These days, the most important areas of research in many different applications, with different tools, are focused on how to get awareness. One of the serious applications is the awareness of the behavior and activities of patients. The importance is due to the need of ubiquitous medical care for individuals. That the doctor knows the patient's physical condition, sometimes is very important. Of course, there are other important applications for this information. There are a variety of methods and tools for measurement, gathering, and analysis of the physical behaviors and activities’ information. One of the most successful tools for this aim are ubiquitous intelligent electronic devices, specifically smartphones, and smart watches. There are many sensors in these devices, some of which can be used to understand the activities of daily living. As an output result, these sensors produce many raw Data. Thus, it is needed to process these information and recognize the individual behavior of the output of this processing. In this paper, the basic components of the analysis phase for this process have been proposed. Simulations validate the benefits and superiority of this method.

A new concept named pseudo information measure is introduced. By this measure, Bayesian Fusion of independent sources of information is extended to a wide range of possible formulations and some new Fusion formulas are calculated. The coincidence between the performance of the proposed method of Fusion with the results that are expected by human logic and output sensitivity of the Fusion process are discussed. Also, we have discussed the resulting flexibility for map building applications. Map building by using the proposed Fusion formulas has been implemented on Khepera robot. The resulting map were fed to "A*" path planning algorithm for comparative purposes. For the resulting routes, two factors are considered: length and a danger measure which is an increasing function of the least distance of the path to obstacles. The results show that by using the proposed Fusion formulas, more informative maps of the environment are obtained by which more appropriate routes are achieved. Based on the selected function, there is a trade-off between the length of the resulting routes and their safety. This flexibility lets us choose the right Fusion function for different map building applications.

In this paper fully centralized, hierarchical decentralized, and fully decentralized Multisensor structures of Kalman filter are introduced and compared with together and with one sensor structure of Kalman filter. Decentralized structures are obtained through parallelism in centralized Kalman filter and give high processing speed. Fully decentralized structure requires no central processor and each processor estimates system's states. Therefore, the system is very resilient to loss of one or more of its processors and its survivability and robustness are increased. Decentralized algorithms are modified so that t-he computation complexity is reduced with keeping the same accuracy. Simulation results 'for time-variant system illustrate clearly that despite of reducing the computation complexity, the accuracy of the estimation is remained the same. Also, Multisensory structures have high accuracy of estimation in comparison to one sensor structure.

In this paper, we compare the performance of state vector Fusion methods for Data Fusion of multi sensors networks by comparing the estimation errors covariance. Here, we represent the three main state vector Data Fusion methods and we prove the equivalency of the estimation error covariance matrices corresponding to these three methods. In last part of the paper, the simulation results are presented to show the effectiveness of the theoretical results. Also, we analyze the computational load of these three methods by simulation analysis.

Depression is one of the most significant and prevalent mental health disorders in today’s world. Early detection of depression is critical, and this study aims to identify depression in individuals using information derived from social media. The use of social media for various purposes has grown in recent years, as these platforms provide valuable insights into both individuals and society. Social media can be effectively utilized to detect depression. Researchers have attempted to identify depression using various types of Data, such as images, text, and audio. Most studies have focused on using only one type of Data, such as text or images, for detection. While these methods have achieved notable results, they have limitations in accuracy that can be addressed by incorporating new methods and integrating multiple Data modalities into the model. In this study, we propose a multimodal model that analyzes text and images together to detect depression. Compared to similar models, our approach achieves an approximate 5% improvement in accuracy, reaching 89.87%, while utilizing significantly less of the original Dataset.

Philadelphia chromosome can be founding 95% of patients with chronic myeloid leukemia (CML) by cytogenetic studies. The fused bcr/abl is transcribed in two types of chimeric mRNA. RT-PCR amplification of these two transcripts have been designed to give two different size products. This assay can detect one positive bcr/abl expressing cell in a back ground of 106 negative bcr/abl cells. The power of this assay is the detection of minimal residual disease (MRD) between 6-12 months following bone marrow transplantation (BMT) is an independent and significant factor that predicts the relapse in future. The aim of optimization was to detect β2 microglobulin (β 2M) mRNA. Detection of β2 mRNA and absence of bcr/abl indicates that the patient is negative for MRD and as a result, there is molecular remission in addition to clinical remission. To monitor MRD we tested a patient's blood sample who had tolerated allogenic BMT 7 years ago. bcr/abl wasn't detected in this patient and only β2 M was observed. This result confirmed the absence of MRD in this case. To effectively monitor minimal leukemic activity after BMT, we used a competitive RT- PCR to quantify expression of the characteristic bcr/abl Fusion gene mRNA in patients with CML.    

Today due to the importance and necessity of implementing security systems in homes and other buildings, systems with higher certainty, lower cost and with sensor Fusion methods are more attractive, as an applicable and high performance methods for the researchers. In this paper, the application of Dempster-Shafer evidential theory and also the newer, more general one Dezert-Smarandache theory for implementing as a home security system and also using sensor Data Fusion have been considered. The benefits of Multisensor Fusion with direct connection to the control unit, in comparison with the traditional single sensor systems, have been shown.