Organization of Multi-Agent Systems: An Overview

In complex, open, and heterogeneous environments, agents must be able to reorganize towards the most appropriate organizations to adapt unpredictable environment changes within Multi-Agent Systems (MAS). Types of reorganization can be seen from two different levels. The individual agents level (micro-level) in which an agent changes its behaviors and interactions with other agents to adapt its local environment. And the organizational level (macro-level) in which the whole system changes it structure by adding or removing agents. This chapter is dedicated to overview different aspects of what is called MAS Organization including its motivations, paradigms, models, and techniques adopted for statically or dynamically organizing agents in MAS.Comment: 12 page

The Effect of Emotional Intelligence on Organization Performance Using the Big Five Personality Traits”: An Applied Study on Higher Education Institutions

Purpose: The purpose of this paper is to investigate to what extent emotional intelligence (EI) affects organization performance through the Big Five personality traits (BFPT) in higher education institutions. Design/Methodology: Based on the Structural Equation Model, this study examines 270 faculty members within a higher education institution, to test an estimated model presenting the effect of top management EI on organization performance in the presence of the BFPT. The hypothesized model indicates that there is no significance for the presence of the one of the dimensions of EI domain as an independent variable. Thus, this dimension is deleted and another hypothesized model is re-estimated. Results/Findings: The findings revealed that EI would strongly predict organization performance through the BFPT. Specifically, only three out of four dimensions of EI would predict organization performance through only three effective dimensions out of five of the BFPT. Theoretical and practical implications: The findings enable a better theoretical understanding of how BFPT mediates the effects of EI on organization performance. Furthermore, the implications from this study allows human resources professionals to improve investigating personalities of potential management before hiring, as well as training and developing current management, as stable management personalities within any organization are vital to achieve high performance. Keywords: Emotional intelligence, Big Five Personality traits, and organization performance. DOI: 10.7176/JAAS/76-06 Publication date:October 31st 2021

The development of local solar irradiance for outdoor computer graphics rendering

Atmospheric effects are approximated by solving the light transfer equation, LTE, of a given viewing path. The resulting accumulated spectral energy (its visible band) arriving at the observer’s eyes, defines the colour of the object currently on the line of sight. Due to the convenience of using a single rendering equation to solve the LTE for daylight sky and distant objects (aerial perspective), recent methods had opt for a similar kind of approach. Alas, the burden that the real-time calculation brings to the foil had forced these methods to make simplifications that were not in line with the actual world observation. Consequently, the results of these methods are laden with visual-errors. The two most common simplifications made were: i) assuming the atmosphere as a full-scattering medium only and ii) assuming a single density atmosphere profile. This research explored the possibility of replacing the real-time calculation involved in solving the LTE with an analytical-based approach. Hence, the two simplifications made by the previous real-time methods can be avoided. The model was implemented on top of a flight simulator prototype system since the requirements of such system match the objectives of this study. Results were verified against the actual images of the daylight skies. Comparison was also made with the previous methods’ results to showcase the proposed model strengths and advantages over its peers

A robust CNN Model for Diagnosis of COVID-19 based on CT scan images and DL techniques

The 2019 Coronavirus (COVID-19) virus has caused damage on people\u27s respiratory systems over the world.  Computed Tomography (CT) is a faster complement for RT-PCR during peak virus spread times. Nowadays, Deep Learning (DL) with CT provides more robust and reliable methods for classifying patterns in medical pictures. In this paper, we proposed a simple low training proposed customized Convolutional Neural Networks (CNN) customized model based on CNN architecture that layers which are optionals may be included such as the layer of batch normalization to reduce time taken for training and a layer with a dropout to deal with overfitting. We employed a huge dataset of chest CT slices images from diverse sources COVIDx-CT, which consists of a 16,146-image dataset with 810 patients of various nationalities. The proposed customized model\u27s classification results compared to the VGG-16, Alex Net, and ResNet50 Deep Learning models. The proposed CNN model shows robustness by achieving an overall accuracy of 93% compared to 88%, 89%, and 95% for the VGG-16, Alex Net, and ResNet50 DL models for the classification of 3 classes. When this relates to binary classification, the classification accuracy of the proposed model and the VGG-16 models were identical (almost 100% accurate), with 0.17% of misclassification in the class of Non-Covid-19, the Alex Net model achieved almost 100% classification accuracy with 0.33% misclassification in the class of Non-Covid-19. Finally, ResNet50 achieved 95% classification accuracy with 5% misclassification in the Non-Covid-19 class.

A robust CNN Model for Diagnosis of COVID-19 based on CT scan images and DL techniques

The 2019 Coronavirus (COVID-19) virus has caused damage on people's respiratory systems over the world.  Computed Tomography (CT) is a faster complement for RT-PCR during peak virus spread times. Nowadays, Deep Learning (DL) with CT provides more robust and reliable methods for classifying patterns in medical pictures. In this paper, we proposed a simple low training proposed customized Convolutional Neural Networks (CNN) customized model based on CNN architecture that layers which are optionals may be included such as the layer of batch normalization to reduce time taken for training and a layer with a dropout to deal with overfitting. We employed a huge dataset of chest CT slices images from diverse sources COVIDx-CT, which consists of a 16,146-image dataset with 810 patients of various nationalities. The proposed customized model's classification results compared to the VGG-16, Alex Net, and ResNet50 Deep Learning models. The proposed CNN model shows robustness by achieving an overall accuracy of 93% compared to 88%, 89%, and 95% for the VGG-16, Alex Net, and ResNet50 DL models for the classification of 3 classes. When this relates to binary classification, the classification accuracy of the proposed model and the VGG-16 models were identical (almost 100% accurate), with 0.17% of misclassification in the class of Non-Covid-19, the Alex Net model achieved almost 100% classification accuracy with 0.33% misclassification in the class of Non-Covid-19. Finally, ResNet50 achieved 95% classification accuracy with 5% misclassification in the Non-Covid-19 class.

Diffusion-weighted images and its application in the clinical diagnostic testing of endometrial focal lesions

Background: Numerous endometrial disorders can create several difficulties for the radiologist due to the overlapping of imaging characteristics and diverse endometrial pathologies. The most frequently utilized imaging tool for diagnosing and characterizing endometrial focal lesions is magnetic resonance imaging (MRI) with diffusion weighted images (DWI).Objective: We conducted this study to determine the efficacy of MRI with DWI in improving the diagnostic accuracy of endometrial focal lesions, especially in the differential diagnosis of benign and malignant focal endometrial masses.Patients and Methods: This study recruited 36 women (21 postmenopausal and 15 premenopausal) who experienced vaginal bleeding and had endometrial thickness and focal endometrial lesions with a distinct echo pattern on ultrasound (US) examination. The age of patients was between 27 to 85 years, with an average of 45.2 years. Ethics Committee approval was obtained in addition to written informed consent from all included patients.Results: The 36 patients included in this study, were classified according to their lesions histopathological results; Benign group (15 lesions; 41.67%) and malignant group (21 lesions; 58.33%). The most common benign lesion was endometrial polyp (9/15) while the most common malignant lesion was endometrial carcinoma (21/21). In the current study MRI with diffusion could correctly diagnose 33 lesions out of 36 lesions, achieving (91.6%) sensitivity, (100%) specificity, (100%) positive predictive value (PPV), (95.6%) negative predictive value (NPV) and accuracy (97.05 %).Conclusion: Integrating DWI and ADC mapping at a high b value in pelvic MRI examination improves the sensitivity, specificity, and precision of diagnosing endometrial focal lesions

Studying the Effect of Potassium Amyl Xanthate Surfactant on Fe, Cu and U Ions for the Pretreatment of Abu Zeneima Sulphate Leach Liquor

In this study, batch experiments were performed to study the behavior of potassium amyl xanthate surfactant on Fe, Cu and U ions for the pretreatment of Abu Zeneima sulphate leach liquor. Various parameters, such as amount of potassium amyl xanthate, pH, stirring time, sample volume to potassium amyl xanthate mass (v/m ratio) and temperature were tested to determine the optimum conditions. The numerical results obtained support the experimental data on decreasing the iron and copper values where 0.1 g potassium amyl xanthate could remove 86.8 mg Fe and 0.98 mg Cu from the studied sulphate solution with no effect on uranium content. FTIR spectroscopy and XRF analysis were used for investigation

Utility of Tissue Inhibitor Metalloproteinase-1 and Osteopontin as Prospective Biomarkers of Early Cardiovascular Complications in Type 2 Diabetes

AIM: This work investigated associations between tissue inhibitor metalloproteinase-1 and diabetic cardiovascular diseases in type 2 diabetic patients; also it investigated the role of osteopontin in the diagnosis of type 2 cardiovascular diabetes complications.SUBJECTS AND METHODS: These were examined on eighty subjects, divided into three groups as follows: twenty volunteer healthy control subjects, thirty type 2 diabetes mellitus (DM) patients, and thirty cardiovascular, diabetic patients. Full clinical measurements were carried out, and the expression level of tissue inhibitor metalloproteinase-1 in blood samples was analysed by real-time PCR, using gene-specific primer pairs. Also osteopontin concentrations had been measured by the enzyme-linked immunosorbent assay. Data were tested statistically by parametric tests.RESULTS: The concentrations of osteopontin and the expression levels of tissue inhibitor metalloproteinase-1 were significantly increased in diabetic and cardiovascular diabetic groups compared to control group also they were significantly increased in the cardiovascular diabetic group compared to the diabetic group.CONCLUSION: Tissue inhibitor metalloproteinase-1 and osteopontin concentrations were significantly increased in diabetic patients with cardiovascular complications than other groups

The role of liver in leptin metabolism in experimental nephrotic syndrome

Leptin is a hormone influencing food intake, energy expenditure and body weight. It is pro-duced by adipocytes, exerts its effects on brain, endocrine pancreas and other organs by acti-vating trans-membrane receptors and is cleared from plasma mainly by the kidneys. Several studies have suggested that leptin's effects on metabolism are mediated by the liver. Our aim was to evaluate the role of the liver in the metabolism of leptin by comparing the serum leptin level in the portal vein with that in inferior vena cava and to study the relationship between leptin and lipoprotein levels in healthy and nephrotic rats. Experimental nephrotic syndrome was conducted in rats by intraperitoneal injection of the supernatant from the kidney suspen-sion obtained by previous unilateral nephrectomy of the same rat and complete Freund's adju-vant. There was a highly significant rise in leptin and lipid profile levels in the nephrotic rats compared with the normal rats. A highly significant increase in leptin in the inferior vena cava was detected compared with the level in the portal veins of nephrotic rats, while insignificant difference was observed in normal rats. This work has stressed the role of liver in leptin and lipid metabolism in nephrotic rats

Validity of sphenoid ostium in relation to posterior wall of maxillary sinus by computed tomography

Background: Sphenoid sinus is the most inaccessible paranasal sinus, enclosed within the sphenoid bone and intimately related to numerous vital neural and vascular structures. Anatomic variation of the sphenoid sinus is well documented and may complicate surgery in such a place.Objective: To assess the reliability of preoperative computed tomography (CT) in determination of the distance between the posterior wall of maxillary sinus (PWMS) and the sphenoid sinus ostium (SSO) in the coronal plane.Patients and methods: This was a prospective study of the distance between the SSO and the PWMS in the coronal plane, which was measured both radiologically in preoperative CT and intraoperatively during endoscopic sinus surgery for patients in need for middle meatal antrostomy and sphenoid sinusotomy at the same side. Distances obtained by both techniques have been tested for the degree of correlation. Number of the included patients was 25.Results: Forty four nasal sides were included in the study. The mean distance between the sphenoid sinus ostium and posterior wall of maxillary sinus in the coronal plane was 6.6 ± 1.8 mm when measured by preoperative CT and 6.9 ± 1.9 mm when measured directly during surgery. No significant difference was found between the mean distances measured by both techniques (p = 0.246) with good agreement between them (r = 0.864).Conclusion: Preoperative CT may be a reliable tool to preoperatively determine the difference in depth between the PWMS and the SSO