Abstract: With its spatial data reliability, interpretation and questioning capabilities, Geographical Information Systems make significant contributions to scientists, planners and practitioners. Geographic information systems have received great attention in today's digital world, growing rapidly, and increasing the efficiency of use. Access to and use of current and accurate geographical data, which are the most important components of the Geographical Information System, has become a necessity rather than a need for sustainable and economic development. This project aims to enable sharing of data collected by public institutions and organizations on a web-based platform. Within the scope of the project, INSPIRE (Infrastructure for Spatial Information in the European Community) data specifications are considered as a road-map. In this context, Turkey's National Geographic Information System (TUCBS) Integration Project supports sharing spatial data within 61 pilot public institutions as complied with defined national standards. In this paper, which is prepared by the project team members in the TUCBS Integration Project, the technical process with a detailed methodology is explained. In this context, the main technical processes of the Project consist of Geographic Data Analysis, Geographic Data Harmonization (Standardization), Web Service Creation (WMS, WFS) and Metadata Creation-Publication. In this paper, the integration process carried out to provide the data produced by 61 institutions to be shared from the National Geographic Data Portal (GEOPORTAL), have been trying to be conveyed with a detailed methodology.
Abstract: Image retrieval is the most interesting technique which is being used today in our digital world. CBIR, commonly expanded as Content Based Image Retrieval is an image processing technique which identifies the relevant images and retrieves them based on the patterns that are extracted from the digital images. In this paper, two research works have been presented using CBIR. The first work provides an automated and interactive approach to the analysis of CBIR techniques. CBIR works on the principle of supervised machine learning which involves feature selection followed by training and testing phase applied on a classifier in order to perform prediction. By using feature extraction, the image transforms such as Contourlet, Ridgelet and Shearlet could be utilized to retrieve the texture features from the images. The features extracted are used to train and build a classifier using the classification algorithms such as Naïve Bayes, K-Nearest Neighbour and Multi-class Support Vector Machine. Further the testing phase involves prediction which predicts the new input image using the trained classifier and label them from one of the four classes namely 1- Normal brain, 2- Benign tumour, 3- Malignant tumour and 4- Severe tumour. The second research work includes developing a tool which is used for tumour stage identification using the best feature extraction and classifier identified from the first work. Finally, the tool will be used to predict tumour stage and provide suggestions based on the stage of tumour identified by the system. This paper presents these two approaches which is a contribution to the medical field for giving better retrieval performance and for tumour stages identification.
Abstract: Mobile technology is very popular nowadays and it provides a digital world where users can experience many value-added services. Service Providers are also eager to offer diverse value-added services to users such as digital identity, mobile financial services and so on. In this context, the security of data storage in smartphones and the security of communication between the smartphone and service provider are critical for the success of these services. In order to provide the required security functions, the SIM card is one acceptable alternative. Since SIM cards include a Secure Element, they are able to store sensitive data, create cryptographically secure keys, encrypt and decrypt data. In this paper, we design and implement a SIM and a smartphone framework that uses a SIM card for secure key generation, key storage, data encryption, data decryption and digital signing for mobile financial services. Our frameworks show that the SIM card can be used as a controlled Secure Element to provide required security functions for popular e-services such as mobile financial services.
Abstract: By the evolvement in technology, the way of
expressing opinions switched direction to the digital world. The
domain of politics, as one of the hottest topics of opinion mining
research, merged together with the behavior analysis for affiliation
determination in texts, which constitutes the subject of this paper.
This study aims to classify the text in news/blogs either as
Republican or Democrat with the minimum number of features. As
an initial set, 68 features which 64 were constituted by Linguistic
Inquiry and Word Count (LIWC) features were tested against 14
benchmark classification algorithms. In the later experiments, the
dimensions of the feature vector reduced based on the 7 feature
selection algorithms. The results show that the “Decision Tree”,
“Rule Induction” and “M5 Rule” classifiers when used with “SVM”
and “IGR” feature selection algorithms performed the best up to
82.5% accuracy on a given dataset. Further tests on a single feature
and the linguistic based feature sets showed the similar results. The
feature “Function”, as an aggregate feature of the linguistic category,
was found as the most differentiating feature among the 68 features
with the accuracy of 81% in classifying articles either as Republican
or Democrat.
Abstract: Rural tourism is usually associated with rural
development because it has strong linkages to rural resources; but it
remains underdeveloped compared to urban tourism. This
underdevelopment of rural tourism serves as a motivation for this
study whose aim is to examine the factors affecting the perceived
satisfaction of rural tourists. The objectives of this study are: to
identify and design theories and models on rural tourism satisfaction,
and to empirically validate these models and theories through a
survey of tourists from the Malealea Lodge which is located in the
Mafeteng District, in the Mountain Kingdom of Lesotho. Data
generated by the collection of questionnaires used by this survey was
analyzed quantitatively using descriptive statistics and correlations in
SPSS after checking the validity and the reliability of the
questionnaire. The main hypothesis behind this study is the
relationship between the demographics of rural tourists, their
motivation, and their satisfaction, as supported by existing literature;
except that motivation is measured in this study according to three
dimensions: push factors, pull factors, and perceived usefulness of
ICTs in the rural tourism experience. Findings from this study
indicate that among the demographics factors, continent of origin and
marital status influence the satisfaction of rural tourists; and their
occupation affects their perceptions on the use of ICTs in rural
tourism. Moreover, only pull factors were found to influence the
satisfaction of rural tourists.