The liberal international order, the liberal peace-building mission and the role of American Exceptionalism in it

Senior Project submitted to The Division of Social Studies of Bard College

THE EFFECT OF EXTERNAL FACTORS ON PROFITABILITY OF ACCEPTED BANKS IN TEHRAN STOCK EXCHANGE

The growth and decline or economic downturn of countries is closely linked to the workings of banking institutions. The banking system offers services without which the economic system of the country remains open. The purpose of this study was to investigate the effect of internal factors on profitability of accepted banks in Tehran Stock Exchange. To describe the research method, Mark, Philip, and Adrian (2009) used the onion model for the research process. This model has 8 layers, and the present study based on the lines of the paradigm were categorized of research on affirmation, the main type of applied research, the method of analytic-hypothesis research, quantitative research strategy, field research, the choice of research method in correlation and time series, the research objectives were descriptive and, finally, the methods and procedures for collecting data of reviewing library resources and financial ratios. The statistical population of this study was equivalent to the total accepted banks in Tehran Stock Exchange. All statistical analyzes were performed at the error level of 5% with the help of Excel 2016 and version 10 of Eviews software. The results of this study revealed that credit risk factors have a linear and significant correlation with profitability (return on equity and equity ratio), stock market indices and profitability (return on assets and equity ratio). JEL: G21, G24, G20  Article visualizations

Flight parameters monitoring system for tracking structural integrity of rotary-wing aircraft

Recent developments in advanced monitoring systems used in conjunction with tracking structural integrity of rotary-wing aircraft are explained. The paper describes: (1) an overview of rotary-wing aircraft flight parameters that are critical to the aircraft loading conditions and each parameter's specific requirements in terms of data collection and processing; (2) description of the monitoring system and its functions used in a survey of rotary-wing aircraft; and (3) description of the method of analysis used for the data. The paper presents a newly-developed method in compiling flight data. The method utilizes the maneuver sequence of events in several pre-identified flight conditions to describe various flight parameters at three specific weight ranges

HistoSegCap: Capsules for Weakly-Supervised Semantic Segmentation of Histological Tissue Type in Whole Slide Images

Digital pathology involves converting physical tissue slides into high-resolution Whole Slide Images (WSIs), which pathologists analyze for disease-affected tissues. However, large histology slides with numerous microscopic fields pose challenges for visual search. To aid pathologists, Computer Aided Diagnosis (CAD) systems offer visual assistance in efficiently examining WSIs and identifying diagnostically relevant regions. This paper presents a novel histopathological image analysis method employing Weakly Supervised Semantic Segmentation (WSSS) based on Capsule Networks, the first such application. The proposed model is evaluated using the Atlas of Digital Pathology (ADP) dataset and its performance is compared with other histopathological semantic segmentation methodologies. The findings underscore the potential of Capsule Networks in enhancing the precision and efficiency of histopathological image analysis. Experimental results show that the proposed model outperforms traditional methods in terms of accuracy and the mean Intersection-over-Union (mIoU) metric

An Investigation of Geographical Spread of Iranian Cities Based on Altitude

The spread of Iranian cities is manifested in different geographical directions including regional, bio-environmental features and many other factors. The purpose of the present study is to investigate and analyze the spread of Iranian cities based on the altitude from the sea level. The method of this research is analytical-descriptive. To analyze the data, the researchers have used the Zapf's most famous formula. Based on this formula, all the Iranian cities were divided into 11 categories in which the lowest category was 26 and the highest was 2790 from the sea level. Generally, the obtained results showed that that the spread of Iranian cities due to good weather condition and altitude from sea level was the most with the number of 227 or 19.30% and the least number of cities was at the altitude of 2536 with only 8 cities

An Investigation of Geographical Spread of Iranian Cities Based on Altitude

The spread of Iranian cities is manifested in different geographical directions including regional, bio-environmental features and many other factors. The purpose of the present study is to investigate and analyze the spread of Iranian cities based on the altitude from the sea level. The method of this research is analytical-descriptive. To analyze the data, the researchers have used the Zapf's most famous formula. Based on this formula, all the Iranian cities were divided into 11 categories in which the lowest category was 26 and the highest was 2790 from the sea level. Generally, the obtained results showed that that the spread of Iranian cities due to good weather condition and altitude from sea level was the most with the number of 227 or 19.30% and the least number of cities was at the altitude of 2536 with only 8 cities

An Investigation of Geographical Spread of Iranian Cities Based on Altitude

The spread of Iranian cities is manifested in different geographical directions including regional, bio-environmental features and many other factors. The purpose of the present study is to investigate and analyze the spread of Iranian cities based on the altitude from the sea level. The method of this research is analytical-descriptive. To analyze the data, the researchers have used the Zapf's most famous formula. Based on this formula, all the Iranian cities were divided into 11 categories in which the lowest category was 26 and the highest was 2790 from the sea level. Generally, the obtained results showed that that the spread of Iranian cities due to good weather condition and altitude from sea level was the most with the number of 227 or 19.30% and the least number of cities was at the altitude of 2536 with only 8 cities

FedD2S: Personalized Data-Free Federated Knowledge Distillation

This paper addresses the challenge of mitigating data heterogeneity among clients within a Federated Learning (FL) framework. The model-drift issue, arising from the noniid nature of client data, often results in suboptimal personalization of a global model compared to locally trained models for each client. To tackle this challenge, we propose a novel approach named FedD2S for Personalized Federated Learning (pFL), leveraging knowledge distillation. FedD2S incorporates a deep-to-shallow layer-dropping mechanism in the data-free knowledge distillation process to enhance local model personalization. Through extensive simulations on diverse image datasets-FEMNIST, CIFAR10, CINIC0, and CIFAR100-we compare FedD2S with state-of-the-art FL baselines. The proposed approach demonstrates superior performance, characterized by accelerated convergence and improved fairness among clients. The introduced layer-dropping technique effectively captures personalized knowledge, resulting in enhanced performance compared to alternative FL models. Moreover, we investigate the impact of key hyperparameters, such as the participation ratio and layer-dropping rate, providing valuable insights into the optimal configuration for FedD2S. The findings demonstrate the efficacy of adaptive layer-dropping in the knowledge distillation process to achieve enhanced personalization and performance across diverse datasets and tasks

ViT-CAT: Parallel Vision Transformers with Cross Attention Fusion for Popularity Prediction in MEC Networks

Mobile Edge Caching (MEC) is a revolutionary technology for the Sixth Generation (6G) of wireless networks with the promise to significantly reduce users' latency via offering storage capacities at the edge of the network. The efficiency of the MEC network, however, critically depends on its ability to dynamically predict/update the storage of caching nodes with the top-K popular contents. Conventional statistical caching schemes are not robust to the time-variant nature of the underlying pattern of content requests, resulting in a surge of interest in using Deep Neural Networks (DNNs) for time-series popularity prediction in MEC networks. However, existing DNN models within the context of MEC fail to simultaneously capture both temporal correlations of historical request patterns and the dependencies between multiple contents. This necessitates an urgent quest to develop and design a new and innovative popularity prediction architecture to tackle this critical challenge. The paper addresses this gap by proposing a novel hybrid caching framework based on the attention mechanism. Referred to as the parallel Vision Transformers with Cross Attention (ViT-CAT) Fusion, the proposed architecture consists of two parallel ViT networks, one for collecting temporal correlation, and the other for capturing dependencies between different contents. Followed by a Cross Attention (CA) module as the Fusion Center (FC), the proposed ViT-CAT is capable of learning the mutual information between temporal and spatial correlations, as well, resulting in improving the classification accuracy, and decreasing the model's complexity about 8 times. Based on the simulation results, the proposed ViT-CAT architecture outperforms its counterparts across the classification accuracy, complexity, and cache-hit ratio