Abstract Using low cost energy is important in wireless sensor networks which need acceptable data transfer. In doing so, there are two approaches to recover erroneous packets, ARQ and FEC. FEC is used with aim to increase link reliability and reduce number of packet retransmission. Mostly in the data transmission, bit errors happen; single-bit or double-bit errors and multiple-bit errors are... Using low cost energy is important in wireless sensor networks which need acceptable data transfer. In doing so, there are two approaches to recover erroneous packets, ARQ and FEC. FEC is used with aim to increase link reliability and reduce number of packet retransmission. Mostly in the data transmission, bit errors happen; single-bit or double-bit errors and multiple-bit errors are present but not frequently. The extension of the conventional error correction capability of 2D-SEC-DED code is used in this work and we did performance evaluation. Read More Read Less

Abstract Wearable devices are extremely important in the coming years. The performance-rich characteristics and a few itches bring challenges in their deployment. To address these solutions, we planned to develop human-computer interfaces where the device can be activated using a two finger touch. The interface can make the device surface unaffected including the display and the device display will not be... Wearable devices are extremely important in the coming years. The performance-rich characteristics and a few itches bring challenges in their deployment. To address these solutions, we planned to develop human-computer interfaces where the device can be activated using a two finger touch. The interface can make the device surface unaffected including the display and the device display will not be hindered. Read More Read Less

Abstract For image classification the TensorFlow is required and we studied the possibility of applying it. We have developed a web-based application with easy portability to various operating systems, which cover all the functionalities incorporated into the library. It follows the client-server model and take advantage of all the options for tuning, such as random crop, random scaling, etc. We did... For image classification the TensorFlow is required and we studied the possibility of applying it. We have developed a web-based application with easy portability to various operating systems, which cover all the functionalities incorporated into the library. It follows the client-server model and take advantage of all the options for tuning, such as random crop, random scaling, etc. We did the experimentation using a set of 772 images of 3 types of objects taken in natural environment that shown the usability of the proposed framework for classification purposes. We convinced that the system can be used to solve general and strictly specialized tasks. Read More Read Less