it is essential that science based preventive approaches like HACCP and Pre requisite Programmes (PRP) be implemented in our shrimp farming operations. PRP is considered as a support system which provides a solid foundation for HACCP. The safety of postlarvae (PL) supplied for brackish water shrimp farming has also become an issue of concern over the past few years. The quality and safety of hatchery produced seeds have been deteriorating and disease outbreaks have become very common in hatcheries. It is in this context that the necessity for following strict quarantine measures with standards and code of practices becomes significant. Though there were a lot of hue and cry on the need for extending the focus of seafood safety assurance from processing and exporting to the pre-harvest and hatchery rearing phases, an experimental move in this direction has been rare or nil. An integrated management system only can assure the effective control of the quality, hygiene and safety related issues. This study therefore aims at designing a safety and quality management system model for implementation in shrimp farming and hatchery operations by linking the concepts of HACCP and PRP.

Targeted Public Distribution System in Food Grains:Extent of Utlization by the Tribal Population in Kerala

In India, Food Security meant supply of food grains and the medium was Public Distribution System. Public Distribution System (PDS) is a rationing mechanism that entitles households to specified quantities of selected commodities at subsidized prices. The Objectives of PDS are maintaining Price Stability, rationing during times of scarcity, welfare of the poor, and keeping a check on private trade. Kerala has registered remarkable improvement in poverty reduction in general over the years among all social sections, including scheduled caste and scheduled tribe population. As part of the structural adjustment intended to reduce public expenditure, PDS has been modified as Revamped PDS (RPDS) during 1992 and later on as Targeted PDS (TPDS) in 1997, intended to target households on the basis of income criterion, classifying people as Below Poverty Line (BPL) and Above Poverty Line (APL). TPDS provides 25Kg. of food gra.ins through the Fair Price Shops per month @ Rs.3/- per Kg. of rice/ wheat to the BPL category and @Rs.8.90 and Rs.6.7O for rice and wheat respectively to the APL category of people. Since TPDS is intended to target the poor people, the subsidy spent by the government for the scheme should be beneficial to the poor people and naturally they should utilize the benefits by purchasing the food grains allotted under the scheme. Several studies have shown that there is underutilization of the allotments under TPDS. Therefore, the extent of utilization of TPDS in food grains, how and why remains as a major hurdle, in improving the structure and system of PDS. Livelihood of the tribal population being under threat due to increasing degradation of the resources, the targeting system ought to be effective among the tribal population. Therefore, performance of the TPDS in food grains, in terms of the utilization by the tribal population in Kerala, impact thereof and the factors, if any, affecting proper utilization were considered as the research problem in this study. The study concentrated on the pattern of consumption of food grains by the tribal people, whether their hunger needs are met by distribution of food grains through the TPDS, extent to which TPDS in food grains reduce their share of expenditure on food in the total household expenditure, and the factors affecting the utilization of the TPDS in food grains by the tribal population. Going through the literature, it has been noted that only few studies concentrated on the utilization of TPDS in food grains among the tribal population in Kerala.The Research Design used in this study is descriptive in nature, but exploratory in some aspects. Idukki, Palakkad and Wayanad have more than 60% of the population of the tribals in the state. Within the three districts mentioned above, 14 villages with scheduled tribe concentration were selected for the study. 95 tribal colonies were selected from among the various tribal settlements. Collection of primary data was made from 1231 households with in the above tribal colonies. Analysis of data on the socio-economic factors of the tribal people, pattern of food consumption, extent of reduction in the share of expenditure on food among the household expenditure of the tribal people and the impact of TPDS on the tribal families etc. and testing of hypotheses to find out the relation/association of each of the six variables, using the data on BPL and APL categories of households separately have resulted in findings such as six percent of the tribal families do not have Ration Cards, average per capita consumption of food grains by the tribal people utilizing TPDS meets 62% of their minimum requirement, whereas the per capita consumption of food grains by the tribal people is higher than the national average per capita consumption, 63% deficiency in food grains may be felt by tribal people in general, if TPDS is withdrawn, and the deficit for BPL tribal people may be 82%, TPDS facilitates a reduction of 9.71% in the food expenditure among the total household expenditure of the tribal people in general, share of food to non-food among BPL category of tribals is 55:45 and 40:60 among the APL, Variables, viz. household income, number of members in the family and distance of FPS from tribal settlements etc. have influence on the quantity of rice being purchased by the tribal people from the Fair Price Shops, and there is influence of household income and distance of FPS from tribal settlements on the quantity of rice being purchased by the tribal people from the open market. Rationing with differential pricing on phased allotments, rectification of errors in targeting, anomalies in norms and procedures for classifying tribal people as BPL/APL, exclusive Income Generation for tribal population, paddy cultivation in the landholdings possessed by the tribal people, special drive for allotment of Ration Cards to the tribal people, especially those belonging to the BPL category, Mobile Fair Price Shops in tribal settlements, ensure quality of the food grains distributed through the TPDS, distribution of wheat flour in packed condition instead of wheat through the Fair Price Shops are recommended to address the shortcomings and weaknesses of the TPDS vis-avis the tribal population in Kerala.

An Alternative Approach To Computer System Security Monitoring And Enhancement Through System Call Sequence Analysis

Modern computer systems are plagued with stability and security problems: applications lose data, web servers are hacked, and systems crash under heavy load. Many of these problems or anomalies arise from rare program behavior caused by attacks or errors. A substantial percentage of the web-based attacks are due to buffer overflows. Many methods have been devised to detect and prevent anomalous situations that arise from buffer overflows. The current state-of-art of anomaly detection systems is relatively primitive and mainly depend on static code checking to take care of buffer overflow attacks. For protection, Stack Guards and I-leap Guards are also used in wide varieties.This dissertation proposes an anomaly detection system, based on frequencies of system calls in the system call trace. System call traces represented as frequency sequences are profiled using sequence sets. A sequence set is identified by the starting sequence and frequencies of specific system calls. The deviations of the current input sequence from the corresponding normal profile in the frequency pattern of system calls is computed and expressed as an anomaly score. A simple Bayesian model is used for an accurate detection.Experimental results are reported which show that frequency of system calls represented using sequence sets, captures the normal behavior of programs under normal conditions of usage. This captured behavior allows the system to detect anomalies with a low rate of false positives. Data are presented which show that Bayesian Network on frequency variations responds effectively to induced buffer overflows. It can also help administrators to detect deviations in program flow introduced due to errors.

Qualitative Air Flow Modelling and Analysis of Data Centre Air Conditioning as Multiple Jet Array

Data centre is a centralized repository,either physical or virtual,for the storage,management and dissemination of data and information organized around a particular body and nerve centre of the present IT revolution.Data centre are expected to serve uniinterruptedly round the year enabling them to perform their functions,it consumes enormous energy in the present scenario.Tremendous growth in the demand from IT Industry made it customary to develop newer technologies for the better operation of data centre.Energy conservation activities in data centre mainly concentrate on the air conditioning system since it is the major mechanical sub-system which consumes considerable share of the total power consumption of the data centre.The data centre energy matrix is best represented by power utilization efficiency(PUE),which is defined as the ratio of the total facility power to the IT equipment power.Its value will be greater than one and a large value of PUE indicates that the sub-systems draw more power from the facility and the performance of the data will be poor from the stand point of energy conservation. PUE values of 1.4 to 1.6 are acievable by proper design and management techniques.Optimizing the air conditioning systems brings enormous opportunity in bringing down the PUE value.The air conditioning system can be optimized by two approaches namely,thermal management and air flow management.thermal management systems are now introduced by some companies but they are highly sophisticated and costly and do not catch much attention in the thumb rules.

Analysis of System Signals Based on Cross Recurrence Method for System Dynamics Characterization

Natural systems are inherently non linear. Recurrent behaviours are typical of natural systems. Recurrence is a fundamental property of non linear dynamical systems which can be exploited to characterize the system behaviour effectively. Cross recurrence based analysis of sensor signals from non linear dynamical system is presented in this thesis. The mutual dependency among relatively independent components of a system is referred as coupling. The analysis is done for a mechanically coupled system specifically designed for conducting experiment. Further, cross recurrence method is extended to the actual machining process in a lathe to characterize the chatter during turning. The result is verified by permutation entropy method. Conventional linear methods or models are incapable of capturing the critical and strange behaviours associated with the dynamical process. Hence any effective feature extraction methodologies should invariably gather information thorough nonlinear time series analysis. The sensor signals from the dynamical system normally contain noise and non stationarity. In an effort to get over these two issues to the maximum possible extent, this work adopts the cross recurrence quantification analysis (CRQA) methodology since it is found to be robust against noise and stationarity in the signals. The study reveals that the CRQA is capable of characterizing even weak coupling among system signals. It also divulges the dependence of certain CRQA variables like percent determinism, percent recurrence and entropy to chatter unambiguously. The surrogate data test shows that the results obtained by CRQA are the true properties of the temporal evolution of the dynamics and contain a degree of deterministic structure. The results are verified using permutation entropy (PE) to detect the onset of chatter from the time series. The present study ascertains that this CRP based methodology is capable of recognizing the transition from regular cutting to the chatter cutting irrespective of the machining parameters or work piece material. The results establish this methodology to be feasible for detection of chatter in metal cutting operation in a lathe.

Studies on the bacteria associated with Penaeus indicus in a culture system

Ocean persists as a rich and renewable source of cheap protein for the whole world. Among the prawns/shrimps landed from the Indian Ocean and her backwaters, more than 90% are exported to affluent countries. The Indian white prawn Penaeus indicus, constitutes the major portion of the frozen shrimps exported from India every year. The present study is aimed at gathering information on the total heterotrophic bacteria (THB) associated with B. indicus, with special reference to eggs, nauplii, zoeae, mysis, and post larvae in hatchery, and juveniles and adults in culture pond. Simultaneously, IHB associated with E. indicus in its natural habitat also is studied for comparison. It is envisaged that this information will be highly useful for modifying the existing hatchery and pond management-practices.

A Prototype for a Multimodal Biometric Security system based on Face and Audio Signatures

Any automatically measurable, robust and distinctive physical characteristic or personal trait that can be used to identify an individual or verify the claimed identity of an individual, referred to as biometrics, has gained significant interest in the wake of heightened concerns about security and rapid advancements in networking, communication and mobility. Multimodal biometrics is expected to be ultra-secure and reliable, due to the presence of multiple and independent—verification clues. In this study, a multimodal biometric system utilising audio and facial signatures has been implemented and error analysis has been carried out. A total of one thousand face images and 250 sound tracks of 50 users are used for training the proposed system. To account for the attempts of the unregistered signatures data of 25 new users are tested. The short term spectral features were extracted from the sound data and Vector Quantization was done using K-means algorithm. Face images are identified based on Eigen face approach using Principal Component Analysis. The success rate of multimodal system using speech and face is higher when compared to individual unimodal recognition systems

Nitrification in a packed bed bioreactor integrated into amarine recirculating maturation system under different substrate concentrations and flow rates

BACKGROUND: A packed bed bioreactor (PBBR) activated with an indigenous nitrifying bacterial consortia was developed and commercialized for rapid establishment of nitrification in brackish water and marine hatchery systems in the tropics. The present study evaluated nitrification in PBBR integrated into a Penaeus monodon recirculating maturation system under different substrate concentrations and flow rates. RESULTS:Instantnitrificationwasobservedafter integration ofPBBRinto thematuration system.TANandNO2-Nconcentrations were always maintained below0.5 mg L−1 during operation. The TANandNO2-N removalwas significant (P < 0.001) in all the six reactor compartments of the PBBR having the substrates at initial concentrations of 2, 5 and 10 mg L−1. The average volumetric TAN removal rates increased with flow rates from 43.51 (250 L h−1) to 130.44 (2500 L h−1) gTAN m−3 day−1 (P < 0.05). FISH analysis of the biofilms after 70 days of operation gave positive results with probes NSO 190 ((β ammonia oxidizers), NsV 443 (Nitrosospira spp.) NEU (halophilic Nitrosomonas), Ntspa 712 (Phylum Nitrospira) indicating stability of the consortia. CONCLUSION: The PBBR integrated into the P. monodon maturation system exhibited significant nitrification upon operation for 70 days as well as at different substrate concentrations and flow rates. This system can easily be integrated into marine and brackish water aquaculture systems, to establish instantaneous nitrification