The presence of bias in low-cost inertial sensors has always been a fundamental problem in the estimation of Euler angles. The Transfer alignment technique involves using two sets of sensors: a set of low-cost sensors (which may have significant bias) and a set of high-accuracy sensors (which provide reliable data). By comparing the outputs of these two sets, the biases in the low-cost sensors can be estimated and corrected. To achieve this goal, it is necessary to obtain the difference between the master and slave frames. The “master frame” typically refers to the coordinate system defined by the high-accuracy sensors, while the “slave frame” refers to the coordinate system defined by the low-cost sensors. In this article, the method of small rotation angles is used to calculate this difference between the two frames. This article proposes a new alignment algorithm that is both fast and accurate. The biases of accelerometers and gyroscopes can be rapidly estimated and compensated for. The alignment discussed in this article is conducted during motion, which is more complex than stationary mode estimation. The desired maneuver in this study is a constant acceleration maneuver, where the biases of both the accelerometer and gyroscope are well estimated. For other maneuvers, gyroscope biases may not be accurately estimated, while accelerometer biases are generally well estimated. The estimated biases for accelerometers and gyroscopes are often noisy due to errors in the inertial sensors; therefore, preprocessing filtering is also performed to estimate the biases smoothly.

Transfer alignment of master and slave systems plays a key role in the inertial navigation accuracy of the marine cooperative vehicles. Accuracy enhancement of misalignment angle and orientation estimation is the main purpose of the Transfer alignment. Velocity and orientation matching is a well-known method for Transfer alignment. However, in many applications, there are no velocity measurements of both the master and slave systems due to weight, dimensional and technological limitations of accurate speed sensors, such as Doppler Velocity Loggers (DVL). Angular velocity configuration is a suitable solution for Transfer alignment in this situation. However, the orientation error cannot be estimated in this configuration. Taking this drawback into account, a new configuration based on using the integral of angular velocity in addition to angular velocity measurement is presented for Transfer alignment in the current research. Furthermore, appropriate abilities are considered to estimate the dynamic misalignment angle, orientation error and also measurement errors of the slave gyroscope. Two linear and non-linear observation models are developed for the Transfer alignment configuration. The simulation results reveal the appropriate performance of the proposed configuration for marine application, especially when there are no accurate velocity measurements. Based on the simulation results, the performance of the non-linear observation model is better than linear ones in dynamic misalignment angle estimation. Moreover, it can be inferred from the orientation error estimation that rich data in high-maneuvered motion is necessary for required estimation accuracy. Additionally, 200 runs of Monte-Carlo simulation are developed and the estimation RMSE are presented.

Face recognition from digital images is used for surveillance and authentication in cities, organizations, and personal devices. Internet of Things (IoT)-powered face recognition systems use multiple sensors and one or more servers to process data. All sensor data from initial methods was sent to the central server for processing, raising concerns about sensitive data disclosure. The main concern was that all data from all sectors that could contain confidential information was placed in a central server. Federated learning can solve this problem by using several local model training servers for each region and a central aggregation server to form a global model in IoT networks. This article presents a novel approach to optimize data Transfer and convergence time in federated learning for a face recognition task using Non-dominated Sorting Genetic Algorithm II (NSGA II). The aim of the study is to balance the trade-off between training time and model accuracy in a federated learning environment. The results demonstrate the effectiveness of the proposed approach in reducing data Transfer and convergence time, leading to improved performance in face recognition accuracy. This research provides insights for researchers and practitioners to enhance the efficiency of federated learning in real-world applications.

Introduction: In the current research, it has been tried to qualitatively study all kinds of policies and measures necessary for alignment between teacher preparation programs and democratic social education competencies under the model of teacher education curricula, which include: direct (official) curriculum, Indirect curriculum, informal curriculum (implicit) and unstructured curriculum (hidden) should be identified in the educational system. Method: Qualitative approach and phenomenological method were used in this research. The field of research is Farhangian University of Hormozgan and the participants are  13  lecturers of this university. The sampling method is a combination of convenience and snowball sampling. The research tool was a semi-structured interview. The information was analyzed using thematic analysis method and then using MAXQDA software... Result: The information was analyzed using the theme analysis method and then using MAXQDA software in the form of 2  overarching themes, 8 organizing themes and 25  basic themes. The results of this research showed the basic policies and measures for teacher preparation programs, in the form of two components, strategies and solutions of teacher training curricula, separated by curricula (formal, informal, informal, unstructured curriculum) and with the goal of preparing The formation of teachers has been identified in the educational system to realize the competencies of democratic social education. Conclusion: Therefore, examining the opportunities, facilities, and resources available to achieve these actions should be on the agenda of decision makers and educational planners. It is necessary to pay special attention to the strategies and solutions of teacher training curricula.

Automatic topic detection seems unavoidable in social media analysis due to big text data which their users generate. Clustering-based methods are one of the most important and up-to-date categories in topic detection. The goal of this research is to have a wide study on this category. Therefore, this paper aims to study the main components of clustering-based-topic-detection, which are embedding methods, distance metrics, and clustering algorithms. Transfer learning and consequently pretrained language models and word embeddings have been considered in recent years. Regarding the importance of embedding methods, the efficiency of five new embedding methods, from earlier to recent ones, are compared in this paper. To conduct our study, two commonly used distance metrics, in addition to five important clustering algorithms in the field of topic detection, are implemented by the authors. As COVID-19 has turned into a hot trending topic on social networks in recent years, a dataset including one-month tweets collected with COVID-19-related hashtags is used for this study. More than 7500 experiments are performed to determine tunable parameters. Then all combinations of embedding methods, distance metrics and clustering algorithms (50 combinations) are evaluated using Silhouette metric. Results show that T5 strongly outperforms other embedding methods, cosine distance is weakly better than other distance metrics, and DBSCAN is superior to other clustering algorithms.

Background and Aim: Technology Transfer is a process used to benefit from the scientific experiences of countries in development. The purpose of this study was to investigate the legitimacy of the lease contract in the process of technology Transfer from the perspective of Islamic ethics. Materials and Methods: This qualitative study was conducted using an analytical approach and using published texts, books and articles. After examining the legitimacy of the lease contract in the technology Transfer process, its alignment with Islamic ethics was examined and analyzed. Findings: The contract of hiring of individuals enjoys legal and Jurisprudence validity and legitimacy in Iranian and Islamic law. Legally, in the process of technology Transfer, companies and foreign countries are recognized by the technology owner and its Transferee as contractors who in the process of Transfer do not own any of the manufacturing sectors and receive only wages for their activities, services and consultants. Economically, these causes benefit from both the benefits of technology and the protection of its ownership. Conclusion: From the point of view of Islamic ethics, the lease agreement has considerable legitimacy for the technology Transfer process, which demonstrates the compatibility of the law with Islamic jurisprudence and ethics; it can be a guarantee for the development of the country in the light of technology Transfer.

In this paper, a step-by-step laboratory procedure for performing a satellite's payload’s alignment measurement is presented. Four highly accurate theodolites are used along with two or more alignment corner cube to accurately extract the final attitude. Theodolites are arranged around the satellite in such a way that they have a clear direct view of the alignment cubes mounted on the payload and the satellite. Two theodolites should point to the payload’s alignment cube and the other two theodolites must point to the satellite’s alignment cube. Each theodolite must see at least one other theodolite, directly. Finally, by forming the coordinates systems of the payload and satellite in the theodolites coordinate system along with using the coordinate Transfer matrices, the payload alignment correction matrix will be extracted in detail. The total method accuracy is within the order of few arcseconds.

One of the most important organizational challenges is the strategic alignment between information technology (IT) and business objectives. Organizations have deployed different approaches to achieve strategic alignment and competitive advantage. Enterprise architecture (EA) has been viewed as an effective approach not only for optimum management of IT, but also for strategic alignment of IT applications and business needs. EA maturity indicates the degree of attaining EA project goals, out of which, is the IT-Business alignment. In this paper, the relationship between enterprise architecture maturity (EAM) and strategic alignment maturity model (SAMM) has been investigated to declare whether EAM can act as enabler for SAMM. Research population includes enterprises in which, the EA project is implemented. Pearson’s correlation and regression test have been used for analyzing the data gathered by questionnaire. The findings indicate that the success of EA significantly influences strategic alignment maturity.

One of the critical stages in a display production line is the image alignment of displays that includes the precise adjustment of the geometric parameters and the color of the image. The mutual influences of the parameters of the display's image necessitate a complex and interactive alignment process. In this paper, the effect of the mutual influences of geometric parameters on the alignment process of a display's image are shown, a suitable model for the geometric characteristics of a display's image are suggested and, then, the unknown parameters of the proposed model are estimated by the RLS estimator. Using an off-line estimator, an initial measure of the values of the unknown parameters of the display model is obtained. To modify the model parameters of the consecutive video displays on the production line, an on-line estimator is applied. Variations of the parameters of the display model on a production line are traced using on-line estimation. This model estimation is used to implement an adaptive alignment algorithm. Both the adaptive and the proportional alignment processes have been experimentally implemented under similar working conditions. Experimental results show that the use of the adaptive alignment process considerably increases the speed and reliability of convergence of geometric parameters to their desired values. An IA-32, 3.4 GHz Pentium P4 processor has been used in this research. Considering the rapid developments in UDSM technology and the IA-64 architecture, the application of the proposed adaptive alignment algorithm in an auto-alignment system has the potential for real-time implementation in the near future.