درخت حوزه‌های تخصصی

Performance evaluation, as a tool to know the degree of success of organizations in achieving predetermined goals and a factor in managers' decisions, has been one of the constant needs of organizations. The purpose of this research is to identify performance evaluation indicators and explain the appropriate performance evaluation model in Macro government organizations such as Jam Petrochemical Company. This research is based on the purpose of applied research and also based on the research method with a mixed or combined approach with a sequential exploratory strategy. The required data were collected through qualitative research (interview) and quantitative research (questionnaire). In the quantitative part, the current research can be considered as a non-experimental (descriptive) type of research and a survey type. To analyze the data of the questionnaire, this research has been done in four phases, the first phase is to identify and rank the strengths and weaknesses of Jam Petrochemical Company, and the second phase is to use a Delphi test to identify indicators that are effective in evaluating the performance of Jam Petrochemical Company. The third phase is exploratory factor analysis and determining Dimensions of performance evaluation in Jam Petrochemical Company and finally the fourth phase of structural equations and path analysis. The results of the research showed that considering that the T-statistic for all variables is more significant than 1.96 and also considering the positiveness of the path coefficients, the variables (scientific observation, technology and technology, financial management, managers' responsibility, infrastructure management, management and leadership and human resources) are among the factors that make up the performance evaluation system in Jam Petrochemical Company.

In healthcare, a diagnosis is reached after a thorough physical assessment and analysis of the patient's medicinal history, as well as the utilization of appropriate diagnostic tests and procedures. 1.7 million People worldwide lose their lives every year due to complications from chronic kidney disease (CKD). Despite the availability of other diagnostic approaches, this investigation relies on machine learning because of its superior accuracy. Patients with chronic kidney disease (CKD) who experience health complications like high blood pressure, anemia, mineral-bone disorder, poor nutrition, acid abnormalities, and neurological-complications may benefit from timely and exact recognition of the disease's levels so that they can begin treatment with the most effective medications as soon as possible. Several works have been investigated on the early recognition of CKD utilizing machine-learning (ML) strategies. The accuracy of stage anticipations was not their primary concern. Both binary and multiclass classification methods have been used for stage anticipation in this investigation. Random-Forest (RF), Support-Vector-Machine (SVM), and Decision-Tree (DT) are the prediction models employed. Feature-selection has been carried out through scrutiny of variation and recursive feature elimination utilizing cross-validation (CV). 10-flod CV was utilized to assess the models. Experiments showed that RF utilizing recursive feature removal with CV outperformed SVM and DT.

In today's competitive markets, brands are always trying to create a desirable image of their products and services to elicit more favorable tendencies in customers. Beyond the marketing efforts of brands, there is an important factor that can either strengthen or weaken these marketing efforts. This factor is related to the country of origin or manufacturer of a brand, which can have an impact on consumer behavior and perceptions of products and brands from that country. Therefore, the aim of this research is to investigate the effect of the country of origin and manufacturer on consumer perceptions of the institutional environment of countries and purchasing decisions, taking into account the moderating role of beliefs arising from customer trust. This research is an applied study and, in terms of data collection method, is descriptive-correlational. A library approach was used to extract studies, and a field approach was used to collect statistical data, with the data collection tool being a questionnaire. The study population consisted of customers who own and purchase iPhones from the Apple brand in districts 1, 2, and 3 of Tehran. Descriptive statistics and inferential analysis were used to analyze the data, and the software used to analyze the data was SPSS and smart PLS. The results indicate that the country of origin of a brand has an impact on perceptions of the legitimacy and regulatory environment of that country. Additionally, the results show that the country of manufacture of a brand also has an impact on perceptions of the normative environment and regulatory environment of that country. On the other hand, perceptions of the legitimacy of the country of manufacture of a brand have an impact on customer preferences for a brand and a willingness to pay a higher price for a brand. However, the impact of the country of origin on customer purchasing decisions with the moderating role of beliefs in brand benevolence, honesty, and capability has not been confirmed.

The purpose of this research is to design a model for evaluating the policies of proportionalization of administrative system formations in Iranian National Oil Company. In this regard, the research method was a combination of qualitative and quantitative methods and tools with an applied orientation along with survey strategy and inductive approach. The qualitative part of the research included a review of the records and background of the research and conducting library studies based on the content analysis and meta-composition methods and the Delphi technique, and in the quantitative part, several techniques and tools were used, including interpretive structural modeling and structural equations, factor analysis, pairwise comparison matrix, and questionnaire tools. By carrying out the qualitative stage and refining and screening and verifying the achievements in the quantitative stage, finally 89 indicators in the form of 11 dimensions and 35 components, under the four main concepts of "policy evaluation", "proportionalization", "administrative system formations" and "macro environment" were counted and classified. In the next step, by identifying the relationship and mutual effect of the identified factors, the evaluation model of the design policy and finally the validity and reliability of the model was put into the test and approved. The issue of the optimal size of the government and the public policies related to it has been discussed and debated among political and economic experts for about three decades in the documents of the government and the ruling space of the country with different expressions such as "downsizing", "privatization" and "rationalization". Following the studies conducted in this research, with the premise that on one hand, the correct and scientific evaluation of public policies has an undeniable role in the successful implementation of policies, and on the other hand, in our country, the issue of evaluating public policies has always been like a missing link in the space that governs this territory and better management of resources in Iranian National Oil Company.

Getting highly accurate output in biomedical data processing concerning biomedical signals and images is impossible because biomedical data are generated from various electronic and electrical resources that can deliver the data with noise. Filtering is widely used for signal and image processing applications in medical, multimedia, communications, biomedical electronics, and computer vision. The biggest problem in biomedical signal and image processing is developing a perfect filter for the system. Digital filters are more advanced in precision and stability than analog filters. Digital filters are getting more attention due to the increasing advancements in digital technologies. Hence, most medical image and signal processing techniques use digital filters for preprocessing tasks. This paper briefly explains various filters used in medical image and signal processing. Matlab is a famous mathematical, analytical software with a platform and built-in tools to design filters and experiment with different inputs. Even though this paper implements filters like, Mean, Median, Weighted Average, Guassian, and Bilateral in Python to verify their performance, a suitable filter can be selected for biomedical applications by comparing their performance.

Managers are the most valuable asset for every organization. Organizational health is the term given to a business's capacity to adapt in a constantly evolving world. It refers to “the ability of an organization to cope with change and continue to function with a high-performance workplace culture.” And these days, the organizational environment is always shifting. This study aimed to investigate the dimensions and components of managers’ organizational health at the Azad University Branches of Gilan. The results showed that organizational health has 2 dimensions included "structural and managerial". The structural dimension has 5 components including "organizational atmosphere, organization structure, scientific emphasis, monitoring and evaluation, and organizational justice". The managerial dimension has 5 components including "ethics, goal setting, resource support, effective leadership, and consideration". The effect of all dimensions and components on organizational health was confirmed, and the management dimension with a factor loading of (0.960) has the first rank and the structural dimension with a factor load of (0.947) has the last rank. The results of the Kolmogorov-Smirnov test showed that organizational health variables "structural and managerial" have a normal distribution (p> 0.05). The results of the KMO & Bartlett test indicate that these assumptions are confirmed (p> 0.05). The findings of the study also showed that the presented model has a good fit. Organizational health is a vital aspect of many jobs, including educational jobs, in which managers are required to comply with their employees and subordinates. On the other hand, organizational health will create a pleasant environment for the workplace and increase the spirit of creativity to achieve organizational goals.