Effect Of Raw Material Quality On The Shelf Life Of Frozen Stored Fish And Fishery Products

Frozen storage characteristics and shelflife vary considerably among species as well as within the species (Powrie, 1973; Fennema. 1973). This can be attributed to the variation in the composition of fish among various species. In certain species like sardines and mackerel. wide seasonal variation in chemical composition occur within the species. These variations affect the quality and shelflife. The nutritional level of water. spawning, method of catching, struggling etc. are found to have profound influence on the condition of the fresh fish. Soon after death the deteriorative changes in fish start due to autolysis and bacterial growth. The rate of these changes depends mainly on temperature. The handling methods have great influence on bacterial contamination. Thus the type oi'handling. temperature control. period of chill storage. processing methods. type of freezing, condition of frozen storage and period of storage affect the quality and shelflife Of the fisho In the present study extensive investigations were carried out on various factors affecting the quality of fish as well as their effect on the physical. chemical and sensory qualities of fish during frozen storage and the shelflife

Studies On Vulcanization, Rheology And Reinforcement Of Natural Rubber Latex With Special Reference To Accelerator Combinations, Surface Active Agents And Gamma Irradiation

In the present work, studies on vulcanization, rheology and reinforcement of natural rubber latex with special reference to accelerator combinations, surface active agents and gamma irradiation have been undertaken. In vulcanization, the choice of vulcanization system, the extent and mc-zie of vulcanization and network structure of the vulcanizate are important factors contributing to the overall quality of the product. The vulcanization system may be conventional type using elemental sulfur or a system involving sulfur donors. The latter type is used mainly in the manufacture of heat resistant products. For improving the technical properties of the products such as modulus and tensile strength, different accelerator combinations are used. It is known that accelerators have a strong effect on the physical properties of rubber vulcanizates. A perusal of the literature indicates that fundamental studies on the above aspects of latex technology are very limited. Thereforea systematic study on vulcanization, rheology and reinforcement of natural rubber latex with reference to the effect of accelerator combinations, surface active agents and gamma irradiation has been undertaken. The preparation and evaluation of some products like latex thread was also undertaken as a part of the study. The thesis consists of six chapter

Matemáticas Empresariales II: Función real de varias variables y Óptimos de una función escalar. Material didáctico de soporte

Material didáctico de soporte para la asignatura Matemáticas Empresariales I de la Diplomatura en Ciencias Empresariales de la Universitat de Barcelona

Matemáticas empresariales II: introducción a la matemática financiera. Material didáctico de soporte

Material didáctico de soporte para las clases de la asignatura Matemáticas Empresariales II de la Diplomatura en Ciencias Empresariales de la Universitat de Barcelona

Chitosan as a wall material for a microencapsulated delivery system for Macrobrachium rosenbergii(de Man) larvae

Chitosan has beenwidely accepted as awall material for preparing microcapsules of various purposes in human medicine. The possibility of using chitosan as a wall material for microencapsulating nutrients and drugs for aquaculture purposes, speci¢cally to Macrobrachium rosenbergii larvae was evaluated in this study. Two types of chitosan-coated microcapsules were prepared using either acetone (MEC-A) or NaOH (MEC-N) as the cross-linking agents. They were compared with a microbound diet relative to total leaching of nutrients and free amino acids (FAA). Among the microcapsules, MEC-N showed the lowest level of total leaching of nutrients (23.3%) during 5 h of immersion in seawater and released 65% FAA after 60min. During laboratory trials,75% larvae had accepted the MEC-N capsule. The results of the study suggest that chitosan can be used as a wall material for preparing microcapsules to deliver drugs and nutrients to M. rosenbergii larvae.

Preparation and characterisation of "Y-Fe203 as tape recording material

Optimum conditions for the preparation of tape recording quality Y-Fe20 s by the thermal decomposition of ferrous oxalate dihydrate have been established. Formation of the intermediate F%O~ which is most important in forming Y-FezO 3 takes place only in the presence of water vapour. Various stages of decomposition have been characterised by DTA, TG, DTG, and x-ray powder diffraction. The method for the preparation of acicular "Y-Fe208 that matches very well with the commercial tape recording material has been developed

Synthesis and characterization of γ-Fe2O3—a magnetic tape material

Acicular FeC~O4-2H20 was precipitated from glycerol and starch media. Thermal decomposition of this oxalate in dry and moist nitrogen yielded primarily FeO and Fe 3Oa respectively. Characterization was attempted through DTA, TG, x-ray diffraction, TEM and magnetization studies. It was found that the oxalate can be completely decomposed to FeaO~ in moist nitrogen (PH~o ,"-" 35 torr) at 775 K and then oxidised by dry air to acicular "/-Fe~Oa at 575 K. The resulting material has saturation magnetization (,-,., 70 emu/g), coercive field (N300 Oe) and squareness ratio ( ,~, 0-60-0-65), which values art comparable with those of the commercial samples

A Reinforcement Learning Algorithm to Economic Dispatch Considering Transmission Losses

Reinforcement Learning (RL) refers to a class of learning algorithms in which learning system learns which action to take in different situations by using a scalar evaluation received from the environment on performing an action. RL has been successfully applied to many multi stage decision making problem (MDP) where in each stage the learning systems decides which action has to be taken. Economic Dispatch (ED) problem is an important scheduling problem in power systems, which decides the amount of generation to be allocated to each generating unit so that the total cost of generation is minimized without violating system constraints. In this paper we formulate economic dispatch problem as a multi stage decision making problem. In this paper, we also develop RL based algorithm to solve the ED problem. The performance of our algorithm is compared with other recent methods. The main advantage of our method is it can learn the schedule for all possible demands simultaneously.

Reinforcement Learning approaches to Economic Dispatch problem

This paper presents Reinforcement Learning (RL) approaches to Economic Dispatch problem. In this paper, formulation of Economic Dispatch as a multi stage decision making problem is carried out, then two variants of RL algorithms are presented. A third algorithm which takes into consideration the transmission losses is also explained. Efficiency and flexibility of the proposed algorithms are demonstrated through different representative systems: a three generator system with given generation cost table, IEEE 30 bus system with quadratic cost functions, 10 generator system having piecewise quadratic cost functions and a 20 generator system considering transmission losses. A comparison of the computation times of different algorithms is also carried out.

Reinforcement Learning Solution for Unit Commitment Problem Considering Minimum Start Up and Shut Down Times

Unit Commitment Problem (UCP) in power system refers to the problem of determining the on/ off status of generating units that minimize the operating cost during a given time horizon. Since various system and generation constraints are to be satisfied while finding the optimum schedule, UCP turns to be a constrained optimization problem in power system scheduling. Numerical solutions developed are limited for small systems and heuristic methodologies find difficulty in handling stochastic cost functions associated with practical systems. This paper models Unit Commitment as a multi stage decision making task and an efficient Reinforcement Learning solution is formulated considering minimum up time /down time constraints. The correctness and efficiency of the developed solutions are verified for standard test systems

A Reinforcement Learning Approach to Economic Dispatch using Neural Networks

This paper presents a Reinforcement Learning (RL) approach to economic dispatch (ED) using Radial Basis Function neural network. We formulate the ED as an N stage decision making problem. We propose a novel architecture to store Qvalues and present a learning algorithm to learn the weights of the neural network. Even though many stochastic search techniques like simulated annealing, genetic algorithm and evolutionary programming have been applied to ED, they require searching for the optimal solution for each load demand. Also they find limitation in handling stochastic cost functions. In our approach once we learn the Q-values, we can find the dispatch for any load demand. We have recently proposed a RL approach to ED. In that approach, we could find only the optimum dispatch for a set of specified discrete values of power demand. The performance of the proposed algorithm is validated by taking IEEE 6 bus system, considering transmission losses

Reinforcement Learning solution for Unit Commitment Problem through pursuit method

Unit commitment is an optimization task in electric power generation control sector. It involves scheduling the ON/OFF status of the generating units to meet the load demand with minimum generation cost satisfying the different constraints existing in the system. Numerical solutions developed are limited for small systems and heuristic methodologies find difficulty in handling stochastic cost functions associated with practical systems. This paper models Unit Commitment as a multi stage decision task and Reinforcement Learning solution is formulated through one efficient exploration strategy: Pursuit method. The correctness and efficiency of the developed solutions are verified for standard test systems

Modification of Polypropylene/High Density Polyethylene Blend Using Nanokaolinite Clay and E-Glass Fibre: Preparation, Characterization and Micromechanical Modelling

Upgrading two widely used standard plastics, polypropylene (PP) and high density polyethylene (HDPE), and generating a variety of useful engineering materials based on these blends have been the main objective of this study. Upgradation was effected by using nanomodifiers and/or fibrous modifiers. PP and HDPE were selected for modification due to their attractive inherent properties and wide spectrum of use. Blending is the engineered method of producing new materials with tailor made properties. It has the advantages of both the materials. PP has high tensile and flexural strength and the HDPE acts as an impact modifier in the resultant blend. Hence an optimized blend of PP and HDPE was selected as the matrix material for upgradation. Nanokaolinite clay and E-glass fibre were chosen for modifying PP/HDPE blend. As the first stage of the work, the mechanical, thermal, morphological, rheological, dynamic mechanical and crystallization characteristics of the polymer nanocomposites prepared with PP/HDPE blend and different surface modified nanokaolinite clay were analyzed. As the second stage of the work, the effect of simultaneous inclusion of nanokaolinite clay (both N100A and N100) and short glass fibres are investigated. The presence of nanofiller has increased the properties of hybrid composites to a greater extent than micro composites. As the last stage, micromechanical modeling of both nano and hybrid A composite is carried out to analyze the behavior of the composite under load bearing conditions. These theoretical analyses indicate that the polymer-nanoclay interfacial characteristics partially converge to a state of perfect interfacial bonding (Takayanagi model) with an iso-stress (Reuss IROM) response. In the case of hybrid composites the experimental data follows the trend of Halpin-Tsai model. This implies that matrix and filler experience varying amount of strain and interfacial adhesion between filler and matrix and also between the two fillers which play a vital role in determining the modulus of the hybrid composites.A significant observation from this study is that the requirement of higher fibre loading for efficient reinforcement of polymers can be substantially reduced by the presence of nanofiller together with much lower fibre content in the composite. Hybrid composites with both nanokaolinite clay and micron sized E-glass fibre as reinforcements in PP/HDPE matrix will generate a novel class of high performance, cost effective engineering material.

The Courseware Watchdog: an ontology-based tool for finding and organizing learning material

Topics in education are changing with an ever faster pace. E-Learning resources tend to be more and more decentralised. Users need increasingly to be able to use the resources of the web. For this, they should have tools for finding and organizing information in a decentral way. In this, paper, we show how an ontology-based tool suite allows to make the most of the resources available on the web.

Rissbildung und Zugtragverhalten von mit Stabstahl und Fasern bewehrtem Ultrahochfesten Beton (UHPC)

Ultrahochfester Beton (UHPC) ist ein sehr gefügedichter zementgebundener Werkstoff, der sich nicht nur durch eine hohe Druckfestigkeit, sondern auch durch einen hohen Widerstand gegen jede Form physikalischen oder chemischen Angriffs auszeichnet. Duktiles Nachbruchverhalten bei Druckversagen wird meist durch die Zugabe dünner kurzer Fasern erreicht. In Kombination mit konventioneller Betonstahl- oder Spannbewehrung ermöglicht UHPC die Ausführung sehr schlanker, weitgespannter Konstruktionen und eröffnet zugleich neue Anwendungsgebiete, wie zum Beispiel die flächenhafte Beschichtung von Brückendecks. Durch das Zusammenwirken kontinuierlicher Bewehrungselemente und diskontinuierlich verteilter kurzer Fasern ergeben sich unter Zugbeanspruchung Unterschiede gegenüber dem bekannten Stahl- und Spannbeton. In der vorliegenden Arbeit wird hierzu ein Modell entwickelt und durch eine umfangreiche Versuchsreihe abgesichert. Ausgangspunkt sind experimentelle und theoretische Untersuchungen zum Verbundverhalten von Stabstählen in einer UHPC-Matrix und zum Einfluss einer Faserzugabe auf das Reiß- und Zugtragverhalten von UHPC. Die Modellbildung für UHPC-Zugelemente mit gemischter Bewehrung aus Stabstahl und Fasern erfolgt auf der Grundlage der Vorgänge am diskreten Riss, die daher sehr ausführlich behandelt werden. Für den elastischen Verformungsbereich der Stabbewehrung (Gebrauchslastbereich) kann damit das Last-Verformungs-Verhalten für kombiniert bewehrte Bauteile mechanisch konsistent unter Berücksichtigung des bei UHPC bedeutsamen hohen Schwindmaßes abgebildet werden. Für die praktische Anwendung wird durch Vereinfachungen ein Näherungsverfahren abgeleitet. Sowohl die theoretischen als auch die experimentellen Untersuchungen bestätigen, dass der faserbewehrte UHPC bei Kombination mit kontinuierlichen Bewehrungselementen selbst kein verfestigendes Verhalten aufweisen muss, um insgesamt verfestigendes Verhalten und damit eine verteilte Rissbildung mit sehr keinen Rissbreiten und Rissabständen zu erzielen. Diese Beobachtungen können mit Hilfe der bisher zur Verfügung stehenden Modelle, die im Wesentlichen eine Superposition isoliert ermittelter Spannungs-Dehnungs-Beziehungen des Faserbetons und des reinen Stahls vorsehen, nicht nachvollzogen werden. Wie die eigenen Untersuchungen zeigen, kann durch ausreichend dimensionierte Stabstahlbewehrung zielgerichtet und ohne unwirtschaftlich hohe Fasergehalte ein gutmütiges Verhalten von UHPC auf Zug erreicht werden. Die sichere Begrenzung der Rissbreiten auf deutlich unter 0,1 mm gewährleistet zugleich die Dauerhaftigkeit auch bei ungünstigen Umgebungsbedingungen. Durch die Minimierung des Material- und Energieeinsatzes und die zu erwartende lange Nutzungsdauer lassen sich so im Sinne der Nachhaltigkeit optimierte Bauteile realisieren.