Abstract: Automatic identification of garment design class might play an important role in the garments and fashion industry. To achieve this, essential initial works are found in the literature. For example, construction of a garment database, automatic segmentation of garments from real life images, categorizing them into the type of garments such as shirts, jackets, tops, skirts, etc. It is now essential to find a system such that it will be possible to identify the particular design (printed, striped or single color) of garment product for an automated system to recommend the garment trends. In this paper, we have focused on this specific issue and thus propose two new descriptors namely Completed CENTRIST (cCENTRIST) and Ternary CENTRIST (tCENTRIST). To test these descriptors, we used two different publically available databases. The experimental results of these databases demonstrate that both cCENTRIST and tCENTRIST achieve nearly about 3% more accuracy than the existing state-of-the art methods.
Abstract: Surface electromyographic (sEMG) activity of the biceps muscle was recorded from 13 subjects. Data was recorded while subjects performed dynamic contraction until fatigue and the signals were segmented into two parts (Non-Fatigue and Fatigue). An evolutionary algorithm was used to determine the elbow angles that best separate (using Davies-Bouldin Index, DBI) both Non-Fatigue and Fatigue segments of the sEMG signal. Establishing the optimal elbow angle for feature extraction used in the evolutionary process was based on 70% of the conducted sEMG trials. After completing 26 independent evolution runs, the best run containing the optimal elbow angles for separation (Non-Fatigue and Fatigue) was selected and then tested on the remaining 30% of the data to measure the classification performance. Testing the performance of the optimal angle was undertaken on nine features extracted from each of the two classes (Non-Fatigue and Fatigue) to quantify the performance. Results showed that the optimal elbow angles can be used for fatigue classification, showing 87.90% highest correct classification for one of the features and on average of all eight features (including worst performing features) giving 78.45%.
Abstract: The purpose of this study is to investigate pre-service teachers’ technological, pedagogical and content knowledge (TPACK) in Turkey. By using the “Survey of Pre-service Teachers’ Knowledge of Teaching and Technology” developed by Schmidt et al. (2009), the study sought to determine if significant differences could be found in pre-service teachers’ perceptions of TPACK when examined by gender, age, educational program, year of study, kind of instruction (day or night education) and field experience. Regression analysis was also used to examine if technology knowledge (TK), pedagogical knowledge (PK) and content knowledge (CK) significantly contributed to pre-service teachers’ TPACK development. Participants of this study were 491 elementary pre-service teachers who attended the summer semester at Pamukkale University. The analysis of the collected data found a significant difference in pre-service teachers’ perceptions of the TPACK when examined across gender, program, year of study and field experience, but no significant differences were found regarding age and kind of instruction. Finally, our regression model showed that CK and PK contributed significantly to pre-service teachers’ TPACK development, but TK was not a significant predictor.
Abstract: Since wireless sensor networks (WSNs) have been designed to be deployed in an unsecured, public environment, secured communication is really vital for their wide-spread use. Among all of the communication protocols developed for WSN, the Security Protocols for Sensor Networks (SPINS) is exceptional, as it has been designed with security as a goal. SPINS is composed of two building blocks: Secure Network Encryption Protocol (SNEP) and the “micro” version of the Timed Efficient Streaming Loss-tolerant Authentication (TESLA), named μTESLA. From the inception of SPINS, a number of efforts have been made to validate its security properties. In this paper, we have validated the security properties of SNEP by using an automated security protocol validation tool, named AVISPA. Using the protocol specification language, HLPSL, we model two combined scenarios—node to node key agreement and counter exchange protocols—followed by data transmission. Next, we validate the security properties of these combined protocols, using different AVISPA back-ends. AVISPA reports the models we have developed free from attacks. However, by analyzing the key distribution sub-protocol, we find one threat of a potential DoS attack that we have demonstrated by modeling in AVISPA. Finally, we propose a modification, and AVISPA reports this modified version free from the potential DoS attack.
Abstract: Mobile dispatching applications have become popular for at least two major reasons. The first reason is a more mobile-centric usage pattern, where users relate to apps for fulfilling different needs that they have. In this respect, a vehicle dispatching application for mobile phones is perceived as a modern way of booking a vehicle. The second reason has to do with the advantages that this method has over traditional dispatching systems, such as being able to see the vehicle approaching on a map, being able to rate a driver and the most importantly spurring customer retention. The taxi dispatching business, one of the classes of dispatching businesses, tends to be a medium to lower class fidelity service, where users mostly consider the closest taxi as opposed to quality, which is regarded as being at a relatively consistent level. We propose a new approach for the taxi ordering application , a mobile dispatching system, which allows for a more engaged user base and offers fidelity rewards that are used to enhance the customer retention level based on a built in social customer relationship management (CRM) component. With this approach, we argue that in a business world which is shifting from a consumer-centric marketing to a human-centric model, this apps will allows taxi businesses to better interact with their clients in a more direct and responsible manner. Also this distributed system helps taxi drivers, which can receive orders directly from their clients and will be able to benefit from offering quality services as they can get higher ratings.
Abstract: As smartphones become widespread, a variety of smartphone applications are being developed. This paper proposes a method for indoor localization (i.e., positioning) that uses only smartphones, which are general-purpose mobile terminals, as reference point devices. This method has the following features: (a) the localization system is built with smartphones whose movements are confined to respective limited areas. No fixed reference point devices are used; (b) the method does not depend on the wireless performance of smartphones and does not require information about the propagation characteristics of the radio waves sent from reference point devices, and (c) the method determines the location at the application layer, at which location information can be easily incorporated into high-level services. We have evaluated the level of localization accuracy of the proposed method by building a software emulator that modeled an underground shopping mall. We have confirmed that the determined location is within a small area in which the user can find target objects visually.