Search results for: detect

Authors: Valerie A. Conrade

Abstract:

Introduction: A large body of literature suggests patients who complete fecal immunochemical testing (FIT) kits are likely to identify colorectal cancer sooner than those who do not complete FIT kits. Background: Patients who do not participate in preventative measures such as the FIT kit are at a higher risk of colorectal cancer growing unnoticed. The objective was to see if the method the principal investigator (PI) uses to educate clinical staff on the importance of FIT kit administration provides an increased amount of FIT kit dissemination to patients post clinical education. Methodologies: Data collection via manual tallies took place before and after the clinical staff was educated on the importance of FIT kits. Results: The results showed an increase in FIT kit dissemination post clinical staff education. Through enhanced instruction to the clinical staff regarding the importance of FIT kits, expanding their knowledge on preventative measures to detect colorectal cancer positively impacted nurses and, in turn, their patients.

Keywords: colon cancer, education, fecal immunochemical testing, nursing

Procedia PDF Downloads 117

Authors: T. Penkova, A. Korobko, V. Nicheporchuk, L. Nozhenkova, A. Metus

Abstract:

This paper presents an approach of on-line control of the state of technosphere and environment objects based on the integration of Data Warehouse, OLAP and Expert systems technologies. It looks at the structure and content of data warehouse that provides consolidation and storage of monitoring data. There is a description of OLAP-models that provide a multidimensional analysis of monitoring data and dynamic analysis of principal parameters of controlled objects. The authors suggest some criteria of emergency risk assessment using expert knowledge about danger levels. It is demonstrated now some of the proposed solutions could be adopted in territorial decision making support systems. Operational control allows authorities to detect threat, prevent natural and anthropogenic emergencies and ensure a comprehensive safety of territory.

Keywords: decision making support systems, emergency risk assessment, natural and anthropogenic safety, on-line control, territory

Procedia PDF Downloads 390

Authors: Igor Shardakov, Anton Bykov, Alexey Shestakov, Irina Glot

Abstract:

This article focuses on the cycle of experimental studies of the formation of cracks and debondings in the concrete reinforced with carbon fiber. This research was carried out in Perm National Research Polytechnic University. A series of CFRP-strengthened RC beams was tested to investigate the influence of preload and crack repairing factors on CFRP debonding. IRT was applied to detect the early stage of IC debonding during the laboratory bending tests. It was found that for the beams strengthened under load after crack injecting, СFRP debonding strain is 4-65% lower than for the preliminary strengthened beams. The beams strengthened under the load had a relative area of debonding of 2 times higher than preliminary strengthened beams. The СFRP debonding strain is weakly dependent on the strength of the concrete substrate. For beams with a transverse wrapping anchorage in support sections FRP debonding is not a failure mode.

Keywords: IC debonding, infrared thermography, non-destructive testing methods, quality control, strengthening

Procedia PDF Downloads 242

Authors: Syed Mahbubuz Zaman, A. B. M. Abrar Haque, Mehedi Hassan Nayeem, Misbah Uddin Sagor

Abstract:

Everyday e-mails are being used by millions of people as an effective form of communication over the Internet. Although e-mails allow high-speed communication, there is a constant threat known as spam. Spam e-mail is often called junk e-mails which are unsolicited and sent in bulk. These unsolicited emails cause security concerns among internet users because they are being exposed to inappropriate content. There is no guaranteed way to stop spammers who use static filters as they are bypassed very easily. In this paper, a smart system is proposed that will be using neural networks to approach spam in a different way, and meanwhile, this will also detect the most relevant features that will help to design the spam filter. Also, a comparison of different parameters for different neural network models has been shown to determine which model works best within suitable parameters.

Keywords: long short-term memory, bidirectional long short-term memory, gated recurrent unit, natural language processing, natural language processing

Procedia PDF Downloads 188

Authors: Sanghoon Bae, Hanju Cha

Abstract:

Failed fuel detector (FFD) in research reactor is a very crucial instrument to detect the anomaly from failed fuels in the early stage around primary cooling system (PCS) outlet prior to the decay tank. FFD is considered as a mandatory sensor to ensure the integrity of fuel assemblies and mitigate the consequence from a failed fuel accident. For the effective function of FFD, the location of them should be determined by contemplating the effect from coolant flow around two outlets. For this, the analysis on computational flow dynamics (CFD) should be first performed how the coolant outlet flow including radioactive materials from failed fuels are mixed and discharged through the outlet plenum within certain seconds. The analysis result shows that the outlet flow is well mixed regardless of the position of failed fuel and ultimately illustrates the effect of detector location.

Keywords: computational flow dynamics (CFD), failed fuel detector (FFD), fresh fuel assembly (FFA), spent fuel assembly (SFA)

Procedia PDF Downloads 231

Authors: Amarnath M., Ramachandra C. G., H. Chelladurai, P..Sateesh Kumar, K. Santhosh Kumar

Abstract:

Journal bearings are extensively used sliding contact machine elements to support radial/axial loaded rotors used in various applications viz. automobile crankshaft, turbine propeller shaft, rope conveyer, heavy duty electric motors. The primary reasons for the failures of these bearings include unstable lubricant film, oil degradation, misalignment, etc. This paper describes the results of experimental investigations carried out to detect surface fatigue wear developed on load bearing the contact surfaces of journal bearing. The test bearing was subjected to fatigue load cycles over a period of 600 hours. The vibration signals were acquired from the journal bearing at regular intervals of 100 hrs. These signals were post-processed by using the vibration analysis technique to obtain diagnostic information of wear propagated in the journal-bearing system.

Keywords: fatigue, journal bearing, sound signals, vibration signals, wear

Procedia PDF Downloads 49

Authors: Abhigyan Hedau, Priya Shelke, Riddhi Mirajkar, Shreyash Chaple, Mrunali Gadekar, Himanshu Akula

Abstract:

The heart is the coordinating centre of the major endocrine glandular structure of the body, which produces hormones that profoundly affect the operations of the body, and diagnosing cardiovascular disease is a difficult but critical task. By extracting knowledge and information about the disease from patient data, data mining is a more practical technique to help doctors detect disorders. We use a variety of machine learning methods here, including logistic regression and support vector classifiers (SVC), K-nearest neighbours Classifiers (KNN), Decision Tree Classifiers, Random Forest classifiers and Gradient Boosting classifiers. These algorithms are applied to patient data containing 13 different factors to build a system that predicts heart disease in less time with more accuracy.

Keywords: logistic regression, support vector classifier, k-nearest neighbour, decision tree, random forest and gradient boosting

Procedia PDF Downloads 31

Authors: Ali Ulvi Uzer

Abstract:

Data reduction is an important topic in the field of pattern recognition applications. The basic concept is the reduction of multitudinous amounts of data down to the meaningful parts. The Principal Component Analysis (PCA) method is frequently used for data reduction. The Support Vector Machine (SVM) method is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data, the algorithm outputs an optimal hyperplane which categorizes new examples. This study offers a hybrid approach that uses the PCA for data reduction and Support Vector Machines (SVM) for classification. In order to detect the accuracy of the suggested system, two boreholes taken from the soil sample was used. The classification accuracies for this dataset were obtained through using ten-fold cross-validation method. As the results suggest, this system, which is performed through size reduction, is a feasible system for faster recognition of dataset so our study result appears to be very promising.

Keywords: feature selection, sequential forward selection, support vector machines, soil sample

Procedia PDF Downloads 435

Authors: A. Biran, P. Sobhe Bidari, A. Almazroe, V. Lakshminarayanan, K. Raahemifar

Abstract:

Diabetic Retinopathy (DR) is a severe retinal disease which is caused by diabetes mellitus. It leads to blindness when it progress to proliferative level. Early indications of DR are the appearance of microaneurysms, hemorrhages and hard exudates. In this paper, an automatic algorithm for detection of DR has been proposed. The algorithm is based on combination of several image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Also, Support Vector Machine (SVM) Classifier is used to classify retinal images to normal or abnormal cases including non-proliferative or proliferative DR. The proposed method has been tested on images selected from Structured Analysis of the Retinal (STARE) database using MATLAB code. The method is perfectly able to detect DR. The sensitivity specificity and accuracy of this approach are 90%, 87.5%, and 91.4% respectively.

Keywords: diabetic retinopathy, fundus images, STARE, Gabor filter, support vector machine

Procedia PDF Downloads 278

Authors: Dua Hişam, Serhat İkizoğlu

Abstract:

Identifying the problem behind balance disorder is one of the most interesting topics in the medical literature. This study has considerably enhanced the development of artificial intelligence (AI) algorithms applying multiple machine learning (ML) models to sensory data on gait collected from humans to classify between normal people and those suffering from Vestibular System (VS) problems. Although AI is widely utilized as a diagnostic tool in medicine, AI models have not been used to perform feature extraction and identify VS disorders through training on raw data. In this study, three machine learning (ML) models, the Random Forest Classifier (RF), Extreme Gradient Boosting (XGB), and K-Nearest Neighbor (KNN), have been trained to detect VS disorder, and the performance comparison of the algorithms has been made using accuracy, recall, precision, and f1-score. With an accuracy of 95.28 %, Random Forest Classifier (RF) was the most accurate model.

Keywords: vestibular disorder, machine learning, random forest classifier, k-nearest neighbor, extreme gradient boosting

Procedia PDF Downloads 53

Authors: Fouzi Harrou, Ying Sun, Sofiane Khadraoui

Abstract:

Anomaly detection based on Principal Component Analysis (PCA) was studied intensively and largely applied to multivariate processes with highly cross-correlated process variables. Monitoring metrics such as the Hotelling's T2 and the Q statistics are usually used in PCA-based monitoring to elucidate the pattern variations in the principal and residual subspaces, respectively. However, these metrics are ill suited to detect small faults. In this paper, the Exponentially Weighted Moving Average (EWMA) based on the Q and T statistics, T2-EWMA and Q-EWMA, were developed for detecting faults in the process mean. The performance of the proposed methods was compared with that of the conventional PCA-based fault detection method using synthetic data. The results clearly show the benefit and the effectiveness of the proposed methods over the conventional PCA method, especially for detecting small faults in highly correlated multivariate data.

Keywords: data-driven method, process control, anomaly detection, dimensionality reduction

Procedia PDF Downloads 276

Authors: Hilalah Alturkistani, Alaa AlFaadhel, Nora AlJahani, Fatiha Djebbar

Abstract:

Cloud computing is one of the most widely used technology which provides opportunities and services to government entities, large companies, and standard users. However, cybersecurity risk management studies of cloud computing and resiliency approaches are lacking. This paper proposes resilient cloud cybersecurity risk assessment and management tailored specifically, to Dropbox with two approaches:1) technical-based solution motivated by a cybersecurity risk assessment of cloud services, and 2)a target personnel-based solution guided by cybersecurity-related survey among employees to identify their knowledge that qualifies them withstand to any cyberattack. The proposed work attempts to identify cloud vulnerabilities, assess threats and detect high risk components, to finally propose appropriate safeguards such as failure predicting and removing, redundancy or load balancing techniques for quick recovery and return to pre-attack state if failure happens.

Keywords: cybersecurity risk management plan, resilient cloud computing, cyberattacks, cybersecurity risk assessment

Procedia PDF Downloads 117

Authors: Anirudh Bhaikhel

Abstract:

The exclusive objective of this paper is to develop a device which can pass on the interpreted result of the sensed information to the interfaced communicable devices to avoid or minimise accidents. This device may also be used in case of emergencies like kidnapping, robberies, medical emergencies etc. The present era has seen a rapid metamorphosis in the automobile industry with increasing use of technology and speed. The increase in purchasing power of customers and price war of automobile companies has made an easy access to the automobile users. The use of automobiles has increased tremendously in last 4-5 years thus causing traffic congestions and thus making vehicles more prone to accidents. This device can be an effective measure to counteract cases of abduction. Risks of accidents can be decreased tremendously through the notifications received by these alerts. It will help to detect the upcoming emergencies. This paper includes the simulation of the communication and sensing device required in automobiles using VHDL.

Keywords: automobiles, communication, component, cyclic redundancy check (CRC), modulo-2 arithmetic, parity bits, receiver, sensors, transmitter, turns, VHDL (VHSIC hardware descriptive language)

Procedia PDF Downloads 251

Authors: Kunle Oparinde

Abstract:

The Covid-19 pandemic has seen several rumors and conspiracy theories overtake the truth in many online platforms across several African countries. Just as the coronavirus has travelled widely, misinformation has equally spread. Thus, it is important to launch investigations into these conspiracy theories in order to detect them early and as a result, implore health practitioners and agencies to be more proactive in repelling misinformation while at the same time provide the general populace with purely undiluted information regarding the virus. Through social media posts on platforms such as Twitter, Facebook, and WhatsApp, as well as online platforms such as Google, this study intends to draw as many instances as possible of infodemic and misinformation by reviewing and analyzing these texts and the resulting implication if the misinformation continues to gain popularity. The study discovers the use of conspiracy theories, rumors, hyperbolism, and unverified claims as elements of infodemic used during the coronavirus pandemic. Importantly, the findings of the study will assist the public to be cautious and vigilant against false information that are being peddled as original.

Keywords: infodemic, miscommunication, accuracy, social media, rumors, conspiracy

Procedia PDF Downloads 175

Authors: Priyajeet Kaur Kaleka

Abstract:

Introduction: A dentist is often the first responder in the battle for a patient’s healthy body and maybe the first health professional to observe signs of child abuse, be it physical, emotional, and/or sexual mistreatment. Therefore, it is an ethical responsibility for the dental clinician to detect and report suspected cases of child abuse and neglect (CAN). The main reasons for not reporting suspected cases of CAN, with special emphasis on the third: 1) Uncertainty of the diagnosis, 2) Lack of knowledge of the reporting procedure, and 3) Child abuse and neglect somewhat remained the subject of ignorance among dental professionals because of a lack of advance clinical training. Given these epidemic proportions, there is a scope of further research about dental school curriculum design. Purpose: This study aimed to assess the knowledge and attitude of dentists in Canada regarding signs and symptoms of child abuse and neglect (CAN), reporting procedures, and whether educational strategies followed by dental schools address this sensitive issue. In pursuit of that aim, this abstract summarizes the evidence related to this question. Materials and Methods: Data was collected through a specially designed questionnaire adapted and modified from the author’s previous cross-sectional study on (CAN), which was conducted in Pune, India, in 2016 and is available on the database of PubMed. Design: A random sample was drawn from the targeted population of registered dentists and dental students in Canada regarding their knowledge, professional responsibilities, and behavior concerning child abuse. Questionnaire data were distributed to 200 members. Out of which, a total number of 157 subjects were in the final sample for statistical analysis, yielding response of 78.5%. Results: Despite having theoretical information on signs and symptoms, 55% of the participants indicated they are not confident to detect child physical abuse cases. 90% of respondents believed that recognition and handling the CAN cases should be a part of undergraduate training. Only 4.5% of the participants have correctly identified all signs of abuse due to inadequate formal training in dental schools and workplaces. Although nearly 96.3% agreed that it is a dentist’s legal responsibility to report CAN, only a small percentage of the participants reported an abuse case in the past. While 72% stated that the most common factor that might prevent a dentist from reporting a case was doubt over the diagnosis. Conclusion: The goal is to motivate dental schools to deal with this critical issue and provide their students with consummate training to strengthen their capability to care for and protect children. The educational institutions should make efforts to spread awareness among dental students regarding the management and tackling of CAN. Clinical Significance: There should be modifications in the dental school curriculum focusing on problem-based learning models to assist graduates to fulfill their legal and professional responsibilities. CAN literacy should be incorporated into the dental curriculum, which will eventually benefit future dentists to break this intergenerational cycle of violence.

Keywords: abuse, child abuse and neglect, dentist knowledge, dental school curriculum, problem-based learning

Procedia PDF Downloads 184

Authors: Ajay Kumar, Neha Gupta

Abstract:

This work presents the sensitivity assessment of Gallium Nitride (GaN) material-based FinFET by dielectric modulation in the nanocavity gap for label-free biosensing applications. The significant deflection is observed in the electrical characteristics such as drain current (ID), transconductance (gm), surface potential, energy band profile, electric field, sub-threshold slope (SS), and threshold voltage (Vth) in the presence of biomolecules owing to GaN material. Further, the device sensitivity is evaluated to identify the effectiveness of the proposed biosensor and its capability to detect the biomolecules with high precision or accuracy. Higher sensitivity is observed for Gelatin (k=12) in terms of on-current (SION), threshold voltage (SVth), and switching ratio (SSR) by 104.88%, 82.12%, and 119.73%, respectively. This work is performed using a powerful tool 3D Sentaurus TCAD using a well-calibrated structure. All the results pave the way for GaN-FinFET as a viable candidate for label-free dielectric modulated biosensor applications.

Keywords: biosensor, biomolecules, FinFET, sensitivity

Procedia PDF Downloads 181

Authors: Solehuddin Shuib, Koay Boon Aik, Zainul Ahmad Rajion

Abstract:

There are many types of mechanical failure on the dental implant. In this project, the failure that needs to take into consideration is the bone resorption on the dental implant. Human bone has its ability to remodel after the implantation. As the dental implant is installed into the bone, the bone will detect and change the bone structure to achieve new biomechanical environment. This phenomenon is known as bone remodeling. The objective of the project is to improve the performance of dental implant by using different types of design. These designs are used to analyze and predict the failure of the dental implant by using finite element analysis (FEA) namely ANSYS. The bone is assumed to be fully attached to the implant or cement. Hence, results are then compared with other researchers. The results were presented in the form of Von Mises stress, normal stress, shear stress analysis, and displacement. The selected design will be analyzed further based on a theoretical calculation of bone remodeling on the dental implant. The results have shown that the design constructed passed the failure analysis. Therefore, the selected design is proven to have a stable performance at the recovery stage.

Keywords: dental implant, FEA, bone remodeling, design

Procedia PDF Downloads 486

Authors: Maatoug Hassine, Mourad Hrizi

Abstract:

In this paper, we consider a geometric inverse source problem for the heat equation with Dirichlet and Neumann boundary data. We will reconstruct the exact form of the unknown source term from additional boundary conditions. Our motivation is to detect the location, the size and the shape of source support. We present a one-shot algorithm based on the Kohn-Vogelius formulation and the topological gradient method. The geometric inverse source problem is formulated as a topology optimization one. A topological sensitivity analysis is derived from a source function. Then, we present a non-iterative numerical method for the geometric reconstruction of the source term with unknown support using a level curve of the topological gradient. Finally, we give several examples to show the viability of our presented method.

Keywords: geometric inverse source problem, heat equation, topological optimization, topological sensitivity, Kohn-Vogelius formulation

Procedia PDF Downloads 287

Authors: Surapol Raadnui

Abstract:

This particular work describes an experimental investigation on gear wear in which wear and pitting were intentionally allowed to occur, namely, moisture corrosion pitting, acid-induced corrosion pitting, hard contaminant-related pitting and mechanical induced wear. A back to back spur gear test rig and a grease lubricated worm gear rig were used. The tests samples of wear debris were collected and assessed through the utilization of an optical microscope in order to correlate and compare the debris morphology to pitting and wear degradation of the worn gears. In addition, weight loss from all test gear pairs were assessed with utilization of statistical design of experiment. It can be deduced that wear debris characteristics from both cases exhibited a direct relationship with different pitting and wear modes. Thus, it should be possible to detect and diagnose gear pitting and wear utilization of worn surfaces, generated wear debris and quantitative measurement such as weight loss.

Keywords: predictive maintenance, worm gear, spur gear, wear debris analysis, problem diagnostic

Procedia PDF Downloads 136

Authors: Amrita Anil Agashe, Sumant Tapas, Ajay Verma Yogesh Sonavane, Sourabh Yeravar

Abstract:

Due to advancement in MEMS technology today wireless sensors network has gained a lot of importance. The wide range of its applications includes environmental and habitat monitoring, object localization, target tracking, security surveillance etc. Wireless sensor networks consist of tiny sensor devices called as motes. The constrained computation power, battery power, storage capacity and communication bandwidth of the tiny motes pose challenging problems in the design and deployment of such systems. In this paper, we propose a ubiquitous framework for Real-Time Tracking, Sensing and Management System using IITH motes. Also, we explain the algorithm that we have developed for location management in wireless sensor networks with the aspect of mobility. Our developed framework and algorithm can be used to detect emergency events and safety threats and provides warning signals to handle the emergency.

Keywords: mobility management, motes, multihop, wireless sensor networks

Procedia PDF Downloads 401

Authors: N. Ullah, A. Haddad, F. Van Der Linde

Abstract:

This paper investigates the effects of breaks in bonds, breaks in the earthing system and breaks in earth wire on the rise of the earth potential (EPR) in a substation and at the transmission tower bases using various models of an L6 tower. Different approaches were adopted to examine the integrity of the earthing system and the terminal towers. These effects were investigated to see the associated difference in the EPR magnitudes with respect to a healthy system at various locations. Comparisons of the computed EPR magnitudes were then made between the healthy and unhealthy system to detect any difference. The studies were conducted at power frequency for a uniform soil with different soil resistivities. It was found that full breaks in the double bond of the terminal towers increase the EPR significantly at the fault location, while they reduce EPR at the terminal tower bases. A fault on the isolated section of the grid can result in EPR values up to 8 times of those on a healthy system at higher soil resistivities, provided that the extended earthing system stays connected to the grid.

Keywords: bonding, earthing, EPR, integrity, system

Procedia PDF Downloads 315

Authors: Gyu-Dong Kim, Wuk-Jae Yoo, Sang-Youl Lee

Abstract:

Composite structures offer numerous advantages over conventional structural systems in the form of higher specific stiffness and strength, lower life-cycle costs, and benefits such as easy installation and improved safety. Recently, there has been a considerable increase in the use of composites in engineering applications and as wraps for seismic upgrading and repairs. However, these composites deteriorate with time because of outdated materials, excessive use, repetitive loading, climatic conditions, manufacturing errors, and deficiencies in inspection methods. In particular, damaged fibers in a composite result in significant degradation of structural performance. In order to reduce the failure probability of composites in service, techniques to assess the condition of the composites to prevent continual growth of fiber damage are required. Condition assessment technology and nondestructive evaluation (NDE) techniques have provided various solutions for the safety of structures by means of detecting damage or defects from static or dynamic responses induced by external loading. A variety of techniques based on detecting the changes in static or dynamic behavior of isotropic structures has been developed in the last two decades. These methods, based on analytical approaches, are limited in their capabilities in dealing with complex systems, primarily because of their limitations in handling different loading and boundary conditions. Recently, investigators have introduced direct search methods based on metaheuristics techniques and artificial intelligence, such as genetic algorithms (GA), simulated annealing (SA) methods, and neural networks (NN), and have promisingly applied these methods to the field of structural identification. Among them, GAs attract our attention because they do not require a considerable amount of data in advance in dealing with complex problems and can make a global solution search possible as opposed to classical gradient-based optimization techniques. In this study, we propose an alternative damage-detection technique that can determine the degraded stiffness distribution of vibrating laminated composites made of Glass Fiber-reinforced Polymer (GFRP). The proposed method uses a modified form of the bivariate Gaussian distribution function to detect degraded stiffness characteristics. In addition, this study presents a method to detect the fiber property variation of laminated composite plates from the micromechanical point of view. The finite element model is used to study free vibrations of laminated composite plates for fiber stiffness degradation. In order to solve the inverse problem using the combined method, this study uses only first mode shapes in a structure for the measured frequency data. In particular, this study focuses on the effect of the interaction among various parameters, such as fiber angles, layup sequences, and damage distributions, on fiber-stiffness damage detection.

Keywords: stiffness detection, fiber damage, genetic algorithm, layup sequences

Procedia PDF Downloads 251

Authors: Stephen Rathinaraj Benjamin, Flavio Colmati Junior, Maria Izabel Florindo Guedes, Rosa Amalia Fireman Dutra

Abstract:

A new enzymatic electrochemical biosensor based on multiwall carbon nanotubes and cerium oxide nanoparticles for the detection of rutin has been developed. The cerium oxide nanoparticles /HRP/ multiwall carbon nanotubes/ carbon paste electrode (HRP/ CeO2/MWCNTs/CPE) was prepared by ensuing addition of MWCNTs and HRP on the CPE, followed by the mixing with cerium oxide nanoparticles. Surface physical characteristics of the modified electrode and the electrochemical properties of the composite were investigated by scanning electron microscopy (SEM), transmission electron microscopy (TEM), cylic voltammetry (CV), differential pulse voltammetry (DPV) and square wave voltammetry (SWV). The HRP/ CeO2/MWCNTs/CPE showed good selectivity, stability and reproducibility, which was further applied to detect rutin tablet and capsule samples with satisfactory results.

Keywords: cerium dioxide nanoparticles, horseradish peroxidase, multiwall carbon nanotubes, rutin

Procedia PDF Downloads 374

Authors: Yang Luo, Beibei Wang

Abstract:

In this paper, we present a design methodology of lightweight register transfer level (RTL) hardware threat implemented based on a MAX II FPGA platform. The dynamic power consumed by the toggling of the various bit of registers as well as the dynamic power consumed per unit of logic circuits were analyzed. The hardware threat was designed taking advantage of the differences in dynamic power consumed per unit of logic circuits to hide the transfer information. The experiment result shows that the register hardware threat was successfully implemented by using different dynamic power consumed per unit of logic circuits to hide the key information of DES encryption module. It needs more than 100000 sample curves to reduce the background noise by comparing the sample space when it completely meets the time alignment requirement. In additional, an external trigger signal is playing a very important role to detect the hardware threat in this experiment.

Keywords: side-channel analysis, hardware Trojan, register transfer level, dynamic power

Procedia PDF Downloads 263

Authors: A. T. Kuda, J. J. Dayya, A. Jimoh

Abstract:

This paper investigates the fault detection and Isolation technique of measurement data sets from a three tank system using analytical model-based temporal redundancy which is based on residual generation using parity equations/space approach. It further briefly outlines other approaches of model-based residual generation. The basic idea of parity space residual generation in temporal redundancy is dynamic relationship between sensor outputs and actuator inputs (input-output model). These residuals where then used to detect whether or not the system is faulty and indicate the location of the fault when it is faulty. The method obtains good results by detecting and isolating faults from the considered data sets measurements generated from the system.

Keywords: fault detection, fault isolation, disturbing influences, system failure, parity equation/relation, structured parity equations

Procedia PDF Downloads 284

Authors: Ananta Kumar Das, Sujit Kumar Chakrabarti

Abstract:

Architectural tactics such as heartbeat, ping-echo, encapsulate, encrypt data are techniques that are used to achieve quality attributes of a system. Detecting architectural tactics has several benefits: it can aid system comprehension (e.g., legacy systems) and in the estimation of quality attributes such as safety, security, maintainability, etc. Architectural tactics are typically spread over the source code and are implicit. For large codebases, manual detection is often not feasible. Therefore, there is a need for automated methods of detection of architectural tactics. This paper presents a formalization of the heartbeat architectural tactic and a program analytic approach to detect this tactic in source code. The experiment of the proposed method is done on a set of Java applications. The outcome of the experiment strongly suggests that the method compares well with a manual approach in terms of its sensitivity and specificity, and far supersedes a manual exercise in terms of its scalability.

Keywords: software architecture, architectural tactics, detecting architectural tactics, program analysis, AST, alias analysis

Procedia PDF Downloads 140

Authors: Yasmine Abu Adla, Racha Soubra, Milana Kasab, Mohamad O. Diab, Aly Chkeir

Abstract:

Over the past several years, researchers have shown a great interest in assessing the mobility of elderly people to measure their functional status. Usually, such an assessment is done by conducting tests that require the subject to walk a certain distance, turn around, and finally sit back down. Consequently, this study aims to provide an at home monitoring system to assess the patient’s status continuously. Thus, we proposed a technique to automatically detect when a subject sits down while walking at home. In this study, we utilized a Doppler radar system to capture the motion of the subjects. More than 20 features were extracted from the radar signals, out of which 11 were chosen based on their intraclass correlation coefficient (ICC > 0.75). Accordingly, the sequential floating forward selection wrapper was applied to further narrow down the final feature vector. Finally, 5 features were introduced to the linear discriminant analysis classifier, and an accuracy of 93.75% was achieved as well as a precision and recall of 95% and 90%, respectively.

Keywords: Doppler radar system, stand-to-sit phase, TUG test, machine learning, classification

Procedia PDF Downloads 145

Authors: Namhun Lee, Seong Jin Kim

Abstract:

The construction industry represents one of the largest industries in the United States, yet it continues to face several occupational health and safety challenges. Many workers on construction sites are suffering from extended exposure to stressful situations such as poor and hazardous work environments and task complexity. Stress can be commonly defined as a feeling of emotional or physical tension, which can easily impact construction safety and result in a higher rate of job-related injuries in the construction industry. Physiological signals transmitted from wearable biosensors can be used to detect excessive stress. Therefore, workers’ stress should be detected and mitigated to prevent any type of serious incident or accident proactively. By doing this, construction productivity, as well as job satisfaction, would also be improved in the construction industry. To establish a foundation in this field of research, a conceptual framework for using wearable technology for construction safety has been developed for continuous and automatic monitoring of worker’s stress. The conceptual framework will serve as a foothold in future studies on the application of wearable technology for construction safety.

Keywords: construction safety, occupational stress, stress monitoring, wearable biosensors

Procedia PDF Downloads 137

Authors: Magdi M. E. Zumrawi

Abstract:

Crossing culverts are essential element of rural roads. The paper aims to investigate failures of recently constructed wadi-crossing pipe culverts in Sennar state and provide necessary remedial measures. The investigation is conducted to provide an extensive diagnosis study in order to find out the main structural and hydrological weaknesses of the culverts. Literature of steel pipe culverts related to construction practices and common types of culvert failures and their appropriate mitigation measures were reviewed. A detailed field survey was conducted to detect failures and defects appeared on the existing culverts. The results revealed that seepage of water through the embankment and foundation of the culverts leads to excessive erosion and scouring causing sever failures and damages. The design mistakes and poor construction were detected as the main causes of culverts failures. For sustainability of the culverts, various remedial measures are recommended to be considered in urgent rehabilitation of the existing crossings.

Keywords: culvert, erosion, failure, sustainability

Procedia PDF Downloads 297

Authors: Jyun-Guo You, Wei-Lung Tseng

Abstract:

Herein, this study represents a synthetic route for producing highly luminescent AuNCs based on the integration of two concepts, including thiol-induced luminescence enhancement of ligand-insufficient GSH-AuNCs and Ce3+-induced aggregation of GSH-AuNCs. The synthesis of GSH-AuNCs was conducted by modifying the previously reported procedure. To produce more Au(I)-GSH complexes on the surface of ligand-insufficient GSH-AuNCs, the extra GSH is added to attach onto the AuNC surface. The formed ligand-sufficient GSH-AuNCs (LS-GSH-AuNCs) emit relatively strong luminescence. The luminescence of LS-GSH-AuNCs is further enhanced by the coordination of two carboxylic groups (pKa1 = 2 and pKa2 = 3.5) of GSH and lanthanide ions, which induce the self-assembly of LS-GSH-AuNCs. As a result, the quantum yield of the self-assembled LS-GSH-AuNCs (SA-AuNCs) was improved to be 13%. Interestingly, the SA-AuNCs were dissembled into LS-GSH-AuNCs in the presence of adenosine triphosphate (ATP) because of the formation of the ATP- lanthanide ion complexes. Our assay was employed to detect alkaline phosphatase (ALP) activity over the range of 0.1−10 U/mL with a limit of detection (LOD) of 0.03 U/mL.

Keywords: self-assembly, lanthanide ion, adenosine triphosphate, alkaline phosphatase

Procedia PDF Downloads 158