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.

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.

The transfer of sustainable building technology in the construction industry is of high importance for reducing energy consumption, protecting the environment, and increasing economic efficiency. This process includes indigenous research and development, international collaborations, workforce training, the formulation of supportive regulations, and the implementation of pilot projects. By leveraging these actions, sustainable development in the construction industry can be achieved, which, in addition to reducing costs, helps preserve natural resources and improve the quality of life. This abstract discusses practical solutions and the necessities for the successful implementation of this process. The present study aims to design a model for the transfer of sustainable building technology. The approach used in the research is qualitative and based on the grounded theory strategy. Data were collected using in-depth interview tools. Theoretical saturation was achieved after 11 in-depth interviews using purposeful sampling. In the grounded theory approach applied in this study, 22 general categories were identified during the three stages of open, axial, and selective coding, categorized within a paradigm framework including causal conditions, contextual conditions, intervening conditions, core categories, strategies, and consequences. The results showed that in today's competitive business environment, construction industry managers are seeking solutions to increase efficiency, improve strategic intelligence, reduce costs, and achieve sustainable building. To achieve these objectives, the transfer of sustainable building technologies emerges as a crucial strategy.

The polymerase chain reaction (PCR) was applied to create the colored transgenic ornamental zebrafish with the specific primers designed for muscle promoter of two genes and genes fragments cloned in Tol2 vector containing GFP gene in the ORF region. The 2000 bp and 2300 bp fragments of MYLZ2 and CKMB promoters' genes respectively were amplified by PCR, cloned into Tol2 plasmid expression vector containing SalI restriction enzyme site and transformed into E. coli Dh5α . Positive clones were tested for having fragments by colony PCR with anchor primers and subcultured for extracting recombinant plasmid miniprep. The extracted recombinant plasmid was tested with SalI enzyme digestion and sequenced with universal primers. Positive recombinant plasmids were applied for injection with transcript produced synthetically in the lab into zebrafish one-cell embryo. In this study, 2000 bp and 2300 bp fragments of MYLZ2 and CKMB promoters, respectively, were cloned in an expression vector Tol2 and confirmed by PCR, sequencing and enzymatic digestion. Also, recombinant plasmid was subcultured and purified for injection with a synthetic transcript. One-cell embryos injected by coinjection materials (recombinant plasmid and transcript) were tested by fluorescence microscope for positive GFP expression, where a few offspring of F0 generation were positive for GFP expression in their muscles. Recombinant plasmids with muscle-specific promoters (MYLZ2 and CKMB) were able to induce expression of GFP in some F0 embryos in a transient form and could be applied for consolidation in the next fish generation.

In this study a mathematic model was developed for predicting wood temperature at different depth of wood and time during heating. Fractional differential equations were applied for developing such model. For evaluating accuracy of the model beech wood with density of 0.68gr/cm3 and moisture content of 12 percent was used. Good agreement was found between model predictions and experimental data. Effect of distance from heat resource in wood was explained however with increasing wood thickness or distance from heat resource accuracy of the model reduced. Effect of duration of heating on heat transfer was also described well. Heat loss from edges of wood block under effect of environmental conditions was identified by model. However model has to be modified for increasing its accuracy, it had high ability for predicting temperature at different thickness of wood during heating. When accuracy of the model is increased it can be used for wood drying and heat treatment applications.

competitive advantages for competitiveness, the use of technological cooperation is considered as an effective tool for developing competitive advantage and eliminating the gap between existing and desired capabilities. In this article, an attempt was made to design a model to explain the ethical considerations that play a key role in the effective transfer and establishment of stable relations between the parties. Method: The present study is a descriptive-survey method with a qualitative approach. The statistical population of the research includes expert experts and academics and industrialists. The statistical sample is 10 experts. The sampling method is purposeful non-random using the snowball technique. Document analysis and interview tools have been used to collect data. The data has been analyzed and evaluated using thematic analysis method. Results: According to the initial model, derived from the study of related articles and then its development based on the findings of the interviews conducted with experts and the coding of the research findings, four dimensions including social-cultural, political-legal, health-environmental and economic development dimensions as the main dimensions of the model. Ethics in technology transfer identified. Conclusion: In order to create stable relations between the parties of technology transfer and effective transfer, companies and institutions that intend to transfer technology should consider the above dimensions and related components in transfer projects.

Using multi transmission line (MTL) model, a compact circuit model for mixed multiwall carbon nanotube (MMWCNT) interconnects is proposed. Using the proposed circuit model, an algorithmic model is proposed for calculating the transfer matrix of these interconnects. In the proposed circuit model and also algorithmic model, capacitive, inductive and tunneling effects between the carbon layers is considered. Moreover the concept of distributed circuit block parameters is proposed for this type of interconnects. This model is compact because it can be used in wide range and technology of interconnects. Also using this model, any change in the physical parameters of the nanotubes can be considered in the circuit model and algorithmic model. Using the circuit model and algorithmic model one can calculate various stability and time domain responses for MMWCNT interconnects in VLSI circuits. In this paper after proposing the circuit model and algorithmic model, we have calculated step time response and Nyquist response of MMWCNT interconnects. The results show that by increasing the length and diameter of the tubes, the delay of the interconnects is increased and its stability is increased too.