Search results for: virus detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4044

Search results for: virus detection

1014 Lightweight Hardware Firewall for Embedded System Based on Bus Transactions

Authors: Ziyuan Wu, Yulong Jia, Xiang Zhang, Wanting Zhou, Lei Li

Abstract:

The Internet of Things (IoT) is a rapidly evolving field involving a large number of interconnected embedded devices. In the design of embedded System-on-Chip (SoC), the key issues are power consumption, performance, and security. However, the easy-to-implement software and untrustworthy third-party IP cores may threaten the safety of hardware assets. Considering that illegal access and malicious attacks against SoC resources pass through the bus that integrates IPs, we propose a Lightweight Hardware Firewall (LHF) to protect SoC, which monitors and disallows the offending bus transactions based on physical addresses. Furthermore, under the LHF architecture, this paper refines two types of firewalls: Destination Hardware Firewall (DHF) and Source Hardware Firewall (SHF). The former is oriented to fine-grained detection and configuration, whose core technology is based on the method of dynamic grading units. In addition, we design the SHF based on static entries to achieve lightweight. Finally, we evaluate the hardware consumption of the proposed method by both Field-Programmable Gate Array (FPGA) and IC. Compared with the exciting efforts, LHF introduces a bus latency of zero clock cycles for every read or write transaction implemented on Xilinx Kintex-7 FPGAs. Meanwhile, the DC synthesis results based on TSMC 90nm show that the area is reduced by about 25% compared with the previous method.

Keywords: IoT, security, SoC, bus architecture, lightweight hardware firewall, FPGA

Procedia PDF Downloads 61
1013 An Assessment of the Temperature Change Scenarios Using RS and GIS Techniques: A Case Study of Sindh

Authors: Jan Muhammad, Saad Malik, Fadia W. Al-Azawi, Ali Imran

Abstract:

In the era of climate variability, rising temperatures are the most significant aspect. In this study PRECIS model data and observed data are used for assessing the temperature change scenarios of Sindh province during the first half of present century. Observed data from various meteorological stations of Sindh are the primary source for temperature change detection. The current scenario (1961–1990) and the future one (2010-2050) are acted by the PRECIS Regional Climate Model at a spatial resolution of 25 * 25 km. Regional Climate Model (RCM) can yield reasonably suitable projections to be used for climate-scenario. The main objective of the study is to map the simulated temperature as obtained from climate model-PRECIS and their comparison with observed temperatures. The analysis is done on all the districts of Sindh in order to have a more precise picture of temperature change scenarios. According to results the temperature is likely to increases by 1.5 - 2.1°C by 2050, compared to the baseline temperature of 1961-1990. The model assesses more accurate values in northern districts of Sindh as compared to the coastal belt of Sindh. All the district of the Sindh province exhibit an increasing trend in the mean temperature scenarios and each decade seems to be warmer than the previous one. An understanding of the change in temperatures is very vital for various sectors such as weather forecasting, water, agriculture, and health, etc.

Keywords: PRECIS Model, real observed data, Arc GIS, interpolation techniques

Procedia PDF Downloads 249
1012 Evaluation of the Accuracy of a ‘Two Question Screening Tool’ in the Detection of Intimate Partner Violence in a Primary Healthcare Setting in South Africa

Authors: A. Saimen, E. Armstrong, C. Manitshana

Abstract:

Intimate partner violence (IPV) has been recognised as a global human rights violation. It is universally under diagnosed and the institution of timeous multi-faceted interventions has been noted to benefit IPV victims. Currently, the concept of using a screening tool to detect IPV has not been widely explored in a primary healthcare setting in South Africa, and it was for this reason that this study has been undertaken. A systematic random sampling of 1 in 8 women over a period of 3 months was conducted prospectively at the OPD of a Level 1 Hospital. Participants were asked about their experience of IPV during the past 12 months. The WAST-short, a two-question tool, was used to screen patients for IPV. To verify the result of the screening, women were also asked the remaining questions from the WAST. Data was collected from 400 participants, with a response rate of 99.3%. The prevalence of IPV in the sample was 32%. The WAST-short was shown to have the following operating characteristics: sensitivity 45.2%, specificity 98%,positive predictive value 98%, negative predictive value 79%. The WAST-short lacks sufficient sensitivity and therefore is not an ideal screening tool for this setting. Improvement in the sensitivity of the WAST-short in this setting may be achieved by lowering the threshold for a positive result for IPV screening, and modification of the screening questions to better reflect IPV as understood by the local population.

Keywords: domestic violence, intimate partner violence, screening, screening tools

Procedia PDF Downloads 305
1011 Gene Prediction in DNA Sequences Using an Ensemble Algorithm Based on Goertzel Algorithm and Anti-Notch Filter

Authors: Hamidreza Saberkari, Mousa Shamsi, Hossein Ahmadi, Saeed Vaali, , MohammadHossein Sedaaghi

Abstract:

In the recent years, using signal processing tools for accurate identification of the protein coding regions has become a challenge in bioinformatics. Most of the genomic signal processing methods is based on the period-3 characteristics of the nucleoids in DNA strands and consequently, spectral analysis is applied to the numerical sequences of DNA to find the location of periodical components. In this paper, a novel ensemble algorithm for gene selection in DNA sequences has been presented which is based on the combination of Goertzel algorithm and anti-notch filter (ANF). The proposed algorithm has many advantages when compared to other conventional methods. Firstly, it leads to identify the coding protein regions more accurate due to using the Goertzel algorithm which is tuned at the desired frequency. Secondly, faster detection time is achieved. The proposed algorithm is applied on several genes, including genes available in databases BG570 and HMR195 and their results are compared to other methods based on the nucleotide level evaluation criteria. Implementation results show the excellent performance of the proposed algorithm in identifying protein coding regions, specifically in identification of small-scale gene areas.

Keywords: protein coding regions, period-3, anti-notch filter, Goertzel algorithm

Procedia PDF Downloads 387
1010 Collective Intelligence-Based Early Warning Management for Agriculture

Authors: Jarbas Lopes Cardoso Jr., Frederic Andres, Alexandre Guitton, Asanee Kawtrakul, Silvio E. Barbin

Abstract:

The important objective of the CyberBrain Mass Agriculture Alarm Acquisition and Analysis (CBMa4) project is to minimize the impacts of diseases and disasters on rice cultivation. For example, early detection of insects will reduce the volume of insecticides that is applied to the rice fields through the use of CBMa4 platform. In order to reach this goal, two major factors need to be considered: (1) the social network of smart farmers; and (2) the warning data alarm acquisition and analysis component. This paper outlines the process for collecting the warning and improving the decision-making result to the warning. It involves two sub-processes: the warning collection and the understanding enrichment. Human sensors combine basic suitable data processing techniques in order to extract warning related semantic according to collective intelligence. We identify each warning by a semantic content called 'warncons' with multimedia metaphors and metadata related to these metaphors. It is important to describe the metric to measuring the relation among warncons. With this knowledge, a collective intelligence-based decision-making approach determines the action(s) to be launched regarding one or a set of warncons.

Keywords: agricultural engineering, warning systems, social network services, context awareness

Procedia PDF Downloads 382
1009 Configuration Design and Optimization of the Movable Leg-Foot Lunar Soft-Landing Device

Authors: Shan Jia, Jinbao Chen, Jinhua Zhou, Jiacheng Qian

Abstract:

Lunar exploration is a necessary foundation for deep-space exploration. For the functional limitations of the fixed landers which are widely used currently and are to expand the detection range by the use of wheeled rovers with unavoidable path-repeatability, a movable lunar soft-landing device based on cantilever type buffer mechanism and leg-foot type walking mechanism is presented. Firstly, a 20 DoFs quadruped configuration based on pushrod is proposed. The configuration is of the bionic characteristics such as hip, knee and ankle joints, and can make the kinematics of the whole mechanism unchanged before and after buffering. Secondly, the multi-function main/auxiliary buffers based on crumple-energy absorption and screw-nut mechanism, as well as the telescopic device which could be used to protect the plantar force sensors during the buffer process are designed. Finally, the kinematic model of the whole mechanism is established, and the configuration optimization of the whole mechanism is completed based on the performance requirements of slope adaptation and obstacle crossing. This research can provide a technical solution integrating soft-landing, large-scale inspection and material-transfer for future lunar exploration and even mars exploration, and can also serve as the technical basis for developing the reusable landers.

Keywords: configuration design, lunar soft-landing device, movable, optimization

Procedia PDF Downloads 158
1008 An Exploration of the Pancreatic Cancer miRNome during the Progression of the Disease

Authors: Barsha Saha, Shouvik Chakravarty, Sukanta Ray, Kshaunish Das, Nidhan K. Biswas, Srikanta Goswami

Abstract:

Pancreatic Ductal Adenocarcinoma is a well-recognised cause of cancer death with a five-year survival rate of about 9%, and its incidence in India has been found to be increased manifold in recent years. Due to delayed detection, this highly metastatic disease has a poor prognosis. Several molecular alterations happen during the progression of the disease from pre-cancerous conditions, and many such alterations could be investigated for their biomarker potential. MicroRNAs have been shown to be prognostic for PDAC patients in a variety of studies. We hereby used NGS technologies to evaluate the role of small RNA changes during pancreatic cancer development from chronic pancreatitis. Plasma samples were collected from pancreatic cancer patients (n=16), chronic pancreatitis patients (n=8), and also from normal individuals (n=16). Pancreatic tumour tissue (n=5) and adjacent normal tissue samples (n=5) were also collected. Sequencing of small RNAs was carried out after small RNAs were isolated from plasma samples and tissue samples. We find that certain microRNAs are highly deregulated in pancreatic cancer patients in comparison to normal samples. A combinatorial analysis of plasma and tissue microRNAs and subsequent exploration of their targets and altered molecular pathways could not only identify potential biomarkers for disease diagnosis but also help to understand the underlying mechanism.

Keywords: small RNA sequencing, pancreatic cancer, biomarkers, tissue sample

Procedia PDF Downloads 94
1007 Detection and Quantification of Active Pharmaceutical Ingredients as Adulterants in Garcinia cambogia Slimming Preparations Using NIR Spectroscopy Combined with Chemometrics

Authors: Dina Ahmed Selim, Eman Shawky Anwar, Rasha Mohamed Abu El-Khair

Abstract:

A rapid, simple and efficient method with minimal sample treatment was developed for authentication of Garcinia cambogia fruit peel powder, along with determining undeclared active pharmaceutical ingredients (APIs) in its herbal slimming dietary supplements using near infrared spectroscopy combined with chemometrics. Five featured adulterants, including sibutramine, metformin, orlistat, ephedrine, and theophylline are selected as target compounds. The Near infrared spectral data matrix of authentic Garcinia cambogia fruit peel and specimens degraded by intentional contamination with the five selected APIs was subjected to hierarchical clustering analysis to investigate their bundling figure. SIMCA models were established to ensure the genuiness of Garcinia cambogia fruit peel which resulted in perfect classification of all tested specimens. Adulterated samples were utilized for construction of PLSR models based on different APIs contents at minute levels of fraud practices (LOQ < 0.2% w/w).The suggested approach can be applied to enhance and guarantee the safety and quality of Garcinia fruit peel powder as raw material and in dietary supplements.

Keywords: Garcinia cambogia, Quality control, NIR spectroscopy, Chemometrics

Procedia PDF Downloads 77
1006 Agile Real-Time Field Programmable Gate Array-Based Image Processing System for Drone Imagery in Digital Agriculture

Authors: Sabiha Shahid Antora, Young Ki Chang

Abstract:

Along with various farm management technologies, imagery is an important tool that facilitates crop assessment, monitoring, and management. As a consequence, drone imaging technology is playing a vital role to capture the state of the entire field for yield mapping, crop scouting, weed detection, and so on. Although it is essential to inspect the cultivable lands in real-time for making rapid decisions regarding field variable inputs to combat stresses and diseases, drone imagery is still evolving in this area of interest. Cost margin and post-processing complexions of the image stream are the main challenges of imaging technology. Therefore, this proposed project involves the cost-effective field programmable gate array (FPGA) based image processing device that would process the image stream in real-time as well as providing the processed output to support on-the-spot decisions in the crop field. As a result, the real-time FPGA-based image processing system would reduce operating costs while minimizing a few intermediate steps to deliver scalable field decisions.

Keywords: real-time, FPGA, drone imagery, image processing, crop monitoring

Procedia PDF Downloads 113
1005 A Method for Identifying Unusual Transactions in E-commerce Through Extended Data Flow Conformance Checking

Authors: Handie Pramana Putra, Ani Dijah Rahajoe

Abstract:

The proliferation of smart devices and advancements in mobile communication technologies have permeated various facets of life with the widespread influence of e-commerce. Detecting abnormal transactions holds paramount significance in this realm due to the potential for substantial financial losses. Moreover, the fusion of data flow and control flow assumes a critical role in the exploration of process modeling and data analysis, contributing significantly to the accuracy and security of business processes. This paper introduces an alternative approach to identify abnormal transactions through a model that integrates both data and control flows. Referred to as the Extended Data Petri net (DPNE), our model encapsulates the entire process, encompassing user login to the e-commerce platform and concluding with the payment stage, including the mobile transaction process. We scrutinize the model's structure, formulate an algorithm for detecting anomalies in pertinent data, and elucidate the rationale and efficacy of the comprehensive system model. A case study validates the responsive performance of each system component, demonstrating the system's adeptness in evaluating every activity within mobile transactions. Ultimately, the results of anomaly detection are derived through a thorough and comprehensive analysis.

Keywords: database, data analysis, DPNE, extended data flow, e-commerce

Procedia PDF Downloads 56
1004 Measurement of Qashqaeian Sheep Fetus Parameters by Ultrasonography

Authors: Aboozar Dehghan, S. Sharifi, S. A. Dehghan, Ali Aliabadi, Arash Esfandiari

Abstract:

Ultrasonography is a safe, available and particular method in diagnostic imaging science. In ultrasonography most of body soft tissue imaged in B mode display. Iranian Qashqaeian sheep is an old and domestic breed in Zagros mountain area in central plateau of Iran. Population of this breed in Fars state (study location) is 250000 animals. Gestation age detection in sheep was performed by ultarasonography in Kivircik breed in 2010 in turkey. In this study 5 adult, clinically healthy, Iranian ewes and 1 Iranian ram were selected. We measured biparital diameter that thickened part of fetal skull include (BPD), trunk diameter (TD), fetal heart diameter(FHD), intercostals space of fetus (ICS) and fetal heart rate per minute (FHR) weekly after day 60 after pregnancy. Inguinal area in both sides shaved and cleaned by alcohol 70 degree and covered by enough copulating gel. Trans abdominal Ultarasonography was performed by a convex multi frequency transducer with 2.5-5 MHz frequency. Data were collected and analyzed by on way Annova method in Spss15 software. Mean of BPD, TD, FHD and ICS in day 60 were 14.58, 25.92, 3.53, 2.3mm. FHR can measure on day 109 to 150. TD after day 109 cannot displayed in 1 frame in scanning. Ultrasonography in sheep pregnancy is a particular method. Using this study can help in theriogeniologic disease that affected fetal growth. Differentiating between various sheep breed is a functional result of this study.

Keywords: qashqaeian sheep, fetometry, ultrasonography

Procedia PDF Downloads 545
1003 Motion Performance Analyses and Trajectory Planning of the Movable Leg-Foot Lander

Authors: Shan Jia, Jinbao Chen, Jinhua Zhou, Jiacheng Qian

Abstract:

In response to the functional limitations of the fixed landers, those are to expand the detection range by the use of wheeled rovers with unavoidable path-repeatability in deep space exploration currently, a movable lander based on the leg-foot walking mechanism is presented. Firstly, a quadruped landing mechanism based on pushrod-damping is proposed. The configuration is of the bionic characteristics such as hip, knee and ankle joints, and the multi-function main/auxiliary buffers based on the crumple-energy absorption and screw-nut mechanism. Secondly, the workspace of the end of the leg-foot mechanism is solved by Monte Carlo method, and the key points on the desired trajectory of the end of the leg-foot mechanism are fitted by cubic spline curve. Finally, an optimal time-jerk trajectory based on weight coefficient is planned and analyzed by an adaptive genetic algorithm (AGA). The simulation results prove the rationality and stability of walking motion of the movable leg-foot lander in the star catalogue. In addition, this research can also provide a technical solution integrating of soft-landing, large-scale inspection and material transfer for future star catalogue exploration, and can even serve as the technical basis for developing the reusable landers.

Keywords: motion performance, trajectory planning, movable, leg-foot lander

Procedia PDF Downloads 139
1002 Vision-Based Collision Avoidance for Unmanned Aerial Vehicles by Recurrent Neural Networks

Authors: Yao-Hong Tsai

Abstract:

Due to the sensor technology, video surveillance has become the main way for security control in every big city in the world. Surveillance is usually used by governments for intelligence gathering, the prevention of crime, the protection of a process, person, group or object, or the investigation of crime. Many surveillance systems based on computer vision technology have been developed in recent years. Moving target tracking is the most common task for Unmanned Aerial Vehicle (UAV) to find and track objects of interest in mobile aerial surveillance for civilian applications. The paper is focused on vision-based collision avoidance for UAVs by recurrent neural networks. First, images from cameras on UAV were fused based on deep convolutional neural network. Then, a recurrent neural network was constructed to obtain high-level image features for object tracking and extracting low-level image features for noise reducing. The system distributed the calculation of the whole system to local and cloud platform to efficiently perform object detection, tracking and collision avoidance based on multiple UAVs. The experiments on several challenging datasets showed that the proposed algorithm outperforms the state-of-the-art methods.

Keywords: unmanned aerial vehicle, object tracking, deep learning, collision avoidance

Procedia PDF Downloads 160
1001 Insecticide Resistance Detection on Dengue Vector, Aedes albopictus Obtained from Kapit, Kuching and Sibu Districts in Sarawak State, Malaysia

Authors: Koon Weng Lau, Chee Dhang Chen, Abdul Aziz Azidah, Mohd Sofian-Azirun

Abstract:

Recently, Sarawak state of Malaysia encounter an outbreak of dengue fever. Aedes albopictus has incriminated as one of the important vectors of dengue transmission. Without an effective vaccine, approaches to control or prevent dengue will be a focus on the vectors. The control of Aedes mosquitoes is still dependent on the use of chemical insecticides and insecticide resistance represents a threat to the effectiveness of vector control. This study was conducted to determine the resistance status of 11 active ingredients representing four major insecticide classes: DDT, dieldrin, malathion, fenitrothion, bendiocarb, propoxur, etofenprox, deltamethrin, lambda-cyhalothrin, cyfluthrin, and permethrin. Standard WHO test procedures were conducted to determine the insecticide susceptibility. Aedes albopictus collected from Kapit (resistance ratio, RR = 1.04–3.02), Kuching (RR = 1.17–4.61), and Sibu (RR = 1.06–3.59) exhibited low resistance toward all insecticides except dieldrin. This study reveled that dieldrin is still effective against Ae. albopictus, followed by fenitrothion, cyfluthrin, and deltamethrin. In conclusion, Ae. albopictus in Sarawak exhibited different resistance levels toward various insecticides and alternative solutions should be implemented to prevent further deterioration of the condition.

Keywords: Aedes albopictus, dengue, insecticide resistance, Malaysia

Procedia PDF Downloads 354
1000 Detection the Abundance of Chicken Skin in Hamburger in Tehran

Authors: Ghazanfari Masoumeh, Hajimohammadi Bahador, Eskandari Soheyl, Karimian Khosroshahi Nader

Abstract:

Consumption of ready to cook meat products such as hamburgers, sausages and etc is being increased in the worldwide specially in the big cities , so safety and quality required for food products is very important and vital for consumers with consideration of meat price and increasing demands for meat products, possibility of substitution of cheep and unauthorized textures such as undesirable enclosures animals (massacre, lung tissue, breast of spleen, the organs abdominal cavity, gizzard chicken, skin, etc. ) have increased in the recent years, in this study 30 industrial and 30 handmade hamburgers in fast food restaurants detected out of Iranian national standard for hamburger No. 2304 in using the unauthorized textures. The purpose of this study was to determine using of chicken skin in produced hamburgers from chicken meat in Tehran base on histology methods. The rates of skin used were, 2 % in industrial and 9 % in handmade formula samples. Statistically using the unauthorized textures had significant higher rate in handmade (P < 0.05) in compare with the industrial samples. The results showed the handmade hamburgers with higher adulteration rate and non-compliance with the hamburger national standard could be a potentially health hazard.

Keywords: histology, adulteration, unauthorized textures, undesirable enclosures animals

Procedia PDF Downloads 455
999 Design an Algorithm for Software Development in CBSE Envrionment Using Feed Forward Neural Network

Authors: Amit Verma, Pardeep Kaur

Abstract:

In software development organizations, Component based Software engineering (CBSE) is emerging paradigm for software development and gained wide acceptance as it often results in increase quality of software product within development time and budget. In component reusability, main challenges are the right component identification from large repositories at right time. The major objective of this work is to provide efficient algorithm for storage and effective retrieval of components using neural network and parameters based on user choice through clustering. This research paper aims to propose an algorithm that provides error free and automatic process (for retrieval of the components) while reuse of the component. In this algorithm, keywords (or components) are extracted from software document, after by applying k mean clustering algorithm. Then weights assigned to those keywords based on their frequency and after assigning weights, ANN predicts whether correct weight is assigned to keywords (or components) or not, otherwise it back propagates in to initial step (re-assign the weights). In last, store those all keywords into repositories for effective retrieval. Proposed algorithm is very effective in the error correction and detection with user base choice while choice of component for reusability for efficient retrieval is there.

Keywords: component based development, clustering, back propagation algorithm, keyword based retrieval

Procedia PDF Downloads 378
998 Application of the Electrical Resistivity Tomography and Tunnel Seismic Prediction 303 Methods for Detection Fracture Zones Ahead of Tunnel: A Case Study

Authors: Nima Dastanboo, Xiao-Qing Li, Hamed Gharibdoost

Abstract:

The purpose of this study is to investigate about the geological properties ahead of a tunnel face with using Electrical Resistivity Tomography ERT and Tunnel Seismic Prediction TSP303 methods. In deep tunnels with hydro-geological conditions, it is important to study the geological structures of the region before excavating tunnels. Otherwise, it would lead to unexpected accidents that impose serious damage to the project. For constructing Nosoud tunnel in west of Iran, the ERT and TSP303 methods are employed to predict the geological conditions dynamically during the excavation. In this paper, based on the engineering background of Nosoud tunnel, the important results of applying these methods are discussed. This work demonstrates seismic method and electrical tomography as two geophysical techniques that are able to detect a tunnel. The results of these two methods were being in agreement with each other but the results of TSP303 are more accurate and quality. In this case, the TSP 303 method was a useful tool for predicting unstable geological structures ahead of the tunnel face during excavation. Thus, using another geophysical method together with TSP303 could be helpful as a decision support in excavating, especially in complicated geological conditions.

Keywords: tunnel seismic prediction (TSP303), electrical resistivity tomography (ERT), seismic wave, velocity analysis, low-velocity zones

Procedia PDF Downloads 148
997 Non-Destructive Evaluation for Physical State Monitoring of an Angle Section Thin-Walled Curved Beam

Authors: Palash Dey, Sudip Talukdar

Abstract:

In this work, a cross-breed approach is presented for obtaining both the amount of the damage intensity and location of damage existing in thin-walled members. This cross-breed approach is developed based on response surface methodology (RSM) and genetic algorithm (GA). Theoretical finite element (FE) model of cracked angle section thin walled curved beam has been linked to the developed approach to carry out trial experiments to generate response surface functions (RSFs) of free, forced and heterogeneous dynamic response data. Subsequently, the error between the computed response surface functions and measured dynamic response data has been minimized using GA to find out the optimum damage parameters (amount of the damage intensity and location). A single crack of varying location and depth has been considered in this study. The presented approach has been found to reveal good accuracy in prediction of crack parameters and possess great potential in crack detection as it requires only the current response of a cracked beam.

Keywords: damage parameters, finite element, genetic algorithm, response surface methodology, thin walled curved beam

Procedia PDF Downloads 248
996 Choosing Mountains Over the Beach: Evaluating the Effect of Altitude on Covid Brain Severity and Treatment

Authors: Kennedy Zinn, Chris Anderson

Abstract:

Chronic Covid syndrome (CCS) is a condition in which individuals who test positive for Covid-19 experience persistent symptoms after recovering from the virus. CCS affects every organ system, including the central nervous system. Neurological “long-haul” symptoms last from a few weeks to several months and include brain fog, chronic fatigue, dyspnea, mood dysregulation, and headaches. Data suggest that 10-30% of individuals testing positive for Covid-19 develop CCS. Current literature indicates a decreased quality of life in persistent symptoms. CCS is a pervasive and pernicious COVID-19 sequelae. More research is needed to understand risk factors, impact, and possible interventions. Research frequently cites cytokine storming as noteworthy etiology in CCS. Cytokine storming is a malfunctional immune response and facilitates multidimensional interconnected physiological responses. The most prominent responses include abnormal blood flow, hypoxia/hypoxemia, inflammation, and endothelial damage. Neurological impairments and pathogenesis in CCS parallel that of traumatic brain injury (TBI). Both exhibit impairments in memory, cognition, mood, sustained attention, and chronic fatigue. Evidence suggests abnormal blood flow, inflammation, and hypoxemia as shared causal factors. Cytokine storming is also typical in mTBI. The shared characteristics in symptoms and etiology suggest potential parallel routes of investigation that allow for better understanding of CCS. Research on the effect of altitude in mTBI varies. Literature finds decreased rates of concussions at higher altitudes. Other studies suggest that at a higher altitude, pre-existing mTBI symptoms are exacerbated. This may mean that in CCS, the geographical location where individuals live and the location where individuals experienced acute Covid-19 symptoms may influence the severity and risk of developing CCS. It also suggests that clinics which treat mTBI patients could also provide benefits for those with CCS. This study aims to examine the relationships between altitude and CCS as a risk factor and investigate the longevity and severity of symptoms in different altitudes. Existing patient data from a concussion clinic using fMRI scans and self-reported symptoms will be used for approximately 30 individuals with CCS symptoms. The association between acclimated altitude and CCS severity will be analyzed. Patients will be classified into low, medium, and high altitude groups and compared for differences on fMRI severity scores and self-reported measures. It is anticipated that individuals living in lower altitudes are at higher risk of developing more severe neuropsychological symptoms in CCS. It is also anticipated that a treatment approach for mTBI will also be beneficial to those with CCS.

Keywords: altitude, chronic covid syndrome, concussion, covid brain, EPIC treatment, fMRI, traumatic brain injury

Procedia PDF Downloads 132
995 A Real Time Development Study for Automated Centralized Remote Monitoring System at Royal Belum Forest

Authors: Amri Yusoff, Shahrizuan Shafiril, Ashardi Abas, Norma Che Yusoff

Abstract:

Nowadays, illegal logging has been causing much effect to our forest. Some of it causes a flash flood, avalanche, global warming, and etc. This comprehensibly makes us wonder why, what, and who has made it happened. Often, it already has been too late after we have known the cause of it. Even the Malaysian Royal Belum forest has not been spared from land clearing or illegal activity by the natives although this area has been gazetted as a protected area preserved for future generations. Furthermore, because of its sizeable and wide area, these illegal activities are difficult to monitor and to maintain. A critical action must be called upon to prevent all of these unhealthy activities from recurrence. Therefore, a remote monitoring device must be developed in order to capture critical real-time data such as temperature, humidity, gaseous, fire, and rain detection which indicates the current and preserved natural state and habitat in the forest. Besides, this device location can be detected via GPS by showing the latitudes and longitudes of its current location and then to be transmitted by SMS via GSM system. All of its readings will be sent in real-time for data management and analysis. This result will be benefited to the monitoring bodies or relevant authority in keeping the forest in the natural habitat. Furthermore, this research is to gather a unified data and then will be analysed for its comparison with an existing method.

Keywords: remote monitoring system, forest data, GSM, GPS, wireless sensor

Procedia PDF Downloads 417
994 Accurate Position Electromagnetic Sensor Using Data Acquisition System

Authors: Z. Ezzouine, A. Nakheli

Abstract:

This paper presents a high position electromagnetic sensor system (HPESS) that is applicable for moving object detection. The authors have developed a high-performance position sensor prototype dedicated to students’ laboratory. The challenge was to obtain a highly accurate and real-time sensor that is able to calculate position, length or displacement. An electromagnetic solution based on a two coil induction principal was adopted. The HPESS converts mechanical motion to electric energy with direct contact. The output signal can then be fed to an electronic circuit. The voltage output change from the sensor is captured by data acquisition system using LabVIEW software. The displacement of the moving object is determined. The measured data are transmitted to a PC in real-time via a DAQ (NI USB -6281). This paper also describes the data acquisition analysis and the conditioning card developed specially for sensor signal monitoring. The data is then recorded and viewed using a user interface written using National Instrument LabVIEW software. On-line displays of time and voltage of the sensor signal provide a user-friendly data acquisition interface. The sensor provides an uncomplicated, accurate, reliable, inexpensive transducer for highly sophisticated control systems.

Keywords: electromagnetic sensor, accurately, data acquisition, position measurement

Procedia PDF Downloads 285
993 Development of Lipid Architectonics for Improving Efficacy and Ameliorating the Oral Bioavailability of Elvitegravir

Authors: Bushra Nabi, Saleha Rehman, Sanjula Baboota, Javed Ali

Abstract:

Aim: The objective of research undertaken is analytical method validation (HPLC method) of an anti-HIV drug Elvitegravir (EVG). Additionally carrying out the forced degradation studies of the drug under different stress conditions to determine its stability. It is envisaged in order to determine the suitable technique for drug estimation, which would be employed in further research. Furthermore, comparative pharmacokinetic profile of the drug from lipid architectonics and drug suspension would be obtained post oral administration. Method: Lipid Architectonics (LA) of EVR was formulated using probe sonication technique and optimized using QbD (Box-Behnken design). For the estimation of drug during further analysis HPLC method has been validation on the parameters (Linearity, Precision, Accuracy, Robustness) and Limit of Detection (LOD) and Limit of Quantification (LOQ) has been determined. Furthermore, HPLC quantification of forced degradation studies was carried out under different stress conditions (acid induced, base induced, oxidative, photolytic and thermal). For pharmacokinetic (PK) study, Albino Wistar rats were used weighing between 200-250g. Different formulations were given per oral route, and blood was collected at designated time intervals. A plasma concentration profile over time was plotted from which the following parameters were determined:

Keywords: AIDS, Elvitegravir, HPLC, nanostructured lipid carriers, pharmacokinetics

Procedia PDF Downloads 138
992 Identification of Potential Predictive Biomarkers for Early Diagnosis of Preeclampsia Growth Factors to microRNAs

Authors: Sadia Munir

Abstract:

Preeclampsia is the contributor to the worldwide maternal mortality of approximately 100,000 deaths a year. It complicates about 10% of all pregnancies and is the first cause of maternal admission to intensive care units. Predicting preeclampsia is a major challenge in obstetrics. More importantly, no major progress has been achieved in the treatment of preeclampsia. As placenta is the main cause of the disease, the only way to treat the disease is to extract placental and deliver the baby. In developed countries, the cost of an average case of preeclampsia is estimated at £9000. Interestingly, preeclampsia may have an impact on the health of mother or infant, beyond the pregnancy. We performed a systematic search of PubMed including the combination of terms such as preeclampsia, biomarkers, treatment, hypoxia, inflammation, oxidative stress, vascular endothelial growth factor A, activin A, inhibin A, placental growth factor, transforming growth factor β-1, Nodal, placenta, trophoblast cells, microRNAs. In this review, we have summarized current knowledge on the identification of potential biomarkers for the diagnosis of preeclampsia. Although these studies show promising data in early diagnosis of preeclampsia, the current value of these factors as biomarkers, for the precise prediction of preeclampsia, has its limitation. Therefore, future studies need to be done to support some of the very promising and interesting data to develop affordable and widely available tests for early detection and treatment of preeclampsia.

Keywords: activin, biomarkers, growth factors, miroRNA

Procedia PDF Downloads 441
991 Self-Calibration of Fish-Eye Camera for Advanced Driver Assistance Systems

Authors: Atef Alaaeddine Sarraj, Brendan Jackman, Frank Walsh

Abstract:

Tomorrow’s car will be more automated and increasingly connected. Innovative and intuitive interfaces are essential to accompany this functional enrichment. For that, today the automotive companies are competing to offer an advanced driver assistance system (ADAS) which will be able to provide enhanced navigation, collision avoidance, intersection support and lane keeping. These vision-based functions require an accurately calibrated camera. To achieve such differentiation in ADAS requires sophisticated sensors and efficient algorithms. This paper explores the different calibration methods applicable to vehicle-mounted fish-eye cameras with arbitrary fields of view and defines the first steps towards a self-calibration method that adequately addresses ADAS requirements. In particular, we present a self-calibration method after comparing different camera calibration algorithms in the context of ADAS requirements. Our method gathers data from unknown scenes while the car is moving, estimates the camera intrinsic and extrinsic parameters and corrects the wide-angle distortion. Our solution enables continuous and real-time detection of objects, pedestrians, road markings and other cars. In contrast, other camera calibration algorithms for ADAS need pre-calibration, while the presented method calibrates the camera without prior knowledge of the scene and in real-time.

Keywords: advanced driver assistance system (ADAS), fish-eye, real-time, self-calibration

Procedia PDF Downloads 252
990 A Machine Learning Framework Based on Biometric Measurements for Automatic Fetal Head Anomalies Diagnosis in Ultrasound Images

Authors: Hanene Sahli, Aymen Mouelhi, Marwa Hajji, Amine Ben Slama, Mounir Sayadi, Farhat Fnaiech, Radhwane Rachdi

Abstract:

Fetal abnormality is still a public health problem of interest to both mother and baby. Head defect is one of the most high-risk fetal deformities. Fetal head categorization is a sensitive task that needs a massive attention from neurological experts. In this sense, biometrical measurements can be extracted by gynecologist doctors and compared with ground truth charts to identify normal or abnormal growth. The fetal head biometric measurements such as Biparietal Diameter (BPD), Occipito-Frontal Diameter (OFD) and Head Circumference (HC) needs to be monitored, and expert should carry out its manual delineations. This work proposes a new approach to automatically compute BPD, OFD and HC based on morphological characteristics extracted from head shape. Hence, the studied data selected at the same Gestational Age (GA) from the fetal Ultrasound images (US) are classified into two categories: Normal and abnormal. The abnormal subjects include hydrocephalus, microcephaly and dolichocephaly anomalies. By the use of a support vector machines (SVM) method, this study achieved high classification for automated detection of anomalies. The proposed method is promising although it doesn't need expert interventions.

Keywords: biometric measurements, fetal head malformations, machine learning methods, US images

Procedia PDF Downloads 288
989 Saudi Human Awareness Needs: A Survey in How Human Causes Errors and Mistakes Leads to Leak Confidential Data with Proposed Solutions in Saudi Arabia

Authors: Amal Hussain Alkhaiwani, Ghadah Abdullah Almalki

Abstract:

Recently human errors have increasingly become a very high factor in security breaches that may affect confidential data, and most of the cyber data breaches are caused by human errors. With one individual mistake, the attacker will gain access to the entire network and bypass the implemented access controls without any immediate detection. Unaware employees will be vulnerable to any social engineering cyber-attacks. Providing security awareness to People is part of the company protection process; the cyber risks cannot be reduced by just implementing technology; the human awareness of security will significantly reduce the risks, which encourage changes in staff cyber-awareness. In this paper, we will focus on Human Awareness, human needs to continue the required security education level; we will review human errors and introduce a proposed solution to avoid the breach from occurring again. Recently Saudi Arabia faced many attacks with different methods of social engineering. As Saudi Arabia has become a target to many countries and individuals, we needed to initiate a defense mechanism that begins with awareness to keep our privacy and protect the confidential data against possible intended attacks.

Keywords: cybersecurity, human aspects, human errors, human mistakes, security awareness, Saudi Arabia, security program, security education, social engineering

Procedia PDF Downloads 160
988 Metal-Organic Frameworks-Based Materials for Volatile Organic Compounds Sensing Applications: Strategies to Improve Sensing Performances

Authors: Claudio Clemente, Valentina Gargiulo, Alessio Occhicone, Giovanni Piero Pepe, Giovanni Ausanio, Michela Alfè

Abstract:

Volatile organic compound (VOC) emissions represent a serious risk to human health and the integrity of the ecosystems, especially at high concentrations. For this reason, it is very important to continuously monitor environmental quality and develop fast and reliable portable sensors to allow analysis on site. Chemiresistors have become promising candidates for VOC sensing as their ease of fabrication, variety of suitable sensitive materials, and simple sensing data. A chemoresistive gas sensor is a transducer that allows to measure the concentration of an analyte in the gas phase because the changes in resistance are proportional to the amount of the analyte present. The selection of the sensitive material, which interacts with the target analyte, is very important for the sensor performance. The most used VOC detection materials are metal oxides (MOx) for their rapid recovery, high sensitivity to various gas molecules, easy fabrication. Their sensing performance can be improved in terms of operating temperature, selectivity, and detection limit. Metal-organic frameworks (MOFs) have attracted a lot of attention also in the field of gas sensing due to their high porosity, high surface area, tunable morphologies, structural variety. MOFs are generated by the self-assembly of multidentate organic ligands connecting with adjacent multivalent metal nodes via strong coordination interactions, producing stable and highly ordered crystalline porous materials with well-designed structures. However, most MOFs intrinsically exhibit low electrical conductivity. To improve this property, MOFs can be combined with organic and inorganic materials in a hybrid fashion to produce composite materials or can be transformed into more stable structures. MOFs, indeed, can be employed as the precursors of metal oxides with well-designed architectures via the calcination method. The MOF-derived MOx partially preserved the original structure with high surface area and intrinsic open pores, which act as trapping centers for gas molecules, and showed a higher electrical conductivity. Core-shell heterostructures, in which the surface of a metal oxide core is completely coated by a MOF shell, forming a junction at the core-shell heterointerface, can also be synthesized. Also, nanocomposite in which MOF structures are intercalated with graphene related materials can also be produced, and the conductivity increases thanks to the high mobility of electrons of carbon materials. As MOF structures, zinc-based MOFs belonging to the ZIF family were selected in this work. Several Zn-based materials based and/or derived from MOFs were produced, structurally characterized, and arranged in a chemo resistive architecture, also exploring the potentiality of different approaches of sensing layer deposition based on PLD (pulsed laser deposition) and, in case of thermally labile materials, MAPLE (Matrix Assisted Pulsed Laser Evaporation) to enhance the adhesion to the support. The sensors were tested in a controlled humidity chamber, allowing for the possibility of varying the concentration of ethanol, a typical analyte chosen among the VOCs for a first survey. The effect of heating the chemiresistor to improve sensing performances was also explored. Future research will focus on exploring new manufacturing processes for MOF-based gas sensors with the aim to improve sensitivity, selectivity and reduce operating temperatures.

Keywords: chemiresistors, gas sensors, graphene related materials, laser deposition, MAPLE, metal-organic frameworks, metal oxides, nanocomposites, sensing performance, transduction mechanism, volatile organic compounds

Procedia PDF Downloads 63
987 Using Squeezed Vacuum States to Enhance the Sensitivity of Ground Based Gravitational Wave Interferometers beyond the Standard Quantum Limit

Authors: Giacomo Ciani

Abstract:

This paper reviews the impact of quantum noise on modern gravitational wave interferometers and explains how squeezed vacuum states are used to push the noise below the standard quantum limit. With the first detection of gravitational waves from a pair of colliding black holes in September 2015 and subsequent detections including that of gravitational waves from a pair of colliding neutron stars, the ground-based interferometric gravitational wave observatories LIGO and VIRGO have opened the era of gravitational-wave and multi-messenger astronomy. Improving the sensitivity of the detectors is of paramount importance to increase the number and quality of the detections, fully exploiting this new information channel about the universe. Although still in the commissioning phase and not at nominal sensitivity, these interferometers are designed to be ultimately limited by a combination of shot noise and quantum radiation pressure noise, which define an envelope known as the standard quantum limit. Despite the name, this limit can be beaten with the use of advanced quantum measurement techniques, with the use of squeezed vacuum states being currently the most mature and promising. Different strategies for implementation of the technology in the large-scale detectors, in both their frequency-independent and frequency-dependent variations, are presented, together with an analysis of the main technological issues and expected sensitivity gain.

Keywords: gravitational waves, interferometers, squeezed vacuum, standard quantum limit

Procedia PDF Downloads 151
986 Descriptive Study of Adverse Drug Reactions in a Paediatric Hospital in Mongolia from 2015 to 2019

Authors: Khaliun Nyambayar, Nomindari Azzaya, Batkhuyag Purevjav

Abstract:

Pharmacovigilance was officially introduced in Mongolia in 2003, in accordance with the Health Minister Order 183 for the registry of adverse drug reactions (ADR), approved in 2006 and was reviewed in 2010. This study was designed to evaluate the incidence and common types of adverse drug reactions among hospitalized children, the frequency of adverse drug reaction reported by health care providers, and the follow-up processes resulting from adverse drug reactions. A retrospective study of paediatric patients who experienced an adverse drug reaction from 2015 to 2019, extracted from the “yellow” card at the State Research Center for Maternal and Child Health, (city). A total of 417 adverse drug reactions were reported with an overall incidence was 80 (21.5%). Adverse reactions resulting from the use of antibiotics (particularly gentamycin, cephalosporins, and vancomycin) were usually mild. ADR’s were reported by physicians and nurses (93.8%), pharmacists (6.25%). Although documentation of physician notification occurred for 93% of adverse drug reactions, only 29% of cases were documented in the patient's medical chart, 13% included follow-up education for individuals involved, and 10% were updated in the allergy profile of the hospital computer system. Measures to improve the detection and reporting of adverse drug reactions by all health care professionals should be improved, to enhance our understanding of the nature and impact of these reactions in children.

Keywords: adverse drug reaction, pediatric, yellow card, Mongolia

Procedia PDF Downloads 113
985 Quantitative Evaluation of Endogenous Reference Genes for ddPCR under Salt Stress Using a Moderate Halophile

Authors: Qinghua Xing, Noha M. Mesbah, Haisheng Wang, Jun Li, Baisuo Zhao

Abstract:

Droplet digital PCR (ddPCR) is being increasingly adopted for gene detection and quantification because of its higher sensitivity and specificity. According to previous observations and our lab data, it is essential to use endogenous reference genes (RGs) when investigating gene expression at the mRNA level under salt stress. This study aimed to select and validate suitable RGs for gene expression under salt stress using ddPCR. Six candidate RGs were selected based on the tandem mass tag (TMT)-labeled quantitative proteomics of Alkalicoccus halolimnae at four salinities. The expression stability of these candidate genes was evaluated using statistical algorithms (geNorm, NormFinder, BestKeeper and RefFinder). There was a small fluctuation in cycle threshold (Ct) value and copy number of the pdp gene. Its expression stability was ranked in the vanguard of all algorithms, and was the most suitable RG for quantification of expression by both qPCR and ddPCR of A. halolimnae under salt stress. Single RG pdp and RG combinations were used to normalize the expression of ectA, ectB, ectC, and ectD under four salinities. The present study constitutes the first systematic analysis of endogenous RG selection for halophiles responding to salt stress. This work provides a valuable theory and an approach reference of internal control identification for ddPCR-based stress response models.

Keywords: endogenous reference gene, salt stress, ddPCR, RT-qPCR, Alkalicoccus halolimnae

Procedia PDF Downloads 104