j. ghasemi

In this paper, a new intrusion detection system (IDS) is presented to deal with distributed denial of service (DDoS) attacks. A combined algorithm based on Harris Hawks Optimization (HHO) and Dragonfly Algorithm (DA) is proposed to select relevant features and eliminate irrelevant and redundant features from the NSL-KDD dataset. The extracted features are presented to a multilayer perceptron (MLP) neural network. This network (as a classifier) divides the network traffic into two classes, normal and attack categories. Performance of the proposed model is evaluated with two standard and widely-used datasets in the field of intrusion detection: NSL-KDD and UNSW-NB15. The results of the simulations clearly show the superiority of the proposed method compared to the previous methods in terms of critical evaluation criteria such as accuracy, precision, recall, and F-Measure. Specifically, the proposed method exhibited improvements of 96.9%, 97.6%, 96%, and 96.8% in these metrics, respectively (compared to the baseline method). The main reason for these improvements is the ability of the combined algorithm to intelligently select the optimal features and reduce the dimensions of the data. This careful selection of features allows the MLP neural network to focus on critical information, increasing the classification accuracy and ultimately improving the performance of the intrusion detection system. This research showed that combining optimization algorithms and machine learning works well. So, it is effective for tackling DDoS attacks. It can lead to better intrusion detection systems. These systems will be more efficient and accurate.

Sufficient public parking lots (PLs) are essential for developing of sustainable cities. Different factors such as location, accessibility, safety, and environmental effects must be considered to ensure PLs stability. New technologies such as intelligent parking systems, electric vehicle (EV) charging stations (CSs), and green infrastructure make PLs more sustainable and efficient. In addition to providing parking spaces for ordinary cars (OCs), PLs provide charging services for EVs. After completing charging, EVs can be transferred to another place in the PL to provide charging service for more EVs. This problem is a motivation to present an optimization process for park scheduling in this paper. The proposed process is based on minimizing the number of required chargers. The considered constraints in the optimal scheduling process include providing the requested charging service and parking space for all EVs and OCs. The required parking space is determined based on the available databases and the simultaneous presence of vehicles in the PL. Statistical simulations produce different scenarios of vehicles in PL. The findings demonstrate that the suggested approach enhances the utilization of EV charging infrastructure in PLs. It can address the issue of random parking in public places and determine the parking routine.

Tomato (Solanum lycopersicum L.) is one of the most popular and widely consumed vegetable fruits all over the world. Given the vast area (about 2200 hectares) under cultivation of this crop in Golestan province (north of Iran) and the importance of replacing old open-pollinated cultivars with new high-yielding hybrid cultivars, a field study was carried out by evaluating the new determinate tomato hybrid genotypes suitable for outdoor cultivation named A-Z15 and A-Z16 along with Mahdis (control) hybrid cultivar. A-Z16 consisted of two treatments of without and with treating seeds with Probio 96 bacteria named A-Z16a and A-Z16-b, respectively. This study was carried out during 2022 in two agricultural research stations of Golestan, Gorgan and Gonbad Experiments carried out as complete block designs with three replications. Characteristics such as fruit yield/hectare, average weight of fruit, number of fruit carpel, percentage of fruit size (small, medium, large), diameter and length of fruit, number of fruit cavity, fruits/plant, pH of fruit juice, amount of total soluble solids, proportion of fruits with white layer and shelf life of fruit after harvest were recorded and measured. The results of analysis of variances showed significant differences in most of the examined traits in two experimental locations. Based on mean comparisons, cultivar Mahdis (control) was superior in fruit yield and fruits/plant, but this cultivar in qualitative characteristics such as shelf life of fruit, the lower proportion of fruits with white layer and total soluble solids was ranked last. The highest average weight of fruit and shelf life of fruit belonged to A-Z16-b. After Mahdis, A-Z16-b produced highest fruit yield. In conclusion, Mahdis (control) and in a lesser extent A-Z16-b (A-Z16-a treated with Probio 96 bacteria) showed better fruit yield attributes compared to others.

Consideration of social responsibility by organizations is one of the factors influencing the quality of services and development of human resources and can be based on organizational performance assessment. In this regard, the main objective of this descriptive-correlational research was the investigation and cross -validation of social responsibility components from the perspectives of agricultural extension field staff. The statistical population was composed of 250 agricultural extension field staff in Tehran province. According to the Cochran formula, 135 of them were selected through quota sampling method. Data was collected with a questionnaire which its face and discriminant validity was at a satisfactory level. Questionnaire reliability was confirmed by composite reliability index (ranged from 0.85 to 0.93). Accordingly, the main expected current research contribution was to provide a standard scale for measuring the level of social responsibility of the agricultural extension organization. The results showed that the questionnaire used to measure and distinguish the dimensions of social responsibility of the Agricultural Extension Organization is of acceptable validity and after refining its items and adapting it to the organizational culture of the country, it has an plausible ability to distinguish the levels of social responsibility of the organization. Considering the importance of measuring the social responsibility of the organization in assessing the performance of agricultural extension activities, as well as the formation of the basis for the development of extension activities, some practical suggestions have been forwarded.

Some unit operations of food process engineering such as drying consumes a high amount of energy. Therefore, analysis of energy and exergy can be a suitable method to manage the energy consumption of the drying. Hence, in the present research, analysis of energy and exergy for the drying process of lemon verbena leaves was performed.

A cabinet solar dryer was employed to investigate the energy consumption of thin layer drying of lemon verbena leaves. The dryer had a galvanized solar plate collector which had a surface area of 0.75 m2 and to absorb the maximum solar energy, the collector painted with the black color. The collector was set at an angle of 45 degrees relative to the horizon and an electric blower was installed in the bottom of the collector to blow the ambient air through the solar collector and hence, hot air entered the drying chamber to dry the lemon verbena leaves. In order to record the air temperature and humidity in different locations of the dryer, an Arduino board with 8 smart sensors (AM2301, with temperature accuracy of 0.5°C and humidity accuracy of 3%) were used. To obtain the initial moisture content of the leaves, they inserted in an electrical oven for 16 hours at a temperature of 70°C. In order to measure the moisture content of the leaves during drying, they weighted at different times using a digital balance (A & D, Japan with accuracy of 0.001 g).Energy consumption rate of the drying was calculated by Equation (1):Where, Ein: energy consumption rate (kW), : mass flow rate of drying air (kg s-1), cp: specific heat of drying air (kJ kg-1 °C-1), Δt: temperature difference between the ambient air and drying air (°C).Also, the specific energy consumption of drying (SEC) was calculated by Equation (2):Where; SEC: Specific energy consumption (MJ kg-1 of removed water) t: drying time (s), and M: mass of removed water from the drying material (kg).Also, useful power can be calculated from Equation (3):Where; Eout: useful power (kW), ms: Evaporation rate (kg s-1), lg: latent heat of vaporization (kJ kg-1 of water)In order to calculate energy efficiency, Equation (4) was used: Also inlet and outlet exergy were calculated by equations (5) and (6), respectively: Where; T1: Inlet air temperature into the drying chamber (°C), T2: Outlet air temperature from the drying chamber (°C), T0: Ambient air temperature (°C).
Also, Equations (7) and (8) were used to calculate exergy efficiency and loss, respectively:

The results of energy analysis showed specific energy consumption (SEC) increased with increasing of drying temperature and decreasing of air velocity. Accordingly, in the air velocity of 2 m s-1 and the temperatures of 30, 40, and 50 ˚C, SEC were 276.3, 694.7, and 708.0 MJ kg-1 of removed water, respectively. While SEC for an air velocity of 2.5 m s-1 and air temperatures of 30, 40, and 50 ˚C were 266.9, 469.8, and 638.0 MJ kg-1 of removed water, respectively, the corresponded values for air velocity of 3 m s-1 were as 217.0, 391.3, and 501.8 MJ kg-1 of removed water, respectively. Also, the results revealed that with an increase of temperature and a reduction of velocity, energy efficiency reduced, so that the maximum value of energy efficiency observed in an experiment with temperature of 30˚C and velocity of 3 m s-1. Also, the highest value of exergy efficiency obtained in temperature of 50˚C and velocity of 3 m s-1.

A hot air solar dryer was used for drying lemon verbena leaves. Results of specific energy consumption of drying showed a high amount of fossil fuels can be saved by using this dryer. Also, from the aspect of energy and exergy efficiency, using of the dryer in the lower temperature and higher air velocity is recommended.

Noise pollution is becoming a severe issue for the patients admitted in intensive care units (ICUs). For the reduction of noise pollution in hospitals, researchers recommend proper training and adherence to protocols. The present study aimed to assess the effect of the training of nurses on the reduction of noise pollution in ICUs. This clinical trial was conducted at Tehran University of Medical Sciences and Iran University of Medical Sciences, which were randomly selected as the intervention and control groups, respectively. Before the intervention, noise intensity was measured at four locations inside the ICUs of the selected universities (entrance and exit, nursing stations, center of the department, and patients' bedside). Afterwards, methods for the control of noise pollution were introduced to the nurses in the intervention group in the form of a training workshop. Two months after the intervention, noise intensity was measured in the selected locations in the intervention and control groups. Noise intensity was measured using a sound meter in decibels (dB), and the dB-scale sound pressure level in LA networks (corresponding to the hearing of humans) was measured every two hours for three consecutive days.  According to the results of paired t-test, the intra-group effects of training regarding the correlation of the mean and standard deviation of the sound pressure level was estimated at 55.37±5.43 and 57.79±4.96 in the intervention group before and after the intervention, respectively, which indicated a significant difference in this regard (P<0.001). In addition, comparison of the intervention and control groups using independent t-test indicated a significant difference between the groups before and after the intervention (P<0.001). Also, the result of covariance test was not significant in intervention group and control group. According to the results, the training of nurses on the control of noise pollution was effective in the reduction of this issue. Therefore, it is recommended that noise pollution in hospitals be reduced through implementing in-service training workshops for nurses, asking nurses to be quite and promote sleep, and exploit silence signs in ICUs.

Depth control autonomous underwater vehicle due to disturbances, noise and non-linear dynamics is very important and difficult in the field of systems control and for the solving it in methods that are robust to the uncertainty of the system is needed. To deal with such uncertainties and disturbances, sliding mode control has been used. Generally, The main advantage of this method is robust to uncertainties and disturbances, But due to the computational delays and restrictions on operators immediately change is not possible and leads to the phenomenon of chattering in control signal and excitation high-frequency dynamics. In this paper, depth control of an autonomous underwater vehicle is considered. To solve the problem chattering in the system under study, We tried to be used the combination of sliding mode control and artificial neural network. The use of the artificial neural network has led to the estimation of the uncertainties of the system and the chattering domain in the control signal is effectively reduced. Simulation show that the sliding mode method problems in depth control of underwater vehicle using artificial neural network capabilities has been fixed and the system properly controlled.

Climate is one of the most important environmental factors that impact human life and activities. Therefore, it is important to know about climate zones for planning and spatial development of different reigns. The main purpose of this research is zoning the temperature of Iran using fuzzy clustering. Data about mean of daily dry temperature, maximum temperature, minimum temperature, dew point temperature and wet temperature of 63 synoptic stations in Iran were collected from meteorology office during 1989 to 2013. Data were reduced in MATLAB software using SVD method and clustered using fuzzy clustering. Results indicate 6 temperature clusters in Iran. Temperature zoning of Iran is affected by the Caspian Sea, Persian Gulf, Oman Sea, Alborz and Zagros mountain ridges, and internal areas of Iran.

Scoring systems have been developed to predict outcomes in the critical patients and to facilitate the decision making and resource allocation for management of such patients.

The aim of this study was to compare Acute Physiology and Chronic Health Evaluation II (APACHE II) and Simplified Acute Physiology Score II (SAPS II) in predicting hospital mortality of intensive care unit patients.

This cross-sectional study was conducted on 88 patients admitted to the intensive care unit because of trauma or surgery in Shahid Rajaee hospital، Qazvin 2008. During the first 24 hours of admission، the results of clinical examination and biochemical assays and demographic information were collected to complete each of the scoring systems. Observed mortality and predicted mortality were recorded and compared. Detection value of scoring systems was assessed by Receiver Operating Characteristic (ROC) curves and data were analyzed using logistic regression analysis and Chi-Square test.

M ean age of patients was 44. 25 ± 23. 09 years (2 to 86 years). Observed mortality in ICU was 32. 5% and predicted mortalities were 23. 63±24. 2% and 19. 88±15. 1% according to SAPS II and APACHE II، respectively. There was positive significant correlation between SAPS II and APACHE II scoring systems and between these two scoring systems and observed mortality. There was also positive significant correlation between SAPS II and APACHE II values and GCS score. Area under the ROC curve (AUC) of APACHE II was greater than SAPS II for predicting observed mortality (0. 823 vs. 0. 790).

With regards to the results، both APACHE II and SAPS II scoring systems can be used to predict mortality of intensive care unit patients، but not to help in definite decision-making.

Agricultural engineering and technical consulting services (agricultural advisory services), have been initiated to provide, among other facilitating affairs, job opportunities for agricultural graduates; while without entrepreneurial activities and simply relying on public sector contracts many of them will not be able to be economically sustainable and preserve their members employment. So this study was conducted to evaluate the entrepreneurship development mechanisms prevalent among these firms. Using a two-stage sampling method, 102 people were selected from 500 companies’ members. Data was collected through a questionnaire the validity of which was confirmed by a panel of experts. The reliability of the main scale employed in the study was assessed through Cronbach’s Alpha equaled to 0.87. Findings revealed that the skills of: decision making, marketing, planning and predicting, as well as communication skills along with facilitating loan grants from banks were the most important variables from the viewpoint of companies’ members. Factor analysis categorized the examined variables in seven factors of: 1) managerial skills, 2) major entrepreneurial skills, 3) infrastructural, 4) business planning skills, 5) agricultural practical skills, 6) educational and finally 7) cultural factors. These factors were determinants of 73.65 percent of the variance among the solutions.