Search results for: aerial imaging and detection

Authors: Wangxu Xia

Abstract:

BACKGROUND BI-RADS 4 lesions raise the possibility of malignancy that warrant further clinical and radiologic work-up. This study aimed to evaluate the predictive performance of diffusion-weighted imaging(DWI) and microcalcifications on mammography for predicting malignancy of BI-RADS 4 lesions. In addition, the predictive performance of DWI combined with microcalcifications was alsocompared with the Kaiser score. METHODS During January 2021 and June 2023, 144 patients with 178 BI-RADS 4 lesions underwent conventional MRI, DWI, and mammography were included. The lesions were dichotomized intobenign or malignant according to the pathological results from core needle biopsy or surgical mastectomy. DWI was performed with a b value of 0 and 800s/mm2 and analyzed using theapparent diffusion coefficient, and a Kaiser score > 4 was considered to suggest malignancy. Thediagnostic performances for various diagnostic tests were evaluated with the receiver-operatingcharacteristic (ROC) curve. RESULTS The area under the curve (AUC) for DWI was significantly higher than that of the of mammography (0.86 vs 0.71, P<0.001), but was comparable with that of the Kaiser score (0.86 vs 0.84, P=0.58). However, the AUC for DWI combined with mammography was significantly highthan that of the Kaiser score (0.93 vs 0.84, P=0.007). The sensitivity for discriminating malignant from benign BI-RADS 4 lesions was highest at 89% for Kaiser score, but the highest specificity of 83% can be achieved with DWI combined with mammography. CONCLUSION DWI combined with microcalcifications on mammography could discriminate malignant BI-RADS4 lesions from benign ones with a high AUC and specificity. However, Kaiser score had a better sensitivity for discrimination.

Keywords: MRI, DWI, mammography, breast disease

Procedia PDF Downloads 59

Authors: Mohammed Alenezy

Abstract:

The function of cardiac motion can be used as an indicator of the heart abnormality by evaluating longitudinal, circumferential, and Radial Strain of the left ventricle. In this paper, the Radial Strain and SR is studied using tagged MRI (tMRI) data during the cardiac cycle on the mid-ventricle level of the left ventricle. Materials and methods: The short-axis view of the left ventricle of five healthy human (three males and two females) and four healthy male rats were imaged using tagged magnetic resonance imaging (tMRI) technique covering the whole cardiac cycle on the mid-ventricle level. Images were processed using Image J software to calculate the left ventricle wall Radial Strain and radial SR. The left ventricle Radial Strain and radial SR were calculated at the mid-ventricular level during the cardiac cycle. The peak Radial Strain for the human and rat heart was 40.7±1.44, and 46.8±0.68 respectively, and it occurs at 40% of the cardiac cycle for both human and rat heart. The peak diastolic and systolic radial SR for human heart was -1.78 s-1 ± 0.02 s-1 and 1.10±0.08 s-1 respectively, while for rat heart it was -5.16± 0.23s-1 and 4.25±0.02 s-1 respectively. Conclusion: This results show the ability of the tMRI data to characterize the cardiac motion during the cardiac cycle including diastolic and systolic phases which can be used as an indicator of the cardiac dysfunction by estimating the left ventricle Radial Strain and radial SR at different locations of the cardiac tissue. This study approves the validity of the tagged MRI data to describe accurately the cardiac radial motion.

Keywords: left ventricle, radial strain, tagged MRI, cardiac cycle

Procedia PDF Downloads 483

Authors: Sandip Suman

Abstract:

Mechanical defects (cracks, voids, irregularities) in rocket motor propellant are not new and it is induced due to various reasons, which could be an improper manufacturing process, lot-to-lot variation in chemicals or just the natural aging of the products. These defects are normally identified during the examination of radiographic films by quality inspectors. However, a lot of times, these defects are under or over-classified by human inspectors, which leads to unpredictable performance during lot acceptance tests and significant economic loss. The human eye can only visualize larger cracks and defects in the radiographs, and it is almost impossible to visualize every small defect through the human eye. A different artificial intelligence-based machine vision methodology has been proposed in this work to identify and classify the structural defects in the radiographic films of rocket motors with solid propellant. The proposed methodology can extract the features of defects, characterize them, and make intelligent decisions for acceptance or rejection as per the customer requirements. This will automatize the defect detection process during manufacturing with human-like intelligence. It will also significantly reduce production downtime and help to restore processes in the least possible time. The proposed methodology is highly scalable and can easily be transferred to various products and processes.

Keywords: artificial intelligence, machine vision, defect detection, rocket motor propellant grains

Procedia PDF Downloads 98

Authors: Fares Senouci, Bachir Imine

Abstract:

This document provides numerical and experimental optimization of the aerodynamic performance of a drone equipped with three types of horizontal stabilizer. To build this optimal configuration, an experimental and numerical study was conducted on three parameters: the geometry of the stabilizer (horizontal form or reverse V form), the position of the horizontal stabilizer (up or down), and the landing gear position (closed or open). The results show that up-stabilizer position with respect to the horizontal plane of the fuselage provides better aerodynamic performance, and that the landing gear increases the lift in the zone of stability, that is to say where the flow is not separated.

Keywords: aerodynamics, drag, lift, turbulence model, wind tunnel

Procedia PDF Downloads 252

Authors: Najmeh Abedzadeh, Matthew Jacobs

Abstract:

An intrusion detection system (IDS) is a software application that monitors malicious activities and generates alerts if any are detected. However, most network activities in IDS datasets are normal, and the relatively few numbers of attacks make the available data imbalanced. Consequently, cyber-attacks can hide inside a large number of normal activities, and machine learning algorithms have difficulty learning and classifying the data correctly. In this paper, a comprehensive literature review is conducted on different types of algorithms for both implementing the IDS and methods in correcting the imbalanced IDS dataset. The most famous algorithms are machine learning (ML), deep learning (DL), synthetic minority over-sampling technique (SMOTE), and reinforcement learning (RL). Most of the research use the CSE-CIC-IDS2017, CSE-CIC-IDS2018, and NSL-KDD datasets for evaluating their algorithms.

Keywords: IDS, imbalanced datasets, sampling algorithms, big data

Procedia PDF Downloads 328

Authors: Sai S. Hari, Shriram Ramanujam, Unnati Trivedi

Abstract:

The advent of mass transit systems like rail, metro, maglev, and various other rail based transport has pacified the requirement of public transport for the masses to a great extent. However, the abatement of the demand does not necessarily mean it is managed efficiently, eloquently or in an encapsulating manner. The primary problem identified that the one this paper seeks to solve is the dipsomaniac like manner in which the compartments are occupied. This problem is solved by using a comparison of an empty train and an occupied one. The pixel data of an occupied train is compared to the pixel data of an empty train. This is done using canny edge detection technique. After the comparison it intimates the passengers at the consecutive stops which compartments are not occupied or have low occupancy. Thus, redirecting them and preventing overcrowding.

Keywords: canny edge detection, comparison, encapsulation, redirection

Procedia PDF Downloads 333

Authors: Adisu Mengesha Assefa

Abstract:

The field of cardiovascular care is being transformed by the incorporation of Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), collectively known as Extended Reality (XR), into medical education, procedural planning, and patient care. This review examines the state-of-the-art applications of XR in cardiology, emphasizing its role in enhancing the precision of interventional procedures and understanding complex anatomical structures. XR technologies complement conventional imaging methods by enabling immersive three-dimensional interaction that facilitates both preoperative planning and intraoperative guidance. Despite these promising developments, challenges such as harmonizing data, integrating various imaging systems, and addressing the prevalence of cybersickness remain. Ethical considerations, including maintaining physician focus and ensuring patient safety, are crucial when implementing XR in clinical settings. This review summarizes the existing literature and highlights the need for more rigorous future studies to validate therapeutic benefits and ensure safe application. By examining both the potential and the challenges, this paper aims to delineate the current and future roles of XR in cardiovascular care, emphasizing the necessity for continued innovation and ethical oversight to improve patient outcomes.

Keywords: virtual reality, augmented reality, mixed reality, cardiovascular care, education, preprocedural planning, intraoperative guidance, postoperative patient rehabilitation

Procedia PDF Downloads 37

Authors: Ankit Shai

Abstract:

CRC or Cyclic Redundancy Check is one of the most common, and one of the most powerful error-detecting codes implemented on modern computers. Most of the modern communication protocols use some error detection algorithms in digital networks and storage devices to detect accidental changes to raw data between transmission and reception. Cyclic Redundancy Check, or CRC, is the most popular one among these error detection codes. CRC properties are defined by the generator polynomial length and coefficients. The aim of this project is to implement an efficient FPGA based CRC-8 that accepts a 32 bit input, taking into consideration optimal chip area and high performance, using VHDL. The proposed architecture is implemented on Xilinx ISE Simulator. It is designed while keeping in mind the hardware design, complexity and cost factor.

Keywords: cyclic redundancy checker, CRC-8, 32-bit input, FPGA, VHDL, ModelSim, Xilinx

Procedia PDF Downloads 292

Authors: Aragorn Joaquin Pineda Dela Cruz

Abstract:

Road traffic congestion is continually deteriorating in Hong Kong. The largest contributing factor is the increase in vehicle fleet size, resulting in higher competition over the utilisation of road space. This study proposes a project that can process closed-circuit television images and videos to provide real-time traffic detection and prediction capabilities. Specifically, a deep-learning model involving computer vision techniques for video and image-based vehicle counting, then a separate model to detect and predict traffic congestion levels based on said data. State-of-the-art object detection models such as You Only Look Once and Faster Region-based Convolutional Neural Networks are tested and compared on closed-circuit television data from various major roads in Hong Kong. It is then used for training in long short-term memory networks to be able to predict traffic conditions in the near future, in an effort to provide more precise and quicker overviews of current and future traffic conditions relative to current solutions such as navigation apps.

Keywords: intelligent transportation system, vehicle detection, traffic analysis, deep learning, machine learning, computer vision, traffic prediction

Procedia PDF Downloads 102

Authors: C. Fernanda da S. Sampaio, M. Gabriela Sadith Perez Paredes, V. Antonio de O. Martins

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Today the transport sector is undergoing a revolution, with the rise of Advanced Driver Assistance Systems (ADAS), industry and society itself will undergo a major transformation. However, the technological development of these applications is a challenge that requires new techniques and great machine learning and artificial intelligence. The study proposes to develop a vehicular perception system called Veibra, which consists of two front cameras for day/night viewing and an embedded device capable of working with Yolov2 image processing algorithms with low computational cost. The strategic version for the market is to assist the driver on the road with the detection of day/night objects, such as road signs, pedestrians, and animals that will be viewed through the screen of the phone or tablet through an application. The system has the ability to perform real-time driver detection and recognition to identify muscle movements and pupils to determine if the driver is tired or inattentive, analyzing the student's characteristic change and following the subtle movements of the whole face and issuing alerts through beta waves to ensure the concentration and attention of the driver. The system will also be able to perform tracking and monitoring through GSM (Global System for Mobile Communications) technology and the cameras installed in the vehicle.

Keywords: advanced driver assistance systems, tracking, traffic signal detection, vehicle perception system

Procedia PDF Downloads 155

Authors: Shahzamani Kiana, Esmaeil Lashgarian Hamed, Merat Shahin

Abstract:

HCV and GBV-C belong to the Flaviviridae family of viruses and GBV-C is the closest virus to HCV genetically. Accumulative research is in progress all over the world to clarify clinical aspects of GBV-C. Possibility of interaction between HCV and GBV-C and also its consequence with other liver diseases are the most important clinical aspects which encourage researchers to develop a technique for simultaneous detection of these viruses. In this study a SYBR Green multiplex real time RT-PCR technique as a new economical and sensitive method was optimized for simultaneous detection of HCV/GBV-C in HCV positive plasma samples. After designing and selection of two pairs of specific primers for HCV and GBV-C, SYBR Green Real time RT-PCR technique optimization was performed separately for each virus. Establishment of multiplex PCR was the next step. Finally our technique was performed on positive and negative plasma samples. 89 cirrhotic HCV positive plasma samples (29 of genotype 3 a and 27 of genotype 1a) were collected from patients before receiving treatment. 14% of genotype 3a and 17.1% of genotype 1a showed HCV/GBV-C co-infection. As a result, 13.48% of 89 samples had HCV/GBV-C co-infection that was compatible with other results from all over the world. Data showed no apparent influence of HGV co-infection on the either clinical or virological aspect of HCV infection. Furthermore, with application of multiplex Real time RT-PCR technique, more time and cost could be saved in clinical-research settings.

Keywords: HCV, GBV-C, cirrhotic patients, multiplex real time RT- PCR

Procedia PDF Downloads 295

Authors: Mohamed Ahmed Madkour, Haitham Magdy Hamad

Abstract:

This research aims to study of the surgery science and imaging in ancient Egypt, and how to diagnose the surgical cases, whether due to injuries or disease that requires surgical intervention, Medical diagnosis and how to treat it. The ancient Egyptian physician tried to change over from magic and theological thinking to become a stand-alone experimental science, they were able to distinguish between diseases and they divide them into internal and external diseases even this division exists to date in modern medicine. There is no evidence to recognize the amount of human knowledge in the prehistoric knowledge of medicine and surgery except skeleton. It is not far from the human being in those times familiar with some means of treatment, Surgery in the Stone age was rudimentary, Flint stone was used after trimming in a certain way as a lancet to slit and open the skin. Wooden tree branches were used to make splints to treat bone fractures. Surgery developed further when copper was discovered, it led to the advancement of Egyptian civilization, then modern and advanced tools appeared in the operating theater like a knife or a scalpel. The climate and environmental conditions have preserved medical papyri and human remains that have confirmed their knowledge of surgical methods including sedation. The ancient Egyptians reached a great importance in surgery, evidenced by the scenes that depict the pathological image and the surgical process, but the image alone is not sufficient to prove the pathology, its presence in ancient Egypt and its treatment method. As there are a number of medical papyri, especially Edwin Smith and Ebris, which prove the ancient Egyptian surgeon's knowledge of the pathological condition that It requires a surgical intervention, otherwise its diagnosis and the method of treatment will not be described with such accuracy through these texts. Some surgeries are described in the department of surgery at Ebris papyrus. The level of surgery in ancient Egypt was high, and they performed surgery such as hernias and Aneurysm, however we have not received a lengthy explanation of the various surgeries and the surgeon has usually only said “treated surgically”. It is evident in the Ebris papyrus that they used sharp surgical tools and cautery in operations where bleeding is expected, such as hernias, arterial sacs and tumors.

Keywords: ancient Egypt, archaeology, Egyptian history, ancient asurgical imaging, Egyptian civilization, civilization

Procedia PDF Downloads 82

Authors: Natalia Efremova, Sergey Tarasenko

Abstract:

We propose a novel neural network architecture for visual saliency detections, which utilizes neuro physiologically plausible mechanisms for extraction of salient regions. The model has been significantly inspired by recent findings from neuro physiology and aimed to simulate the bottom-up processes of human selective attention. Two types of features were analyzed: color and direction of maximum variance. The mechanism we employ for processing those features is PCA, implemented by means of normalized Hebbian learning and the waves of spikes. To evaluate performance of our model we have conducted psychological experiment. Comparison of simulation results with those of experiment indicates good performance of our model.

Keywords: neural network models, visual saliency detection, normalized Hebbian learning, Oja's rule, psychological experiment

Procedia PDF Downloads 348

Authors: Sayed Maeen Badshah, Kuen-Song Lin, Abrar Hussain, Jamshid Hussain

Abstract:

Liver cancer is a significant global health issue, ranking fifth in incidence and second in mortality. Effective therapeutic strategies are urgently needed to combat this disease, particularly in regions with high prevalence. This study focuses on developing and characterizing fluorescent organometallic frameworks as distinct drug delivery carriers with potential applications in both the treatment and biological imaging of liver cancer. This work introduces two distinct organometallic frameworks: the cake-shaped GQD@NH₂-MIL-125 and the cross-shaped M8U6/FM8U6. The GQD@NH₂-MIL-125 framework is particularly noteworthy for its high fluorescence, making it an effective tool for biological imaging. X-ray diffraction (XRD) analysis revealed specific diffraction peaks at 6.81ᵒ (011), 9.76ᵒ (002), and 11.69ᵒ (121), with an additional significant peak at 26ᵒ (2θ), corresponding to the carbon material. Morphological analysis using Field Emission Scanning Electron Microscopy (FE-SEM), and Transmission Electron Microscopy (TEM) demonstrated that the framework has a front particle size of 680 nm and a side particle size of 55±5 nm. High-resolution TEM (HR-TEM) images confirmed the successful attachment of graphene quantum dots (GQDs) onto the NH2-MIL-125 framework. Fourier-Transform Infrared (FT-IR) spectroscopy identified crucial functional groups within the GQD@NH₂-MIL-125 structure, including O-Ti-O metal bonds within the 500 to 700 cm⁻¹ range, and N-H and C-N bonds at 1,646 cm⁻¹ and 1,164 cm⁻¹, respectively. BET isotherm analysis further revealed a specific surface area of 338.1 m²/g and an average pore size of 46.86 nm. This framework also demonstrated UV-active properties, as identified by UV-visible light spectra, and its photoluminescence (PL) spectra showed an emission peak around 430 nm when excited at 350 nm, indicating its potential as a fluorescent drug delivery carrier. In parallel, the cross-shaped M8U6/FM8U6 frameworks were synthesized and characterized using X-ray diffraction, which identified distinct peaks at 2θ = 7.4 (111), 8.5 (200), 9.2 (002), 10.8 (002), 12.1 (220), 16.7 (103), and 17.1 (400). FE-SEM, HR-TEM, and TEM analyses revealed particle sizes of 350±50 nm for M8U6 and 200±50 nm for FM8U6. These frameworks, synthesized from terephthalic acid (H₂BDC), displayed notable vibrational bonds, such as C=O at 1,650 cm⁻¹, Fe-O in MIL-88 at 520 cm⁻¹, and Zr-O in UIO-66 at 482 cm⁻¹. BET analysis showed specific surface areas of 740.1 m²/g with a pore size of 22.92 nm for M8U6 and 493.9 m²/g with a pore size of 35.44 nm for FM8U6. Extended X-ray Absorption Fine Structure (EXAFS) spectra confirmed the stability of Ti-O bonds in the frameworks, with bond lengths of 2.026 Å for MIL-125, 1.962 Å for NH₂-MIL-125, and 1.817 Å for GQD@NH₂-MIL-125. These findings highlight the potential of these organometallic frameworks for enhanced liver cancer therapy through precise drug delivery and imaging, representing a significant advancement in nanomaterial applications in biomedical science.

Keywords: liver cancer cells, metal organic frameworks, Doxorubicin (DOX), drug release.

Procedia PDF Downloads 9

Authors: Jacob Wahl, Jane Zhang

Abstract:

This paper describes the development and characterization of a prototype IoT network for use with agricultural imaging and monitoring applications. The sensor and gateway nodes are designed using the ESP32 SoC with integrated Bluetooth Low Energy 4.2 and Wi-Fi. A development board, the Arducam IoTai ESP32, is used for prototyping, testing, and power measurements. Google’s Firebase is used as the cloud storage site for image data collected by the sensor. The sensor node captures images using the OV2640 2MP camera module and transmits the image data to the gateway via Bluetooth Low Energy. The gateway then uploads the collected images to Firebase via a known nearby Wi-Fi network connection. This image data can then be processed and analyzed by computer vision and machine learning pipelines to assess crop growth or other needs. The sensor node achieves a wireless transmission data throughput of 220kbps while consuming 150mA of current; the sensor sleeps at 162µA. The sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day based on the development board power measurements. This network can be utilized by any application that requires high data rates, low power consumption, short-range communication, and large amounts of data to be transmitted at low-frequency intervals.

Keywords: Bluetooth low energy, ESP32, firebase cloud, IoT, smart farming

Procedia PDF Downloads 138

Authors: Arian Hosseini, Mahmudul Hasan

Abstract:

To address the increasing need for efficient and accurate content moderation, we propose an efficient and lightweight deep classification ensemble structure. Our approach is based on a combination of simple visual features, designed for high-accuracy classification of violent content with low false positives. Our ensemble architecture utilizes a set of lightweight models with narrowed-down color features, and we apply it to both images and videos. We evaluated our approach using a large dataset of explosion and blast contents and compared its performance to popular deep learning models such as ResNet-50. Our evaluation results demonstrate significant improvements in prediction accuracy, while benefiting from 7.64x faster inference and lower computation cost. While our approach is tailored to explosion detection, it can be applied to other similar content moderation and violence detection use cases as well. Based on our experiments, we propose a "think small, think many" philosophy in classification scenarios. We argue that transforming a single, large, monolithic deep model into a verification-based step model ensemble of multiple small, simple, and lightweight models with narrowed-down visual features can possibly lead to predictions with higher accuracy.

Keywords: deep classification, content moderation, ensemble learning, explosion detection, video processing

Procedia PDF Downloads 55

Authors: Mark Osborn

Abstract:

Clustered, regularly interspaced short palindromic repeat (CRISPR/Cas) proteins can be designed to bind specified DNA and RNA sequences and hold great promise for the accurate detection of nucleic acids for diagnostics. Commercially available reagents were integrated into a CRISPR/Cas9-based lateral flow assay that can detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequences with single-base specificity. This approach requires minimal equipment and represents a simplified platform for field-based deployment. A rapid, multiplex fluorescence CRISPR/Cas9 nuclease cleavage assay capable of detecting and differentiating SARS-CoV-2, influenza A and B, and respiratory syncytial virus in a single reaction was also developed. These findings provide proof of principle for CRISPR/Cas9 point-of-care diagnosis that can detect specific SARS-CoV-2 strain(s). Further, Cas9 cleavage allows for a scalable fluorescent platform for identifying respiratory viral pathogens with overlapping symptomology. Collectively, this approach is a facile platform for diagnostics with broad application to user-defined sequence interrogation and detection.

Keywords: CRISPR/Cas9, lateral flow assay, SARS-Co-V2, single-nucleotide resolution

Procedia PDF Downloads 184

Authors: Carlos Gordon, Patricio Encalada, Henry Lema, Diego Leon, Dennis Chicaiza

Abstract:

The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms.

Keywords: autonomous navigation, machine learning, path planning, robotic operative system, open source computer vision library

Procedia PDF Downloads 177

Authors: Gourg Ebrahim Shafik Eskandar

Abstract:

This research aims to study of the surgery science and imaging in ancient Egypt, and how to diagnose the surgical cases, whether due to injuries or disease that requires surgical intervention, Medical diagnosis and how to treat it. The ancient Egyptian physician tried to change over from magic and theological thinking to become a stand-alone experimental science, they were able to distinguish between diseases and they divide them into internal and external diseases even this division exists to date in modern medicine. There is no evidence to recognize the amount of human knowledge in the prehistoric knowledge of medicine and surgery except skeleton. It is not far from the human being in those times familiar with some means of treatment, Surgery in the Stone age was rudimentary, Flint stone was used after trimming in a certain way as a lancet to slit and open the skin. Wooden tree branches were used to make splints to treat bone fractures. Surgery developed further when copper was discovered, it led to the advancement of Egyptian civilization, then modern and advanced tools appeared in the operating theater like a knife or a scalpel, there is evidence of surgery performed in ancient Egypt during the dynastic period (323 – 3200 BC). The climate and environmental conditions have preserved medical papyri and human remains that have confirmed their knowledge of surgical methods including sedation. The ancient Egyptians reached a great importance in surgery, evidenced by the scenes that depict the pathological image and the surgical process, but the image alone is not sufficient to prove the pathology, its presence in ancient Egypt and its treatment method. As there are a number of medical papyri, especially Edwin Smith and Ebris, which prove the ancient Egyptian surgeon's knowledge of the pathological condition that It requires a surgical intervention, otherwise its diagnosis and the method of treatment will not be described with such accuracy through these texts. Some surgeries are described in the department of surgery at Ebris papyrus (recipes from 863 to 877). The level of surgery in ancient Egypt was high, and they performed surgery such as hernias and Aneurysm, however we have not received a lengthy explanation of the various surgeries and the surgeon has usually only said “treated surgically”. It is evident in the Ebris papyrus that they used sharp surgical tools and cautery in operations where bleeding is expected, such as hernias, arterial sacs and tumors.

Keywords: ancient egypt, egypt, surgical imaging, surgery in the stone age

Procedia PDF Downloads 22

Authors: Tien-Li Chang, Huang-Chi Huang, Zhao-Chi Chen, Wun-Yi Chen

Abstract:

The droplet-based microfluidic are used as micro-reactors for chemical and biological assays. Hence, the precise addition of reagents into the droplets is essential for this function in the scope of lab-on-a-chip applications. To obtain the characteristics (size, velocity, pressure, and frequency of production) of droplets, this study describes an integrated on-chip method of real-time signal detection. By controlling and manipulating the fluids, the flow behavior can be obtained in the droplet-based microfluidics. The detection method is used a type of infrared sensor. Through the varieties of droplets in the microfluidic devices, the real-time conditions of velocity and pressure are gained from the sensors. Here the microfluidic devices are fabricated by polydimethylsiloxane (PDMS). To measure the droplets, the signal acquisition of sensor and LabVIEW program control must be established in the microchannel devices. The devices can generate the different size droplets where the flow rate of oil phase is fixed 30 μl/hr and the flow rates of water phase range are from 20 μl/hr to 80 μl/hr. The experimental results demonstrate that the sensors are able to measure the time difference of droplets under the different velocity at the voltage from 0 V to 2 V. Consequently, the droplets are measured the fastest speed of 1.6 mm/s and related flow behaviors that can be helpful to develop and integrate the practical microfluidic applications.

Keywords: microfluidic, droplets, sensors, single detection

Procedia PDF Downloads 493

Authors: I. A. Farhat, M. Bin Hasan

Abstract:

A developed approach for the protection of power transmission lines using Support Vector Machines (SVM) technique is presented. In this paper, the SVM technique is utilized for the classification and isolation of faults in power transmission lines. Accurate fault classification and location results are obtained for all possible types of short circuit faults. As in distance protection, the approach utilizes the voltage and current post-fault samples as inputs. The main advantage of the method introduced here is that the method could easily be extended to any power transmission line.

Keywords: fault detection, classification, diagnosis, power transmission line protection, support vector machines (SVM)

Procedia PDF Downloads 559

Authors: Ari S. Prabowo, Nia Febriyanti, Haryono B. Santosa

Abstract:

Security function that is called as Physical Protection Systems (PPS) has functions to detect, delay and response. Physical Protection Systems (PPS) in Detection and Radiation Measurement Laboratory needs to be improved continually by using internal resources. The nuclear security culture provides some potentials to support this research. The study starts by identifying the security function’s weaknesses and its strengths of security culture as a purpose. Secondly, the strengths of security culture are implemented in the laboratory management. Finally, a simulation was done to measure its effectiveness. Some changes were happened in laboratory personnel behaviors and procedures. All became more prudent. The results showed a good influence of nuclear security culture in laboratory security functions.

Keywords: laboratory, physical protection system, security culture, security function

Procedia PDF Downloads 185

Authors: Nir Nissim, Erez Shalom, Tomer Lancewiki, Yuval Elovici, Yuval Shahar

Abstract:

Background: A Medical Device (MD) is an instrument, machine, implant, or similar device that includes a component intended for the purpose of the diagnosis, cure, treatment, or prevention of disease in humans or animals. Medical devices play increasingly important roles in health services eco-systems, including: (1) Patient Diagnostics and Monitoring; Medical Treatment and Surgery; and Patient Life Support Devices and Stabilizers. MDs are part of the medical device eco-system and are connected to the network, sending vital information to the internal medical information systems of medical centers that manage this data. Wireless components (e.g. Wi-Fi) are often embedded within medical devices, enabling doctors and technicians to control and configure them remotely. All these functionalities, roles, and uses of MDs make them attractive targets of cyber-attacks launched for many malicious goals; this trend is likely to significantly increase over the next several years, with increased awareness regarding MD vulnerabilities, the enhancement of potential attackers’ skills, and expanded use of medical devices. Significance: We propose to develop and implement Cyber-Med, a unique collaborative project of Ben-Gurion University of the Negev and the Clalit Health Services Health Maintenance Organization. Cyber-Med focuses on the development of a comprehensive detection framework that relies on a critical attack repository that we aim to create. Cyber-Med will allow researchers and companies to better understand the vulnerabilities and attacks associated with medical devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The Cyber-Med detection framework will consist of two independent, but complementary detection approaches: one for known attacks, and the other for unknown attacks. These modules incorporate novel ideas and algorithms inspired by our team's domains of expertise, including cyber security, biomedical informatics, and advanced machine learning, and temporal data mining techniques. The establishment and maintenance of Cyber-Med’s up-to-date attack repository will strengthen the capabilities of Cyber-Med’s detection framework. Major Findings: Based on our initial survey, we have already found more than 15 types of vulnerabilities and possible attacks aimed at MDs and their eco-system. Many of these attacks target individual patients who use devices such pacemakers and insulin pumps. In addition, such attacks are also aimed at MDs that are widely used by medical centers such as MRIs, CTs, and dialysis engines; the information systems that store patient information; protocols such as DICOM; standards such as HL7; and medical information systems such as PACS. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched against MDs. Very little research has been conducted in order to protect these devices from cyber-attacks, since most of the development and engineering efforts are aimed at the devices’ core medical functionality, the contribution to patients’ healthcare, and the business aspects associated with the medical device.

Keywords: medical device, cyber security, attack, detection, machine learning

Procedia PDF Downloads 357

Authors: Davit Mirzoyan, Ararat Khachatryan

Abstract:

A process corner monitoring circuit (PCMC) is presented in this work. The circuit generates a signal, the logical value of which depends on the process corner only. The signal can be used in both digital and analog circuits for testing and compensation of process variations (PV). The presented circuit uses only metal-oxide-semiconductor (MOS) transistors, which allow increasing its detection accuracy, decrease power consumption and area. Due to its simplicity the presented circuit can be easily modified to monitor parametrical variations of only n-type and p-type MOS (NMOS and PMOS, respectively) transistors, resistors, as well as their combinations. Post-layout simulation results prove correct functionality of the proposed circuit, i.e. ability to monitor the process corner (equivalently die-to-die variations) even in the presence of within-die variations.

Keywords: detection, monitoring, process corner, process variation

Procedia PDF Downloads 525

Authors: Kirti Gosavi, Anita Bhole

Abstract:

The paper demonstrates simulation and steady-state performance of three phase squirrel cage induction motor and detection of rotor broken bar fault using MATLAB. This simulation model is successfully used in the fault detection of rotor broken bar for the induction machines. A dynamic model using PWM inverter and mathematical modelling of the motor is developed. The dynamic simulation of the small power induction motor is one of the key steps in the validation of the design process of the motor drive system and it is needed for eliminating advertent design errors and the resulting error in the prototype construction and testing. The simulation model will be helpful in detecting the faults in three phase induction motor using Motor current signature analysis.

Keywords: squirrel cage induction motor, pulse width modulation (PWM), fault diagnosis, induction motor

Procedia PDF Downloads 633

Authors: Ippei Kamihira, Takashi Nakajima, Taiyo Matsumura, Hikaru Miura, Takashi Ono

Abstract:

In this research, the goal was construction of a system by which multiple sensors were used to observe the daily life behavior of persons living alone (while respecting their privacy). Using this information to judge such conditions as a bad physical condition or falling in the home, etc., so that these abnormal conditions can be made known to relatives and third parties. The daily life patterns of persons living alone are expressed by the number of responses of sensors each time that a set time period has elapsed. By comparing data for the prior two weeks, it was possible to judge a situation as 'normal' when the person was in a good physical condition or as 'abnormal' when the person was in a bad physical condition.

Keywords: sensors, elderly living alone, abnormality detection, iifestyle habit

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Authors: Angela Maria Fasnacht

Abstract:

Detection of anomalies due to contaminants’ presence, also known as early detection systems in water treatment plants, has become a critical point that deserves an in-depth study for their improvement and adaptation to current requirements. The design of these systems requires a detailed analysis and processing of the data in real-time, so it is necessary to apply various statistical methods appropriate to the data generated, such as Spearman’s Correlation, Factor Analysis, Cross-Correlation, and k-fold Cross-validation. Statistical analysis and methods allow the evaluation of large data sets to model the behavior of variables; in this sense, statistical treatment or analysis could be considered a vital step to be able to develop advanced models focused on machine learning that allows optimized data management in real-time, applied to early detection systems in water treatment processes. These techniques facilitate the development of new technologies used in advanced sensors. In this work, these methods were applied to identify the possible correlations between the measured parameters and the presence of the glyphosate contaminant in the single-pass system. The interaction between the initial concentration of glyphosate and the location of the sensors on the reading of the reported parameters was studied.

Keywords: glyphosate, emergent contaminants, machine learning, probes, sensors, predictive

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Authors: Kyung Jin Kim, Jiwon Kwak, Jae-Hoon Lee, Soo Suk Lee

Abstract:

MicroRNAs (miRNA) are a class of endogenous, single-stranded, small, and non-protein coding RNA molecules typically 20-25 nucleotides long. They are thought to regulate the expression of other genes in a broad range by binding to 3’- untranslated regions (3’-UTRs) of specific mRNAs. The detection of miRNAs is very important for understanding of the function of these molecules and in the diagnosis of variety of human diseases. However, detection of miRNAs is very challenging because of their short length and high sequence similarities within miRNA families. So, a simple-to-use, low-cost, and highly sensitive method for the detection of miRNAs is desirable. In this study, we demonstrate a novel bi-directional extension (BDE) assay. In the first step, a specific linear RT primer is hybridized to 6-10 base pairs from the 3’-end of a target miRNA molecule and then reverse transcribed to generate a cDNA strand. After reverse transcription, the cDNA was hybridized to the 3’-end which is BDE sequence; it played role as the PCR template. The PCR template was amplified in an SYBR green-based quantitative real-time PCR. To prove the concept, we used human brain total RNA. It could be detected quantitatively in the range of seven orders of magnitude with excellent linearity and reproducibility. To evaluate the performance of BDE assay, we contrasted sensitivity and specificity of the BDE assay against a commercially available poly (A) tailing method using miRNAs for let-7e extracted from A549 human epithelial lung cancer cells. The BDE assay displayed good performance compared with a poly (A) tailing method in terms of specificity and sensitivity; the CT values differed by 2.5 and the melting curve showed a sharper than poly (A) tailing methods. We have demonstrated an innovative, cost-effective BDE assay that allows improved sensitivity and specificity in detection of miRNAs. Dynamic range of the SYBR green-based RT-qPCR for miR-145 could be represented quantitatively over a range of 7 orders of magnitude from 0.1 pg to 1.0 μg of human brain total RNA. Finally, the BDE assay for detection of miRNA species such as let-7e shows good performance compared with a poly (A) tailing method in terms of specificity and sensitivity. Thus BDE proves a simple, low cost, and highly sensitive assay for various miRNAs and should provide significant contributions in research on miRNA biology and application of disease diagnostics with miRNAs as targets.

Keywords: bi-directional extension (BDE), microRNA (miRNA), poly (A) tailing assay, reverse transcription, RT-qPCR

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Authors: S. Maniruzzaman, N. Ramanujam, Qazi Akhter Rasool, Swapan Kumar Biswas, P. Prasad, Chandrakanta Ojha

Abstract:

Landslide is one of the major natural disasters in South Asian countries. Applying 2D Electrical Resistivity Tomographic Imaging estimation of geometry, thickness, and depth of failure zone of the landslide can be made. Landslide is a pertinent problem in Nilgris plateau next to Himalaya. Nilgris range consists of hard Archean metamorphic rocks. Intense weathering prevailed during the Pre-Cambrian time had deformed the rocks up to 45m depth. The landslides are dominant in the southern and eastern part of plateau of is comparatively smaller than the northern drainage basins, as it has low density of drainage; coarse texture permitted the more of infiltration of rainwater, whereas in the northern part of the plateau entombed with high density of drainage pattern and fine texture with less infiltration than run off, and low to the susceptible to landslide. To get comprehensive information about the landslide zone 2D Electrical Resistivity Tomographic imaging study with CRM 500 Resistivity meter are used in Coonoor– Mettupalyam sector of Nilgiris plateau. To calculate Factor of Safety the infinite slope model of Brunsden and Prior is used. Factor of Safety can be expressed (FS) as the ratio of resisting forces to disturbing forces. If FS < 1 disturbing forces are larger than resisting forces and failure may occur. The geotechnical parameters of soil samples are calculated on the basis upon the apparent resistivity values for litho units of measured from 2D ERT image of the landslide zone. Relationship between friction angles for various soil properties is established by simple regression analysis from apparent resistivity data. Increase of water content in slide zone reduces the effectiveness of the shearing resistance and increase the sliding movement. Time-lapse resistivity changes to slope failure is determined through geophysical Factor of Safety which depends on resistivity and site topography. This ERT technique infers soil property at variable depths in wider areas. This approach to retrieve the soil property and overcomes the limit of the point of information provided by rain gauges and porous probes. Monitoring of slope stability without altering soil structure through the ERT technique is non-invasive with low cost. In landslide prone area an automated Electrical Resistivity Tomographic Imaging system should be installed permanently with electrode networks to monitor the hydraulic precursors to monitor landslide movement.

Keywords: 2D ERT, landslide, safety factor, slope stability

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Authors: Nyimas Annissa Mutiara Andini

Abstract:

Every year, children develop hydrocephalus during the first year of life. If it is not treated, hydrocephalus can lead to brain damage, a loss in mental and physical abilities, and even death. To be treated, first, we have to do a proper diagnosis using some examinations especially to detect hydrocephalus earlier. One of the examination that could be done is using a head circumference measurement. Increased head circumference is a first and main sign of hydrocephalus, especially in infant (0-1 year age). Head circumference is a measurement of a child's head largest area. In this measurement, we want to get the distance from above the eyebrows and ears and around the back of the head using a measurement tape. If the head circumference of an infant is larger than normal, this infant might potentially suffer hydrocephalus. If early diagnosis and timely treatment of hydrocephalus could be done most children can recover successfully. There are some problems with early detection of hydrocephalus using regular tape for head circumference measurement. One of the problem is the infant’s comfort. We need to make the infant feel comfort along the head circumference measurement to get a proper result of the examination. For that, we can use a helpful stuff, like a hat. This paper is aimed to describe the possibility of using a head circumference measuring instrument for early detection of hydrocephalus in an infant with a mike hat, coloured-tape-in-hat. In the first life, infants’ head size is about 35 centimeters. First three months after that infants will gain 2 centimeters each month. The second three months, infant’s head circumference will increase 1 cm each month. And for the six months later, the rate is 0.5 cm per month, and end up with an average of 47 centimeters. This formula is compared to the WHO’s head circumference growth chart. The shape of this tape-in-hat is alike an upper arm measurement. This tape-in-hat diameter is about 47 centimeters. It contains twelve different colours range by age. If it is out of the normal colour, the infant potentially suffers hydrocephalus. This examination should be done monthly. If in two times of measurement there still in the same range abnormal of head circumference, or a rapid growth of the head circumference size, the infant should be referred to a pediatrician. There are the pink hat for girls and blue hat for boys. Based on this paper, we know that this measurement can be used to help early detection of hydrocephalus in an infant.

Keywords: head circumference, hydrocephalus, infant, mike hat

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