Abstract Query optimization is an important task in the client / server environment of a distributed database, where large data locations are widely distributed, such as distribution of health epidemiology data based DBD on geographic information systems (GIS). In order to generate query optimization on a distributed database it is necessary to have a proper method on a particular query process function. The query process requires important attention especially... Query optimization is an important task in the client / server environment of a distributed database, where large data locations are widely distributed, such as distribution of health epidemiology data based DBD on geographic information systems (GIS). In order to generate query optimization on a distributed database it is necessary to have a proper method on a particular query process function. The query process requires important attention especially in distributed databases, because the result of a cost-based query process (access fees and communication costs) is affected by the involvement of the number of attributes and sites visited. If a query can be decomposed into subqueries that require operations on a separate database (geographically) and can determine the exact site access sequence of a query process query circuit then the operating costs for the query process will be minimal. When a query process in a distributed database occurs, queries operations will search for data from various attributes in a scattered database table, whereas query processes often do not require all the attributes of the table. Therefore, in order to optimize the query required minimum query operation cost (communication cost and access cost). One way to minimize the cost of queries is to separate attributes that are not required by a query, thereby reducing the amount of time communication and access. Can not make mistakes in the separation of attributes, attributes should not be split indiscriminately, because if not appropriate it will result in the amount of access costs are getting larger and ultimately reduce the performance of the query process itself. To perform such attribute separation can be done by Vertical Fragmentation method. In this experiment will be conducted by comparing the results of separation attributes. Separation of attributes will be done by using Vertical Fragmentation method to source health database tables (database testing), while the algorithm used for attribute separation is Bond Energy Algorithm (BEA) and Graphic Based Vertical Partitioning (GBVP). The initial result of vertical fragmentation in both algorithms is the determination of what attributes will be separated from a number of specific query processes. The result of separation of attributes from each algorithm will be compared and evaluated using Partitioned Evaluator (PE). The purpose of evaluation of the result of separation of attribute is to know the amount of access cost of some attributes from each algorithm. Thus it will be known the most optimal algorithm in the operation of the query process. Algorithms that have better performance are algorithms that have the lowest execution time. The purpose of this research is to perform query optimization by applying the correct algorithm, by way of framing the method of fragmentation between BEA algorithm with GBVT to then concluded algorithm which has query optimization performance from the most optimal query process so it is suitable to be applied as query operation on distributed database in field health. Read More Read Less

Abstract The use of traditional medicine is increasing rapidly in many societies due to its efficiency and affordability. The locally available herbs are basically used in the treatment of symptoms and diseases. Herbal Medicines have proved effective in many cases and outperformed the chemical drugs. Subsequently, the need arose to develop an herbal repository containing the taxonomy hierarchy that represents the structured knowledge of herbs and could be integrated in... The use of traditional medicine is increasing rapidly in many societies due to its efficiency and affordability. The locally available herbs are basically used in the treatment of symptoms and diseases. Herbal Medicines have proved effective in many cases and outperformed the chemical drugs. Subsequently, the need arose to develop an herbal repository containing the taxonomy hierarchy that represents the structured knowledge of herbs and could be integrated in many medical applications that use the herbs in the treatment in an accurate and effective way. Today, Medical ontologies have become the most efficient way for representing declarative knowledge about diseases, symptoms, medications, and diagnosis. Many ontologies have been elaborated in the few past years for some well-known traditional medicine like the Chinese, African and Korean traditional medicine. Few of these existing ontologies tried to relate traditional medicine ontologies with known 'modern' medical ontologies. Linking traditional medicine ontologies with medical ontologies can benefit in the treatment process where herbs can be used effectively. In this paper, we are proposing a new ontology to be used for the herbal medicine. We are also introducing an algorithm to align our ontology with the symptoms ontology SYMP and with the diseases ontology DOID. The MeSH ontology is the source of our herbal concepts. We are actually using this ontology in an educational expert system that prescribes herbs for the treatment of casual symptoms. In addition, new herbal blends can be suggested, and conflicting herbs effects can be detected through this system. A simple e-health portal has been developed to interact with the expert system. Read More Read Less

Abstract In the collaborative serious game, adaptation is one of the main factors could be considered in the phase of conception since they can contribute to improve learning performance. Learning styles present one of the most factors that affect learning outcomes. Game-based learning (GBL) that takes into account learning styles in the process of adaptation, it furnishes to learners a greater benefit owing in the personalization of learning... In the collaborative serious game, adaptation is one of the main factors could be considered in the phase of conception since they can contribute to improve learning performance. Learning styles present one of the most factors that affect learning outcomes. Game-based learning (GBL) that takes into account learning styles in the process of adaptation, it furnishes to learners a greater benefit owing in the personalization of learning and contents materials according to their proper learning styles. In this paper, Adaptive system that personalize a collaborative serious game based on learning style proposed by Felder and Silverman is described. This system used trace and agent technology. A model of trace and group model are developed to extract adaptation knowledge in order to form plan that will be executed by Npc player. To evaluate a system, an experiment has been conducted on group of students. From the experimental results, it is concluded that the adaptive collaborative serious game based on learning style improve learning outcomes and effectiveness, and promote learning motivation. Read More Read Less

Abstract The main objective of this research work is to find the keywords in the captured/scanned print document images in the image database. Document images are becoming more popular in today's world and these are used in paperless offices and digital libraries. Information retrieval from the document images is a very challenging task. Hence, there is a need for developing searching strategies to find the required information from these... The main objective of this research work is to find the keywords in the captured/scanned print document images in the image database. Document images are becoming more popular in today's world and these are used in paperless offices and digital libraries. Information retrieval from the document images is a very challenging task. Hence, there is a need for developing searching strategies to find the required information from these document images as per user's needs, becomes very essential in nowadays. Traditionally Optical Character Recognition (OCR) tools are used for information retrieval from the document images, but it's not an efficient method. Word spotting is an inventive method for searching the document images and to retrieve relevant information without any conversion. In this work an algorithm Enhanced Dynamic Time Warping was proposed to for finding keywords from document images, it is based on word spotting technique. Different matching algorithms are made available for word spotting. Popular algorithms are Normalization Cross Correlation (NCC) and Dynamic Time Warping (DTW). In this work, we have compared the performance of these two existing algorithms with the proposed algorithm named as Enhanced Dynamic Time Warping algorithm (EDTW). Different image formats and different sizes of images are used for experimentation. From the results it is observed that the proposed algorithm has produced good results than an existing one. Read More Read Less