Search results for: explosive detection devices
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5690

Search results for: explosive detection devices

1700 Imp_hist-Si: Improved Hybrid Image Segmentation Technique for Satellite Imagery to Decrease the Segmentation Error Rate

Authors: Neetu Manocha

Abstract:

Image segmentation is a technique where a picture is parted into distinct parts having similar features which have a place with similar items. Various segmentation strategies have been proposed as of late by prominent analysts. But, after ultimate thorough research, the novelists have analyzed that generally, the old methods do not decrease the segmentation error rate. Then author finds the technique HIST-SI to decrease the segmentation error rates. In this technique, cluster-based and threshold-based segmentation techniques are merged together. After then, to improve the result of HIST-SI, the authors added the method of filtering and linking in this technique named Imp_HIST-SI to decrease the segmentation error rates. The goal of this research is to find a new technique to decrease the segmentation error rates and produce much better results than the HIST-SI technique. For testing the proposed technique, a dataset of Bhuvan – a National Geoportal developed and hosted by ISRO (Indian Space Research Organisation) is used. Experiments are conducted using Scikit-image & OpenCV tools of Python, and performance is evaluated and compared over various existing image segmentation techniques for several matrices, i.e., Mean Square Error (MSE) and Peak Signal Noise Ratio (PSNR).

Keywords: satellite image, image segmentation, edge detection, error rate, MSE, PSNR, HIST-SI, linking, filtering, imp_HIST-SI

Procedia PDF Downloads 131
1699 Plasma Electrolytes and Gamma Glutamyl Transpeptidase (GGT) Status in Dementia Subjects in Southern Nigeria

Authors: Salaam Mujeeb, Adeola Segun, Abdullahi Olasunkanmi

Abstract:

Dementia is becoming a major concern as the world population is increasing and elderly populations are being neglected. Liver and kidney Diseases have been implicated as risk factors in the etiology of Dementia. This study, therefore, evaluates the plasma Gamma Glutamyl Transferase (GGT) activity and plasma Electrolytes in other to find an association between the biomarkers and Dementia. The subjects (38) were age and sex-matched with their corresponding controls and structured questionnaires were used to obtain medical information. Using spectrophotometric and ion selective Electrode techniques respectively, we found and elevated GGT activity in the Dementia Subjects. Remarkably, no association was found between the plasma Electrolytes level and Dementia subjects. It was also observed that severity of Dementia worsens with age. Moreover, the condition of the dementia subjects worsens with reducing weight. Furthermore, the presence of Comorbidity e.g. Hypertension, Obesity, Diabetes and Habits like Smoking, Drugs and Alcohol consumption interferes with Electrolyte balance. Weight loss monitoring and IBM check are advised in Elderly individuals particularly females as they may be inductive of early or future cognitive impairments. Therefore, it might be useful as an early detection tool. Government and society should invest more on the Geriatric population by establishing Old people's home and providing social care services.

Keywords: clinical characteristics, dementia, electrolytes, gamma glutamyl transpeptidase, GGT

Procedia PDF Downloads 320
1698 Evaluation of Immune Checkpoint Inhibitors in Cancer Therapy

Authors: Mir Mohammad Reza Hosseini

Abstract:

In new years immune checkpoint inhibitors have gathered care as being one of the greatest talented kinds of immunotherapy on the prospect. There has been a specific emphasis on the immune checkpoint molecules, cytotoxic T-lymphocyte antigen-4 (CTLA-4) and programmed cell death protein 1 (PD-1). In 2011, ipilimumab, the primary antibody obstructive an immune checkpoint (CTLA4) was authorized. It is now documented that recognized tumors have many devices of overpowering the antitumor immune response, counting manufacture of repressive cytokines, staffing of immunosuppressive immune cells, and upregulation of coinhibitory receptors recognized as immune checkpoints. This was fast followed by the growth of monoclonal antibodies directing PD1 (pembrolizumab and nivolumab) and PDL1 (atezolizumab and durvalumab). Anti-PD1/PDL1 antibodies have developed some of the greatest extensively set anticancer therapies. We also compare and difference their present place in cancer therapy and designs of immune-related toxicities and deliberate the role of dual immune checkpoint inhibition and plans for the organization of immune-related opposing proceedings. In this review, the employed code and present growth of numerous immune checkpoint inhibitors are abridged, while the communicating device and new development of Immune checkpoint inhibitors in cancer therapy-based synergistic therapies with additional immunotherapy, chemotherapy, phototherapy, and radiotherapy in important and clinical educations in the historical 5 years are portrayed and tinted. Lastly, we disapprovingly measure these methods and effort to find their fortes and faintness based on pre-clinical and clinical information.

Keywords: checkpoint, cancer therapy, PD-1, PDL-1, CTLA4, immunosuppressive

Procedia PDF Downloads 158
1697 Cognitive Functioning and Cortisol Suppression in Major Depression in a Long-Term Perspective

Authors: Pia Berner Hansson, Robert Murison Anders Lund, Hammar Åsa

Abstract:

Major Depressive Disorder (MDD) is often associated with high levels of stress and disturbances in the Hypothalamic Pituitary Adrenal (HPA) system, yielding high levels of cortisol, in addition to cognitive dysfunction. Previous studies in this patient group have shown a relationship between cortisol profile and cognitive functioning in the acute phase of MDD and that the patients had significantly less suppression after dexamethasone administration. However, few studies have investigated this relationship over time and in phases of symptom reduction. The aim of the present study was to examine the relationships between cortisol levels after the Dexamethasone Suppression Test (DST) and cognitive function in a long term perspective in MDD patients. Patients meeting the DSM-IV criteria for a MDD were included in the study and tested in symptom reduction. A control group was included. Cortisol was measured in saliva collected with Salivette sampling devices. Saliva samples were collected 4 times during a 24 hours period over two consecutive days: at awakening, after 45 minutes, after 7 hours and at 11 pm. Dexamethasone (1.0 mg) was given on Day 1 at 11 pm. The neuropsychological test battery consisted of standardized tests measuring memory and Executive Functioning (EF). Cortisol levels did not differ significantly between patients and controls on Day 1 or Day 2. Both groups showed significant suppression after Dexamethasone. There were no correlations between cortisol levels or suppression after Dexamethasone and cognitive measures. The results indicate that the HPA-axis functioning normalizes in phases of symptom reduction in MDD patients and that there no relation between cortisol profile and cognitive functioning in memory or EF.

Keywords: depression, MDD, cortisol, suppression, cognitive functioning

Procedia PDF Downloads 325
1696 Biochemical and Molecular Analysis of Staphylococcus aureus Various Isolates from Different Places

Authors: Kiran Fatima, Kashif Ali

Abstract:

Staphylococcus aureus is an opportunistic human as well as animal pathogen that causes a variety of diseases. A total of 70 staphylococci isolates were obtained from soil, water, yogurt, and clinical samples. The likely staphylococci clinical isolates were identified phenotypically by different biochemical tests. Molecular identification was done by PCR using species-specific 16S rRNA primer pairs, and finally, 50 isolates were found to be positive as Staphylococcus aureus, sciuri, xylous and cohnii. Screened isolates were further analyzed by several microbiological diagnostics tests, including gram staining, coagulase, capsule, hemolysis, fermentation of glucose, lactose, maltose, and sucrose tests enzymatic reactions. It was found that 78%, 81%, and 51% of isolates were positive for gelatin hydrolysis, protease, and lipase activities, respectively. Antibiogram analysis of isolated Staphylococcus aureus strains with respect to different antimicrobial agents revealed resistance patterns ranging from 57 to 96%. Our study also shows 70% of strains to be MRSA, 54.3% as VRSA, and 54.3% as both MRSA and VRSA. All the identified isolates were subjected to detection of mecA, nuc, and hlb genes, and 70%, 84%, and 40% were found to harbour mecA, nuc, and hlb genes, respectively. The current investigation is highly important and informative for the high-level multidrug-resistant Staphylococcus aureus infections inclusive also of methicillin and vancomycin.

Keywords: MRSA, VRSA, mecA, MSSA

Procedia PDF Downloads 121
1695 The Impact of Artificial Intelligence on Human Rights Legislations and Evolution

Authors: Nawal Yacoub Halim Abdelmasih

Abstract:

The intersection between development and human rights has been the factor of scholarly debate for a long term. therefore, some of standards, which enlarge from the proper to development to the human rights-based totally method to development, had been adopted to apprehend the dynamics among the two standards. no matter these attempts, the exact relationship among improvement and human rights has not been completely determined but. however, the inevitable interdependence between the two notions and the idea that improvement efforts ought to be undertaken with the aid of giving due regard to human rights ensures has won momentum in recent years. then again, the emergence of sustainable development as a extensively common technique in development dreams and policies makes this unsettled convergence even extra complicated. The vicinity of sustainable improvement in human rights regulation discourse and the function of the latter in making sure the sustainability of development applications name for a scientific observe. as a result, this newsletter seeks to discover the relationship among development and human rights, particularly focusing at the location given to sustainable development principles in international human proper regulation. it'll similarly quest whether or not there is a proper to sustainable improvement diagnosed therein. as a result, the item asserts that the ideas of sustainable improvement are immediately or circuitously diagnosed in diverse human rights contraptions, which affords an affirmative response to the question raised hereinabove. This paintings, therefore, will make expeditions via international and regional human rights devices in addition to case legal guidelines and interpretative hints of human rights bodies to show this speculation.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security

Procedia PDF Downloads 8
1694 Reconfigurable Consensus Achievement of Multi Agent Systems Subject to Actuator Faults in a Leaderless Architecture

Authors: F. Amirarfaei, K. Khorasani

Abstract:

In this paper, reconfigurable consensus achievement of a team of agents with marginally stable linear dynamics and single input channel has been considered. The control algorithm is based on a first order linear protocol. After occurrence of a LOE fault in one of the actuators, using the imperfect information of the effectiveness of the actuators from fault detection and identification module, the control gain is redesigned in a way to still reach consensus. The idea is based on the modeling of change in effectiveness as change of Laplacian matrix. Then as special cases of this class of systems, a team of single integrators as well as double integrators are considered and their behavior subject to a LOE fault is considered. The well-known relative measurements consensus protocol is applied to a leaderless team of single integrator as well as double integrator systems, and Gersgorin disk theorem is employed to determine whether fault occurrence has an effect on system stability and team consensus achievement or not. The analyses show that loss of effectiveness fault in actuator(s) of integrator systems affects neither system stability nor consensus achievement.

Keywords: multi-agent system, actuator fault, stability analysis, consensus achievement

Procedia PDF Downloads 327
1693 Dynamic Cardiac Mitochondrial Proteome Alterations after Ischemic Preconditioning

Authors: Abdelbary Prince, Said Moussa, Hyungkyu Kim, Eman Gouda, Jin Han

Abstract:

We compared the dynamic alterations of mitochondrial proteome of control, ischemia-reperfusion (IR) and ischemic preconditioned (IPC) rabbit hearts. Using 2-DE, we identified 29 mitochondrial proteins that were differentially expressed in the IR heart compared with the control and IPC hearts. For two of the spots, the expression patterns were confirmed by Western blotting analysis. These proteins included succinate dehydrogenase complex, Acyl-CoA dehydrogenase, carnitine acetyltransferase, dihydrolipoamide dehydrogenase, Atpase, ATP synthase, dihydrolipoamide succinyltransferase, ubiquinol-cytochrome c reductase, translation elongation factor, acyl-CoA dehydrogenase, actin alpha, succinyl-CoA Ligase, dihydrolipoamide S-succinyltransferase, citrate synthase, acetyl-Coenzyme A dehydrogenase, creatine kinase, isocitrate dehydrogenase, pyruvate dehydrogenase, prohibitin, NADH dehydrogenase (ubiquinone) Fe-S protein, enoyl Coenzyme A hydratase, superoxide dismutase [Mn], and 24-kDa subunit of complex I. Interestingly, most of these proteins are associated with the mitochondrial respiratory chain, antioxidant enzyme system, and energy metabolism. The results provide clues as to the cardioprotective mechanism of ischemic preconditioning at the protein level and may serve as potential biomarkers for detection of ischemia-induced cardiac injury.

Keywords: ischemic preconditioning, mitochondria, proteome, cardioprotection

Procedia PDF Downloads 343
1692 Study and Simulation of the Thrust Vectoring in Supersonic Nozzles

Authors: Kbab H, Hamitouche T

Abstract:

In recent years, significant progress has been accomplished in the field of aerospace propulsion and propulsion systems. These developments are associated with efforts to enhance the accuracy of the analysis of aerothermodynamic phenomena in the engine. This applies in particular to the flow in the nozzles used. One of the most remarkable processes in this field is thrust vectoring by means of devices able to orientate the thrust vector and control the deflection of the exit jet in the engine nozzle. In the study proposed, we are interested in the fluid thrust vectoring using a second injection in the nozzle divergence. This fluid injection causes complex phenomena, such as boundary layer separation, which generates a shock wave in the primary jet upstream of the fluid interacting zone (primary jet - secondary jet). This will cause the deviation of the main flow, and therefore of the thrust vector with reference to the axis nozzle. In the modeling of the fluidic thrust vector, various parameters can be used. The Mach number of the primary jet and the injected fluid, the total pressures ratio, the injection rate, the thickness of the upstream boundary layer, the injector position in the divergent part, and the nozzle geometry are decisive factors in this type of phenomenon. The complexity of the latter challenges researchers to understand the physical phenomena of the turbulent boundary layer encountered in supersonic nozzles, as well as the calculation of its thickness and the friction forces induced on the walls. The present study aims to numerically simulate the thrust vectoring by secondary injection using the ANSYS-FLUENT, then to analyze and validate the results and the performances obtained (angle of deflection, efficiency...), which will then be compared with those obtained by other authors.

Keywords: CD Nozzle, TVC, SVC, NPR, CFD, NPR, SPR

Procedia PDF Downloads 129
1691 Capnography for Detection of Return of Spontaneous Circulation Pseudo-Pea

Authors: Yiyuan David Hu, Alex Lindqwister, Samuel B. Klein, Karen Moodie, Norman A. Paradis

Abstract:

Introduction: Pseudo-Pulseless Electrical Activity (p-PEA) is a lifeless form of profound cardiac shock characterized by measurable cardiac mechanical activity without clinically detectable pulses. Patients in pseudo-PEA carry different prognoses than those in true PEA and may require different therapies. End-tidal carbon dioxide (ET-CO2) is a reliable indicator of the return of spontaneous circulation (ROSC) in ventricular fibrillation and true-PEA but has not been studied p-PEA. Hypothesis: ET-CO2 can be used as an independent indicator of ROSC in p-PEA resuscitation. Methods: 30kg female swine (N = 14) under intravenous anesthesia were instrumented with aortic and right atrial micromanometer pressure. ECG and ET-CO2 were measured continuously. p-PEA was induced by ventilation with 6% oxygen in 94% nitrogen and was defined as a systolic Ao less than 40 mmHg. The statistical relationships between ET-CO2 and ROSC are reported. Results: ET-CO2 during resuscitation strongly correlated with ROSC (Figure 1). Mean ET-CO2 during p-PEA was 28.4 ± 8.4, while mean ET-CO2 in ROSC for 100% O2 cohort was 42.2 ± 12.6 (p < 0.0001), mean ET-CO2 in ROSC for 100% O2 + CPR was 33.0 ± 15.4 (p < 0.0001). Analysis of slope was limited to one minute of resuscitation data to capture local linearity; assessment began 10 seconds after resuscitation started to allow the ventilator to mix 100% O2. Pigs who would recover with 100% O2 had a slope of 0.023 ± 0.001, oxygen + CPR had a slope of 0.018 ± 0.002, and oxygen + CPR + epinephrine had a slope of 0.0050 ± 0.0009. Conclusions: During resuscitation from porcine hypoxic p-PEA, a rise in ET-CO2 is indicative of ROSC.

Keywords: ET-CO2, resuscitation, capnography, pseudo-PEA

Procedia PDF Downloads 183
1690 Design of Speed Bump Recognition System Integrated with Adjustable Shock Absorber Control

Authors: Ming-Yen Chang, Sheng-Hung Ke

Abstract:

This research focuses on the development of a speed bump identification system for real-time control of adjustable shock absorbers in vehicular suspension systems. The study initially involved the collection of images of various speed bumps, and rubber speed bump profiles found on roadways. These images were utilized for training and recognition purposes through the deep learning object detection algorithm YOLOv5. Subsequently, the trained speed bump identification program was integrated with an in-vehicle camera system for live image capture during driving. These images were instantly transmitted to a computer for processing. Using the principles of monocular vision ranging, the distance between the vehicle and an approaching speed bump was determined. The appropriate control distance was established through both practical vehicle measurements and theoretical calculations. Collaboratively, with the electronically adjustable shock absorbers equipped in the vehicle, a shock absorber control system was devised to dynamically adapt the damping force just prior to encountering a speed bump. This system effectively mitigates passenger discomfort and enhances ride quality.

Keywords: adjustable shock absorbers, image recognition, monocular vision ranging, ride

Procedia PDF Downloads 63
1689 An Integrative Computational Pipeline for Detection of Tumor Epitopes in Cancer Patients

Authors: Tanushree Jaitly, Shailendra Gupta, Leila Taher, Gerold Schuler, Julio Vera

Abstract:

Genomics-based personalized medicine is a promising approach to fight aggressive tumors based on patient's specific tumor mutation and expression profiles. A remarkable case is, dendritic cell-based immunotherapy, in which tumor epitopes targeting patient's specific mutations are used to design a vaccine that helps in stimulating cytotoxic T cell mediated anticancer immunity. Here we present a computational pipeline for epitope-based personalized cancer vaccines using patient-specific haplotype and cancer mutation profiles. In the workflow proposed, we analyze Whole Exome Sequencing and RNA Sequencing patient data to detect patient-specific mutations and their expression level. Epitopes including the tumor mutations are computationally predicted using patient's haplotype and filtered based on their expression level, binding affinity, and immunogenicity. We calculate binding energy for each filtered major histocompatibility complex (MHC)-peptide complex using docking studies, and use this feature to select good epitope candidates further.

Keywords: cancer immunotherapy, epitope prediction, NGS data, personalized medicine

Procedia PDF Downloads 244
1688 Dishonesty and Achievement: An Experiment of Self-Revealing Individual Cheating

Authors: Gideon Yaniv, Erez Siniver, Yossef Tobol

Abstract:

The extensive body of economic and psychological research correlating between students' cheating and their grade point average (GPA) consistently finds a significant negative relationship between cheating and the GPA. However, this literature is entirely based on students' responses to direct question surveys that inquire whether they have ever cheated on their academic assignments. The present paper reports the results of a two-round experiment designed to expose student cheating at the individual level and correlate it with their GPAs. The experiment involved two classes of third-year economics students incentivized by a competitive reward to answer a multiple-choice trivia quiz without consulting their electronic devices. While this forbiddance was deliberately overlooked in the first round, providing an opportunity to cheat, it was strictly enforced in the second, conducted two months later in the same classes with the same quiz. A comparison of subjects' performance in the two rounds, self-revealed a considerable extent of cheating in the first one. Regressing the individual cheating levels on subjects' gender and GPA exhibited no significant differences in cheating between males and females. However, cheating of both genders was found to significantly increase with their GPA, implying, in sharp contrast with the direct question surveys, that higher achievers are bigger cheaters. A second experiment, which allowed subjects to answer the quiz in the privacy of their own cars, reveals that when really feeling safe to cheat, many subjects would cheat maximally, challenging the literature's claim that people generally cheat modestly.

Keywords: academic achievement, cheating behavior, experimental data, grade-point average

Procedia PDF Downloads 201
1687 A Sensitive Uric Acid Electrochemical Sensing in Biofluids Based on Ni/Zn Hydroxide Nanocatalyst

Authors: Nathalia Florencia Barros Azeredo, Josué Martins Gonçalves, Pamela De Oliveira Rossini, Koiti Araki, Lucio Angnes

Abstract:

This work demonstrates the electroanalysis of uric acid (UA) at very low working potential (0 V vs Ag/AgCl) directly in body fluids such as saliva and sweat using electrodes modified with mixed -Ni0.75Zn0.25(OH)2 nanoparticles exhibiting stable electrocatalytic responses from alkaline down to weakly acidic media (pH 14 to 3 range). These materials were prepared for the first time and fully characterized by TEM, XRD, and spectroscopic techniques. The electrochemical properties of the modified electrodes were evaluated in a fast and simple procedure for uric acid analyses based on cyclic voltammetry and chronoamperometry, pushing down the detection and quantification limits (respectively of 2.3*10-8 and 7.6*10-8 mol L-1) with good repeatability (RSD = 3.2% for 30 successive analyses pH 14). Finally, the possibility of real application was demonstrated upon realization of unexpectedly robust and sensitive modified FTO (fluorine doped tin oxide) glass and screen-printed sensors for measurement of uric acid directly in real saliva and sweat samples, with no significant interference of usual concentrations of ascorbic acid, acetaminophen, lactate and glucose present in those body fluids (Fig. 1).

Keywords: nickel hydroxide, mixed catalyst, uric acid sensors, biofluids

Procedia PDF Downloads 125
1686 Development of Trigger Tool to Identify Adverse Drug Events From Warfarin Administered to Patient Admitted in Medical Wards of Chumphae Hospital

Authors: Puntarikorn Rungrattanakasin

Abstract:

Objectives: To develop the trigger tool to warn about the risk of bleeding as an adverse event from warfarin drug usage during admission in Medical Wards of Chumphae Hospital. Methods: A retrospective study was performed by reviewing the medical records for the patients admitted between June 1st,2020- May 31st, 2021. ADEs were evaluated by Naranjo’s algorithm. The international normalized ratio (INR) and events of bleeding during admissions were collected. Statistical analyses, including Chi-square test and Reciever Operating Characteristic (ROC) curve for optimal INR threshold, were used for the study. Results: Among the 139 admissions, the INR range was found to vary between 0.86-14.91, there was a total of 15 bleeding events, out of which 9 were mild, and 6 were severe. The occurrence of bleeding started whenever the INR was greater than 2.5 and reached the statistical significance (p <0.05), which was in concordance with the ROC curve and yielded 100 % sensitivity and 60% specificity in the detection of a bleeding event. In this regard, the INR greater than 2.5 was considered to be an optimal threshold to alert promptly for bleeding tendency. Conclusions: The INR value of greater than 2.5 (>2.5) would be an appropriate trigger tool to warn of the risk of bleeding for patients taking warfarin in Chumphae Hospital.

Keywords: trigger tool, warfarin, risk of bleeding, medical wards

Procedia PDF Downloads 142
1685 Computer Aided Analysis of Breast Based Diagnostic Problems from Mammograms Using Image Processing and Deep Learning Methods

Authors: Ali Berkan Ural

Abstract:

This paper presents the analysis, evaluation, and pre-diagnosis of early stage breast based diagnostic problems (breast cancer, nodulesorlumps) by Computer Aided Diagnosing (CAD) system from mammogram radiological images. According to the statistics, the time factor is crucial to discover the disease in the patient (especially in women) as possible as early and fast. In the study, a new algorithm is developed using advanced image processing and deep learning method to detect and classify the problem at earlystagewithmoreaccuracy. This system first works with image processing methods (Image acquisition, Noiseremoval, Region Growing Segmentation, Morphological Operations, Breast BorderExtraction, Advanced Segmentation, ObtainingRegion Of Interests (ROIs), etc.) and segments the area of interest of the breast and then analyzes these partly obtained area for cancer detection/lumps in order to diagnosis the disease. After segmentation, with using the Spectrogramimages, 5 different deep learning based methods (specified Convolutional Neural Network (CNN) basedAlexNet, ResNet50, VGG16, DenseNet, Xception) are applied to classify the breast based problems.

Keywords: computer aided diagnosis, breast cancer, region growing, segmentation, deep learning

Procedia PDF Downloads 85
1684 Detection of Paenibacillus larvae (American Foulbrood Disease) by the PCR and Culture in the Remains of the Hive Collected at the Bottom of the Colony

Authors: N. Adjlane, N. Haddad

Abstract:

The American foulbrood is one of the most serious diseases that may affect brood of larvae and pupae stages. The causative organism is a gram positive bacterium Paaenibacillus larvae. American foulbrood infected apiaries suffer from severe economic losses, resulting from significant decreases in honeybee populations and honey production. The aim of this study was to detect Paenibacillus larvae in the remains collected at the bottom of the hive from the suspected hives by direct PCR and culture growth. A total of 56 suspected beehive wax debris samples collected in 40 different apiaries located in the central region of Algeria. MYPGP the culture medium is used during all the identifications of the bacterium. After positive results on samples, biochemical confirmation tests (test of catalase, presence hydrolysis of casein) and microscopic (gram stain) are used in order to verify the accuracy of the initial results. The QIAamp DNA Mini Kit is used to identify the DNA of Paaenibacillus larvae. Paaenibacillus larvae were identified in 14 samples out of 16 by the PCR. A suspected culture-negative sample was found positive through evaluation with PCR. This research is for the bacterium Paaenibacillus larvae in the debris of the colony is an effective method for diagnosis of the pathology of American foulbrood.

Keywords: Paenibacillus larvae, honeybee, PCR, microbiological method

Procedia PDF Downloads 404
1683 Analysis of Vibratory Signals Based on Local Mean Decomposition (LMD) for Rolling Bearing Fault Diagnosis

Authors: Toufik Bensana, Medkour Mihoub, Slimane Mekhilef

Abstract:

The use of vibration analysis has been established as the most common and reliable method of analysis in the field of condition monitoring and diagnostics of rotating machinery. Rolling bearings cover a broad range of rotary machines and plays a crucial role in the modern manufacturing industry. Unfortunately, the vibration signals collected from a faulty bearing are generally nonstationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA), and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that, the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. The results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, rolling element bearing, local mean decomposition, condition monitoring

Procedia PDF Downloads 382
1682 Giftedness Cloud Model: A Psychological and Ecological Vision of Giftedness Concept

Authors: Rimeyah H. S. Almutairi, Alaa Eldin A. Ayoub

Abstract:

The aim of this study was to identify empirical and theoretical studies that explored giftedness theories and identification. In order to assess and synthesize the mechanisms, outcomes, and impacts of gifted identification models. Thus, we sought to provide an evidence-informed answer to how does current giftedness theories work and effectiveness. In order to develop a model that incorporates the advantages of existing models and avoids their disadvantages as much as possible. We conducted a systematic literature review (SLR). The disciplined analysis resulted in a final sample consisting of 30 appropriate searches. The results indicated that: (a) there is no uniform and consistent definition of Giftedness; (b) researchers are using several non-consistent criteria to detect gifted, and (d) The detection of talent is largely limited to early ages, and there is obvious neglect of adults. This study contributes to the development of Giftedness Cloud Model (GCM) which defined as a model that attempts to interpretation giftedness within an interactive psychological and ecological framework. GCM aims to help a talented to reach giftedness core and manifestation talent in creative productivity or invention. Besides that, GCM suggests classifying giftedness into four levels of mastery, excellence, creative productivity, and manifestation. In addition, GCM presents an idea to distinguish between talent and giftedness.

Keywords: giftedness cloud model, talent, systematic literature review, giftedness concept

Procedia PDF Downloads 162
1681 Vapochromism of 3,3’,5,5’-Tetramethylbenzidine-Tetrasilisicfluormica Intercalation Compounds with High Selectivity for Water and Acetonitrile

Authors: Reira Kinoshita, Shin'ichi Ishimaru

Abstract:

Vapochromism is a type of chromism in which the color of a substance changes when it is exposed to the vapor of volatile materials, and has been investigated for the application of chemical sensors for volatile organic compounds causing sick building syndrome and health hazards in workspaces. We synthesized intercalation compounds of 3,3',5,5'-tetramethylbenzidine (TMB), and tetrasilisicfluormica (TSFM) by the commonly used cation-exchange method with the cation ratio TMB²⁺/CEC of TSFM = 1.0, 2.0, 2.7 and 5.4 to investigate the vapochromism of these materials. The obtained samples were characterized by powder XRD, XRF, TG-DTA, N₂ adsorption, and SEM. Vapochromism was measured for each sample under a controlled atmosphere by a handy reflectance spectrometer directly from the outside of the glass sample tubes. The color was yellow for all specimens vacuum-dried at 50 °C, but it turned green under H₂O vapor exposure for the samples with TMB²⁺/CEC = 2.0, 2.7, and 5.4 and blue under acetonitrile vapor for all cation ratios. Especially the sample TMB²⁺/CEC = 2.0 showed clear chromism both for water and acetonitrile. On the other hand, no clear color change was observed for vapors of alcohols, acetone, and non-polar solvents. From these results, this material can be expected to apply for easy detection of humidity and acetonitrile vapor in the environment.

Keywords: chemical sensor, intercalation compound, tetramethylbenzidine, tetrasilisicfluormica, vapochromism, volatile organic compounds

Procedia PDF Downloads 105
1680 Prevalence Of Listeria And Salmonella Contamination In Fda Recalled Foods

Authors: Oluwatofunmi Musa-Ajakaiye, Paul Olorunfemi M.D MPH, John Obafaiye

Abstract:

Introduction: The U.S Food and Drug Administration (FDA) reports the public notices for recalled FDA-regulated products over periods of time. It study reviewed the primary reasons for recalls of products of various types over a period of 7 years. Methods: The study analyzed data provided in the FDA’s archived recalls for the years 2010-2017. It identified the various reasons for product recalls in the categories of foods, beverages, drugs, medical devices, animal and veterinary products, and dietary supplements. Using SPSS version 29, descriptive statistics and chi-square analysis of the data were performed. Results (numbers, percentages, p-values, chi-square): Over the period of analysis, a total of 931 recalls were reported. The most frequent reason for recalls was undeclared products (36.7%). The analysis showed that the most recalled product type in the data set was foods and beverages, representing 591 of all recalled products (63.5%).In addition, it was observed that foods and beverages represent 77.2% of products recalled due to the presence of microorganisms. Also, a sub-group analysis of recall reasons of food and beverages found that the most prevalent reason for such recalls was undeclared products (50.1%) followed by Listeria (17.3%) then Salmonella (13.2%). Conclusion: This analysis shows that foods and beverages have the greatest percentages of total recalls due to the presence of undeclared products listeria contamination and Salmonella contamination. The prevalence of Salmonella and Listeria contamination suggests that there is a high risk of microbial contamination in FDA-approved products and further studies on the effects of such contamination must be conducted to ensure consumer safety.

Keywords: food, beverages, listeria, salmonella, FDA, contamination, microbial

Procedia PDF Downloads 57
1679 Reorientation of Anisotropic Particles in Free Liquid Microjets

Authors: Mathias Schlenk, Susanne Seibt, Sabine Rosenfeldt, Josef Breu, Stephan Foerster

Abstract:

Thin liquid jets on micrometer scale play an important role in processing such as in fiber fabrication, inkjet printing, but also for sample delivery in modern synchrotron X-ray devices. In all these cases the liquid jets contain solvents and dissolved materials such as polymers, nanoparticles, fibers pigments or proteins. As liquid flow in liquid jets differs significantly from flow in capillaries and microchannels, particle localization and orientation will also be different. This is of critical importance for applications, which depend on well-defined homogeneous particle and fiber distribution and orientation in liquid jets. Investigations of particle orientation in liquid microjets of diluted solutions have been rare, despite their importance. With the arise of micro-focused X-ray beams it has become possible to scan across samples with micrometer resolution to locally analyse structure and orientation of the samples. In the present work, we used this method to scan across liquid microjets to determine the local distribution and orientation of anisotropic particles. The compromise wormlike block copolymer micelles as an example of long flexible fibrous structures, hectorite materials as a model of extended nanosheet structures, and gold nanorods as an illustration of short stiff cylinders to comprise all relevant anisotropic geometries. We find that due to the different velocity profile in the liquid jet, which resembles plug flow, the orientation of the particles which was generated in the capillary is lost or changed into non-oriented or bi-axially orientations depending on the geometrical shape of the particle.

Keywords: anisotropic particles, liquid microjets, reorientation, SAXS

Procedia PDF Downloads 331
1678 ZnS and Graphene Quantum Dots Nanocomposite as Potential Electron Acceptor for Photovoltaics

Authors: S. M. Giripunje, Shikha Jindal

Abstract:

Zinc sulphide (ZnS) quantum dots (QDs) were synthesized successfully via simple sonochemical method. X-ray diffraction (XRD), scanning electron microscopy (SEM) and high resolution transmission electron microscopy (HRTEM) analysis revealed the average size of QDs of the order of 3.7 nm. The band gap of the QDs was tuned to 5.2 eV by optimizing the synthesis parameters. UV-Vis absorption spectra of ZnS QD confirm the quantum confinement effect. Fourier transform infrared (FTIR) analysis confirmed the formation of single phase ZnS QDs. To fabricate the diode, blend of ZnS QDs and P3HT was prepared and the heterojunction of PEDOT:PSS and the blend was formed by spin coating on indium tin oxide (ITO) coated glass substrate. The diode behaviour of the heterojunction was analysed, wherein the ideality factor was found to be 2.53 with turn on voltage 0.75 V and the barrier height was found to be 1.429 eV. ZnS-Graphene QDs nanocomposite was characterised for the surface morphological study. It was found that the synthesized ZnS QDs appear as quasi spherical particles on the graphene sheets. The average particle size of ZnS-graphene nanocomposite QDs was found to be 8.4 nm. From voltage-current characteristics of ZnS-graphene nanocomposites, it is observed that the conductivity of the composite increases by 104 times the conductivity of ZnS QDs. Thus the addition of graphene QDs in ZnS QDs enhances the mobility of the charge carriers in the composite material. Thus, the graphene QDs, with high specific area for a large interface, high mobility and tunable band gap, show a great potential as an electron-acceptors in photovoltaic devices.

Keywords: graphene, heterojunction, quantum confinement effect, quantum dots(QDs), zinc sulphide(ZnS)

Procedia PDF Downloads 148
1677 Sea-Land Segmentation Method Based on the Transformer with Enhanced Edge Supervision

Authors: Lianzhong Zhang, Chao Huang

Abstract:

Sea-land segmentation is a basic step in many tasks such as sea surface monitoring and ship detection. The existing sea-land segmentation algorithms have poor segmentation accuracy, and the parameter adjustments are cumbersome and difficult to meet actual needs. Also, the current sea-land segmentation adopts traditional deep learning models that use Convolutional Neural Networks (CNN). At present, the transformer architecture has achieved great success in the field of natural images, but its application in the field of radar images is less studied. Therefore, this paper proposes a sea-land segmentation method based on the transformer architecture to strengthen edge supervision. It uses a self-attention mechanism with a gating strategy to better learn relative position bias. Meanwhile, an additional edge supervision branch is introduced. The decoder stage allows the feature information of the two branches to interact, thereby improving the edge precision of the sea-land segmentation. Based on the Gaofen-3 satellite image dataset, the experimental results show that the method proposed in this paper can effectively improve the accuracy of sea-land segmentation, especially the accuracy of sea-land edges. The mean IoU (Intersection over Union), edge precision, overall precision, and F1 scores respectively reach 96.36%, 84.54%, 99.74%, and 98.05%, which are superior to those of the mainstream segmentation models and have high practical application values.

Keywords: SAR, sea-land segmentation, deep learning, transformer

Procedia PDF Downloads 167
1676 Identification System for Grading Banana in Food Processing Industry

Authors: Ebenezer O. Olaniyi, Oyebade K. Oyedotun, Khashman Adnan

Abstract:

In the food industry high quality production is required within a limited time to meet up with the demand in the society. In this research work, we have developed a model which can be used to replace the human operator due to their low output in production and slow in making decisions as a result of an individual differences in deciding the defective and healthy banana. This model can perform the vision attributes of human operators in deciding if the banana is defective or healthy for food production based. This research work is divided into two phase, the first phase is the image processing where several image processing techniques such as colour conversion, edge detection, thresholding and morphological operation were employed to extract features for training and testing the network in the second phase. These features extracted in the first phase were used in the second phase; the classification system phase where the multilayer perceptron using backpropagation neural network was employed to train the network. After the network has learned and converges, the network was tested with feedforward neural network to determine the performance of the network. From this experiment, a recognition rate of 97% was obtained and the time taken for this experiment was limited which makes the system accurate for use in the food industry.

Keywords: banana, food processing, identification system, neural network

Procedia PDF Downloads 465
1675 Design and Characterization of a Smart Composite Fabric for Knee Brace

Authors: Rohith J. K., Amir Nazemi, Abbas S. Milani

Abstract:

In Paralympic sports, athletes often depend on some form of equipment to enable competitive sporting, where most of this equipment would only allow passive physiological supports and discrete physiological measurements. Active feedback physiological support and continuous detection of performance indicators, without time or space constraints, would be beneficial in more effective training and performance measures of Paralympic athletes. Moreover, occasionally the athletes suffer from fatigue and muscular stains due to improper monitoring systems. The latter challenges can be overcome by using Smart Composites technology when manufacturing, e.g., knee brace and other sports wearables utilities, where the sensors can be fused together into the fabric and an assisted system actively support the athlete. This paper shows how different sensing functionality may be created by intrinsic and extrinsic modifications onto different types of composite fabrics, depending on the level of integration and the employed functional elements. Results demonstrate that fabric sensors can be well-tailored to measure muscular strain and be used in the fabrication of a smart knee brace as a sample potential application. Materials, connectors, fabric circuits, interconnects, encapsulation and fabrication methods associated with such smart fabric technologies prove to be customizable and versatile.

Keywords: smart composites, sensors, smart fabrics, knee brace

Procedia PDF Downloads 174
1674 Oral Examination: An Important Adjunct to the Diagnosis of Dermatological Disorders

Authors: Sanjay Saraf

Abstract:

The oral cavity can be the site for early manifestations of mucocutaneous disorders (MD) or the only site for occurrence of these disorders. It can also exhibit oral lesions with simultaneous associated skin lesions. The MD involving the oral mucosa commonly presents with signs such as ulcers, vesicles and bullae. The unique environment of the oral cavity may modify these signs of the disease, thereby making the clinical diagnosis an arduous task. In addition to the unique environment of oral cavity, the overlapping of the signs of various mucocutaneous disorders, also makes the clinical diagnosis more intricate. The aim of this review is to present the oral signs of dermatological disorders having common oral involvement and emphasize their importance in early detection of the systemic disorders. The aim is also to highlight the necessity of oral examination by a dermatologist while examining the skin lesions. Prior to the oral examination, it must be imperative for the dermatologists and the dental clinicians to have the knowledge of oral anatomy. It is also important to know the impact of various diseases on oral mucosa, and the characteristic features of various oral mucocutaneous lesions. An initial clinical oral examination is may help in the early diagnosis of the MD. Failure to identify the oral manifestations may reduce the likelihood of early treatment and lead to more serious problems. This paper reviews the oral manifestations of immune mediated dermatological disorders with common oral manifestations.

Keywords: dermatological investigations, genodermatosis, histological features, oral examination

Procedia PDF Downloads 350
1673 Computational Fluid Dynamics (CFD) Simulation Approach for Developing New Powder Dispensing Device

Authors: Revanth Rallapalli

Abstract:

Manually dispensing solids and powders can be difficult as it requires gradually pour and check the amount on the scale to be dispensed. Current systems are manual and non-continuous in nature and are user-dependent and difficult to control powder dispensation. Recurrent dosing of powdered medicines in precise amounts quickly and accurately has been an all-time challenge. Various new powder dispensing mechanisms are being designed to overcome these challenges. A battery-operated screw conveyor mechanism is being innovated to overcome the above problems faced. These inventions are numerically evaluated at the concept development level by employing Computational Fluid Dynamics (CFD) of gas-solids multiphase flow systems. CFD has been very helpful in development of such devices saving time and money by reducing the number of prototypes and testing. Furthermore, this paper describes a simulation of powder dispensation from the trocar’s end by considering the powder as secondary flow in air, is simulated by using the technique called Dense Discrete Phase Model incorporated with Kinetic Theory of Granular Flow (DDPM-KTGF). By considering the volume fraction of powder as 50%, the transportation of powder from the inlet side to trocar’s end side is done by rotation of the screw conveyor. Thus, the performance is calculated for a 1-sec time frame in an unsteady computation manner. This methodology will help designers in developing design concepts to improve the dispensation and also at the effective area within a quick turnaround time frame.

Keywords: DDPM-KTGF, gas-solids multiphase flow, screw conveyor, Unsteady

Procedia PDF Downloads 175
1672 Parameter Estimation for Contact Tracing in Graph-Based Models

Authors: Augustine Okolie, Johannes Müller, Mirjam Kretzchmar

Abstract:

We adopt a maximum-likelihood framework to estimate parameters of a stochastic susceptible-infected-recovered (SIR) model with contact tracing on a rooted random tree. Given the number of detectees per index case, our estimator allows to determine the degree distribution of the random tree as well as the tracing probability. Since we do not discover all infectees via contact tracing, this estimation is non-trivial. To keep things simple and stable, we develop an approximation suited for realistic situations (contract tracing probability small, or the probability for the detection of index cases small). In this approximation, the only epidemiological parameter entering the estimator is the basic reproduction number R0. The estimator is tested in a simulation study and applied to covid-19 contact tracing data from India. The simulation study underlines the efficiency of the method. For the empirical covid-19 data, we are able to compare different degree distributions and perform a sensitivity analysis. We find that particularly a power-law and a negative binomial degree distribution meet the data well and that the tracing probability is rather large. The sensitivity analysis shows no strong dependency on the reproduction number.

Keywords: stochastic SIR model on graph, contact tracing, branching process, parameter inference

Procedia PDF Downloads 74
1671 Electroencephalogram Based Approach for Mental Stress Detection during Gameplay with Level Prediction

Authors: Priyadarsini Samal, Rajesh Singla

Abstract:

Many mobile games come with the benefits of entertainment by introducing stress to the human brain. In recognizing this mental stress, the brain-computer interface (BCI) plays an important role. It has various neuroimaging approaches which help in analyzing the brain signals. Electroencephalogram (EEG) is the most commonly used method among them as it is non-invasive, portable, and economical. Here, this paper investigates the pattern in brain signals when introduced with mental stress. Two healthy volunteers played a game whose aim was to search hidden words from the grid, and the levels were chosen randomly. The EEG signals during gameplay were recorded to investigate the impacts of stress with the changing levels from easy to medium to hard. A total of 16 features of EEG were analyzed for this experiment which includes power band features with relative powers, event-related desynchronization, along statistical features. Support vector machine was used as the classifier, which resulted in an accuracy of 93.9% for three-level stress analysis; for two levels, the accuracy of 92% and 98% are achieved. In addition to that, another game that was similar in nature was played by the volunteers. A suitable regression model was designed for prediction where the feature sets of the first and second game were used for testing and training purposes, respectively, and an accuracy of 73% was found.

Keywords: brain computer interface, electroencephalogram, regression model, stress, word search

Procedia PDF Downloads 182