Search results for: speed hump detection

Authors: Mamta M. Barapatre, V. N. Sahare

Abstract:

Since from long time two wheeled vehicle self-balancing has always been a back-breaking task for both human and robots. Leaning a bicycle driving is long time process and goes through building knowledge base for parameter decision making while balancing robots. In order to create this machine learning phase with embedded system the proposed system is designed. The system proposed aims to construct a bicycle automaton, power-driven by an electric motor, which could balance by itself and move along a specific path. This path could be wavy with bumps and varying widths. The key aim was to construct a cycle which self-balances itself by controlling its handle. In order to take a turn, the mass was transferred to the center. In order to maintain the stability, the bicycle bot automatically turned the handle and a turn. Some problems were faced by the team which were Speed, Steering mechanism through mass- distribution (leaning), Center of mass location and gyroscopic effect of its wheel. The idea proposed have potential applications in automation of transportation system and is most efficient.

Keywords: gyroscope-flywheel, accelerometer, servomotor-controller, self stability concept

Procedia PDF Downloads 278

Authors: Shivani Jha, Klaus Baier, Rafiq Azzam, Ramakar Jha

Abstract:

In India, generally people migrate from rural area to the urban area for better infra-structural facilities, high standard of living, good job opportunities and advanced transport/communication availability. In fact, unplanned urban development due to migration of people causes seriou damage to the land use, water pollution and available water resources. In the present work, an attempt has been made to use satellite data of different years for urban change detection of Chennai metropolitan city along with pattern analysis to generate future scenario of urban development using buffer zoning in GIS environment. In the analysis, SRTM (30m) elevation data and IRS-1C satellite data for the years 1990, 2000, and 2014, are used. The flow accumulation, aspect, flow direction and slope maps developed using SRTM 30 m data are very useful for finding suitable urban locations for industrial setup and urban settlements. Normalized difference vegetation index (NDVI) and Principal Component Analysis (PCA) have been used in ERDAS imagine software for change detection in land use of Chennai metropolitan city. It has been observed that the urban area has increased exponentially in Chennai metropolitan city with significant decrease in agriculture and barren lands. However, the water bodies located in the study regions are protected and being used as freshwater for drinking purposes. Using buffer zone analysis in GIS environment, it has been observed that the development has taken place in south west direction significantly and will do so in future.

Keywords: urban change, satellite data, the Chennai metropolis, change detection

Procedia PDF Downloads 408

Authors: Yash Jain

Abstract:

The US Center for Disease Control has recommended wearing masks to slow the spread of the virus. The research uses a video feed from a camera to conduct real-time classifications of whether or not a human is correctly wearing a mask, incorrectly wearing a mask, or not wearing a mask at all. Utilizing two distinct datasets from the open-source website Kaggle, a mask detection network had been trained. The first dataset that was used to train the model was titled 'Face Mask Detection' on Kaggle, where the dataset was retrieved from and the second dataset was titled 'Face Mask Dataset, which provided the data in a (YOLO Format)' so that the TinyYoloV3 model could be trained. Based on the data from Kaggle, two machine learning models were implemented and trained: a Tiny YoloV3 Real-time model and a two-stage neural network classifier. The two-stage neural network classifier had a first step of identifying distinct faces within the image, and the second step was a classifier to detect the state of the mask on the face and whether it was worn correctly, incorrectly, or no mask at all. The TinyYoloV3 was used for the live feed as well as for a comparison standpoint against the previous two-stage classifier and was trained using the darknet neural network framework. The two-stage classifier attained a mean average precision (MAP) of 80%, while the model trained using TinyYoloV3 real-time detection had a mean average precision (MAP) of 59%. Overall, both models were able to correctly classify stages/scenarios of no mask, mask, and incorrectly worn masks.

Keywords: datasets, classifier, mask-detection, real-time, TinyYoloV3, two-stage neural network classifier

Procedia PDF Downloads 162

Authors: Edemealem Desalegn Kingawa, Kafte Tasew Timkete, Mekashaw Girmaw Abebe, Terefe Feyisa, Abiyot Bitew Mihretie, Senait Teklemarkos Haile

Abstract:

Currently, hate speech is a growing challenge for society, individuals, policymakers, and researchers, as social media platforms make it easy to anonymously create and grow online friends and followers and provide an online forum for debate about specific issues of community life, culture, politics, and others. Despite this, research on identifying and detecting hate speech is not satisfactory performance, and this is why future research on this issue is constantly called for. This paper provides a systematic review of the literature in this field, with a focus on approaches like word embedding techniques, machine learning, deep learning technologies, hate speech terminology, and other state-of-the-art technologies with challenges. In this paper, we have made a systematic review of the last six years of literature from Research Gate and Google Scholar. Furthermore, limitations, along with algorithm selection and use challenges, data collection, and cleaning challenges, and future research directions, are discussed in detail.

Keywords: Amharic hate speech, deep learning approach, hate speech detection review, Afaan Oromo hate speech detection

Procedia PDF Downloads 177

Authors: Behrooz Nikahval, Mohammad Saeed Ahrari-Khafi, Sakineh Behroozpoor, Saeed Nazifi

Abstract:

Osteoarthritis (OA) is a progressive and degenerative condition of the articular cartilage and other joints’ structures. It is essential to diagnose this condition as early as possible. The present research was performed to measure the Osteoprotegrin (OPG) and Tumor Necrosis Factor α (TNF-α) in synovial fluid and blood serum of dogs with surgically transected cruciate ligament as a model of OA, to evaluate if measuring of these parameters can be used as a way of early diagnosis of OA. In the present study, four mature, clinically healthy dogs were selected to investigate the effect of experimental OA, on OPG and TNF-α as a way of early detection of OA. OPG and TNF-α were measured in synovial fluid and blood serum on days 0, 14, 28, 90 and 180 after surgical transaction of cranial cruciate ligament in one stifle joint. Statistical analysis of the results showed that there was a significant increase in TNF-α in both synovial fluid and blood serum. OPG showed a decrease two weeks after OA induction. However, it fluctuated afterward. In conclusion, TNF-α could be used in both synovial fluid and blood serum as a way of early detection of OA; however, further research still needs to be conducted on OPG values in OA detection.

Keywords: osteoarthritis, osteoprotegrin, tumor necrosis factor α, synovial fluid, serum, dog

Procedia PDF Downloads 318

Authors: Saman Ghaffarian, Ilgin Gökaşar

Abstract:

This paper presents a new automatic vehicle detection method from very high resolution aerial images to measure traffic density. The proposed method starts by extracting road regions from image using road vector data. Then, the road image is divided into equal sections considering resolution of the images. Gradient vectors of the road image are computed from edge map of the corresponding image. Gradient vectors on the each boundary of the sections are divided where the gradient vectors significantly change their directions. Finally, number of vehicles in each section is carried out by calculating the standard deviation of the gradient vectors in each group and accepting the group as vehicle that has standard deviation above predefined threshold value. The proposed method was tested in four very high resolution aerial images acquired from Istanbul, Turkey which illustrate roads and vehicles with diverse characteristics. The results show the reliability of the proposed method in detecting vehicles by producing 86% overall F1 accuracy value.

Keywords: aerial images, intelligent transportation systems, traffic density measurement, vehicle detection

Procedia PDF Downloads 379

Authors: Shashank Gahlaut, Chandrashekhar Sharan, J. P. Singh

Abstract:

Increasing incidence of antibiotic-resistant bacteria is a big concern for the treatment of pathogenic diseases. The effect of treatment of patients with antibiotics often leads to the evolution of antibiotic resistance in the pathogens. The detection of antibiotic or antimicrobial resistant bacteria (microbes) is quite essential as it is becoming one of the big threats globally. Here we propose a novel technique to tackle this problem. We are taking a step forward to prevent the infections and diseases due to drug resistant microbes. This detection is based on some unique features of silver (a noble metal) nanorods (AgNRs) which are fabricated by a physical deposition method called thermal glancing angle deposition (GLAD). Silver nanorods are found to be highly sensitive and selective for hydrogen sulfide (H2S) gas. Color and water wetting (contact angle) of AgNRs are two parameters what are effected in the presence of this gas. H₂S is one of the major gaseous products evolved in the bacterial metabolic process. It is also known as gasotransmitter that transmits some biological singles in living systems. Nitric Oxide (NO) and Carbon mono oxide (CO) are two another members of this family. Orlowski (1895) observed the emission of H₂S by the bacteria for the first time. Most of the microorganism produce these gases. Here we are focusing on H₂S gas evolution to determine live/dead and antibiotic-resistant bacteria. AgNRs array has been used for the detection of H₂S from micro-organisms. A mobile app is also developed to make it easy, portable, user-friendly, and cost-effective.

Keywords: antibiotic resistance, hydrogen sulfide, live and dead bacteria, mobile app

Procedia PDF Downloads 145

Authors: Ali Motalebi Saraji, Reza Zarei Lamuki

Abstract:

Speed control and behavior improvement of permanent magnet synchronous motors (PMSM) that have reliable performance, low loss, and high power density, especially in industrial drives, are of great importance for researchers. Because of its importance in this paper, coefficients optimization of proportional-integrator-derivative fractional order controller is presented using Particle Swarm Optimization (PSO) algorithm in order to improve the behavior of PMSM in its speed control loop. This improvement is simulated in MATLAB software for the proposed optimized proportional-integrator-derivative fractional order controller with a Genetic algorithm and compared with a full order controller with a classic optimization method. Simulation results show the performance improvement of the proposed controller with respect to two other controllers in terms of rising time, overshoot, and settling time.

Keywords: speed control loop of permanent magnet synchronous motor, fractional and full order proportional-integrator-derivative controller, coefficients optimization, particle swarm optimization, improvement of behavior

Procedia PDF Downloads 146

Authors: Mamouni Mohammed Dhiya Eddine

Abstract:

This work aims at studying the exploitation of high-speed networks of clusters for distributed storage. Parallel applications running on clusters require both high-performance communications between nodes and efficient access to the storage system. Many studies on network technologies led to the design of dedicated architectures for clusters with very fast communications between computing nodes. Efficient distributed storage in clusters has been essentially developed by adding parallelization mechanisms so that the server(s) may sustain an increased workload. In this work, we propose to improve the performance of distributed storage systems in clusters by efficiently using the underlying high-performance network to access distant storage systems. The main question we are addressing is: do high-speed networks of clusters fit the requirements of a transparent, efficient and high-performance access to remote storage? We show that storage requirements are very different from those of parallel computation. High-speed networks of clusters were designed to optimize communications between different nodes of a parallel application. We study their utilization in a very different context, storage in clusters, where client-server models are generally used to access remote storage (for instance NFS, PVFS or LUSTRE). Our experimental study based on the usage of the GM programming interface of MYRINET high-speed networks for distributed storage raised several interesting problems. Firstly, the specific memory utilization in the storage access system layers does not easily fit the traditional memory model of high-speed networks. Secondly, client-server models that are used for distributed storage have specific requirements on message control and event processing, which are not handled by existing interfaces. We propose different solutions to solve communication control problems at the filesystem level. We show that a modification of the network programming interface is required. Data transfer issues need an adaptation of the operating system. We detail several propositions for network programming interfaces which make their utilization easier in the context of distributed storage. The integration of a flexible processing of data transfer in the new programming interface MYRINET/MX is finally presented. Performance evaluations show that its usage in the context of both storage and other types of applications is easy and efficient.

Keywords: distributed storage, remote file access, cluster, high-speed network, MYRINET, zero-copy, memory registration, communication control, event notification, application programming interface

Procedia PDF Downloads 219

Authors: Mini P. Singh, Manasi Majumdar, Kapil Goyal, Pvm Lakshmi, Deepak Bhatia, Radha Kanta Ratho

Abstract:

India is endemic for Hepatitis E virus and frequent water borne outbreaks are reported. The conventional diagnosis rests on the detection of serum anti-HEV IgM antibodies which may take 7-10 days to develop. Early diagnosis in such a situation is desirable for the initiation of prompt control measures. The present study compared three diagnostic methods in 60 samples collected during two suspected HEV outbreaks in the vicinity of Chandigarh, India. The anti-HEV IgM, HEV antigen and HEV-RNA could be detected in serum samples of 52 (86.66%), 16 (26.66%) and 18 (30%) patients respectively. The suitability of saliva samples for antibody detection was also evaluated in 21 paired serum- saliva samples. A total of 15 serum samples showed the presence of anti HEV IgM antibodies, out of which 10 (10/15; 66.6%) were also positive for these antibodies in saliva samples (χ2 = 7.636, p < 0.0057), thus showing a concordance of 76.91%. The positivity of reverse transcriptase PCR and HEV antigen detection was 100% within one week of illness which declined to 5-10% thereafter. The outbreak was attributed to HEV Genotype 1, Subtype 1a and the clinical and environmental strains clustered together. HEV antigen and RNA were found to be an early diagnostic marker with 96.66% concordance. The results indicate that the saliva samples can be used as an alternative to serum samples in an outbreak situation.

Keywords: HEV-antigen, outbreak, phylogenetic analysis, saliva

Procedia PDF Downloads 420

Authors: Igor Belykh

Abstract:

Anti-scatter grids used in radiographic imaging for the contrast enhancement leave specific artifacts. Those artifacts may be visible or may cause Moiré effect when a digital image is resized on a diagnostic monitor. In this paper, we propose an automated grid artifacts detection and suppression algorithm which is still an actual problem. Grid artifacts detection is based on statistical approach in spatial domain. Grid artifacts suppression is based on Kaiser bandstop filter transfer function design and application avoiding ringing artifacts. Experimental results are discussed and concluded with description of advantages over existing approaches.

Keywords: grid, computed radiography, pattern recognition, image processing, filtering

Procedia PDF Downloads 283

Authors: Mayssa Bensalah, Atef Boujelben, Mouna Baklouti, Mohamed Abid

Abstract:

Image segmentation has a fundamental role in analysis and interpretation for many applications. The automated segmentation of organs and tissues throughout the body using computed imaging has been rapidly increasing. Indeed, it represents one of the most important parts of clinical diagnostic tools. In this paper, we discuss a thorough literature review of recent methods of tumour segmentation from medical images which are briefly explained with the recent contribution of various researchers. This study was followed by comparing these methods in order to define new directions to develop and improve the performance of the segmentation of the tumour area from medical images.

Keywords: features extraction, image segmentation, medical images, tumor detection

Procedia PDF Downloads 167

Authors: Zahra Khan

Abstract:

Surface-Enhanced Raman Spectroscopy (SERS) has received increased attention in recent years, focusing on biological and medical applications due to its great sensitivity as well as molecular specificity. In the context of biological samples, there are generally two methodologies for SERS based applications: label-free detection and the use of SERS tags. The necessity of tagging can make the process slower and limits the use for real life. Label-free detection offers the advantage that it reports direct spectroscopic evidence associated with the target molecule rather than the label. Reproducible, highly monodisperse gold nanoparticles (Au NPs) were synthesized using a relatively facile seed-mediated growth method. Different capping agents (TRIS, citrate, and CTAB) were used during synthesis, and characterization was performed. They were then mixed with different analyte solutions before drop-casting onto a glass slide prior to Raman measurements to see which NPs displayed the highest SERS activity as well as their stability. A host of different analytes were tested, both non-biomolecules and biomolecules, which were all successfully detected using this method at concentrations as low as 10-3M with salicylic acid reaching a detection limit in the nanomolar range. SERS was also performed on samples with a mixture of analytes present, whereby peaks from both target molecules were distinctly observed. This is a fast and effective rapid way of testing samples and offers potential applications in the biomedical field as a tool for diagnostic and treatment purposes.

Keywords: gold nanoparticles, label free, seed-mediated growth, SERS

Procedia PDF Downloads 125

Authors: Siobhan O’Shea, Sangeetha Vijaysri Nair, Hee Cheol Kim, Charles Thomas Nugent, Cheuk Yan William Tong, Sam Douthwaite, Andrew Worlock

Abstract:

The Aptima® HIV-1 Quant Dx Assay is a fully automated assay on the Panther system. It is based on Transcription-Mediated Amplification and real time detection technologies. This assay is intended for monitoring HIV-1 viral load in plasma specimens and for the detection of HIV-1 in plasma and serum specimens. Nine-hundred and seventy nine specimens selected at random from routine testing at St Thomas’ Hospital, London were anonymised and used to compare the performance of the Aptima HIV-1 Quant Dx assay and Roche COBAS® AmpliPrep/COBAS® TaqMan® HIV-1 Test, v2.0. Two-hundred and thirty four specimens gave quantitative HIV-1 viral load results in both assays. The quantitative results reported by the Aptima Assay were comparable those reported by the Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 Test, v2.0 with a linear regression slope of 1.04 and an intercept on -0.097. The Aptima assay detected HIV-1 in more samples than the Roche assay. This was not due to lack of specificity of the Aptima assay because this assay gave 99.83% specificity on testing plasma specimens from 600 HIV-1 negative individuals. To understand the reason for this higher detection rate a side-by-side comparison of low level panels made from the HIV-1 3rd international standard (NIBSC10/152) and clinical samples of various subtypes were tested in both assays. The Aptima assay was more sensitive than the Roche assay. The good sensitivity, specificity and agreement with other commercial assays make the HIV-1 Quant Dx Assay appropriate for both viral load monitoring and detection of HIV-1 infections.

Keywords: HIV viral load, Aptima, Roche, Panther system

Procedia PDF Downloads 375

Authors: Aniela Pop, Ianina Birsan, Corina Orha, Rodica Pode, Florica Manea

Abstract:

Carbon nanofiber-epoxy composite electrode has been investigated through voltammetric and amperometric techniques in order to detect parabens from aqueous solutions. The occurrence into environment as emerging pollutants of these preservative compounds has been extensively studied in the last decades, and consequently, a rapid and reliable method for their quantitative quantification is required. In this study, methylparaben (MP) and propylparaben (PP) were chosen as representatives for paraben class. The individual electrochemical detection of each paraben has been successfully performed. Their electrochemical oxidation occurred at the same potential value. Their simultaneous quantification should be assessed electrochemically only as general index of paraben class as a cumulative signal corresponding to both MP and PP from solution. The influence of pH on the electrochemical signal was studied. pH ranged between 1.3 and 9.0 allowed shifting the detection potential value to smaller value, which is very desired for the electroanalysis. Also, the signal is better-defined and higher sensitivity is achieved. Differential-pulsed voltammetry and square-wave voltammetry were exploited under the optimum pH conditions to improve the electroanalytical performance for the paraben detection. Also, the operation conditions were selected, i.e., the step potential, modulation amplitude and the frequency. Chronomaprometry application as the easiest electrochemical detection method led to worse sensitivity, probably due to a possible fouling effect of the electrode surface. The best electroanalytical performance was achieved by pulsed voltammetric technique but the selection of the electrochemical technique is related to the concrete practical application. A good reproducibility of the voltammetric-based method using carbon nanofiber-epoxy composite electrode was determined and no interference effect was found for the cation and anion species that are common in the water matrix. Besides these characteristics, the long life-time of the electrode give to carbon nanofiber-epoxy composite electrode a great potential for practical applications.

Keywords: carbon nanofiber-epoxy composite electrode, electroanalysis, methylparaben, propylparaben

Procedia PDF Downloads 225

Authors: Philipp Wenger, Michael Beltle, Stefan Tenbohlen, Uwe Riechert

Abstract:

The integration of renewable energy introduces new challenges to the transmission grid, as the power generation is located far from load centers. The associated necessary long-range power transmission increases the demand for high voltage direct current (HVDC) transmission lines and DC distribution grids. HVDC gas-insulated switchgears (GIS) are considered being a key technology, due to the combination of the DC technology and the long operation experiences of AC-GIS. To ensure long-term reliability of such systems, insulation defects must be detected in an early stage. Operational experience with AC systems has proven evidence, that most failures, which can be attributed to breakdowns of the insulation system, can be detected and identified via partial discharge (PD) measurements beforehand. In AC systems the identification of defects relies on the phase resolved partial discharge pattern (PRPD). Since there is no phase information within DC systems this method cannot be transferred to DC PD diagnostic. Furthermore, the behaviour of e.g. free-moving particles differs significantly at DC: Under the influence of a constant direct electric field, charge carriers can accumulate on particles’ surfaces. As a result, a particle can lift-off, oscillate between the inner conductor and the enclosure or rapidly bounces at just one electrode, which is known as firefly motion. Depending on the motion and the relative position of the particle to the electrodes, broadband electromagnetic PD pulses are emitted, which can be recorded by ultra-high frequency (UHF) measuring methods. PDs are often accompanied by light emissions at the particle’s tip which enables optical detection. This contribution investigates PD characteristics of free moving metallic particles in a commercially available 300 kV SF6-insulated HVDC-GIS. The influences of various defect parameters on the particle motion and the PD characteristic are evaluated experimentally. Several particle geometries, such as cylinder, lamella, spiral and sphere with different length, diameter and weight are determined. The applied DC voltage is increased stepwise from inception voltage up to UDC = ± 400 kV. Different physical detection methods are used simultaneously in a time-synchronized setup. Firstly, the electromagnetic waves emitted by the particle are recorded by an UHF measuring system. Secondly, a photomultiplier tube (PMT) detects light emission with a wavelength in the range of λ = 185…870 nm. Thirdly, a high-speed camera (HSC) tracks the particle’s motion trajectory with high accuracy. Furthermore, an electrically insulated electrode is attached to the grounded enclosure and connected to a current shunt in order to detect low frequency ion currents: The shunt measuring system’s sensitivity is in the range of 10 nA at a measuring bandwidth of bw = DC…1 MHz. Currents of charge carriers, which are generated at the particle’s tip migrate through the gas gap to the electrode and can be recorded by the current shunt. All recorded PD signals are analyzed in order to identify characteristic properties of different particles. This includes e.g. repetition rates and amplitudes of successive pulses, characteristic frequency ranges and detected signal energy of single PD pulses. Concluding, an advanced understanding of underlying physical phenomena particle motion in direct electric field can be derived.

Keywords: current shunt, free moving particles, high-speed imaging, HVDC-GIS, UHF

Procedia PDF Downloads 160

Authors: Qiang Zhang, Xiaojian Hu1

Abstract:

Intersection is the place where vehicles and pedestrians must pass through, turn and evacuate. Obtaining the motion data of vehicles near the intersection is of great significance for transportation research. Since there are usually many targets and there are more conflicts between targets, this makes it difficult to obtain vehicle motion parameters in traffic videos of intersections. According to the characteristics of traffic videos, this paper applies video technology to realize the automated track, count and trajectory extraction of vehicles to collect traffic data by roadside surveillance cameras installed near the intersections. Based on the video recognition method, the vehicles in each lane near the intersection are tracked with extracting trajectory and counted respectively in various degrees of occlusion and visibility. The performances are compared with current recognized CPU-based algorithms of real-time tracking-by-detection. The speed of the presented system is higher than the others and the system has a better real-time performance. The accuracy of direction has reached about 94.99% on average, and the accuracy of classification and statistics has reached about 75.12% on average.

Keywords: tracking and statistics, vehicle, signalized intersection, motion parameter, trajectory

Procedia PDF Downloads 221

Authors: Sheema Shuja Khattak, Gule Saman, Imran Khan, Abdus Salam

Abstract:

Image segmentation plays an important role in medical imaging applications. Therefore, accurate methods are needed for the successful segmentation of medical images for diagnosis and detection of various diseases. In this paper, we have used maximum entropy to achieve image segmentation. Maximum entropy has been calculated using Shannon, Renyi, and Tsallis entropies. This work has novelty based on the detection of skin lesion caused by the bite of a parasite called Sand Fly causing the disease is called Cutaneous Leishmaniasis.

Keywords: shannon, maximum entropy, Renyi, Tsallis entropy

Procedia PDF Downloads 463

Authors: Abdul Ghaffar Memon, Xiao Hong Zhou, Yunpeng Xing, Ruoyu Wang, Miao He

Abstract:

Due to deleterious environmental and health effects of the Hg²⁺ ions, various online, detection methods apart from the traditional analytical tools have been developed by researchers. Biosensors especially, label, label-free, colorimetric and optical sensors have advanced with sensitive detection. However, there remains a gap of ultrasensitive quantification as noise interact significantly especially in the AuNP based label-free colorimetry. This study reported an amplification strategy using Exo-III enzyme for target recycling of Hg²⁺ ions in a T-rich hairpin loop metallobase label-free colorimetric nanosensor with an improved sensitivity using unmodified gold nanoparticles (uGNPs) as an indicator. The two T-rich metallobase hairpin loop structures as 5’- CTT TCA TAC ATA GAA AAT GTA TGT TTG -3 (HgS1), and 5’- GGC TTT GAG CGC TAA GAA A TA GCG CTC TTT G -3’ (HgS2) were tested in the study. The thermodynamic properties of HgS1 and HgS2 were calculated using online tools (http://biophysics.idtdna.com/cgi-bin/meltCalculator.cgi). The lab scale synthesized uGNPs were utilized in the analysis. The DNA sequence had T-rich bases on both tails end, which in the presence of Hg²⁺ forms a T-Hg²⁺-T mismatch, promoting the formation of dsDNA. Later, the Exo-III incubation enable the enzyme to cleave stepwise mononucleotides from the 3’ end until the structure become single-stranded. These ssDNA fragments then adsorb on the surface of AuNPs in their presence and protect AuNPs from the induced salt aggregation. The visible change in color from blue (aggregation stage in the absence of Hg²⁺) and pink (dispersion state in the presence of Hg²⁺ and adsorption of ssDNA fragments) can be observed and analyzed through UV spectrometry. An ultrasensitive quantitative nanosensor employing Exo-III assisted target recycling of mercury ions through label-free colorimetry with nanomolar detection using uGNPs have been achieved and is further under the optimization to achieve picomolar range by avoiding the influence of the environmental matrix. The proposed strategy will supplement in the direction of uGNP based ultrasensitive, rapid, onsite, label-free colorimetric detection.

Keywords: colorimetric, Exo-III, gold nanoparticles, Hg²⁺ detection, label-free, signal amplification

Procedia PDF Downloads 311

Authors: M. Dasgupta, S. Banerjee

Abstract:

Content Based Image Retrieval (CBIR) coupled with Case Based Reasoning (CBR) is a paradigm that is becoming increasingly popular in the diagnosis and therapy planning of medical ailments utilizing the digital content of medical images. This paper presents a survey of some of the promising approaches used in the detection of abnormalities in retina images as well in mammographic screening and detection of regions of interest in MRI scans of the brain. We also describe our proposed algorithm to detect hard exudates in fundus images of the retina of Diabetic Retinopathy patients.

Keywords: case based reasoning, exudates, retina image, similarity based retrieval

Procedia PDF Downloads 348

Authors: David G. Maxinez, Andrés Ferreyra Ramírez, Liliana Castillo Sánchez, Nancy Adán Mendoza, Carlos Aviles Cruz

Abstract:

This research describes the use of fuzzy logic in detection, assessment, analysis and evaluation of children with behavioral disorders. It shows how to acquire and analyze ambiguous, vague and full of uncertainty data coming from the input variables to get an accurate assessment result for each of the typologies presented by children with behavior problems. Behavior disorders analyzed in this paper are: hyperactivity (H), attention deficit with hyperactivity (DAH), conduct disorder (TD) and attention deficit (AD).

Keywords: alteration, behavior, centroid, detection, disorders, economic, fuzzy logic, hyperactivity, impulsivity, social

Procedia PDF Downloads 563

Authors: Shekher Kummari, V. Sunil Kumar, K. Vengatajalabathy Gobi

Abstract:

A simple, cost-effective, reusable and reagent-free electrochemical biosensor is developed with functionalized multiwall carbon nanotube paste electrode (f-CNTPE) for the sensitive and selective determination of the important chemotherapeutic drug methotrexate (MTX), which is widely used for the treatment of various cancer and autoimmune diseases. The electrochemical response of the fabricated electrode towards the detection of MTX is examined by cyclic voltammetry (CV), differential pulse voltammetry (DPV) and square wave voltammetry (SWV). CV studies have shown that f-CNTPE electrode system exhibited an excellent electrocatalytic activity towards the oxidation of MTX in phosphate buffer (0.2 M) compared with a conventional carbon paste electrode (CPE). The oxidation peak current is enhanced by nearly two times in magnitude. Applying the DPV method under optimized conditions, a linear calibration plot is achieved over a wide range of concentration from 4.0×10⁻⁷ M to 5.5×10⁻⁶ M with the detection limit 1.6×10⁻⁷ M. further, by applying the SWV method a parabolic calibration plot was achieved starting from a very low concentration of 1.0×10⁻⁸ M, and the sensor could detect as low as 2.9×10⁻⁹ M MTX in 10 s and 10 nM were detected in steady state current-time analysis. The f-CNTPE shows very good selectivity towards the specific recognition of MTX in the presence of important biological interference. The electrochemical biosensor detects MTX in-vitro directly from pharmaceutical sample, undiluted urine and human blood serum samples at a concentration range 5.0×10⁻⁷ M with good recovery limits.

Keywords: amperometry, electrochemical detection, human blood serum, methotrexate, MWCNT, SWV

Procedia PDF Downloads 309

Authors: Joanna Cabaj, Sylwia Baluta, Karol Malecha, Kamila Drzozga

Abstract:

Catecholamines are the principal neurotransmitters that mediate a variety of the central nervous system functions, such as motor control, cognition, emotion, memory processing, and endocrine modulation. Dysfunctions in catecholamine neurotransmission are induced in some neurologic and neuropsychiatric diseases. Changeable neurotransmitters level in biological fluids can be a marker of several neurological disorders. Because of its significance in analytical techniques and diagnostics, sensitive and selective detection of neurotransmitters is increasingly attracting a lot of attention in different areas of bio-analysis or biomedical research. Recently, fluorescent techniques for detection of catecholamines have attracted interests due to their reasonable cost, convenient control, as well as maneuverability in biological environments. Nevertheless, with the observed need for a sensitive and selective catecholamines sensor, the development of a convenient method for this neurotransmitter is still at its basic level. The manipulation of nanostructured materials in conjunction with biological molecules has led to the development of a new class of hybrid modified biosensors in which both enhancement of charge transport and biological activity preservation may be obtained. Immobilization of biomaterials on electrode surfaces is the crucial step in fabricating electrochemical as well as optical biosensors and bioelectronic devices. Continuing systematic investigation in the manufacturing of enzyme–conducting sensitive systems, here is presented a convenient fluorescence sensing strategy for catecholamines detection based on FRET (fluorescence resonance energy transfer) phenomena observed for, i.e., complexes of Fe²⁺ and epinephrine. The biosensor was constructed using low temperature co-fired ceramics technology (LTCC). This sensing system used the catalytical oxidation of catecholamines and quench of the strong luminescence of obtained complexes due to FRET. The detection process was based on the oxidation of substrate in the presence of the enzyme–laccase/tyrosinase.

Keywords: biosensor, conducting polymer, enzyme, FRET, LTCC

Procedia PDF Downloads 257

Authors: Neeraj Neeraj, Soumen Basu, Banibrata Maity

Abstract:

Glutathione (GSH) is one of the most important biomolecules having small molecular weight, which helps in various cellular functions like regulation of gene, xenobiotic metabolism, preservation of intracellular redox activities, signal transduction, etc. Therefore, the detection of GSH requires huge attention by using extremely selective and sensitive techniques. Herein, a rapid fluorometric nanosensor is designed by combining carbon dots (Cdots) and MnO₂ nanoparticles of different sizes for the detection of GSH. The bottom-up approach, i.e., microwave method, was used for the preparation of the water soluble and greatly fluorescent Cdots by using ascorbic acid as a precursor. MnO₂ nanospheres of different sizes (large, medium, and small) were prepared by varying the ratio of concentration of methionine and KMnO₄ at room temperature, which was confirmed by HRTEM analysis. The successive addition of MnO₂ nanospheres in Cdots results fluorescence quenching. From the fluorescence intensity data, Stern-Volmer quenching constant values (KS-V) were evaluated. From the fluorescence intensity and lifetime analysis, it was found that the degree of fluorescence quenching of Cdots followed the order: large > medium > small. Moreover, fluorescence recovery studies were also performed in the presence of GSH. Fluorescence restoration studies also show the order of turn on follows the same order, i.e., large > medium > small, which was also confirmed by quantum yield and lifetime studies. The limits of detection (LOD) of GSH in presence of Cdots@different sized MnO₂ nanospheres were also evaluated. It was observed thatLOD values were in μM region and lowest in case of large MnO₂ nanospheres. The separation distance (d) between Cdots and the surface of different MnO₂ nanospheres was determined. The d values increase with increase in the size of the MnO₂ nanospheres. In summary, the synthesized Cdots@MnO₂ nanocomposites acted as a rapid, simple, economical as well as environmental-friendly nanosensor for the detection of GSH.

Keywords: carbon dots, fluorescence, glutathione, MnO₂ nanospheres, turn off-on

Procedia PDF Downloads 152

Authors: Mallikarjuna Rao Gundavarapu, Ch. Mallikarjuna Rao, K. Anuradha Bai

Abstract:

Real Time Video Tracking is a challenging task for computing professionals. The performance of video tracking techniques is greatly affected by background detection and elimination process. Local regions of the image frame contain vital information of background and foreground. However, pixel-level processing of local regions consumes a good amount of computational time and memory space by traditional approaches. In our approach we have explored the concurrent computational ability of General Purpose Graphic Processing Units (GPGPU) to address this problem. The Gaussian Mixture Model (GMM) with adaptive weighted kernels is used for detecting the background. The weights of the kernel are influenced by local regions and are updated by inter-frame variations of these corresponding regions. The proposed system has been tested with GPU devices such as GeForce GTX 280, GeForce GTX 280 and Quadro K2000. The results are encouraging with maximum speed up 10X compared to sequential approach.

Keywords: connected components, embrace threads, local weighted kernel, structuring elements

Procedia PDF Downloads 440

Authors: Layla El Gaini, Majdouline Belaqziz, Meriem Outaki, Mariam Minhaj

Abstract:

In this study, it introduce and validate a high-performance liquid chromatography method with diode-array detection (HPLC-DAD) specifically designed for the accurate quantification of caffeic acid in phenolic extracts obtained from olive mill wastewater. The separation process of caffeic acid was effectively achieved through the use of an Acclaim Polar Advantage column (5µm, 250x4.6mm). A meticulous multi-step gradient mobile phase was employed, comprising water acidified with phosphoric acid (pH 2.3) and acetonitrile, to ensure optimal separation. The diode-array detection was adeptly conducted within the UV–VIS spectrum, spanning a range of 200–800 nm, which facilitated precise analytical results. The method underwent comprehensive validation, addressing several essential analytical parameters, including specificity, repeatability, linearity, as well as the limits of detection and quantification, alongside measurement uncertainty. The generated linear standard curves displayed high correlation coefficients, underscoring the method's efficacy and consistency. This validated approach is not only robust but also demonstrates exceptional reliability for the focused analysis of caffeic acid within the intricate matrices of wastewater, thus offering significant potential for applications in environmental and analytical chemistry.

Keywords: high-performance liquid chromatography (HPLC-DAD), caffeic acid analysis, olive mill wastewater phenolics, analytical method validation

Procedia PDF Downloads 70

Authors: Mahdi Pirmoradian, Olayinka Adigun, Christos Politis

Abstract:

Cooperative spectrum sensing is a crucial challenge in cognitive radio networks. Cooperative sensing can increase the reliability of spectrum hole detection, optimize sensing time and reduce delay in cooperative networks. In this paper, an efficient central capacity optimization algorithm is proposed to minimize cooperative sensing time in a homogenous sensor network using OR decision rule subject to the detection and false alarm probabilities constraints. The evaluation results reveal significant improvement in the sensing time and normalized capacity of the cognitive sensors.

Keywords: cooperative networks, normalized capacity, sensing time

Procedia PDF Downloads 633

Authors: G. H. Li, M. Liu, H. J. Qi, Q. Zhu, W. Z. He

Abstract:

The drilling and riveting processes are widely used in the assembly of carrier rocket, which makes the efficiency and quality of drilling become the important factor affecting the assembly process. According to the problem existing in the drilling of thick stacked plate (thickness larger than 10mm) of carrier rocket, such as drill break, large noise and burr etc., experimental study of the influence of tool material on the drilling was carried out. The cutting force was measured by a piezoelectric dynamometer, the aperture was measured with an outline projector, and the burr is observed and measured by a digital stereo microscope. Through the measurement, the effects of tool material on the drilling were analyzed from the aspects of drilling force, diameter, and burr. The results show that, compared with carbide drill and coated carbide one, the drilling force of high speed steel is larger. But, the application of high speed steel also has some advantages, e.g. a higher number of hole can be obtained, the height of burr is small, the exit is smooth and the slim burr is less, and the tool experiences wear but not fracture. Therefore, the high speed steel tool is suitable for the drilling of thick stacked plate of 2219 Aluminum alloy.

Keywords: 2219 aluminum alloy, thick stacked plate, drilling, tool material

Procedia PDF Downloads 235

Authors: George Abu-Aqil, Leah Tsror, Elad Shufan, Shaul Mordechai, Mahmoud Huleihel, Ahmad Salman

Abstract:

Pectobacterium and Dickeya spp which negatively affect a wide range of crops are the main causes of the aggressive diseases of agricultural crops. These aggressive diseases are responsible for a huge economic loss in agriculture including a severe decrease in the quality of the stored vegetables and fruits. Therefore, it is important to detect these pathogenic bacteria at their early stages of infection to control their spread and consequently reduce the economic losses. In addition, early detection is vital for producing non-infected propagative material for future generations. The currently used molecular techniques for the identification of these bacteria at the strain level are expensive and laborious. Other techniques require a long time of ~48 h for detection. Thus, there is a clear need for rapid, non-expensive, accurate and reliable techniques for early detection of these bacteria. In this study, infrared spectroscopy, which is a well-known technique with all its features, was used for rapid detection of Pectobacterium and Dickeya spp. at the strain level. The bacteria were isolated from potato plants and tubers with soft rot symptoms and measured by infrared spectroscopy. The obtained spectra were analyzed using different machine learning algorithms. The performances of our approach for taxonomic classification among the bacterial samples were evaluated in terms of success rates. The success rates for the correct classification of the genus, species and strain levels were ~100%, 95.2% and 92.6% respectively.

Keywords: soft rot enterobacteriaceae (SRE), pectobacterium, dickeya, plant infections, potato, solanum tuberosum, infrared spectroscopy, machine learning

Procedia PDF Downloads 101

Authors: Zdzislaw Kaminski, Zbigniew Czyz, Krzysztof Skiba

Abstract:

This paper discusses the CFD simulation of a flow around a rotor of a Vertical Axis Wind Turbine. Numerical simulation, unlike experiments, enables us to validate project assumptions when it is designed and avoid a costly preparation of a model or a prototype for a bench test. CFD simulation enables us to compare characteristics of aerodynamic forces acting on rotor working surfaces and define operational parameters like torque or power generated by a turbine assembly. This research focused on the rotor with the blades capable of modifying their working surfaces, i.e. absorbing wind kinetic energy. The operation of this rotor is based on adjusting angular aperture α of the top and bottom parts of the blades mounted on an axis. If this angular aperture α increases, the working surface which absorbs wind kinetic energy also increases. The operation of turbines is characterized by parameters like the angular aperture of blades, power, torque, speed for a given wind speed. These parameters have an impact on the efficiency of assemblies. The distribution of forces acting on the working surfaces in our turbine changes according to the angular velocity of the rotor. Moreover, the resultant force from the force acting on an advancing blade and retreating blade should be as high as possible. This paper is part of the research to improve an efficiency of a rotor assembly. Therefore, using simulation, the courses of the above parameters were studied in three full rotations individually for each of the blades for three angular apertures of blade working surfaces, i.e. 30 °, 60 °, 90 °, at three wind speeds, i.e. 4 m / s, 6 m / s, 8 m / s and rotor speeds ranging from 100 to 500 rpm. Finally, there were created the characteristics of torque coefficients and power as a function of time for each blade separately and for the entire rotor. Accordingly, the correlation between the turbine rotor power as a function of wind speed for varied values of rotor rotational speed. By processing this data, the correlation between the power of the turbine rotor and its rotational speed for each of the angular aperture of the working surfaces was specified. Finally, the optimal values, i.e. of the highest output power for given wind speeds were read. The research results in receiving the basic characteristics of turbine rotor power as a function of wind speed for the three angular apertures of the blades. Given the nature of rotor operation, the growth in the output turbine can be estimated if angular aperture of the blades increases. The controlled adjustment of angle α enables a smooth adjustment of power generated by a turbine rotor. If wind speed is significant, this type of adjustment enables this output power to remain at the same level (by reducing angle α) with no risk of damaging a construction. This work has been financed by the Polish Ministry of Science and Higher Education.

Keywords: computational fluid dynamics, numerical analysis, renewable energy, wind turbine

Procedia PDF Downloads 217