In this article, by using COMSOL Multiphysics software, by adding an amplifier to the structure of ring resonators in an arbitrary size structure of ring that has a frequency line in telecommunication windows, a resonator wavelength of 1555 nm has been achieved. It is strengthened by changing the size of the rings in sequential structures in a resonator array and changing the place of the amplifier in the structure of the rings, an optimal structure has been achieved, which has reached an amplification of about 40 dB. The amplifier that is added to this structure is suggested to be impurity amplifiers, such as doping a part of the ring by erbium atoms or semiconductor amplifiers

Measuring and observing the local level of industrial reservoirs is always considered one of the most important issues in all industries, to the extent that different methods are used in the field of precision instruments. On the other hand, with the passage of time, due to the wear and tear of old local level gauges and the lifespan of their parts, these devices are always faced with a decrease in measurement accuracy as well as an increase in equipment failure and inefficiency. The focus of this article is on the local measurement of the level, compared to the centralized measurement located in the control room. The results show that, in addition to the local reading of the tank level by the operators, it is possible to send signals and monitor the values in the control room. Currently, a number of magnetic level gauges have been successfully installed and operated on oil tanks, high pressure heaters, deaerators and boilers in Ahvaz Electricity Production Management Company - Ramin Power Plant. For confirmation and validation, the results of this research were compared with two samples of pressure difference gauge and Borden tube pressure gauge. Simplicity and ease of installation and the ability to display high-resolution local and send electrical signals to the steering room are the main features of the magnetic level gauge.

Abstract—We have developed a magnetic probe with a diamond quantum sensor and electromagnetic coils for detection of sentinel lymph nodes (SLNs) as a medical application of diamond quantum sensing. The probe magnetizes the magnetic nanoparticles (MNPs) accumulated in the SLNs and detects the magnetic fields of the magnetic MNPs. We designed a ferromagnetic core that has a unique shape and optimized the magnetic field generation system to improve detection performance, such as magnetic sensitivity and detectable distance. The proposed magnetic core increases the excitation magnetic field strength over a longer distance and suppresses the bias field strength at the location of the diamond quantum sensor. The increase of the excitation field is approximately 370% and the decrease of the bias field is approximately 45%. In addition to the proposed magnetic core, even with the application of a removal coil, the excitation field strength is tenfold compared to the single-coil structure, indicating that further magnetization of MNPs produces a large magnetic field for a longer detectable distance.

Health monitoring systems have a special importance in today's modern medicine, and on the other hand, the inherent readiness of cloud systems in connection with the Internet of Things (IoT) can help improve the efficiency of these systems. In this paper, a method for monitoring the health of patients is presented in the cloud-based IoT environment, which is based on boosting and benefits from deep learning. The use of boosting deep learning algorithms to achieve higher levels of efficiency in patient health monitoring is one of the innovations of this paper. The patient health monitoring data sets have been used in the fields of heart, lung, kidney and brain. In order to measure the effectiveness of the proposed method, it was compared with some other prominent methods and compared with accuracy metrics and F-measure. The results of various tests showed that the proposed method performed better than other compared methods in most cases and achieved higher levels of efficiency.

Long code direct sequence spread spectrum used to robustly communicate against detections, deceptions, and spoofing. In conventional Long-code spread spectrum synchronization methods, short-codes used to transmit the Long code LFSR generator mode at the beginning of the information frame. Since the authorized receiver has the LFSR generator of the long-code, in case of correct synchronization, it can recover the information of the initial state of the LFSR transmitted by the short code and perform the synchronization correctly on the long-code. Using the short code in this method increases the vulnerability of the link to unauthorized receivers. The synchronization algorithm in the structure of the long-code faces the challenge of estimating the initial state of the received signal, and appropriate scenario is not used, it leads to an increase in the synchronization time. The dual folding method is one of the most prominent algorithms in this field and can compensate for synchronization time in the condition of channel time delay. The main challenge is the existence of high Doppler, which cannot be properly compensated and leads to a decrease in the probability of detection. In this paper, direct sequence spread spectrum signal synchronization algorithm of long-code based on dual folding in a high Doppler environment is presented. The proposed algorithm can correctly compensate for channel Doppler using filter bank structure and zero padding. The simulation results show the correct performance of this method in high Doppler conditions.

Two factors of the rapid growth of various sciences in recent years and the growth and spread of the global Internet network have caused several thousand articles in various fields to be published on the Internet every day, and become available to everyone. This problem creates a challenge for the specialists of different sciences, because they have to look for their interests and scientific field in a large number of published articles so that they can always remain an expert. In this research, for the first time, we intend to introduce a recommender system that suggests suitable articles to Persian language users according to their interests. The purpose of this research is to provide basic research for this category of issues in Persian language, to be a starting point for other researchers. In this study, we want to propose articles based on the semantic similarity of the title, abstract and keywords of the article (with appropriate weighting) with the user's academic records. After the implementation and placement of the model as a pilot on the internet platform. A group of undergraduate students evaluated the model's computer software, and the overall accuracy of the system was evaluated at 79%.

Efficient management of energy resources is very important in smart buildings. In this work, model predictive control (MPC) is used to minimize the economic costs of buyers equipped with generation units, energy storage systems and electric vehicles. For this purpose, predictive control manages available energy resources by exploiting future information on energy prices, absorption and generation power profiles, and electric vehicle (EV) usage, such as departure and arrival times and predicted energy consumption. EV Batteries In particular, unlike the heuristic method, the MPC approach has been proven to be able to efficiently manage the available energy resources to ensure full recharging of the EV battery overnight.
Aiming at optimal performance in terms of economic cost minimization in time-varying price scenarios, reducing rms current stresses and recharging capability of EV batteries. Moreover, the proposed control is shown to be able to limit the maximum power absorption from the grid within the defined limits, which is a valuable feature in scenarios with widespread adoption of EVs in order to limit the stress on the electrical system. and the ability to recharge EV batteries. In particular, unlike the heuristic method, the MPC approach is proven to be able to efficiently manage the available energy resources to ensure full recharging of the EV battery overnight while always meeting all system constraints. Moreover, the proposed control is shown to be able to limit the maximum power absorption from the grid within the defined limits, which is a valuable feature in scenarios with widespread adoption of EVs in order to limit the stress on the electrical system. In addition, the proposed control is shown to be able to limit the maximum power absorption from the grid within the defined limits .

This paper presents the design, development and validation of a closed-loop control system for a soft robotic table. A soft table can simultaneously provide independent manipulation of multiple objects, which is an advantage over traditional devices such as robotic arms and conveyor belt systems. This table also allows for the inherent smooth handling of delicate objects. In order to implement the automation tasks, a vision feedback system and an operation controller are developed and integrated into the existing desk prototype to form a closed-loop control. The vision feedback system implements image processing techniques to identify the object position from captured images. The operational controller is integrated from three sets of algorithms including motion planning, stimulus selection and stimulation planning. Two sets of tests were conducted to validate the closed loop system and the soft table capability. The first set confirms the manipulative task of moving an object to a desired location with independent planning and execution. The second set confirms the table's ability to manipulate multiple objects simultaneously and independently. Videos of both tests have been prepared. Attention experts - a soft robotic table has been developed for manipulating delicate objects on a surface. This table is intended for automatic sorting tasks in an industrial environment. Multiple objects placed on the table surface can be simultaneously and independently moved and oriented on the horizontal XY plane. The deformable surface of the table allows smooth manipulation of delicate objects. These are advantages over existing manipulators such as robotic arms and conveyor belt systems. Based on previous experiments, it was found that open-loop control is inefficient for performing automation tasks due to the variability in the motion of objects with soft interactions. To solve this problem, a closed-loop control system for independent object manipulation has been developed, and its detailed design and implementation are presented in this paper. A vision feedback system and a controller are developed to form the proposed closed-loop control. Two sets of experiments involving routine manipulation tasks were performed. It has been proven that the control system is effective in controlling the uncertainty in the object movements and the automatic manipulation of the object by the soft robotic table. The performance of this control system can be improved by better predicting both the deformations on the table surface and the resulting object movements. Placing deformable sensors on the surface of the table is a potential method to achieve such an improvement, and this issue can be explored in future work.