Resource abundance and Survival of indigenous ornamental fishes of central Kerala with emphasis on handling and packing stress in Puntius filamentosus(VALENCIENNES)

This thesis Entitled Resource abundance and survival of indigenous ornamental fishes of central kerala with emphasis on handling and packing stress in puntius filamentosus (valenciennes).Kerala state is endowed with 41 west flowing and three east flowing rivers originating in the Western Ghats. These rivers and their vast network of tributaries and distributaries harbour rich and diversified fish fauna. Most of the freshwater fishes available in Kerala are highly appreciated as ornamental fishes in the national and international markets.Today the ornamental fish industry is one of the largest industries all over the world. The demand for ornamental fishes has been increasing steadily with the enlargement of the industry, such that the current demand for indigenous ornamental fishes have exceeded the supply. This has led to serious concern about the resources available in the country that can be utilised judiciously for the economic benefit of the state. With an aim to fill up the lacuna, a database of freshwater ornamental fishes of Kerala was created as part of the present study. Ornamental fishes destined for export marketing should thrive well in the aquarium conditions.The study reiterates fishes caught from different environmental conditions and feeding habits have a greater ability to adapt and acclimatise to an entirely new environment and food habits. Marketing studies based on the statistics available with Marine Products Export Development Authority show that these species are not being exported at the required level over the past 6 years, when compared to the availability in the water bodies of Kerala. Sustainable utilisation of these resources from the wild using modern management principles and code of conduct for responsible fishing are advisable until captive breeding technology is popularised.

Design and Development of data mining models for the predictions of manpower placement in the technical Domain

Data mining is one of the hottest research areas nowadays as it has got wide variety of applications in common man’s life to make the world a better place to live. It is all about finding interesting hidden patterns in a huge history data base. As an example, from a sales data base, one can find an interesting pattern like “people who buy magazines tend to buy news papers also” using data mining. Now in the sales point of view the advantage is that one can place these things together in the shop to increase sales. In this research work, data mining is effectively applied to a domain called placement chance prediction, since taking wise career decision is so crucial for anybody for sure. In India technical manpower analysis is carried out by an organization named National Technical Manpower Information System (NTMIS), established in 1983-84 by India's Ministry of Education & Culture. The NTMIS comprises of a lead centre in the IAMR, New Delhi, and 21 nodal centres located at different parts of the country. The Kerala State Nodal Centre is located at Cochin University of Science and Technology. In Nodal Centre, they collect placement information by sending postal questionnaire to passed out students on a regular basis. From this raw data available in the nodal centre, a history data base was prepared. Each record in this data base includes entrance rank ranges, reservation, Sector, Sex, and a particular engineering. From each such combination of attributes from the history data base of student records, corresponding placement chances is computed and stored in the history data base. From this data, various popular data mining models are built and tested. These models can be used to predict the most suitable branch for a particular new student with one of the above combination of criteria. Also a detailed performance comparison of the various data mining models is done.This research work proposes to use a combination of data mining models namely a hybrid stacking ensemble for better predictions. A strategy to predict the overall absorption rate for various branches as well as the time it takes for all the students of a particular branch to get placed etc are also proposed. Finally, this research work puts forward a new data mining algorithm namely C 4.5 * stat for numeric data sets which has been proved to have competent accuracy over standard benchmarking data sets called UCI data sets. It also proposes an optimization strategy called parameter tuning to improve the standard C 4.5 algorithm. As a summary this research work passes through all four dimensions for a typical data mining research work, namely application to a domain, development of classifier models, optimization and ensemble methods.

Predictability Of Share Prices In India: A Study Of The Applicability Of Technical Analysis

In spite of the far longed practices of technical analysis by many participants in Indian stock market, none have arrived at the exact position of technical analysis as a tool for foretelling share prices. There is no evidence supporting that one has established its definite role in predicting the behaviour of share price and also to see the extent of validity (how far reliable) of technical tools in Indian stock market. The problem is the vacuum in the arena of securities market analysis where an unrecognised tool is practised, i.e., whether to hold on to technical analysis or to drop it. Again, as already stated in this chapter, its validity need not continue forever. It may become futile as happened in developed markets. Continuous practice of a tool, which is valid only during discontinuous times is also an error. The efficacy of different market phenomena in terms of their ability to foretell the extent and direction of the price movements and reliability thereof remain as not yet proved in. This requires further study in this area so that this controversy may be settled. A solution to the problem requires enquiring and establishing the applicability of technical analysis, if any, there is in the Indian stock market. The study has the following two broad objectives for the purpose of confirming the applicability, if any, of technical analysis in the Indian stock market. The first objective is to ascertain the current validity of ‘traditional holding with respect to patterns’ and the second objective is to ascertain the ‘consistent superiority’, if any, of technical indicators over non-signal strategies in return generation. The study analyses the five patterns, which are widely known and commonly found in publications. They are: (1) Symmetrical Triangles, (2) Rising Wedges, (3) Falling Wedges, (4) Head and Shoulders Top and (5) Head and Shoulders Bottom.

Routing protocol enhancement for handling node mobility in wireless sensor networks

In wireless sensor networks, the routing algorithms currently available assume that the sensor nodes are stationary. Therefore when mobility modulation is applied to the wireless sensor networks, most of the current routing algorithms suffer from performance degradation. The path breaks in mobile wireless networks are due to the movement of mobile nodes, node failure, channel fading and shadowing. It is desirable to deal with dynamic topology changes with optimal effort in terms of resource and channel utilization. As the nodes in wireless sensor medium make use of wireless broadcast to communicate, it is possible to make use of neighboring node information to recover from path failure. Cooperation among the neighboring nodes plays an important role in the context of routing among the mobile nodes. This paper proposes an enhancement to an existing protocol for accommodating node mobility through neighboring node information while keeping the utilization of resources to a minimum.

Routing Protocol Enhancement for handling Node Mobility in Wireless Sensor Networks

In wireless sensor networks, the routing algorithms currently available assume that the sensor nodes are stationary. Therefore when mobility modulation is applied to the wireless sensor networks, most of the current routing algorithms suffer from performance degradation. The path breaks in mobile wireless networks are due to the movement of mobile nodes, node failure, channel fading and shadowing. It is desirable to deal with dynamic topology changes with optimal effort in terms of resource and channel utilization. As the nodes in wireless sensor medium make use of wireless broadcast to communicate, it is possible to make use of neighboring node information to recover from path failure. Cooperation among the neighboring nodes plays an important role in the context of routing among the mobile nodes. This paper proposes an enhancement to an existing protocol for accommodating node mobility through neighboring node information while keeping the utilization of resources to a minimum.

Handling OOV Words in Phrase-Based Statistical Machine Translation for Malayalam

Statistical Machine Translation (SMT) is one of the potential applications in the field of Natural Language Processing. The translation process in SMT is carried out by acquiring translation rules automatically from the parallel corpora. However, for many language pairs (e.g. Malayalam- English), they are available only in very limited quantities. Therefore, for these language pairs a huge portion of phrases encountered at run-time will be unknown. This paper focuses on methods for handling such out-of-vocabulary (OOV) words in Malayalam that cannot be translated to English using conventional phrase-based statistical machine translation systems. The OOV words in the source sentence are pre-processed to obtain the root word and its suffix. Different inflected forms of the OOV root are generated and a match is looked up for the word variants in the phrase translation table of the translation model. A Vocabulary filter is used to choose the best among the translations of these word variants by finding the unigram count. A match for the OOV suffix is also looked up in the phrase entries and the target translations are filtered out. Structuring of the filtered phrases is done and SMT translation model is extended by adding OOV with its new phrase translations. By the results of the manual evaluation done it is observed that amount of OOV words in the input has been reduced considerably

Routing Protocol Enhancement for handling Node Mobility in Wireless Sensor Networks

In wireless sensor networks, the routing algorithms currently available assume that the sensor nodes are stationary. Therefore when mobility modulation is applied to the wireless sensor networks, most of the current routing algorithms suffer from performance degradation. The path breaks in mobile wireless networks are due to the movement of mobile nodes, node failure, channel fading and shadowing. It is desirable to deal with dynamic topology changes with optimal effort in terms of resource and channel utilization. As the nodes in wireless sensor medium make use of wireless broadcast to communicate, it is possible to make use of neighboring node information to recover from path failure. Cooperation among the neighboring nodes plays an important role in the context of routing among the mobile nodes. This paper proposes an enhancement to an existing protocol for accommodating node mobility through neighboring node information while keeping the utilization of resources to a minimum.

Employment Realm in Technical Education in Kerala-A Study on the Problem of Unemployment among Engineers

The The The The growing demandgrowing demandgrowing demandgrowing demandgrowing demandgrowing demandgrowing demandgrowing demandgrowing demandgrowing demandgrowing demandgrowing demandgrowing demand for the expansion of for the expansion of for the expansion of for the expansion of for the expansion of for the expansion of for the expansion of for the expansion of for the expansion of for the expansion of for the expansion of for the expansion of for the expansion of for the expansion of for the expansion of for the expansion of for the expansion of for the expansion of for the expansion of for the expansion of for the expansion of the the the the publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system publicly funded system of education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goodof education as merit and free goods emphasized emphasized emphasized emphasized emphasized emphasized emphasized emphasized emphasized emphasized on large allocation large allocation large allocation large allocation large allocation large allocation large allocation large allocation large allocation large allocation large allocation large allocation large allocation large allocation large allocation large allocation large allocation of funds on of funds on of funds on of funds on of funds on of funds on of funds on of funds on of funds on of funds on of funds for promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting educationfor promoting education. Compared to . Compared to . Compared to . Compared to . Compared to . Compared to . Compared to . Compared to . Compared to . Compared to . Compared to . Compared to . Compared to the rest of Indiathe rest of Indiathe rest of Indiathe rest of Indiathe rest of Indiathe rest of Indiathe rest of Indiathe rest of Indiathe rest of Indiathe rest of Indiathe rest of Indiathe rest of Indiathe rest of Indiathe rest of Indiathe rest of Indiathe rest of Indiathe rest of India, Kerala is far ahead , Kerala is far ahead , Kerala is far ahead , Kerala is far ahead , Kerala is far ahead , Kerala is far ahead , Kerala is far ahead , Kerala is far ahead , Kerala is far ahead , Kerala is far ahead , Kerala is far ahead , Kerala is far ahead , Kerala is far ahead , Kerala is far ahead , Kerala is far ahead , Kerala is far ahead , Kerala is far ahead , Kerala is far ahead , Kerala is far ahead , Kerala is far ahead in this respect in this respect in this respect in this respect in this respect in this respect in this respect in this respect in this respect in this respect in this respect in this respect in this respect in this respect in this respect in this respect primarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the eprimarily because of the earlierarlierarlierarlierarlierarlier political and social political and social political and social political and social political and social political and social political and social political and social political and social political and social political and social political and social political and social political and social political and social political and social political and social political and social political and social political and social political and social compulsions ofcompulsions ofcompulsions ofcompulsions ofcompulsions ofcompulsions ofcompulsions ofcompulsions ofcompulsions ofcompulsions ofcompulsions ofcompulsions ofcompulsions of the state. The prethe state. The prethe state. The prethe state. The prethe state. The prethe state. The prethe state. The prethe state. The prethe state. The prethe state. The prethe state. The prethe state. The prethe state. The prethe state. The prethe state. The prethe state. The prethe state. The prethe state. The presumption of sumption of sumption of sumption of sumption of sumption of sumption of sumption of sumption of sumption of sumption of assured assured assured assured assured assured assured assured and guaranteed and guaranteed and guaranteed and guaranteed and guaranteed and guaranteed and guaranteed and guaranteed and guaranteed and guaranteed and guaranteed and guaranteed and guaranteed and guaranteed and guaranteed employment in employment in employment in employment in employment in employment in employment in employment in employment in employment in employment in employment in the Middle East the Middle East the Middle East the Middle East the Middle East the Middle East the Middle East the Middle East the Middle East the Middle East the Middle East the Middle East the Middle East the Middle East the Middle East the Middle East and also in other and also in other and also in other and also in other and also in other and also in other and also in other and also in other and also in other and also in other and also in other and also in other and also in other and also in other and also in other and also in other and also in other and also in other countries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased furthecountries increased further the scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher educationthe scope of higher education in KeralaKeralaKeralaKeralaKeralaKerala, particularparticularparticularparticularparticularparticularparticularparticularparticularparticularly the technical educationthe technical educationthe technical educationthe technical educationthe technical educationthe technical educationthe technical educationthe technical educationthe technical educationthe technical educationthe technical educationthe technical educationthe technical educationthe technical educationthe technical educationthe technical educationthe technical educationthe technical educationthe