Materials for Fish Nets-Their Properties, Selection and Preservation

The properties of synthetic fibres vary with thc inherent physical characteristics of the basic raw materials used mode of preparation of yarns and method of construction of twines. Since the synthetic fibres as maufactured from polymers which are synthesized from simple chemical units, the qualities of man-made fibres can he influenced by the process of manufacture and certain modifications can even be introduced at the processing stage to meet any specific requirement to a certain extent. Hence, an elaborate study of the properties of fish not twines produced has been taken up with a view to determining their suitability for various types of fishing gear with particular reference to conditions prevailing in India.

FEATURE SELECTION AND COMPARISON OF TWO NAÏVE BAYES CLASSIFICATION METHODS IN THE CONTEXT OF SPAM FILTERING

Treating e-mail filtering as a binary text classification problem, researchers have applied several statistical learning algorithms to email corpora with promising results. This paper examines the performance of a Naive Bayes classifier using different approaches to feature selection and tokenization on different email corpora

Applying Data mining using Statistical Techniques for Career Selection

For years, choosing the right career by monitoring the trends and scope for different career paths have been a requirement for all youngsters all over the world. In this paper we provide a scientific, data mining based method for job absorption rate prediction and predicting the waiting time needed for 100% placement, for different engineering courses in India. This will help the students in India in a great deal in deciding the right discipline for them for a bright future. Information about passed out students are obtained from the NTMIS ( National technical manpower information system ) NODAL center in Kochi, India residing in Cochin University of science and technology

Selection of Marine Yeasts for the Generation of Single Cell Protein from Prawn-shell Waste

Marine yeasts (33 strains) were isolated from the coastal and offshore waters off Cochin. The isolates were identified and then characterized for the utilization of starch, gelatin, lipid, cellulose, urea, pectin, lignin, chitin and prawn-shell waste. Most of the isolates were Candida species. Based on the biochemical characterization, four potential strains were selected and their optimum pH and NaCI concentration for growth were determined. These strains were then inoculated into prawn-shell waste and SCP (single cell protein) generation was noted in terms of the increase in protein content of the final product.

Konzeption eines generischen Vorgehensmodells zur strategieorientierten und partizipativen Einführung komplexer Softwaresysteme unter Berücksichtigung organisatorischer Gestaltungsprozesse

Die Dissertation befasst sich mit der Einführung komplexer Softwaresysteme, die, bestehend aus einer Kombination aus parametrisierter Standardsoftware gepaart mit Wettbewerbsvorteil sichernden Individualsoftwarekomponenten, keine Software-Engineering-Projekte im klassischen Sinn mehr darstellen, sondern einer strategieorientierten Gestaltung von Geschäftsprozessen und deren Implementierung in Softwaresystemen bedürfen. Die Problemstellung einer adäquaten Abwägung zwischen TCO-optimierender Einführung und einer gleichzeitigen vollständigen Unterstützung der kritischen Erfolgsfaktoren des Unternehmens ist hierbei von besonderer Bedeutung. Der Einsatz integrierter betriebswirtschaftlicher Standardsoftware, mit den Möglichkeiten einer TCO-Senkung, jedoch ebenfalls der Gefahr eines Verlustes von Alleinstellungsmerkmalen am Markt durch Vereinheitlichungstendenzen, stellt ein in Einführungsprojekten wesentliches zu lösendes Problem dar, um Suboptima zu vermeiden. Die Verwendung von Vorgehensmodellen, die sich oftmals an klassischen Softwareentwicklungsprojekten orientieren oder vereinfachte Phasenmodelle für das Projektmanagement darstellen, bedingt eine fehlende Situationsadäquanz in den Detailsituationen der Teilprojekte eines komplexen Einführungsprojektes. Das in dieser Arbeit entwickelte generische Vorgehensmodell zur strategieorientierten und partizipativen Einführung komplexer Softwaresysteme im betriebswirtschaftlichen Anwendungsbereich macht - aufgrund der besonders herausgearbeiteten Ansätze zu einer strategieorientierten Einführung, respektive Entwicklung derartiger Systeme sowie aufgrund der situationsadäquaten Vorgehensstrategien im Rahmen der Teilprojektorganisation � ein Softwareeinführungsprojekt zu einem Wettbewerbsfaktor stärkenden, strategischen Element im Unternehmen. Die in der Dissertation diskutierten Überlegungen lassen eine Vorgehensweise präferieren, die eine enge Verschmelzung des Projektes zur Organisationsoptimierung mit dem Softwareimplementierungsprozess impliziert. Eine Priorisierung der Geschäftsprozesse mit dem Ziel, zum einen bei Prozessen mit hoher wettbewerbsseitiger Priorität ein organisatorisches Suboptimum zu vermeiden und zum anderen trotzdem den organisatorischen Gestaltungs- und den Systemimplementierungsprozess schnell und ressourcenschonend durchzuführen, ist ein wesentliches Ergebnis der Ausarbeitungen. Zusätzlich führt die Ausgrenzung weiterer Prozesse vom Einführungsvorgang zunächst zu einem Produktivsystem, welches das Unternehmen in den wesentlichen Punkten abdeckt, das aber ebenso in späteren Projektschritten zu einem System erweitert werden kann, welches eine umfassende Funktionalität besitzt. Hieraus ergeben sich Möglichkeiten, strategischen Anforderungen an ein modernes Informationssystem, das die kritischen Erfolgsfaktoren eines Unternehmens konsequent unterstützen muss, gerecht zu werden und gleichzeitig ein so weit als möglich ressourcenschonendes, weil die Kostenreduktionsaspekte einer Standardlösung nutzend, Projekt durchzuführen. Ein weiterer wesentlicher Aspekt ist die situationsadäquate Modellinstanziierung, also die projektspezifische Anpassung des Vorgehensmodells sowie die situationsadäquate Wahl der Vorgehensweisen in Teilprojekten und dadurch Nutzung der Vorteile der verschiedenen Vorgehensstrategien beim konkreten Projektmanagement. Der Notwendigkeit der Entwicklung einer Projektorganisation für prototypingorientiertes Vorgehen wird in diesem Zusammenhang ebenfalls Rechnung getragen. Die Notwendigkeit der Unternehmen, sich einerseits mit starken Differenzierungspotenzialen am Markt hervorzuheben und andererseits bei ständig sinkenden Margen einer Kostenoptimierung nachzukommen, lässt auch in Zukunft das entwickelte Modell als erfolgreich erscheinen. Hinzu kommt die Tendenz zu Best-Of-Breed-Ansätzen und komponentenbasierten Systemen im Rahmen der Softwareauswahl, die eine ausgesprochen differenzierte Vorgehensweise in Projekten verstärkt notwendig machen wird. Durch die in das entwickelte Modell integrierten Prototyping-Ansätze wird der auch in Zukunft an Bedeutung gewinnenden Notwendigkeit der Anwenderintegration Rechnung getragen.

User Profile Management and Selection in Context-Aware Service Platforms for Networks Beyond 3G

In recent years, progress in the area of mobile telecommunications has changed our way of life, in the private as well as the business domain. Mobile and wireless networks have ever increasing bit rates, mobile network operators provide more and more services, and at the same time costs for the usage of mobile services and bit rates are decreasing. However, mobile services today still lack functions that seamlessly integrate into users’ everyday life. That is, service attributes such as context-awareness and personalisation are often either proprietary, limited or not available at all. In order to overcome this deficiency, telecommunications companies are heavily engaged in the research and development of service platforms for networks beyond 3G for the provisioning of innovative mobile services. These service platforms are to support such service attributes. Service platforms are to provide basic service-independent functions such as billing, identity management, context management, user profile management, etc. Instead of developing own solutions, developers of end-user services such as innovative messaging services or location-based services can utilise the platform-side functions for their own purposes. In doing so, the platform-side support for such functions takes away complexity, development time and development costs from service developers. Context-awareness and personalisation are two of the most important aspects of service platforms in telecommunications environments. The combination of context-awareness and personalisation features can also be described as situation-dependent personalisation of services. The support for this feature requires several processing steps. The focus of this doctoral thesis is on the processing step, in which the user’s current context is matched against situation-dependent user preferences to find the matching user preferences for the current user’s situation. However, to achieve this, a user profile management system and corresponding functionality is required. These parts are also covered by this thesis. Altogether, this thesis provides the following contributions: The first part of the contribution is mainly architecture-oriented. First and foremost, we provide a user profile management system that addresses the specific requirements of service platforms in telecommunications environments. In particular, the user profile management system has to deal with situation-specific user preferences and with user information for various services. In order to structure the user information, we also propose a user profile structure and the corresponding user profile ontology as part of an ontology infrastructure in a service platform. The second part of the contribution is the selection mechanism for finding matching situation-dependent user preferences for the personalisation of services. This functionality is provided as a sub-module of the user profile management system. Contrary to existing solutions, our selection mechanism is based on ontology reasoning. This mechanism is evaluated in terms of runtime performance and in terms of supported functionality compared to other approaches. The results of the evaluation show the benefits and the drawbacks of ontology modelling and ontology reasoning in practical applications.

The Ri chicken breed and livelihoods in North Vietnam: characterization and prospects

For the last twenty years, the consumption of poultry meat has boomed in Vietnam as in the rest of the developing world. Capital-intensive production has grown rapidly to satisfy this demand. Based on a few numbers of genetically uniform strains, these systems threaten biodiversity. In Vietnam, both rural and urban households still keep indigenous chickens as part of a diversified livelihood portfolio. In line with the national in situ conservation strategy, this study approached the context of local poultry keeping in two rural and one suburban districts of Northern Vietnam. It aimed at understanding households’ willingness, constraints and opportunities for practice improvement, including breeds’ management. As the Ri chicken constitutes the large majority of backyard flocks, two particular objectives of this study are the morpho-biometric characterisation of phenotypic diversity among individuals classified as Ri by farmers and an assessment of their productive potential. Chicken was found to hold a different place in livelihoods of the three districts with consequences on the management of genetic resources. The most favourable conditions for improvement of the Ri breed was found in the rural district of Luong-Son, due to market integration. In the more remote district of Ky-Son, living standards were lower and much would be gained from Ri conservation. Ri breed was the most threatened in the suburban Gia-Lam district, where poultry was a minor side-activity, lacking incentive for genetic management. From motives and constraints, tracks about breeding goals are suggested. Further considerations about conservation, improvement, market integration and livelihoods are proposed.

Farmers’ desired traits and selection criteria for maize varieties and their implications for maize breeding: A case study from KwaZulu-Natal Province, South Africa

Adoption of hybrids and improved varieties has remained low in the smallholder farming sector of South Africa, despite maize being the staple food crop for the majority of households. The objective of this study was to establish preferred maize characteristics by farmers which can be used as selection criteria by maize breeders in crop improvement. Data were collected from three villages of a selected smallholder farming area in South Africa using a survey covering 300 households and participatory rural appraisal methodology. Results indicated a limited selection of maize varieties grown by farmers in the area compared to other communities in Africa. More than 97% of the farmers grew a local landrace called Natal-8-row or IsiZulu. Hybrids and improved open pollinated varieties were planted by less than 40% of the farmers. The Natal-8-row landrace had characteristics similar to landraces from eastern and southern Africa and closely resembled Hickory King, a landrace still popular in Southern Africa. The local landrace was preferred for its taste, recycled seed, tolerance to abiotic stresses and yield stability. Preferred characteristics of maize varieties were high yield and prolificacy, disease resistance, early maturity, white grain colour, and drying and shelling qualities. Farmers were willing to grow hybrids if the cost of seed and other inputs were affordable and their preferences were considered. Our results show that breeding opportunities exist for improving the farmers’ local varieties and maize breeders can take advantage of these preferred traits and incorporate them into existing high yielding varieties.

The Koundoum sheep breed in Niger: morpho-biometric study and description of the production system

The diffusion of highly productive breeds across developing countries goes along with a neglect of indigenous breeds, which are well suited to their environment but often show low yields. Thus, in Niger, the flock of Koundoum sheep are rapidly decreasing. The Koundoum is one of the few wool sheep breeds of Africa and shows important adaptive feature to its native environment, i.e. the humid pastures on the banks of the Niger River. To characterise the breed and to understand its production context, a survey has been conducted in 104 herds in four communes along the Niger River (Kollo, Tillabery, Say and Tera). Nine body measurements, including live weight, were taken on 180 adult sheep (101 females and 79 males). The herds varied from 2 to 60 heads, with a median size of eight animals and two thirds of the herds having less than 10 animals. Mainly fed on natural pastures, 85.6% of the herds received crop residues. Only natural mating was practiced. Veterinary care was restricted to anti-helminthic and some indigenous treatments. The frequent affiliation of breeders to professional unions appeared as favourable to the implementation of a collective conservation program. The Koundoum sheep were white or black coated, with the black colour being most frequent (75.6%). Wattles were present in both sexes at similar frequencies of around 14%. All biometric variables were significantly and positively correlated between them. The thoracic perimeter showed the best correlation with live weight in both males and females. Three variables were selected for live weight prediction: thoracic perimeter, height at withers and rump length. From the present study, it is expected that the in situ conservation of the Koundoum sheep will be highly problematic, due to lack of market opportunities for wool and the willingness of smallholders to get involved in pure Koundoum rearing.

Attentional Selection in Object Recognition

A key problem in object recognition is selection, namely, the problem of identifying regions in an image within which to start the recognition process, ideally by isolating regions that are likely to come from a single object. Such a selection mechanism has been found to be crucial in reducing the combinatorial search involved in the matching stage of object recognition. Even though selection is of help in recognition, it has largely remained unsolved because of the difficulty in isolating regions belonging to objects under complex imaging conditions involving occlusions, changing illumination, and object appearances. This thesis presents a novel approach to the selection problem by proposing a computational model of visual attentional selection as a paradigm for selection in recognition. In particular, it proposes two modes of attentional selection, namely, attracted and pay attention modes as being appropriate for data and model-driven selection in recognition. An implementation of this model has led to new ways of extracting color, texture and line group information in images, and their subsequent use in isolating areas of the scene likely to contain the model object. Among the specific results in this thesis are: a method of specifying color by perceptual color categories for fast color region segmentation and color-based localization of objects, and a result showing that the recognition of texture patterns on model objects is possible under changes in orientation and occlusions without detailed segmentation. The thesis also presents an evaluation of the proposed model by integrating with a 3D from 2D object recognition system and recording the improvement in performance. These results indicate that attentional selection can significantly overcome the computational bottleneck in object recognition, both due to a reduction in the number of features, and due to a reduction in the number of matches during recognition using the information derived during selection. Finally, these studies have revealed a surprising use of selection, namely, in the partial solution of the pose of a 3D object.

Model Selection in Summary Evaluation

A difficulty in the design of automated text summarization algorithms is in the objective evaluation. Viewing summarization as a tradeoff between length and information content, we introduce a technique based on a hierarchy of classifiers to rank, through model selection, different summarization methods. This summary evaluation technique allows for broader comparison of summarization methods than the traditional techniques of summary evaluation. We present an empirical study of two simple, albeit widely used, summarization methods that shows the different usages of this automated task-based evaluation system and confirms the results obtained with human-based evaluation methods over smaller corpora.

Feature Selection for Face Detection

We present a new method to select features for a face detection system using Support Vector Machines (SVMs). In the first step we reduce the dimensionality of the input space by projecting the data into a subset of eigenvectors. The dimension of the subset is determined by a classification criterion based on minimizing a bound on the expected error probability of an SVM. In the second step we select features from the SVM feature space by removing those that have low contributions to the decision function of the SVM.

Sales restriction, quality selection and the mode of competition

A regulator imposing “sales restrictions” on firms competing in oligopolistic markets may enhance quality provision by the firms. Moreover, for most restrictions levels, the impact on quality selection is invariant to the mode of competition

Use of decision trees in colour feature selection: application to object recognition in outdoor scenes

A new method for the automated selection of colour features is described. The algorithm consists of two stages of processing. In the first, a complete set of colour features is calculated for every object of interest in an image. In the second stage, each object is mapped into several n-dimensional feature spaces in order to select the feature set with the smallest variables able to discriminate the remaining objects. The evaluation of the discrimination power for each concrete subset of features is performed by means of decision trees composed of linear discrimination functions. This method can provide valuable help in outdoor scene analysis where no colour space has been demonstrated as being the most suitable. Experiment results recognizing objects in outdoor scenes are reported

Enhanced Model Selection for motion segmentation

In this paper a novel rank estimation technique for trajectories motion segmentation within the Local Subspace Affinity (LSA) framework is presented. This technique, called Enhanced Model Selection (EMS), is based on the relationship between the estimated rank of the trajectory matrix and the affinity matrix built by LSA. The results on synthetic and real data show that without any a priori knowledge, EMS automatically provides an accurate and robust rank estimation, improving the accuracy of the final motion segmentation