فهرست مطالب hossein hassanpoor

The irreplaceable role of social networks in human life is undeniable and many people nowadays follow the news through social networks. That's why news media have expanded their coverage through social networks such as Twitter. Evaluating the performance of news agencies on social networks can help them to improve their performance and ultimately attract the audience. In fact, evaluating news techniques to attract the audience and guide public opinion in the desired direction of the media is one of the most important aims of media policy makers. To this end, it seems necessary to provide new and efficient methods for quantitative and qualitative evaluation of the performance of news media. In this research, a three-step method is proposed. In the first stage, the criteria and sub-criteria were ranked using network analysis method. The results of these two steps are used in the data envelopment analysis method and efficient media are identified. The efficient media are then ranked using the Andson-Peterson method. This method was tested on 15 Persian- news networks on Twitter, and the most popular Persian media were ranked. The results indicated that the model used is a suitable and efficient model for evaluating and ranking Persian news networks. Al-Arabiya Farsi, Deutsche Welle Farsi and The Indypersian were selected as the most efficient medias, respectively. The results obtained in comparison by similar researches and the opinion of experts indicated that the proposed model is a suitable and efficient model for evaluating and ranking Persian news agencies

Cognitive performance includes a set of capacities that enable the individuals to recognize, process, and respond to information. Cognitive performance, mental structures, and cognitive functions of strategic organizations’ managers are very critical factors in the success of organizations and achieving their strategic goals. Therefore, this study aims to identify and prioritize the cognitive functions affecting the cognitive performance of strategic managers.

The method used in this research is a qualitative-quantitative sequential mixed research method in which a combination of quantitative and qualitative methods is used sequentially. In this research, first using qualitative methods, the cognitive functions affecting managers' cognitive performance are identified and then in a quantitative phase, using statistical analysis, a novel methods of multi-criteria decision making the identified factors are prioritized.

In the qualitative section, after reviewing the literature, 14 cognitive functions affecting the cognitive performance of managers were extracted and the conceptual model of the research is presented. In the quantitative part, using the implementation of statistical methods and a multi-criteria decision making method, cognitive functions were prioritized and the weight of each of these functions is calculated. "Planning function" and "performing several tasks simultaneously" have been selected as the most important functions among the prioritized cognitive functions, which have obtained the highest average final weight.

It is concluded that avoiding managerial errors due to low levels of managerial performance in any of the cognitive functions can cause irreparable problems that subconsciously reduce the efficiency of relevant organizations. In this research, by identifying and prioritizing cognitive functions affecting the cognitive performance of strategic managers, it is possible to prevent cognitive errors, reduce the accuracy factor, and increase the accuracy of decisions.

Cognitive warfare, in which, using human’s brain cognitive biases, enemy is intending to disturb people’s cognitive abilities, is one type of psychological warfare. In this research, gathering questionnaire, we found that the most important cognitive error used in cognitive warfare in exchange market is Herding; in this line, we try to define an index to measure cognitive warfare intensity in and its impact on exchange market. Using the results of estimations, we predicted how exchange rate will differ.Our results shows that if, taking advantage of real exchange rate index, we control for the inflation rate in Iran and its trade partner and major countries in world trade and also control for monetary policy shocks, herding index, which is used as a proxy for cognitive warfare, could account for almost 50 percent of changes in USD exchange rate. In 45 percent of months the prediction from exchange rate babble by cognitive warfare intensity in previous month have less than one standard deviation error. Moreover, the results of prediction of exchange rate have in more than a half on months have less than 5 percent error. These results are fruitful for preparing against psychological attacks in exchange market, and anti-psychological warfare operations

Wearable electronic devices, which are based on Internet of Things (IoT) and big data computing, are able to continuously collect and process the physiological and environmental data and exchange them with other tools, users, and internet networks. Therefore, despite their potential benefits in health monitoring, they can pose serious risks, especially in breach of privacy. Hence, the main question in this study was to identify the most important strengths, weaknesses, opportunities, and threats related to wearable electronic technologies.

In this study, StArt 3.4 software was used for systematic review. Studies until November 30, 2019 were searched for keywords in “Scopus”, “IEEE”, “PubMed”, “Springer”, “Magiran”, “SID”, and “Sivilica” databases and Google search engine.

After deleting duplicate and unrelated documents, 80 documents were selected for final review and were analyzed using descriptive statistics. Accordingly, the main identified strength, weakness, opportunity, and threat were “improving lifestyle and human capabilities”, “low data reliability and user interface”, “applications in health and medicine”, and “information abuse and privacy breach” with 97.5%, 92.5%, 94%, and 99% frequency, respectively.

The results of this study showed that improving human capabilities and application in medicine and health care are the main driving forces for the development of wearable electronic technologies. Therefore, in order to take advantage of the opportunities and overcome the potential threats of this technology, planning for the development and application of indigenous knowledge, as well as the development of the required standards and rules, must be put on the agenda immediately

The field of neurotechnology has a bright future ahead of it due to its direct impact on human health and the various technological applications. Consequently, this field is of great importance to many developed countries. As far as we know, since most of the neurotechnologies are emerging technologies, there is no proper strategic analysis for this field in the country. The purpose of this study is to determine the technology readiness level (TRL) for the branches of neurotechnology and identify and prioritize the appropriate strategies by evaluating the current state of the country in the neurotechnology field. To achieve this goal, questionnaires are distributed among 40 experts in neuroscience and neural technologies. In the strategy prioritization and data analysis step, the SWOT matrix-based method is used; then, the weights of internal and external factors are determined. After performing a pairwise comparison for selecting the top 5 strategies, a quantitative strategic planning matrix (QSPM) is used in order to rank the selected ones. The results indicate that Iran has the highest technology readiness level (level 6) in the brain-to-computer interfaces and the lowest technology readiness level (level 1) belongs to brain-to-brain interfaces. Finally, 5 top strategies which are weakness- opportunity (WO) strategies are determined.

Biomaterials and nanomaterials have generated a great opportunity in regenerative medicine. Neurological disorders can result in permanent and severe derangement in motor and sensory functions. This study was conducted to examine the effects of selenium nanoparticles (Se NPs) as a chemical inducer for differentiation of PC12 cells into sympathetic-like neurons characterized by neurite outgrowth. Size, surface charge, the shape of Se NPs and the morphology of hydrogels were characterized by dynamic light scattering (DLS), zeta sizer, transmission electron microscopy (TEM) and scanning electron microscopy (SEM), respectively. DAPI staining, RT-PCR and western blot assays were used to evaluate cell attachment and mRNA and protein levels of neuronal markers, respectively. The hydrodynamic size of Se NPs was about 33.55 nm and their surface charge was shifted from -24 to +3.4 mV. The morphological characterization demonstrated monodisperse spherical particles after coating with BSA. SEM images demonstrated that chitosan hydrogel containing Se NPs has suitable pore sizes for penetration of cells. DAPI staining and live/dead assay demonstrated the ability of cell attachment and biocompatibility of hydrogel, respectively. RT-PCR and western blot assays showed that neurite extension of differentiated PC12 cells can be linked to significantly increased mRNA levels of Map2, β-tubulin, increased protein levels of neurofilament-200 (NF200) as neuronal markers and decreased protein levels of ki67 protein as a proliferation marker. Collectively, our findings show that Se NPs can act as a chemical inducer for the differentiation of PC12 cells into sympathetic-like