Sharif Digital Repository

The injection process on cell is a very accurate and sensitive operation. This method is used for several new invented approaches such as tracytoplasmic Cell Injection or drug delivery. Controlling the injection force in micro scale is one of the problems of mentioned operations. Current huge and expensive laboratorial devices are helping the operators to do injection operation with :nore success. In this study a simple and novel microelectromechanical (MEMS) mechanism for doing injection process automatically on the biological cells is proposed. In order to controlling this device properly, we should model and simulate the operation condition from initial position to final condition. This... 

Cardiovascular diseases are one of the major causes of mortality in humans. One way to diagnose heart diseases and abnormalities is processing of cardiac signals such as ECG.In many of these processes, inter-beat and intra-beat features of ECG signal must be extracted. These features include peak, onset and offset of ECG waves,meaningful intervals and segments that can be defined for ECG signal. ECG fiducial point (FP) extraction refers to identifying the location of the peak as well as the onset and offset of the P-wave,QRS complex and T-wave which convey clinically useful information. However, the precise segmentation of each ECG beat is a difficult task, even for experienced... 

In this thesis, an enhanced local mean-field (MF) model that is suitable for simulating the electroencephalogram (EEG) in different depths of anesthesia is presented. The main building elements of the model (e.g. excitatory and inhibitory populations) are taken from two pioneer MF models designed by Steyn-Ross et al and Bojak & Liley, and then a new slow ionic mechanism is included in the main model. Generally, in mean-field models, some sigmoid-shape functions determine firing rates of neural populations according to their mean membrane potentials. In the enhanced model, the sigmoid function corresponding to excitatory population is redefined to be also a function of the slow ionic... 

In the process of recording electrical activity of the brain, the signal of interest is usually contaminated with different activities arising from various sources of noise and artifact such as muscle activity. This renders denoising as an important preprocessing stage in some ElectroEncephaloGraphy (EEG) applications such as source localization. In this thesis, we propose six methods for noise cancelation of epileptic signals. The first two methods, which are based on Generalized EigenValue Decomposition (GEVD) and Denoising Source Separation (DSS) frameworks, are used to denoise interictal data. To extract a priori information required by GEVD and DSS, we propose a series of preprocessing... 

Text summarization and classification are two important tasks in natural language processing. Text summarization involves condensing a piece of text into its main points, making it easier to understand. On the other hand, text classification involves categorizing a text into predefined categories based on its content. Text summarization can be achieved through various methods, such as extractive summarization, where key sentences or phrases are extracted from the original text. The present research aims to classify and summarize news texts in the Persian Daily News dataset. This objective is carried out in two stages. First, the texts in this dataset are classified using the ParsBERT... 

Providing quality hospital services depends on the efficient and correct implementation of processes. Therapeutic care processes are a set of activities that are carried out with the aim of diagnosing, treating and preventing any disease in order to improve and promote the patient's health. The purpose of this study is to use process mining techniques to discover and improve healthcare processes. The case study of this research is a psychiatric hospital in Shiraz. The approach implemented in this research consists of three main stages including data pre-processing, model discovery phase, and analysis phase. Three algorithms including Heuristic Miner, Inductive Miner, and ILP Miner were used... 

At building industry and other construction industries concrete process can be named as the most important part of making structure process, it is important because concrete is responsible of bearing compressive stress at the structure, and most of concrete quality depends on the curing after concreting. Concrete operation at the structure causes using other sciences like heat transfer science to increase the concert quality. Since freezing phenomenon causes serve decrease at concrete quality and the only way is destruction and repeating concreting which is very hard and sometimes impossible and also using chemical additive to decrease freezing point decreases quality and also is... 

Supervision is considered one of the fundamental pillars in the construction of building projects within the country's engineering system. Enhancing the supervision process for construction projects can significantly improve the quality of buildings nationwide. However, in many cases, the supervision process has not effectively fulfilled its assigned responsibilities and has encountered numerous challenges. This study aims to identify and prioritize the challenges present in the operational processes of supervisors within the engineering system. The primary objective of this research is to identify and analyze these challenges and propose solutions to enhance supervisors' performance and... 

Introducing the basic concepts of solar desalination systems, improving the performance and efficiency of the solar system under vacuum has been investigated. Further, according to the classification of the types of solar desalination systems, the details of their existing designs have been discussed. The solar desalination system under vacuum is classified into two types of solar systems under natural vacuum and under forced vacuum. The solar system under natural vacuum is divided into one-story and multi-story, while the solar system under forced vacuum is classified into two types, single-effect and multi-effect. Previous studies as well as the most important recent developments in this... 

This study investigates the performance of the Reinforced Concrete column and Steel beam (RCS) structural system at the system level, with a focus on evaluating seismic design coefficients (R-factor, Ω₀, and Cd) using FEMA P-695 methodology. The RCS system provides a more efficient alternative to conventional steel and reinforced concrete moment-resisting frames, offering higher damping and lateral stiffness in RC columns along with greater energy dissipation in steel beams. Although several studies have examined the RCS system's performance, most have concentrated on the connection level. In this study, 32 archetypes are designed with variations in building heights, span lengths, concrete... 

The construction system, as a fundamental pillar of any country's development, requires meticulous oversight and the employment of qualified professionals. The introduction of qualified contractors in Iran as a measure to enhance the quality of construction projects and eliminate unqualified individuals from this field has been a valuable step. However, legal and operational shortcomings, as well as challenges in the contracts between contractors and employers, have hindered the effectiveness of this role. This study aimed to identify and prioritize the challenges in the workflows of qualified contractors and propose solutions for their improvement. Key identified challenges include... 

Concrete has always been one of the most widely used materials in the construction industry and has attracted the attention of researchers. It offers advantages such as desirable mechanical and durability properties, low cost, stability, and workability. The cement in concrete is responsible for the emission of 5-7% of carbon dioxide gas in the world. Most researchers have proposed geopolymer concrete (GPC) in order to reduce the environmental impact of concrete and have implemented structures using this type of concrete in different countries. The mechanical and durability properties of GPC have been investigated in recent years through conducting several tests. However, previous... 

In the field of cancer diagnosis, particularly brain tumors, the priority is to achieve highly accurate tumor detection. Deep learning has shown remarkable potential in object detection tasks, making it a valuable tool for identifying brain tumors. We have proposed a new method for combining the strength of Faster R-CNN in detecting objects and the ability of Vision Transformer’s (Faster-VIT) ability to extract essential features. The proposed method significantly improves the accuracy and efficiency of brain tumor detection in MRI images. We have called the proposed combination Faster-VIT. To assess the effectiveness of the proposed method, we have utilized the Br35H dataset, comprising... 

Today, reliability assessment of production systems is crucial for ensuring continuous production and minimizing operational and maintenance (O&M) costs. One way to assess reliability at the system level is to create a reliability block diagram (RBD) and estimate the failure rates of equipment over their operational periods. This approach has been utilized in this thesis, focusing on assessment of the reliability of various units within the methanol plant at Khark Petrochemical Complex. In this context, understanding the condition of the equipment criticality is essential for constructing the reliability block diagram. The Crespo model and total criticality per risk (CTR) measure have been... 

Bearings play a critical role in the functionality of rotating equipment across various industries, accounting for approximately 50% of equipment failures due to bearing malfunctions. Accurate life prediction of bearings is essential not only for preventing unexpected breakdowns and subsequent damage but also for minimizing unnecessary replacements of functional bearings, which can lead to increased operational costs. With the rise of artificial intelligence, numerous predictive models have been developed; however, many of these require extensive datasets, which are often unavailable in industrial settings. Data collection is typically irregular, based on the sensitivity of the equipment,... 

Energy efficiency in desalination systems is primarily hindered by high-energy-consuming equipment, such as compressors. This study explores a novel cycle of combined ejector desalination involving a two-phase state and a solar vacuum tube collector designed to generate saturated steam at a lower temperature. The mechanism involves water entering the ejector's primary nozzle in the liquid phase, pulling steam generated by the collector at a reduced pressure and temperature. This process facilitates the separation of desalinated water from saltwater, resulting in purified water in a variable phase. The performance of the ejector was thoroughly evaluated, including how primary and secondary... 

Dump trucks are one of the most important and valuable equipment used in mining, and the implementation of proper maintenance and monitoring programs for these machines is of special significance. The most critical part of a dump truck is its diesel engine, and the most effective method for monitoring its condition is to conduct lubricant analysis. Accuracy and speed in the lubricant analysis process significantly contribute to enhancing the efficiency of maintenance and monitoring programs for the equipment. Given the complexities of analyzing the condition of diesel engines in dump trucks due to the interactions among multiple engine parameters and various lubricant characteristics, there... 

The stock market is vital to the economy as it serves as a key indicator of economic health. AI algorithms can process vast amounts of market data at high speeds, identifying patterns and trends that are often invisible to human analysts. Forecasting future stock trends poses significant challenges due to the complex inter-stock and intra-stock dynamics that influence stock prices. Recently, graph neural networks have shown promising results by modeling multiple stocks as graph-structured data. However, many of these approaches depend on manually defined factors to construct static stock graphs, which fail to capture the rapidly changing interdependencies between stocks. In this work,... 

Focusing on developing the EEPS (Energy Electric and Power System) based on the SG (Smart Grid) infrastructure to achieve implementation of EI (Energy Internet) ultimately, in order to analyze and manage the energy/power consumption, requires a robust embedded EMS (Energy Management System) to implement real-time LF (Load Forecasting), prevent the power waste and realize consumption management which eventually leads toward the smart industries/buildings. STLF (Short Term Load Forecasting) is an essential component that an industrial plant requires to manage the power, regarding the load fluctuations during production, and compulsory requirement of cost mitigation. This thesis, in order to... 

Thermosyphon heat pipes are vacuum-sealed two-phase heat transfer devices, commonly called vertical or inclined heat pipes without wicks under the influence of gravity. They comprise a sealed, evacuated tube partially filled with a working fluid. The lower section of the tube serves as the evaporator, where heat input causes the liquid to vaporize. This vapor moves upward to the condenser, where it releases heat and condenses back into liquid form, and the condensed liquid returns to the evaporator by gravity. The adiabatic section, which is located between the evaporator and condenser, is well insulated to allow the vapor to pass through with minimal heat loss. These systems utilize the...