فهرست مطالب rezvan abbasi

Urban planning, as a professional activity, is ethically complex. and all its aspects, from theoretical thoughts to professional activities, are related to ethical issues. This relationship is so strong that for thinking clearly and comprehensively about planning one should develop some understanding of how key ideas in ethics relate to planning and their integration with this profession. One way of integrating ethical ideas with the planning profession is to integrate it with the professional codes. This research aims to present a clear image of the relationship between the philosophy of ethics and the planning profession, in particular the codes of professional ethics, and examines the position of these ethical theories in these codes. The results of the synthesis of qualitative studies and the examination of the relationship between the principles extracted from these studies and the principles found in the ethical codes of Iran, the United States and Canada show that the American ethical codes are most closely related to ethical theories and various ethical ideas have been involved in the formulation of the content of these codes, from classical theories to more recent t, from teleological theories to deontological Theories and virtue ethics. In Canada's codes of professional ethics, almost all ethical theories examined in qualitative research can be traced, especially environmental ethics and its different approaches. Ethical codes related to planning in Iran have a limited relationship with normative theories, and the relevant ones are related to more classical ethical theories such as Kant's and Ross's theories.

In recent years, medicine supply chain management has become more significant, especially after the Covid-19 pandemic. The most important issue is supply chain cost control. If the drug inventory is not properly managed, it will lead to issues such as the lack of inventory of certain drugs, provision of excess inventory, increased costs, and, finally, patient dissatisfaction.

In this study, an attempt has been made to predict and manage the pharmaceutical needs of hospitals using an efficient deep-learning algorithm. The drug consumption data for ten years of Besat General Hospital in Hamedan are extracted from the HIS database. As a case study, the accuracy of the predictive model is evaluated, especially for cefazolin. We use a deep model to analyze the medical time-series data efficiently. This model consists of a Long Short-Term Memory network, which can sufficiently recognize the change history in time-series prediction applications. The proposed model with many adjustable parameters in the deep architecture will bring good performance to overcome the complexities of the learning problem.

Using the deep learning method can increase robustness by reducing the effects of complexity and uncertainty in medical data. The average forecasting error for the proposed method is 0.043, and the measured values for RMSE, MAE, and R2  are 0.335, 0.260, and 0.851, respectively.

A comprehensive comparison between some other predictive methods and the implemented model shows the outperformance of the proposed approach. Additionally, the evaluation results indicate the efficiency of the proposed approach.

Ethics is related to choice and practical judgment. Since the nature of urban planning is related to the pursuit of community interests through determining appropriate actions for the future during successive choices in complex settings and uncertain conditions, it can be said that ethical considerations are an inseparable part of it and it is inevitable to integrate the philosophy of ethics with the thoughts and professional efforts of planning. In general, addressing the ethical questions of "do's and don'ts" and examining "the nature and meaning of moral values" in planning is always urgent and necessary but challenges raised in the contemporary era, the emphasis of new theoretical positions on attention to contextual differences and conflicts in perceptions and interpretations of values and ethical principles of planning, and ultimately the dispersion and reduction of attention to the area of planning ethics in the recent decades, the necessity of reviewing and rethinking the content of research published in this area has become more prominent. The current research aims to present a comprehensive view of ethics in planning by identifying dominant themes in the literature, specifying existing research gaps, and of course introducing new paths to complete the various dimensions of planning ethics. With answering to the questions like: what are the main priorities of researchers regarding ethics in urban planning? Which subjects and issues have been neglected in the existing researches and what perspectives can be suggested for future researches in this area? This research provides a general view of ethics in planning and its changes over time.

This research is a systematic investigation of a specific subject to improve or expand knowledge, it is considered basic research that has been conducted with a qualitative approach (thematic analysis). Table 1. Methodological design in this research General stages Descriptions Outputs Review strategy Explaining the qualitative systematic review using thematic analysis The review plan  Data collection Identifying key concepts and searching for primary sources Finding 224 sources as articles, dissertations, book chapters 110 researches enter the analysis stage as a final data set. Refinement and selection of the most relevant studies Analyzing and synthesizing the dataset Descriptive analysis of research Temporal and geographical distribution and researches focus area Content analysis in five steps: Reading the full text of documents in the dataset; Selecting textual codes; Extracting basic themes; Synthesizing the basic themes and creating organizing themes; Grouping the organizing themes and generating the global themes.identifying three global themes: integration of ethical theories with planning theory, ethics in the realm of professional practice, and ethical considerations in the Academic realm. introducing potential paths for future research.

By analyzing the final data set, we have identified three global themes: integration of ethical theories with planning theory, ethics in the realm of professional practice, and ethical considerations in the academic realm.Research under the First global theme, integrating ethical theories with planning theory is qualitative and discusses the nature and role of planning based on ethical philosophy. With an extroverted approach, these works focus on normative ethical theories and seek to explain the most basic criteria of rightness and wrongness and do and don'ts in planning. Second global them, ethics in the realm of professional practice is focused on the ethical dimensions and aspects of the planning practice including Ethical attitudes of planners, the complexities of decision-making and ethical judgment in the planning process, ethics in planning techniques, and the direct application of ethical theories in practice. Research under the third global theme, ethics, and ethical considerations in the academic realm of planning is focused on teaching ethics in planning and ethics in planning research.

According to the investigations of the present research, the research focused on ethics in planning has been scattered and separated over time and their balance has decreased in different layers (Figure 5). In the 1990s, most of the themes receivedthe attention of researchers, but since the beginning of the 21st century, we have seen a decline in direct attention to this research field at various levels. Of course, a series of themes such as extracting the values of planners, investigating the nature and content of professional codes, and teaching ethics in planning have always been welcomed by researchers. The continuation of attention to these themes shows things like learning from action, determining ethical frameworks through a bottom-up process, and extracting the inner values of planning have always been emphasized by researchers. . Also, the flow of research in the last two decades shows that the context of planning and the importance and impact of contextual differences in the selection, interpretation, and teaching of ethical concepts and ideas have become more prominent.

A general review of the planning ethics literature shows that the concerns related to the ethics and values of planning are largely dominated by normative concerns. The researchers of this field, instead of exploring more deeply the "nature and meaning of ethical values and principles" (meta-ethical field) and how to identify the appropriate solution in each specific situation, focus on the normative Deontological frameworks derived from Western contexts, which put forth universal normative principles and procedures without considering the impact of context and culture on knowledge and behavior.

In recent years, medicine supply chain management has become more significant, especially after the Covid-19 pandemic. The most important issue is supply chain cost control. Medicine costs include nearly 30% of hospital expenses. If the drug inventory is not properly managed, it will lead to issues such as the lack of inventory of certain drugs, provision of excess inventory, increased costs, and, finally, patient dissatisfaction.

In this study, an attempt has been made to predict and manage the pharmaceutical needs of hospitals using artificial neural networks and deep learning algorithms. The prescription and consumption information of one of the general hospitals in Hamedan city from 2013 until 2017 was extracted from the HIS databases. Since most drugs have different and specific characteristics and it is impossible to create the same prediction model for all drugs, the employed dataset is limited to the category of antibiotics. As a case study, the accuracy of the predictive model is evaluated, especially for cefazolin. We use a deep model to analyze the medical data time series efficiently. This model consists of two parts, a Convolutional Neural Network and a Long Short-Term Memory network (LSTM), which can sufficiently recognize the change history in time series prediction applications. The proposed model with many adjustable parameters in convolutional neural networks will bring good performance to overcome the complexities of the learning problem.

Using deep learning in the training process can increase robustness by reducing the effects of complexity and uncertainty in medical data. Eventually, the prediction evaluation results and analytical criteria such as forecasting error and convergence speed and some statistical tests like R^2, MAE, and RMSE were presented. The average forecasting error for the proposed method is 0.028, and the measured values for RMSE, MAE, and R^2 are 0.095, 0.081, and 0.788, respectively.

A comprehensive comparison between some other predictive methods and the implemented model shows the outperformance of the proposed approach. Additionally, the evaluation results indicate the efficiency of the proposed approach.

The increase in the power generated by the wind hashad effects on the performance of the power system incases such as power quality, safety, stability, andvoltage control. The wind turbines are used to generateelectrical energy from wind. They can work in fixedor variable speeds. The asynchronous generator isdirectly connected to the grid for the fixed-speed windturbines. In order to connect the DFIG (Doubly-FedInduction Generator) to the grid, this machine must beable to integrate its generated power into the grid in aspecific voltage (the grid voltage level). The mainDFIG controlling method is the use of field-orientedvector control for regulating the rotor flux. The DFIGvector control consists of two main parts as grid sideconverter control and rotor side converter control. Therotor side converter is used to control the grid outputpower. This converter regulates the power factors inthe terminals, and actually restores the generatedpower deviation from the reference power through thePID controllers, besides guaranteeing the stability ofthe induction generator. In the current study, the powerwas controlled through the determination of the PIDoptimal coefficient of the rotor and grid sidescontrollers and the gray wolf algorithm in theMATLAB software. In addition, the stability of thesmall signal of the grid equipped with the doubly-fedwind generator in the wind speed turbulenceconditions was optimized to satisfy the requiredcriteria in output active and reactive power of a DFIG.From the simulation results it is observed that theproposed controller yields better results whencompared to other methods in literature in terms ofperformance index.

This paper is concerned with the eradication of tumor cells in the human body by defining an optimal protocol using a polynomial approximation technique for the injection of chemotherapy drugs. The dynamics of the system are described based on immune-oncology. Variation of host, tumor, and immune cells’ populations are studied in the model during the injection of the chemotherapeutic drugs. The objective is the minimization of cancerous cells' average population by minimum drug injection to avoid the destructive side-effects of these chemotherapeutic substances. It should be done by stabilizing the population of host and immune cells around a free-tumor desirable health condition. This optimization problem by considering the nonlinear model of the system makes applying nonlinear optimal control inevitable. Solving Hamilton-Jacobi-Bellman (HJB) nonlinear partial differential equation (PDE) for the system is put into our perspective to cope with this problem. Since the dynamics of the system are not polynomial, it comprises fractional terms, this PDE cannot be solved straightforwardly. We take advantage of the power series expansion technique to approximate the solution of the PDE with satisfactory accuracy. Finally, a series of simulations are carried out to prove the capability of the controller in terms of robustness and sensitivity, increasing convergence rate for the elimination of cancerous cells, and enlargement of the domain of attraction.

One of the most complex and controversial issues in financial markets is the prediction of price and stock returns which is always a matter of interest to shareholders. The stock market is vulnerable to various factors that affect the price fluctuations in the stock market. The development of a strong stock market algorithm that can accurately predict stock behaviour is important to maximize profits and minimize the loss of investors. Although in addition to the history of each share, other psychological factors affect the value of each share, in this research, an artificial intelligence model is proposed based on long short-term memory and text embedding. In addition to being paid to the stock market in the form of time series data; In order to investigate the psychological force of the market, features are also extracted from news sites. And finally, based on the combination of features extracted from news sites and time-series data, predicts the future of the stock market. The results of the evaluations show the proposed model can predict the market future truly.