Every newspaper publisher faced with the problem of determining the number of copies of newspaper and distributing them to the retail traders. Two aspects need to be balanced out in order to optimize the economical su...
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Every newspaper publisher faced with the problem of determining the number of copies of newspaper and distributing them to the retail traders. Two aspects need to be balanced out in order to optimize the economical success which is the number of unsold copies should be minimal to reduce the cost of production, and the sell-out rate should be minimal to maximize the number of sold copies. Thus, a good sales rate prediction is necessary to optimize both antagonistic aspects. This paper utilized artificial neural network to predict newspaper sales for one vendor in the area of Sungai Petani, Malaysia. The predicted sales value can help the company to optimize their sales. The main objective is to develop a prototype that apply artificial neural network so that it can predict the future trend as well as the future daily sale. The network will consist of three layer which is input layer, one hidden layer and output layer. The input layer will have six input node where this will be the factor that will affect the output which is the number of copies that sold. The network will be trained with history data of a one year records of data. The output produced has the error value as low as 1.24% while the correlation coefficient between prediction and actual value is 0.1197.
Log server is significant for every organization *** generates huge amount of data every day and of different *** data holds valuable information which is complex to be interpreted unless with the aid of web log analy...
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Log server is significant for every organization *** generates huge amount of data every day and of different *** data holds valuable information which is complex to be interpreted unless with the aid of web log analysis *** rules is a data mining technique which is able to derived patterns from data in log server *** paper presents the analysis of log server data particularly on the usage of network *** Appriori algorithm is implemented in the pattern discovery and a tool named UMPNA assist in the process of derive the *** results from the analysis can help network administrator increase the network performance.
Formal Methods are very tough subject to softwareengineering student. It happens because of the mathematics involvement during software development. Students normally feel very difficult to derive formal specificatio...
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Formal Methods are very tough subject to softwareengineering student. It happens because of the mathematics involvement during software development. Students normally feel very difficult to derive formal specification from informal requirement. The problem always happen is to derive the Z notation in the formal specification. The formal specification is all about the operation inside the requirement needed from the customer using mathematical statement. If there do not know the logic of the operation the notation might goes wrong. In this paper, we propose an approach to deriving formal specifications from informal requirement using Venn diagram for creating formal specification in term of training environment to make our student understand. The Venn diagram that we use is purposely for the basic level. It is used to visualize in the branch of mathematics known as set theory. It shows all of the possible mathematical or logical relationships between sets groups of things. With this Venn diagram they can visualize the operation of their notation. To show how to implement the Venn diagram we chose a case study. We show how to convert the Venn diagram to formal specification which is the important part during development of Z schema. Then, we do an analysis of an assignment given to a group of student to know whether the Venn diagram is really helpful for them or not.
Requirements are critical to system validation as they guide all subsequent stages of systems development. Inadequately specified requirements generate systems that require major revisions or cause system failure enti...
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This paper presents the mechanism practice linked to the skills and knowledge added to the refurbishment *** sustainable of career as building refurbishment manager is to feed the managers with skills and knowledge,st...
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This paper presents the mechanism practice linked to the skills and knowledge added to the refurbishment *** sustainable of career as building refurbishment manager is to feed the managers with skills and knowledge,strategically made in facing the future that is full of uncertainties and *** research focus on the sustainability factors through the analysis results that gathered from interview and ***,it relates to identify the current practice in dealing with the process of the refurbishment project toward *** of skills and knowledge among the project managers are the mechanism that firm or agencies to look forward.
Smart Electronic Visitor Information System (SEVIMS) is an application to replace traditional visitor registration and information management activities. SEVIMS able to record visitor information during visitor regist...
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Smart Electronic Visitor Information System (SEVIMS) is an application to replace traditional visitor registration and information management activities. SEVIMS able to record visitor information during visitor registration by using visitor's Malaysia Government Multipurpose Card (MyKad). An implementation of mobile smart card reader with biometric verification has increase the high level of security and access control. With additional features, the identity of visitor can be verify based on matching of his/her thumbprint with the thumbprint image stored in MyKad. The benefits of sophisticated SEVIMS are enhancing the level of security enforced in premises, providing an organized view of visitor records and reducing the time spent on managing visitor information.
The notation and environment in conceptual modelling transform developers' initial perception about a system to a concrete model. Any usability constraints that the notation and environment impose on the modeling ...
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The notation and environment in conceptual modelling transform developers' initial perception about a system to a concrete model. Any usability constraints that the notation and environment impose on the modeling ...
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The advent of high-throughput techniques such as microarray data enabled researchers to elucidate process in a cell that fruitfully useful for pathological and medical. For such opportunities, microarray gene expressi...
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ISBN:
(纸本)9781424437740
The advent of high-throughput techniques such as microarray data enabled researchers to elucidate process in a cell that fruitfully useful for pathological and medical. For such opportunities, microarray gene expression data have been explored and applied for various types of studies e.g. gene association, gene classification and construction of gene network. Unfortunately, since gene expression data naturally have a few of samples and thousands of genes, this leads to a biological and technical problems. Thus, the availability of artificial intelligence techniques couples with statistical methods can give promising results for addressing the problems. These approaches derive two well known methods: supervised and unsupervised. Whenever possible, these two superior methods can work well in classification and clustering in term of class discovery and class prediction. Significantly, in this paper we will review the benefit of network-based in term of interaction data for classification in identification of class cancer.
Study on topology structure of protein interaction network has been suggested as a potential effort to discover biological functions and cellular mechanisms at systems level. In this work, we introduced a graph partit...
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Study on topology structure of protein interaction network has been suggested as a potential effort to discover biological functions and cellular mechanisms at systems level. In this work, we introduced a graph partitioning method to partition protein interaction network into several clusters of interacting proteins that share similar functions called functional modules. Our proposed method encompasses three major steps which are preprocessing, informative proteins selection and graph partitioning algorithm. We utilized the protein-protein interaction dataset from MIPS to test the proposed method. We use gene ontology information to validate the biological significance of the detected modules. We also downloaded protein complex information to evaluate the performance of our method. In our analysis, the method showed high accuracy performance indicates that this method capable to detect highly significance modules. Hence, this showed that functional modules detected by the proposed method are biologically significant which can be used to predict uncharacterized proteins and infer new complexes.
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