A case-based reasoning methodology to formulating polyurethanes

Formulation of polyurethanes is a complex problem poorly understood as it has developed more as an art rather than a science. Only a few experts have mastered polyurethane (PU) formulation after years of experience and the major raw material manufacturers largely hold such expertise. Understanding of PU formulation is at present insufficient to be developed from first principles. The first principle approach requires time and a detailed understanding of the underlying principles that govern the formulation process (e.g. PU chemistry, kinetics) and a number of measurements of process conditions. Even in the simplest formulations, there are more that 20 variables often interacting with each other in very intricate ways. In this doctoral thesis the use of the Case-Based Reasoning and Artificial Neural Network paradigm is proposed to enable support for PUs formulation tasks by providing a framework for the collection, structure, and representation of real formulating knowledge. The framework is also aimed at facilitating the sharing and deployment of solutions in a consistent and referable way, when appropriate, for future problem solving. Two basic problems in the development of a Case-Based Reasoning tool that uses past flexible PU foam formulation recipes or cases to solve new problems were studied. A PU case was divided into a problem description (i. e. PU measured mechanical properties) and a solution description (i. e. the ingredients and their quantities to produce a PU). The problems investigated are related to the retrieval of former PU cases that are similar to a new problem description, and the adaptation of the retrieved case to meet the problem constraints. For retrieval, an alternative similarity measure based on the moment's description of a case when it is represented as a two dimensional image was studied. The retrieval using geometric, central and Legendre moments was also studied and compared with a standard nearest neighbour algorithm using nine different distance functions (e.g. Euclidean, Canberra, City Block, among others). It was concluded that when cases were represented as 2D images and matching is performed by using moment functions in a similar fashion to the approaches studied in image analysis in pattern recognition, low order geometric and Legendre moments and central moments of any order retrieve the same case as the Euclidean distance does when used in a nearest neighbour algorithm. This means that the Euclidean distance acts a low moment function that represents gross level case features. Higher order (moment's order>3) geometric and Legendre moments while enabling finer details about an image to be represented had no standard distance function counterpart. For the adaptation of retrieved cases, a feed-forward back-propagation artificial neural network was proposed to reduce the adaptation knowledge acquisition effort that has prevented building complete CBR systems and to generate a mapping between change in mechanical properties and formulation ingredients. The proposed network was trained with the differences between problem descriptions (i.e. mechanical properties of a pair of foams) as input patterns and the differences between solution descriptions (i.e. formulation ingredients) as the output patterns. A complete data set was used based on 34 initial formulations and a 16950 epochs trained network with 1102 training exemplars, produced from the case differences, gave only 4% error. However, further work with a data set consisting of a training set and a small validation set failed to generalise returning a high percentage of errors. Further tests on different training/test splits of the data also failed to generalise. The conclusion reached is that the data as such has insufficient common structure to form any general conclusions. Other evidence to suggest that the data does not contain generalisable structure includes the large number of hidden nodes necessary to achieve convergence on the complete data set.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Special oils for halal and safe cosmetics

Three types of non conventional oils were extracted, analyzed and tested for toxicity. Date palm kernel oil (DPKO), mango kernel oil (MKO) and Ramputan seed oil (RSO). Oil content for tow cultivars of dates Deglect Noor and Moshkan was 9.67% and 7.30%, respectively. The three varieties of mango were found to contain about 10% oil in average. The red yellow types of Ramputan were found to have 11 and 14% oil, respectively. The phenolic compounds in DPKO, MKO and RSO were 0.98, 0.88 and 0.78 mg/ml Gallic acid equivalent, respectively. Oils were analyzed for their fatty acid composition and they are rich in oleic acid C18:1 and showed the presence of (dodecanoic acid) lauric acid C12:0, which reported to appear some antimicrobial activities. All extracted oils, DPKO, MKO and RSO showed no toxic effect using prime shrimp bioassay. Since these oils are stable, melt at skin temperature, have good lubricity and are great source of essential fatty acids; they could be used as highly moisturizing, cleansing and nourishing oils because of high oleic acid content. They are ideal for use in such halal cosmetics such as Science, Engineering and Technology 75 skin care and massage, hair-care, soap and shampoo products

Blood type examination of Cigentur community as efforts to realize community care for health

Counseling and early examination of blood type to the community at Cigentur village has not been done before. Blood transfusion from incompatible types can cause immunological transfusion reactions and clinical aspects such as the incompatibility of the blood type systems ABO. The community engagement method consists of direct information to the community by visiting every communities house (door to door). Besides, the engagement was also carried out quietly, namely, the residents came to the post directly located at the Wiswa Anak Yatim Piatu, At-Taqwa. After conducting a health test, people who provide personal information from the results of their blood tests. In addition to identifying blood types, this activity provides more knowledge about the health of each that is related to the utilization that has been identified by the group. The results of this activity can be in the form of initial information to determine the policies of each community in carrying out social activities such as blood transfusion. The types of rhesus tests from the communityof Cigentur must be done for information about blood type identification are complete

Acetylcholine esterase as a possible marker for the detection of halal way of slaughtering

Introduction: Different methods of slaughtering are being practiced because of differences in religious guidelines and environmental issues (use of electricity) or convenience of handling etc. Variation in methods of slaughtering results in different conditions namely, release of varying amount of blood and different degree of movement of its body parts prior to death. These issues are related to the release of neurotransmitter (NT) at the neuro-muscular junction (NMJ) eventually is subject to be released from the body through the blood flow. Experimental design: Muscle samples from chicken in small pieces were collected immediately after slaughtering. Slaughtering was carried out using sharp knife. Two different conditions pertaining to the Islamic guidelines of slaughtering were investigated. such as whether the neck was severed (S+) or not (S-) from the body during slaughtering and whether the animal just after slaughtering was released (R+) or not (R-). The level of acetylecholine esterase mRNA involved in the degradation of acetylecholine, a NT at NMJ was investigated by RT-PCR. Results: The level of acetylecholine esterase mRNA was not detected in the sample obtained from the chicken slaughtered following Islamic guidelines i.e., neck should not be severed and body should be released just after the slaughtering (R+S-). Conclusions: Level of acetylcholine or acetylcholine esterase can be used as a biomarker to identify if the slaughtering is performed following Islamic guidelines

Calophyllum canum : antibacterial and anticancer plant

Human have used plants as a source of medicine throughout the world since time immemorial. Today there are at least 120 distinct chemical substances derived from plants that are considered as important drugs currently in use in one or more countries in the world. In particular, 60% drugs currently in clinical use for treatment of cancer were found to be of natural origin. Calophyllum canum is a large tree which grows in South East Asia and which is popular for its timber. This plant belongs to the family Guttiferae; a family that boasts species which are rich in bioactive phytochemicals. Some species are believed to having medicinal values and are used against several diseases including anti-inflammatory, anti infectious, astringent and antipyretic. We have successfully isolated two compounds from the methanol extract of Calophyllum canum stembarks that active inhibit the growth of Staphylococcus aureus (ATCC 29213 and ATCC 25923). The cytotoxic study on the extracts revealed that the n-hexane extract had the strongest antiproliferation activity, followed by the methanol extract. n-hexane strongly inhibited the growth of TE1 and MCF7 cell lines. IC50 for n-hexane and methanol extract activity on the A549 cell line was found to be 27.96 μg/mL and 78.9 μg/mL respectively.The compounds (CE0 - CE5) isolated from ethyl acetate extract of C. canum are active to inhibit cell proliferation of human cervix adenocarcinoma cells

Knowledge-based product support systems

This research helps bridge the gap between conventional product support, where the support system is considered as a stand-alone application, and the new paradigm of responsive one, where the support system frequently communicates with its environment and reacts to stimuli. This new paradigm would enable product support knowledge to be captured, stored, processed, and updated automatically, being delivered to the users when, where and in the form they need it. The research reported in this thesis first defines Product Support Systems (PRSSs) as electronic means that provide accurate and up-to-date information to the user in a coherent and personalised manner. Product support knowledge is then identified as the integration of product, task, user, and support documentation knowledge. Next, the thesis focuses on an ontology-based model of the structure, relations, and attributes of product support knowledge. In that model product support virtual documentation (PSVD) is presented as an aggregation of Information Objects (IOs) and Information Object Clusters (IOCs). The description of PSVD is followed by an analysis of the relation between IOs, IOCs, and domain knowledge. Then, the thesis builds on the ontology-based representation of product support knowledge and explores the synergy between product support, problem solving, and knowledge engineering. As a result, a structured problem solving approach is introduced that combines case-based adaptation and model-based generation techniques. Based on that approach a knowledge engineering framework for product support systems is developed. A conceptual model of context-aware product support systems that extends the framework is then introduced. The conceptual model includes an ontology-based representation of knowledge related to the users, their activities, the support environment, and the device being used. An approach to semi-automatically integrating design and documentation data is also proposed as part of context-aware product support systems development process.EThOS - Electronic Theses Online ServiceGBUnited Kingdo