Clustering algorithms are used in many Natural Language Processing (NLP) tasks. They have proven to be popular and effective tools to use to discover groups of similar linguistic items. In this exploratory paper, we propose a new clustering algorithm to automatically cluster together similar sentences based on the sentences’ part-of-speech syntax. The algorithm generates and merges together the clusters using a syntactic similarity metric based on a hierarchical organization of the parts-of-speech. We demonstrate the features of this algorithm by implementing it in a question type classification system, in order to determine the positive or negative impact of different changes to the algorithm.

Electronic commerce (e-commerce) has the potential to improve the competitiveness of the enterprises. A decision support system, used in e-commerce, is a term used to describe any software engine that enhances the user’s ability to make decisions. The paper presents a new approach for decision support system modeling. This approach is applied by a modification and extension of existing decision support system architecture by multi-agent technology and agent-based simulation models. Multi-agent technology is one of the fastest growing fields of information and communication technology – new agent-based services, products, and applications are being developed almost every day. Agent-based simulation model is applied to coordinate, control, and simulate the architecture of decision support system, used in e-commerce. The proposed architecture improves the existing decision support systems and gains competitive advantage.

Electronic passports have known a wide and fast deployment all around the world since the International Civil Aviation Organization the world has adopted standards whereby passports can store biometric identifiers. The use of biometrics for identification has the potential to make the lives easier, and the world people live in a safer place. The purpose of biometric passports is to prevent the illegal entry of traveler into a specific country and limit the use of counterfeit documents by more accurate identification of an individual. The paper analyses the face, fingerprint, palm print and iris biometric e-passport design. The paper also provides a cryptographic security analysis of the e-passport using face fingerprint, palm print and iris biometric that are intended to provide improved security in protecting biometric information of the e-passport bearer.

With the adoption of Internet, online shopping has provided a convenience way to purchase goods or services from anywhere at any time in recent years globally. Especially, convenience stores are available for consumers to pick up goods ordered from Internet shops in Taiwan. Therefore, convenience stores have become an important success factor for increasing a lot of profit in online shopping in Taiwan.
In the past, researches have indicated that consumers dare not or are not willing to purchase goods in online shopping. The reasons include the problem of security and the lack of consumers’ trust. Thus, these problems constitute a key barrier to the use of online shopping as well as long-term commitment to the relationship building. Therefore, there is a need to build up consumers’ trust in order to overcome the influential factors in online shopping. In this paper, we use statistic analysis method by questionnaires to discuss the characteristics of pick-up goods in the convenience stores and illustrate the relationship between consumers’ trust in online shopping and pick-up goods behavior in convenience stores. In our experiment, questionnaire items are measured by Likert scale. In 227 valid questionnaires, 90% participants deeply believe that pick-up goods in the convenience stores can promote consumers’ trust in online shopping.

Mobility becomes a distinct feature for a wireless mobile cellular system. For the traffic which is non stationary and is away from the base station, the chances of a call to be handed off are increased. In urban mobile cellular systems, especially when the cell size becomes relatively small, the procedure has a significant impact on system performance. Blocking probability of originating calls and the forced termination probability of ongoing calls are the primary criteria for indicating this performance. In this paper, we report our recent work on closed form solutions to the blocking probability followed by dropping probability in wireless cellular networks with . First, we develop a performance model of a cell in a wireless network where the effect of arrivals and the use of guard channels are included. Then we simulate the Traffic Model with exploiting our model.

Recent years, feature selection is chief concern in text classification. A major characteristic in text classification is the high dimensionality of the feature space. Therefore, feature selection is strongly considered as one of the crucial part in text document categorization. Selecting the best features to represent documents can reduce the dimensionality of feature space hence increase the performance. Feature selection is performed here using Document Frequency Threshold. This paper focus on SVM based text message classification using document frequency threshold. The experiment is performed with NUS SMS text messages data set. An experimental result shows that the results of proposed method are more efficient.

Weather forecasting is a vital application in meteorology and has been one of the most scientifically and technologically challenging problems around the world in the last century. In this paper, we investigate the use of data mining techniques in forecasting maximum temperature, rainfall, evaporation and wind speed. This was carried out using Artificial Neural Network and Decision Tree algorithms and meteorological data collected between 2000 and 2009 from the city of Ibadan, Nigeria. A data model for the meteorological data was developed and this was used to train the classifier algorithms. The performances of these algorithms were compared using standard performance metrics, and the algorithm which gave the best results used to generate classification rules for the mean weather variables. A predictive Neural Network model was also developed for the weather prediction program and the results compared with actual weather data for the predicted periods. The results show that given enough case data, Data Mining techniques can be used for weather forecasting and climate change studies.

In recent days every application must need power management. In this paper we presented a various techniques to handle the power management in IC. Power dissipation in a IC is base on power used by the IC and also by heat dissipation. To reduce energy use or to minimize heat dissipation some of the techniques are briefly discussed in this paper. Power management is becoming an increasingly urgent problem for almost every category of design and application, as power density, measured in watts per square millimeter, rises at an alarming rate. Power needs to be considered at the very early stages of a design, when the opportunity to save power is at a maximum. At the same time, making a design extremely power efficient results in trading off area and/or timing. For a Integrated Circuit (IC) perspective, effective energy management for a SoC (System-on-a-chip) must be built into the design starting at the architecture stage; and low-power techniques need to be employed at every stage of the design, from RTL (Register Transfer Level) to GDSII. This paper explains about the combination of techniques used for low power approach in integrated circuits (IC) or Chip