Sharif Digital Repository

In this research, we focus on r-gather and (r; ϵ)-gather clustering. In the r-gather clustering, the input points are in metric space and must be clustered such that each cluster has at least r points and the objective is to minimize the radius of clustering. (r; ϵ)-gather clustering is a kind of r-gather clustering such that at most nϵ points can be unclustered. MapReduce model is one of the most used parallel models to process huge data and processes the input data in some machine simultaneously in parallel.In this research, we give a lower bound for the approximation factor of r-gather clustering in MapReduce model. This lower bound works in MapReduce model even an optimal algorithm... 

T lymphocytes or T cells are a type of white blood cell that play an important role in the immune system. Memory T cells are a subset of them that are able to reactivate when being re-exposed to the pathogen. Because of the properties of these cells, they are an attractive choice for immunotherapy. Initial memory subgroups were shown to be more persistently effective in immunotherapies. However little is known about development and differentiation of these subgroups. With the discovery of a new subset of T cells, called T memory stem cells (TSCM), They are considered to develop through four stages, naive T cells (TN), T memory stem cells (TSCM), central memory T cells (TCM) and effector... 

The objective of this dissertation is to develop a model to monitor and project the long-term changes in meteorological drought under climate change at watershed scale. In this model, drought is defined based on joint precipitation-temperature values since negative correlation between precipitation and temperature implies that drier periods are often warmer, and therefore, the consequences of drought are more severe compared to low-precipitation periods with mild temperature. This is of particular importance considering global warming. To quantify drought, an indicator called precipitation-temperature deciles index, which is an extension of precipitation deciles index, is introduced. Copula... 

Nowadays, researchers working on classifiers which are designed to predict minority class. In this work, we attempt to improve fraud detection performance, with minimum possible complexity. In this regard, by incrementing model sensitivity to minority class samples, we solve the problem of model ignorance to these instances. Moreover, by using clustering, we cluster similar inputs based on their features, and split each class to smaller bins. Then with considering the fact that, prediction probability threshold influences the final performance, we define statistical hypothesis testing exclusively for each cluster to evaluate predictions with expected range. In this method, model is not... 

The standard model of Cosmology (ΛCDM, based on the cosmological constant and cold dark matter) is the simplest model that many of its predictions match with observations. Large scale observations are one of the most important observational data in Cosmology. This type of observation reveals that the cosmos have a web-like structure at large scales called "Cosmic web". This web consists of dense regions full of galaxies (Knot), long filamentary structures (Filament), flat sheets (Sheet), and low-density vast regions (Void). The cosmic web is the most prominent representative of the distribution of galaxies and dark matter in large scales and studying it can provide cosmologists with valuable... 

Number of smart devices is increasing due to the expanding use and vast variety of Internet of Things (IoT) applications. One of the most important challenges in IoT applications is finding the best route for information flow, among a large number of devices with different features.In 2012, the Internet Engineering Task Force (IETF) standardized and introduced the routing protocol for low-power and lossy networks (RPL). Low setup time and loop avoidance are two advantages of RPL. However, in RPL, unbalanced loads on the network causes congestion on some routes, resulting in the loss of many packets. Therefore, due to congestion in the nodes, RPL does not provide much reliability. In... 

Clustering presents valuable information in discovery of the climatic zones. To use clustering approaches, similarity measure, clustering algorithm, and clustering validity index should be determined. To find climatic zones over Middle East nad North Africa (MENA), this study performs k-means clustering with Euclidean distance as the similarity measure on four monthly precipitation datasets (CRU, GPCC, UDEL, and PREC/L) and two monthly temperature datasets (CRU, NOAA GHCN-CAMS). This study aims to validate clustering results and find a proper number of clusters. For this purpose, five traditional validity indices are examined on experimental datasets. Results show significant differences... 

The research in this study aims to analyze data in healthcare, especially the diagnosis of several diseases caused by heart failure. Analyzing and analyzing this data can lead to the discovery of relationships and patterns that can play an important role in the decision-making process of relevant officials in any field. Today, medical data around the world is stored in large volumes for future research. Various infrastructures and software have been set up in many health centers and research centers affiliated with those organizations.In this research, the general process of work is such that the data related to the heart sounds, which are in the four broad categories of S1 to S4, are... 

In recent years, the attention of marketing researchers has shifted from numerical product rating to user-generated content. Because of this, customers' online reviews now play a very important role in the destiny of Internet businesses. Today, huge and comprehensive platforms have been developed to record and analyze online customer reviews. This type of unstructured data that users and Internet shoppers create based on their experiences of using products and services, has a significant impact on gaining and losing the trust of other users. After reading each review, each user can express their opinion about the usefulness of that comment, which can be seen by others. Large Internet... 

In recent years, Internet advertising has become increasingly customized to individual users. As advertising carry on refining its capacities, it is more likely to be seen as insightful and useful by everyone. Consumers, particularly Gen Y and older members of Gen Z, are becoming more accepting of relevant advertising as digital acquaintance. Consumers now welcome active advertising that responds and reflects social activity, location, and brand and product preferences in real-time. This ability to be agile within the consumer’s connected experience is an emerging revenue driver and will continue to grow as ad platforms and ad presentations become smarter. But more personalization results in... 

Nowadays, the brain drain problem has become a challenge for countries of origin (COO) and a blessing for countries hosting student migrants. This issue has been studied in many domestic and international types of research. These studies' results can lead to the ability to identify the causes and discover methods to solve this problem. For several decades, the human capital flight has been one of the most challenging educational-economic-social problems in Iran and has grown significantly in recent years. The waste of the country's resources, the ineffectiveness of the education provided to students to improve the country's condition and its construction, the social and psychological... 

In recent decades, the science of studying complex systems has started to evolve and mature. Complex systems research is becoming ever more important in both the natural and social sciences. The study of mathematical complex system models is used for many scientific questions poorly suited to the traditional mechanistic conception provided by science. Examples of complex systems are Earth's global climate, organisms, the human brain, social organization, an ecosystem, a living cell, and ultimately the entire universe. Motivations for studying complex and self-organized systems can be somewhat divided between science, or attempts to understand such systems, and engineering, or attempts to... 

Cerebral palsy (CP) is one the most prevalent neuromusculoskeletal disease amongst children. Damage in the central nervous system (CNS) causes defective growth of the musculoskeletal system during infancy to maturity, then leading to impairment of selective motor control (SMC), spasticity and sometimes contracture of musculotendinous junction. Treatment of Cerebral Palsy is limited to reduce complications. Medical procedures such as neurosurgery and orthopaedic surgeries or rehabilitation used as a common operation. Recently studies in the field of synergy directed a new path to understanding of human motor control complexity besides identification of functionality of musculoskeletal... 

Since the start of Covid-19 pandemic lately in 2019 from Wuhan in China, a lot of countries encountered it. Healthcare sysytems are the most important system against pandemics so it is needed to measure the efficiency of healthcare systems against Covid-19 in order to find best practices. In this research, a 3-phased method is proposed to evaluate the performance of the healthcare systems. In the first phase, countries are clustered, in the second phase the DEA model is applied in 2 separate parts, in one part with considering clusters and in another without it. In the third phase resilience is introduced for Covid-19 and then it is used as a criterion beside two other criteria, DEA result... 

Today, machine learning has many applications in various industries, and healthcare is not an exception. Machine learning algorithms are used for medical diagnosis, make predictions about patients’ future health, newly-discovered treatment effect on patients prediction, drug recommendation system, build risk models and survival estimators and health risk prediction models. One of the topics that has received less attention in the world, especially in Iran, is the prediction of the surgery duration. This is very important because operating rooms in hospitals are the primary source of hospital revenue; We also need to predict the duration of surgery as accurately as possible in order to... 

Spatial transcriptomics is a new technology that, in addition to transcriptomic cell information, provides spatial information for each of the sample cells and, if possible, histological images of the cells. Despite much research on cell indexing, little research has been done on using cell spatial information to cluster cells, and existing methods can be improved. The aim of this study is to use cell spatial data to extract more information from the samples and to better identify the cell conditions in the images, leading to better clustering than current methods. In the proposed method, in order to use spatial location data and transcriptomics simultaneously, the samples are modeled using... 

We study the problem of preclustering a set B of imprecise points in Rd. we wish to cluster the regions specifying the potential locations of the points such that, no matter where the points are located within their regions, the resulting clustering approximates the optimal clustering for those locations. We consider k-median clustering, and obtain the following results.First we present a (6k, 2)-preclustering in R2. Then we present a preclusterings for balls in Rd, including a (3k, α)-preclustering with α = 13.9 for the k-median problem. At last we show that we need at least 3k − 3 preclusters to obtain a bounded approximation ratio for this problem  

Every year, a high percentage of university graduates go abroad to continue their studies. Large amount of them, especially those who graduated from better universities, do not return to Iran. the emigration of these people, who are considered to be of the best graduates in the country, and their non-return to the country leads to Decrease in the average capability of the country's human resources, waste of resources spent on them from a national perspective, Decrease in the productivity at the internal universities, industries and services and increase in the country's scientific distance from the other countries. the 1370s are an important section in the country's history due to post-war... 

The performance of the power plant decreases during its lifetime and deviates from its design and initial operation conditions; Maintenance issues, variety of operational patterns, market limitations and financial goals have been caused this situation. Knowing the appropriate actions and finding the optimal operation conditions of the power plant can support the system to restore its initial operational performance and bring it closer to its design condition. In this research, with historical data helps of a steam thermal power plant in Kermanshah, unsupervised machine learning techniques have been used to identify operational patterns, which lead to the identification of optimal operating... 

Reliability-centered maintenance (RCM) is one of the main maintenance methodologies that ensures the continuity of the organization's physical assets in order to meet the expectations of its stakeholders. Despite the widespread use of artificial intelligence in maintenance, the use of these tools to improve the RCM implementation process is a new issue. To this end, in this dissertation, using artificial intelligence and soft computing tools, an upgraded RCM system is introduced so that in addition to increasing the accuracy in the implementation of RCM processes, the time and cost required to implement these processes has reduced, and made it possible to record and store the knowledge of...