Nowadays, the use of Rehabilitation Robots for stroke patients has been growing rapidly. However, there was a limited scope of using such Rehabilitation Robots for patients suffer from an accidental physical fracture. Since the pain condition of such accidents needs a critical treatment, precise control of such robotic manipulators is mandatory. This paper presents the design and control of the Elbow-Forearm Rehabilitation Robot by considering the pain level of the patient. This design consists of the mechatronic design processes including mechanical design, controller design, and Virtual prototyping using ADAMS-MATLAB Co-simulation. The pain level is estimated using three parameters i.e the patient general condition, the muscle strain, and the duration of exercise from the beginning of rehabilitation. Based on these three input parameters, the manipulator's desired range of motion has been determined using the Fuzzy Logic System. The output of this fuzzy logic system would be an input to the main control system. ADAMS-MATLAB Cosimulation is carried out based on three reference inputs i.e Step, sinusoidal and the proposed fuzzy reference input. Using step input, we have discussed the step response characteristics of the developed system. The Co-simulation of the ADAMS dynamic model is realized with a 30 degree oscillating motion by providing a sinusoidal input. Finally, using the developed fuzzy reference input, we have done a Co-simulation of ADAMS plant. The simulation result demonstrates that the proposed PID controller with gains Kp=0.001 and Ki=0.01 yields 99.6% of accuracy in the tracking of the reference input as compared to the simulation without introducing controller which has an accuracy of 94.9%. The simulation also shows that derivative gain (Kd) of the PID controller has no effect on the system so that it is over damping system. From the above three simulation schemes, we can conclude that the Elbow-Forearm rehabilitation robot could be controlled as per the desired signal. Since this desired signal is developed from the pain level of the patient, we can say that the system is controlled as per the pain level of the patient.

Nowadays our energy needs have grown exponentially corresponding with human population growth and technological advancement. Energy consumption linked to non-renewable resources contributes to greenhouse gas emissions and enhances resource depletion. Most of the researchers were proven that the worldwide concern about CO 2 emissions and the reduction in the use of coal fuels have increased the interest in using biomass fuel for electricity production, because there is no net increase in CO 2 emissions from biomass (agricultural residues such as straw, bagasse, coffee husk, and rice husks) combustion. Furthermore, coffee husk which has high energy potential was not taken into account for the generation of energy. However, this paper investigates the energy generation in coffee husk, and suggests coffee husk is an energy source. The datum was collected from the south western region of Ethiopia (Tepi town), and its equipment was selected. Coffee husk was tested experimentally in Addis Ababa University with Eager 300 software for running the equipment, storing the data and analyzing. The results obtained that calorific values were 18.98 MJ/kg. Overall the result demonstrates that the proposed coffee husk has high energy potential for the generation of energy.

The need for internet of things (IoT) and machine-to-machine communication (MTC) has been growing rapidly all across the world. To meet the client's needs, many literature reviews were undertaken in several countries. Orthogonal frequency division multiplexing (OFDM), Universal Filtered Multi-Carrier (UFMC), filter-bank multicarrier offset construction amplitude modulation (FBMC-OQAM), generalized frequency division multiplexing (GFDM), and others are candidates for LTE, LTE advance, and 5G, according to the majority of the researchers. However, because it is sensitive to propagation and noise, such as amplitude, with a huge dynamic range, it requires RF power amplifiers with a high peak to average power quantitative relationship; consequently, it is not recommended for LTE, LTE advance, or 5G. As a result, the same concerns were addressed by introducing innovative type filtered orthogonal frequency division multiplexing (F- OFDM), which was the subject of this study. In addition, F-OFDM mathematical models were constructed and simulated in the MATLAB software environment. To validate the proposed innovative F-OFDM, OFDM was compared. For innovative F-OFDM, the simulated result was 0.00083333 bit error rate (BER). Furthermore, the bit error rate (BER) of F-OFDM over OFDM was 89.4 percent, and the peak to average power ratio was 17 percent. The simulation results unmistakably show that the suggested innovative F-OFDM is the greatest fit for LTE, LTE advanced, and 5G contenders.

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