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As spasticity is a major cause of illness in patients that suffer from spinal cord injury (SCI), there are several limitations in the present robotic-based therapy for the treatment of acute SCI patients. A large literature is present for the use of full body exoskeletons, but due to their limitations such as uneasiness due to repetitive motion, does not meet the anthropometric range. As manual therapy is tiresome, a need for ankle-foot therapy exoskeleton was felt and Ankle-Foot Orthosis was developed. This paper presents an ankle-foot therapy exoskeleton device for spasticity treatment of acute SCI patients to reduce the manual efforts of physiotherapists. The proposed device has one Degree of Freedom (DOF) in the sagittal plane in ankle joint. This paper analyses the control design of the prototype and clinical trial results on SCI patients, which show that the proposed prototype is viable in improving the range of ankle motion alleviating the spasticity with p = 0.000365.

In this paper, modified dragonfly algorithm (MDA) with ant lion optimization (ALO) based Load Flow Analysis (LFA) with hybrid power flow controller in comparison with unified power flow controller is established. The proposed technique is exemplify at enhanced search ability, random reduction and decreased complexity. Here, search behavior of dragonflies is updated to ALO algorithm. Hence, the combination of these two optimization algorithm is named as MDA2LO technique. In this paper, load flow studies are suggested with obtain voltage, real and reactive power and load angle in each bus of power system to divide their steady state circumstances utilizing MDA2LO approach. The proposed system is actualized on MATLAB/Simulink working platform. The proposed study is experienced at IEEE 30 and 14 bus system. The performance of proposed system is compared to previous method like salp swarm algorithm-firefly (SSA-FF), combination of modified salp swarm optimization algorithm and moth-flame optimization called CMSSMFO and dragonfly algorithm (DA).The result accuracy (RA) of proposed and existing method is also analyzed. The RA of the proposed hybrid system is 52.7699% and SSA-FF is 9.665%, CMSSMFO is 11.995%, DA is 10.721%. Overall, the comparison outcomes decide the benefit of proposed system and confirm their potential for resolving these issues.

The paper presents an approach to develop assistive devices by combining multimodal biosignals and radio frequency identification (RFID). The brain and eye signals have been used as multimodal biosignals to control the movement of a robot in four directions and help reach near the object following a predefined path. RFID shared control over object identification, and the gripper arm connected at the end effector of the robot performs pick and place operations. Horizontal electrooculography (EOG) has been used for x-directional movement control and electroencephalography (EEG) signal obtained by visual stimulus, called steady-state visual-evoked potential (SSVEP) has been used for y-directional movement control of a robot. The SSVEP signal has also been used to ring an alarm in case of an emergency call by the user. Two parameters classification accuracy (CA) and information transfer rate (ITR) have been calculated for the performance evaluation of the proposed multimodal-shared control model and have shown improved results as compared to previous literature. The results also proved that the proposed model can be used for real-time mobility assistive applications.

With the upgrading needs of automation and prediction requirements in the industries, automation for improving the quality of the product and prediction of the product cycle to make product more economical. Now a days the use of artificial intelligence techniques becoming crucial to apply in the industries which makes the products more reliable, robust and economical. This paper deals and explains the different techniques of artificial intelligence. Also covers the review of the different applications of these techniques in the industries. This paper covers the review of Artificial intelligence techniques applied in the different fields like civil engineering, biomedical engineering, mechanical engineering, electrical and electronics engineering and many more.

From the past few years, research has gained an ardent pace in the field of fault detection and diagnosis in induction motors. In the current scenario, software is being introduced with diagnostic features to improve stability and reliability in fault diagnostic techniques. Human involvement in decision making for fault detection is slowly being replaced by Artificial Intelligence techniques. In this paper, a brief introduction of eccentricity fault is presented along with their causes and effects on the health of induction motors. Various indices used to detect eccentricity are being introduced along with their boundary conditions and their future scope of research. At last, merits and demerits of all indices are discussed and a comparison is made between them.

From the aspect of saving energy, there is a continuous modification in communication technology and information in order to satisfy all customers demand. Today customers are demanding for accurate energy measurement, timely data and for good customer services. The best solution is smart grid system with various communication technologies which can be cost effective and electrical section to have a bidirectional communication in which information about electrical energy consumption is shared between consumers as well as by utility for remote checking. This paper describes the monitoring of energy consumption with Arduino Uno board and Ethernet using IoT (Internet of Things) concept. This proposed design eliminates human inclusion in the conservation of electricity. The consumer can receive the information about consumption of energy by using IP address on their devices. The web client code is uploaded for checking the client information such as location, content, connection, and disconnection to the web server. This proposed system gives reliable and accurate information regarding electrical energy management system (EMS) through Internet of things (IoT).

Modern power system is dealt with overloading problem especially transmission network which works on their maximum limit. Today's power system network tends to become unstable and prone to collapse due to disturbances. Flexible AC Transmission system (FACTS) provides solution to problems like line overloading, voltage stability, losses, power flow etc. FACTS can play important role in improving static and dynamic performance of power system. FACTS devices need high initial investment. Therefore, FACTS location, type and their rating are vital and should be optimized to place in the network for maximum benefit. In this paper, different optimization methods like Particle Swarm Optimization (PSO), Genetic Algorithm (GA) etc. are discussed and compared for optimal location, type and rating of devices. FACTS devices such as Thyristor Controlled Series Compensator (TCSC), Static Var Compensator (SVC) and Static Synchronous Compensator (STATCOM) are considered here. Mentioned FACTS controllers effects on different IEEE bus network parameters like generation cost, active power loss, voltage stability etc. have been analyzed and compared among the devices.

The Real-Time Simulator tools have high computing technologies, improved performance. They are widely used for design and improvement of electrical systems. The advancement of the software tools like MATLAB/SIMULINK with its Real-Time Workshop (RTW) and Real-Time Windows Target (RTWT), real-time simulators are used extensively in many engineering fields, such as industry, education, and research institutions. OPAL-RT-OP4510 is a Real-Time Simulator which is used in both industry and academia. In this paper, the real-time simulation of IEEE-5-Bus network is carried out by means of OPAL-RT-OP4510 with CRO and other hardware. The performance of the network is observed with the introduction of fault at various locations. The waveforms of voltage, current, active and reactive power are observed in the MATLAB simulation environment and on the CRO. Also, Load Flow Analysis (LFA) of IEEE-5-Bus network is computed using MATLAB/Simulink power-gui load flow tool.

This paper presents design of a sustainable solar Photo voltaic system for an Indian cities based residential/community house, integrated with grid, supporting it as supplementary sources, to meet energy demand of domestic loads. The role of renewable energy sources in Distributed Generation (DG) is increasingly being recognized as a supplement and an alternative to large conventional central power supply. Though centralized economic system that solely depends on cities is hampered due to energy deficiency, the use of solar energy in cities is never been tried widely due to technical inconvenience and high installation cost. To mitigate these problems, this paper proposes an optimized design of grid-tied PV system without storage which is suitable for Indian origin as it requires less installallation cost and supplies residential loads when the grid power is unavailable. The energy requirement is mainly fulfilled from PV energy module for critical load of a city located residential house and supplemented by grid/DG for base and peak load. The system has been developed for maximum daily household demand of 50kWp and can be scaled to any higher value as per requirement of individual/community building ranging from 50kWp to 60kWp as per the requirement. A simplified control system model has been developed to optimize and control flow of power from these sources. The simulation work, using MATLAB Simulink software for proposed energy management, has resulted in an optimal yield leading efficient power flow control of proposed system.