Wireless channels are typically much more noisy than wired links and subjected to fading due to multipath  propagation which result in ISI and hence high error rate. Adaptive modulation is a powerful technique to improve the tradeoff between spectral efficiency and Bit Error Rate (BER). In order to adjust the transmission rate, channel state information (CSI) is required at the transmitter side.

In this paper the performance enhancement of using linear prediction along with channel estimation to track the channel variations and adaptive modulation were examined. The simulation results shows that the channel estimation is sufficient for low Doppler frequency shifts (<30 Hz), while channel prediction is much more suited at

This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat

Free-Space Optical (FSO) can provide high-speed communications when the effect of turbulence is not serious. However, Space-Time-Block-Code (STBC) is a good candidate to mitigate this seriousness. This paper proposes a hybrid of an Optical Code Division Multiple Access (OCDMA) and STBC in FSO communication for last mile solutions, where access to remote areas is complicated. The main weakness effecting a FSO link is the atmospheric turbulence. The feasibility of employing STBC in OCDMA is to mitigate these effects. The current work evaluates the Bit-Error-Rate (BER) performance of OCDMA operating under the scintillation effect, where this effect can be described by the gamma-gamma model. The most obvious finding to emerge from the analysis

The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

International Journal on Technical and Physical Problems of Engineering

Manual fruit picking is labor-intensive and can damage fruit. Fully mechanized picking is efficient, but it also risks fruit damage. Therefore, semi-automated tools are needed to improve bitter orange picking. This paper presents a smart manual picker designed to facilitate picking while predicting fruit maturity based on picking force as well as various chemical and physical parameters using machine learning (ML). The study methodology consists of five stages: (1) manufacturing the smart picker, (2) picking 50 bitter orange samples, (3) measuring the characteristics of the bitter oranges in the laboratory, (4) training different ML models, and (5) identifying the most accurate model for predicting fruit maturity. The results indicate that