4 resultados para continuous performance
em Cochin University of Science
Resumo:
The present study shows design and development of a performance evaluation prototype for IT organizations in the context of outsourcing. The main objective of this research is to help an IT organization in the context of outsourcing to realize its current standing, so it can take corrective steps where ever necessary and strive for continuous improvement. Service level management (SLM) process plays a crucial role in controlling the quality provision for IT service. Out sourcing is the process of entrusting the responsibility of providing certain goods and services to an external party. We have tried to identify as many as twenty complexities and categorized in to four headings. Complexities associated with contracts and SLAs,SLM process,SLM organization and complexities due to intrinsic characteristics. In this study it is possible to measure the quality of the performance of an IT organization in an outsourcing environment effectively
Resumo:
Performance of any continuous speech recognition system is dependent on the accuracy of its acoustic model. Hence, preparation of a robust and accurate acoustic model lead to satisfactory recognition performance for a speech recognizer. In acoustic modeling of phonetic unit, context information is of prime importance as the phonemes are found to vary according to the place of occurrence in a word. In this paper we compare and evaluate the effect of context dependent tied (CD tied) models, context dependent (CD) and context independent (CI) models in the perspective of continuous speech recognition of Malayalam language. The database for the speech recognition system has utterance from 21 speakers including 11 female and 10 males. Our evaluation results show that CD tied models outperforms CI models over 21%.
Resumo:
L-Glutamine amidohydrolase (L-glutaminase, EC 3.5.1.2) is a therapeutically and industrially important enzyme. Because it is a potent antileukemic agent and a flavor-enhancing agent used in the food industry, many researchers have focused their attention on L-glutaminase. In this article, we report the continuous production of extracellular L-glutaminase by the marine fungus Beauveria bassiana BTMF S-10 in a packed-bed reactor. Parameters influencing bead production and performance under batch mode were optimized in the order-support (Na-alginate) concentration, concentration of CaCl2 for bead preparation, curing time of beads, spore inoculum concentration, activation time, initial pH of enzyme production medium, temperature of incubation, and retention time. Parameters optimized under batch mode for L-glutaminase production were incorporated into the continuous production studies. Beads with 12 × 108 spores/g of beads were activated in a solution of 1% glutamine in seawater for 15 h, and the activated beads were packed into a packed-bed reactor. Enzyme production medium (pH 9.0) was pumped through the bed, and the effluent was collected from the top of the column. The effect of flow rate of the medium, substrate concentration, aeration, and bed height on continuous production of L-glutaminase was studied. Production was monitored for 5 h in each case, and the volumetric productivity was calculated. Under the optimized conditions for continuous production, the reactor gave a volumetric productivity of 4.048 U/(mL·h), which indicates that continuous production of the enzyme by Ca-alginate-immobilizedspores is well suited for B. bassiana and results in a higher yield of enzyme within a shorter time. The results indicate the scope of utilizing immobilized B. bassiana for continuous commercial production of L-glutaminase
Resumo:
The country has witnessed tremendous increase in the vehicle population and increased axle loading pattern during the last decade, leaving its road network overstressed and leading to premature failure. The type of deterioration present in the pavement should be considered for determining whether it has a functional or structural deficiency, so that appropriate overlay type and design can be developed. Structural failure arises from the conditions that adversely affect the load carrying capability of the pavement structure. Inadequate thickness, cracking, distortion and disintegration cause structural deficiency. Functional deficiency arises when the pavement does not provide a smooth riding surface and comfort to the user. This can be due to poor surface friction and texture, hydro planning and splash from wheel path, rutting and excess surface distortion such as potholes, corrugation, faulting, blow up, settlement, heaves etc. Functional condition determines the level of service provided by the facility to its users at a particular time and also the Vehicle Operating Costs (VOC), thus influencing the national economy. Prediction of the pavement deterioration is helpful to assess the remaining effective service life (RSL) of the pavement structure on the basis of reduction in performance levels, and apply various alternative designs and rehabilitation strategies with a long range funding requirement for pavement preservation. In addition, they can predict the impact of treatment on the condition of the sections. The infrastructure prediction models can thus be classified into four groups, namely primary response models, structural performance models, functional performance models and damage models. The factors affecting the deterioration of the roads are very complex in nature and vary from place to place. Hence there is need to have a thorough study of the deterioration mechanism under varied climatic zones and soil conditions before arriving at a definite strategy of road improvement. Realizing the need for a detailed study involving all types of roads in the state with varying traffic and soil conditions, the present study has been attempted. This study attempts to identify the parameters that affect the performance of roads and to develop performance models suitable to Kerala conditions. A critical review of the various factors that contribute to the pavement performance has been presented based on the data collected from selected road stretches and also from five corporations of Kerala. These roads represent the urban conditions as well as National Highways, State Highways and Major District Roads in the sub urban and rural conditions. This research work is a pursuit towards a study of the road condition of Kerala with respect to varying soil, traffic and climatic conditions, periodic performance evaluation of selected roads of representative types and development of distress prediction models for roads of Kerala. In order to achieve this aim, the study is focused into 2 parts. The first part deals with the study of the pavement condition and subgrade soil properties of urban roads distributed in 5 Corporations of Kerala; namely Thiruvananthapuram, Kollam, Kochi, Thrissur and Kozhikode. From selected 44 roads, 68 homogeneous sections were studied. The data collected on the functional and structural condition of the surface include pavement distress in terms of cracks, potholes, rutting, raveling and pothole patching. The structural strength of the pavement was measured as rebound deflection using Benkelman Beam deflection studies. In order to collect the details of the pavement layers and find out the subgrade soil properties, trial pits were dug and the in-situ field density was found using the Sand Replacement Method. Laboratory investigations were carried out to find out the subgrade soil properties, soil classification, Atterberg limits, Optimum Moisture Content, Field Moisture Content and 4 days soaked CBR. The relative compaction in the field was also determined. The traffic details were also collected by conducting traffic volume count survey and axle load survey. From the data thus collected, the strength of the pavement was calculated which is a function of the layer coefficient and thickness and is represented as Structural Number (SN). This was further related to the CBR value of the soil and the Modified Structural Number (MSN) was found out. The condition of the pavement was represented in terms of the Pavement Condition Index (PCI) which is a function of the distress of the surface at the time of the investigation and calculated in the present study using deduct value method developed by U S Army Corps of Engineers. The influence of subgrade soil type and pavement condition on the relationship between MSN and rebound deflection was studied using appropriate plots for predominant types of soil and for classified value of Pavement Condition Index. The relationship will be helpful for practicing engineers to design the overlay thickness required for the pavement, without conducting the BBD test. Regression analysis using SPSS was done with various trials to find out the best fit relationship between the rebound deflection and CBR, and other soil properties for Gravel, Sand, Silt & Clay fractions. The second part of the study deals with periodic performance evaluation of selected road stretches representing National Highway (NH), State Highway (SH) and Major District Road (MDR), located in different geographical conditions and with varying traffic. 8 road sections divided into 15 homogeneous sections were selected for the study and 6 sets of continuous periodic data were collected. The periodic data collected include the functional and structural condition in terms of distress (pothole, pothole patch, cracks, rutting and raveling), skid resistance using a portable skid resistance pendulum, surface unevenness using Bump Integrator, texture depth using sand patch method and rebound deflection using Benkelman Beam. Baseline data of the study stretches were collected as one time data. Pavement history was obtained as secondary data. Pavement drainage characteristics were collected in terms of camber or cross slope using camber board (slope meter) for the carriage way and shoulders, availability of longitudinal side drain, presence of valley, terrain condition, soil moisture content, water table data, High Flood Level, rainfall data, land use and cross slope of the adjoining land. These data were used for finding out the drainage condition of the study stretches. Traffic studies were conducted, including classified volume count and axle load studies. From the field data thus collected, the progression of each parameter was plotted for all the study roads; and validated for their accuracy. Structural Number (SN) and Modified Structural Number (MSN) were calculated for the study stretches. Progression of the deflection, distress, unevenness, skid resistance and macro texture of the study roads were evaluated. Since the deterioration of the pavement is a complex phenomena contributed by all the above factors, pavement deterioration models were developed as non linear regression models, using SPSS with the periodic data collected for all the above road stretches. General models were developed for cracking progression, raveling progression, pothole progression and roughness progression using SPSS. A model for construction quality was also developed. Calibration of HDM–4 pavement deterioration models for local conditions was done using the data for Cracking, Raveling, Pothole and Roughness. Validation was done using the data collected in 2013. The application of HDM-4 to compare different maintenance and rehabilitation options were studied considering the deterioration parameters like cracking, pothole and raveling. The alternatives considered for analysis were base alternative with crack sealing and patching, overlay with 40 mm BC using ordinary bitumen, overlay with 40 mm BC using Natural Rubber Modified Bitumen and an overlay of Ultra Thin White Topping. Economic analysis of these options was done considering the Life Cycle Cost (LCC). The average speed that can be obtained by applying these options were also compared. The results were in favour of Ultra Thin White Topping over flexible pavements. Hence, Design Charts were also plotted for estimation of maximum wheel load stresses for different slab thickness under different soil conditions. The design charts showed the maximum stress for a particular slab thickness and different soil conditions incorporating different k values. These charts can be handy for a design engineer. Fuzzy rule based models developed for site specific conditions were compared with regression models developed using SPSS. The Riding Comfort Index (RCI) was calculated and correlated with unevenness to develop a relationship. Relationships were developed between Skid Number and Macro Texture of the pavement. The effort made through this research work will be helpful to highway engineers in understanding the behaviour of flexible pavements in Kerala conditions and for arriving at suitable maintenance and rehabilitation strategies. Key Words: Flexible Pavements – Performance Evaluation – Urban Roads – NH – SH and other roads – Performance Models – Deflection – Riding Comfort Index – Skid Resistance – Texture Depth – Unevenness – Ultra Thin White Topping