Search results for: automatic incident detection
1305 Supporting 'vulnerable' Students to Complete Their Studies During the Economic Crisis in Greece: The Umbrella Program of International Hellenic University
Authors: Rigas Kotsakis, Nikolaos Tsigilis, Vasilis Grammatikopoulos, Evridiki Zachopoulou
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During the last decade, Greece has faced an unprecedented financial crisis, affecting various aspects and functionalities of Higher Education. Besides the restricted funding of academic institutions, the students and their families encountered economical difficulties that undoubtedly influenced the effective completion of their studies. In this context, a fairly large number of students in Alexander campus of International Hellenic University (IHU) delay, interrupt, or even abandon their studies, especially when they come from low-income families, belong to sensitive social or special needs groups, they have different cultural origins, etc. For this reason, a European project, named “Umbrella”, was initiated aiming at providing the necessary psychological support and counseling, especially to disadvantaged students, towards the completion of their studies. To this end, a network of various academic members (academic staff and students) from IHU, namely iMentor, were implicated in different roles. Specifically, experienced academic staff trained students to serve as intermediate links for the integration and educational support of students that fall into the aforementioned sensitive social groups and face problems for the completion of their studies. The main idea of the project is held upon its person-centered character, which facilitates direct student-to-student communication without the intervention of the teaching staff. The backbone of the iMentors network are senior students that face no problem in their academic life and volunteered for this project. It should be noted that there is a provision from the Umbrella structure for substantial and ethical rewards for their engagement. In this context, a well-defined, stringent methodology was implemented for the evaluation of the extent of the problem in IHU and the detection of the profile of the “candidate” disadvantaged students. The first phase included two steps, (a) data collection and (b) data cleansing/ preprocessing. The first step involved the data collection process from the Secretary Services of all Schools in IHU, from 1980 to 2019, which resulted in 96.418 records. The data set included the School name, the semester of studies, a student enrolling criteria, the nationality, the graduation year or the current, up-to-date academic state (still studying, delayed, dropped off, etc.). The second step of the employed methodology involved the data cleansing/preprocessing because of the existence of “noisy” data, missing and erroneous values, etc. Furthermore, several assumptions and grouping actions were imposed to achieve data homogeneity and an easy-to-interpret subsequent statistical analysis. Specifically, the duration of 40 years recording was limited to the last 15 years (2004-2019). In 2004 the Greek Technological Institutions were evolved into Higher Education Universities, leading into a stable and unified frame of graduate studies. In addition, the data concerning active students were excluded from the analysis since the initial processing effort was focused on the detection of factors/variables that differentiated graduate and deleted students. The final working dataset included 21.432 records with only two categories of students, those that have a degree and those who abandoned their studies. Findings of the first phase are presented across faculties and further discussed.Keywords: higher education, students support, economic crisis, mentoring
Procedia PDF Downloads 1151304 Adjustable Aperture with Liquid Crystal for Real-Time Range Sensor
Authors: Yumee Kim, Seung-Guk Hyeon, Kukjin Chun
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An adjustable aperture using a liquid crystal is proposed for real-time range detection and obtaining images simultaneously. The adjustable aperture operates as two types of aperture stops which can create two different Depth of Field images. By analyzing these two images, the distance can be extracted from camera to object. Initially, the aperture stop has large size with zero voltage. When the input voltage is applied, the aperture stop transfer to smaller size by orientational transition of liquid crystal molecules in the device. The diameter of aperture stop is 1.94mm and 1.06mm. The proposed device has low driving voltage of 7.0V and fast response time of 6.22m. Compact size aperture of 6×6×1.1 mm3 is assembled in conventional camera which contain 1/3” HD image sensor and focal length of 3.3mm that can be used in autonomous. The measured range was up to 5m. The adjustable aperture has high stability due to no mechanically moving parts. This range sensor can be applied to the various field of 3D depth map application which is the Advanced Driving Assistance System (ADAS), drones and manufacturing machine.Keywords: adjustable aperture, dual aperture, liquid crystal, ranging and imaging, ADAS, range sensor
Procedia PDF Downloads 3811303 Aromatic Medicinal Plant Classification Using Deep Learning
Authors: Tsega Asresa Mengistu, Getahun Tigistu
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Computer vision is an artificial intelligence subfield that allows computers and systems to retrieve meaning from digital images. It is applied in various fields of study self-driving cars, video surveillance, agriculture, Quality control, Health care, construction, military, and everyday life. Aromatic and medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, and other natural health products for therapeutic and Aromatic culinary purposes. Herbal industries depend on these special plants. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs, and going to export not only industrial raw materials but also valuable foreign exchange. There is a lack of technologies for the classification and identification of Aromatic and medicinal plants in Ethiopia. The manual identification system of plants is a tedious, time-consuming, labor, and lengthy process. For farmers, industry personnel, academics, and pharmacists, it is still difficult to identify parts and usage of plants before ingredient extraction. In order to solve this problem, the researcher uses a deep learning approach for the efficient identification of aromatic and medicinal plants by using a convolutional neural network. The objective of the proposed study is to identify the aromatic and medicinal plant Parts and usages using computer vision technology. Therefore, this research initiated a model for the automatic classification of aromatic and medicinal plants by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides the root, flower and fruit, latex, and barks. The study was conducted on aromatic and medicinal plants available in the Ethiopian Institute of Agricultural Research center. An experimental research design is proposed for this study. This is conducted in Convolutional neural networks and Transfer learning. The Researcher employs sigmoid Activation as the last layer and Rectifier liner unit in the hidden layers. Finally, the researcher got a classification accuracy of 66.4 in convolutional neural networks and 67.3 in mobile networks, and 64 in the Visual Geometry Group.Keywords: aromatic and medicinal plants, computer vision, deep convolutional neural network
Procedia PDF Downloads 4381302 Quality Assurance in Cardiac Disorder Detection Images
Authors: Anam Naveed, Asma Andleeb, Mehreen Sirshar
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In the article, Image processing techniques have been applied on cardiac images for enhancing the image quality. Two types of methodologies considers for survey, invasive techniques and non-invasive techniques. Different image processes for improvement of cardiac image quality and reduce the amount of radiation exposure for invasive techniques are explored. Different image processing algorithms for enhancing the noninvasive cardiac image qualities are described. Beside these two methodologies, third methodology has applied on live streaming of heart rate on ECG window for extracting necessary information, removing noise and enhancing quality. Sensitivity analyses have been carried out to investigate the impacts of cardiac images for diagnosis of cardiac arteries disease and how the enhancement on images will help the cardiologist to diagnoses disease. The paper evaluates strengths and weaknesses of different techniques applied for improved the image quality and draw a conclusion. Some specific limitations must be considered for whole survey, like the patient heart beat must be 70-75 beats/minute while doing the angiography, similarly patient weight and exposure radiation amount has some limitation.Keywords: cardiac images, CT angiography, critical analysis, exposure radiation, invasive techniques, invasive techniques, non-invasive techniques
Procedia PDF Downloads 3521301 Creation of a Trust-Wide, Cross-Speciality, Virtual Teaching Programme for Doctors, Nurses and Allied Healthcare Professionals
Authors: Nelomi Anandagoda, Leanne J. Eveson
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During the COVID-19 pandemic, the surge in in-patient admissions across the medical directorate of a district general hospital necessitated the implementation of an incident rota. Conscious of the impact on training and professional development, the idea of developing a virtual teaching programme was conceived. The programme initially aimed to provide junior doctors, specialist nurses, pharmacists, and allied healthcare professionals from medical specialties and those re-deployed from other specialties (e.g., ophthalmology, GP, surgery, psychiatry) the knowledge and skills to manage the deteriorating patient with COVID-19. The programme was later developed to incorporate the general internal medicine curriculum. To facilitate continuing medical education whilst maintaining social distancing during this period, a virtual platform was used to deliver teaching to junior doctors across two large district general hospitals and two community hospitals. Teaching sessions were recorded and uploaded to a common platform, providing a resource for participants to catch up on and re-watch teaching sessions, making strides towards reducing discrimination against the professional development of less than full-time trainees. Thus, creating a learning environment, which is inclusive and accessible to adult learners in a self-directed manner. The negative impact of the pandemic on the well-being of healthcare professionals is well documented. To support the multi-disciplinary team, the virtual teaching programme evolved to included sessions on well-being, resilience, and work-life balance. Providing teaching for learners across the multi-disciplinary team (MDT) has been an eye-opening experience. By challenging the concept that learners should only be taught within their own peer groups, the authors have fostered a greater appreciation of the strengths of the MDT and showcased the immense wealth of expertise available within the trust. The inclusive nature of the teaching and the ease of joining a virtual teaching session has facilitated the dissemination of knowledge across the MDT, thus improving patient care on the frontline. The weekly teaching programme has been running for over eight months, with ongoing engagement, interest, and participation. As described above, the teaching programme has evolved to accommodate the needs of its learners. It has received excellent feedback with an appreciation of its inclusive, multi-disciplinary, and holistic nature. The COVID-19 pandemic provided a catalyst to rapidly develop novel methods of working and training and widened access/exposure to the virtual technologies available to large organisations. By merging pedagogical expertise and technology, the authors have created an effective online learning environment. Although the authors do not propose to replace face-to-face teaching altogether, this model of virtual multidisciplinary team, cross-site teaching has proven to be a great leveler. It has made high-quality teaching accessible to learners of different confidence levels, grades, specialties, and working patterns.Keywords: cross-site, cross-speciality, inter-disciplinary, multidisciplinary, virtual teaching
Procedia PDF Downloads 1701300 The Incident of Concussion across Popular American Youth Sports: A Retrospective Review
Authors: Rami Hashish, Manon Limousis-Gayda, Caitlin H. McCleery
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Introduction: A leading cause of emergency room visits among youth (in the United States), is sports-related traumatic brain injuries. Mild traumatic brain injuries (mTBIs), also called concussions, are caused by linear and/or angular acceleration experienced at the head and represent an increasing societal burden. Due to the developing nature of the brain in youth, there is a great risk for long-term neuropsychological deficiencies following a concussion. Accordingly, the purpose of this paper is to investigate incidence rates of concussion across gender for the five most common youth sports in the United States. These include basketball, track and field, soccer, baseball (boys), softball (girls), football (boys), and volleyball (girls). Methods: A PubMed search was performed for four search themes combined. The first theme identified the outcomes (concussion, brain injuries, mild traumatic brain injury, etc.). The second theme identified the sport (American football, soccer, basketball, softball, volleyball, track, and field, etc.). The third theme identified the population (adolescence, children, youth, boys, girls). The last theme identified the study design (prevalence, frequency, incidence, prospective). Ultimately, 473 studies were surveyed, with 15 fulfilling the criteria: prospective study presenting original data and incidence of concussion in the relevant youth sport. The following data were extracted from the selected studies: population age, total study population, total athletic exposures (AE) and incidence rate per 1000 athletic exposures (IR/1000). Two One-Way ANOVA and a Tukey’s post hoc test were conducted using SPSS. Results: From the 15 selected studies, statistical analysis revealed the incidence of concussion per 1000 AEs across the considered sports ranged from 0.014 (girl’s track and field) to 0.780 (boy’s football). Average IR/1000 across all sports was 0.483 and 0.268 for boys and girls, respectively; this difference in IR was found to be statistically significant (p=0.013). Tukey’s post hoc test showed that football had significantly higher IR/1000 than boys’ basketball (p=0.022), soccer (p=0.033) and track and field (p=0.026). No statistical difference was found for concussion incidence between girls’ sports. Removal of football was found to lower the IR/1000 for boys without a statistical difference (p=0.101) compared to girls. Discussion: Football was the only sport showing a statistically significant difference in concussion incidence rate relative to other sports (within gender). Males were overall more likely to be concussed than females when football was included (1.8x), whereas concussion was more likely for females when football was excluded. While the significantly higher rate of concussion in football is not surprising because of the nature and rules of the sport, it is concerning that research has shown higher incidence of concussion in practices than games. Interestingly, findings indicate that girls’ sports are more concussive overall when football is removed. This appears to counter the common notion that boys’ sports are more physically taxing and dangerous. Future research should focus on understanding the concussive mechanisms of injury in each sport to enable effective rule changes.Keywords: gender, football, soccer, traumatic brain injury
Procedia PDF Downloads 1411299 Molecular Detection of Crimean-Congo Hemorrhagic Fever in Ticks of Golestan Province, Iran
Authors: Nariman Shahhosseini, Sadegh Chinikar
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Introduction: Crimean-Congo hemorrhagic fever virus (CCHFV) causes severe disease with fatality rates of 30%. The virus is transmitted to humans through the bite of an infected tick, direct contact with the products of infected livestock and nosocomially. The disease occurs sporadically throughout many of African, Asian, and European countries. Different species of ticks serve either as vector or reservoir for CCHFV. Materials and Methods: A molecular survey was conducted on hard ticks (Ixodidae) in Golestan province, north of Iran during 2014-2015. Samples were sent to National Reference Laboratory of Arboviruses (Pasteur Institute of Iran) and viral RNA was detected by RT-PCR. Results: Result revealed the presence of CCHFV in 5.3% of the selected ticks. The infected ticks belonged to Hy. dromedarii, Hy. anatolicum, Hy. marginatum, and Rh. sanguineus. Conclusions: These data demonstrates that Hyalomma ticks are the main vectors of CCHFV in Golestan province. Thus, preventive strategies such as using acaricides and repellents in order to avoid contact with Hyalomma ticks are proposed. Also, personal protective equipment (PPE) must be utilized at abattoirs.Keywords: tick, CCHFV, surveillance, vector diversity
Procedia PDF Downloads 3721298 Health Assessment and Disorders of External Respiration Function among Physicians
Authors: A. G. Margaryan
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Aims and Objectives: Assessment of health status and detection disorders of external respiration functions (ERF) during preventative medical examination among physicians of Armenia. Subjects and Methods: Overall, fifty-nine physicians (17 men and 42 women) were examined and spirometry was carried out. The average age of the physicians was 50 years old. The studies were conducted on the Micromedical MicroLab 3500 Spirometer. Results: 25.4% among 59 examined physicians are overweight; 22.0% of them suffer from obesity. Two physicians are currently smokers. About half of the examined physicians (50.8%) at the time of examination were diagnosed with some diseases and had different health-related problems (excluding the problems related to vision and hearing). FVC was 2.94±0.1, FEV1 – 2.64±0.1, PEF – 329.7±19.9, and FEV1%/FVC – 89.7±1.3. Pathological changes of ERF are identified in 23 (39.0%) cases. 28.8% of physicians had first degree of restrictive disorders, 3.4% – first degree of combined obstructive/ restrictive disorders, 6.8% – second degree of combined obstructive/ restrictive disorders. Only three physicians with disorders of the ERF were diagnosed with chronic bronchitis and bronchial asthma. There were no statistically significant changes in ERF depending on the severity of obesity (P> 0.05). Conclusion: The study showed the prevalence of ERF among physicians, observing mainly mild and moderate changes in ERF parameters.Keywords: Armenia, external respiration function, health status, physicians
Procedia PDF Downloads 2021297 Internet-Of-Things and Ergonomics, Increasing Productivity and Reducing Waste: A Case Study
Authors: V. Jaime Contreras, S. Iliana Nunez, S. Mario Sanchez
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Inside a manufacturing facility, we can find innumerable automatic and manual operations, all of which are relevant to the production process. Some of these processes add more value to the products more than others. Manual operations tend to add value to the product since they can be found in the final assembly area o final operations of the process. In this areas, where a mistake or accident can increase the cost of waste exponentially. To reduce or mitigate these costly mistakes, one approach is to rely on automation to eliminate the operator from the production line - requires a hefty investment and development of specialized machinery. In our approach, the center of the solution is the operator through sufficient and adequate instrumentation, real-time reporting and ergonomics. Efficiency and reduced cycle time can be achieved thorough the integration of Internet-of-Things (IoT) ready technologies into assembly operations to enhance the ergonomics of the workstations. Augmented reality visual aids, RFID triggered personalized workstation dimensions and real-time data transfer and reporting can help achieve these goals. In this case study, a standard work cell will be used for real-life data acquisition and a simulation software to extend the data points beyond the test cycle. Three comparison scenarios will run in the work cell. Each scenario will introduce a dimension of the ergonomics to measure its impact independently. Furthermore, the separate test will determine the limitations of the technology and provide a reference for operating costs and investment required. With the ability, to monitor costs, productivity, cycle time and scrap/waste in real-time the ROI (return on investment) can be determined at the different levels to integration. This case study will help to show that ergonomics in the assembly lines can make significant impact when IoT technologies are introduced. Ergonomics can effectively reduce waste and increase productivity with minimal investment if compared with setting up to custom machine.Keywords: augmented reality visual aids, ergonomics, real-time data acquisition and reporting, RFID triggered workstation dimensions
Procedia PDF Downloads 2141296 Generative Design of Acoustical Diffuser and Absorber Elements Using Large-Scale Additive Manufacturing
Authors: Saqib Aziz, Brad Alexander, Christoph Gengnagel, Stefan Weinzierl
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This paper explores a generative design, simulation, and optimization workflow for the integration of acoustical diffuser and/or absorber geometry with embedded coupled Helmholtz-resonators for full-scale 3D printed building components. Large-scale additive manufacturing in conjunction with algorithmic CAD design tools enables a vast amount of control when creating geometry. This is advantageous regarding the increasing demands of comfort standards for indoor spaces and the use of more resourceful and sustainable construction methods and materials. The presented methodology highlights these new technological advancements and offers a multimodal and integrative design solution with the potential for an immediate application in the AEC-Industry. In principle, the methodology can be applied to a wide range of structural elements that can be manufactured by additive manufacturing processes. The current paper focuses on a case study of an application for a biaxial load-bearing beam grillage made of reinforced concrete, which allows for a variety of applications through the combination of additive prefabricated semi-finished parts and in-situ concrete supplementation. The semi-prefabricated parts or formwork bodies form the basic framework of the supporting structure and at the same time have acoustic absorption and diffusion properties that are precisely acoustically programmed for the space underneath the structure. To this end, a hybrid validation strategy is being explored using a digital and cross-platform simulation environment, verified with physical prototyping. The iterative workflow starts with the generation of a parametric design model for the acoustical geometry using the algorithmic visual scripting editor Grasshopper3D inside the building information modeling (BIM) software Revit. Various geometric attributes (i.e., bottleneck and cavity dimensions) of the resonator are parameterized and fed to a numerical optimization algorithm which can modify the geometry with the goal of increasing absorption at resonance and increasing the bandwidth of the effective absorption range. Using Rhino.Inside and LiveLink for Revit, the generative model was imported directly into the Multiphysics simulation environment COMSOL. The geometry was further modified and prepared for simulation in a semi-automated process. The incident and scattered pressure fields were simulated from which the surface normal absorption coefficients were calculated. This reciprocal process was repeated to further optimize the geometric parameters. Subsequently the numerical models were compared to a set of 3D concrete printed physical twin models, which were tested in a .25 m x .25 m impedance tube. The empirical results served to improve the starting parameter settings of the initial numerical model. The geometry resulting from the numerical optimization was finally returned to grasshopper for further implementation in an interdisciplinary study.Keywords: acoustical design, additive manufacturing, computational design, multimodal optimization
Procedia PDF Downloads 1581295 Study of Electro Magnetic Acoustic Transducer to Detect Flaw in Pipeline
Authors: Yu-Lin Shen, Ming-Kuen Chang
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In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electro Magnetic Acoustic Transducer Testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length.. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.Keywords: EMAT, NDT, artificial defect, ultrasonic testing
Procedia PDF Downloads 4751294 Detecting HCC Tumor in Three Phasic CT Liver Images with Optimization of Neural Network
Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza
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The aim of the present work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. Based on feature selection in different phases, in this research, we design a neural network system that has optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each ROI, 6 distinct set of texture features are extracted such as first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. We show that with the injection of liquid and the analysis of more phases the high relevant features in each region changed. Our results show that for detecting HCC tumor phase3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between these two classes according to our method, relates to first order histogram parameters with the accuracy of 85% in phase 1, 95% phase 2, and 95% in phase 3.Keywords: multi-phasic liver images, texture analysis, neural network, hidden layer
Procedia PDF Downloads 2621293 Water Detection in Aerial Images Using Fuzzy Sets
Authors: Caio Marcelo Nunes, Anderson da Silva Soares, Gustavo Teodoro Laureano, Clarimar Jose Coelho
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This paper presents a methodology to pixel recognition in aerial images using fuzzy $c$-means algorithm. This algorithm is a alternative to recognize areas considering uncertainties and inaccuracies. Traditional clustering technics are used in recognizing of multispectral images of earth's surface. This technics recognize well-defined borders that can be easily discretized. However, in the real world there are many areas with uncertainties and inaccuracies which can be mapped by clustering algorithms that use fuzzy sets. The methodology presents in this work is applied to multispectral images obtained from Landsat-5/TM satellite. The pixels are joined using the $c$-means algorithm. After, a classification process identify the types of surface according the patterns obtained from spectral response of image surface. The classes considered are, exposed soil, moist soil, vegetation, turbid water and clean water. The results obtained shows that the fuzzy clustering identify the real type of the earth's surface.Keywords: aerial images, fuzzy clustering, image processing, pattern recognition
Procedia PDF Downloads 4821292 Rauvolfine B Isolated from the Bark of Rauvolfia reflexa (Apocynaceae) Induces Apoptosis through Activation of Caspase-9 Coupled with S Phase Cell Cycle Arrest
Authors: Mehran Fadaeinasab, Hamed Karimian, Najihah Mohd Hashim, Hapipah Mohd Ali
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In this study, three indole alkaloids namely; rauvolfine B, macusine B, and isoreserpiline have been isolated from the dichloromethane crude extract of Rauvolfia reflexa bark (Apocynaceae). The structural elucidation of the isolated compounds has been performed using spectral methods such as UV, IR, MS, 1D, and 2D NMR. Rauvolfine B showed anti proliferation activity on HCT-116 cancer cell line, its cytotoxicity induction was observed using MTT assay in eight different cell lines. Annexin-V is serving as a marker for apoptotic cells and the Annexin-V-FITC assay was carried out to observe the detection of cell-surface Phosphatidylserine (PS). Apoptosis was confirmed by using caspase-8 and -9 assays. Cell cycle arrest was also investigated using flowcytometric analysis. rauvolfine B had exhibited significantly higher cytotoxicity against HCT-116 cell line. The treatment significantly arrested HCT-116 cells in the S phase. Together, the results presented in this study demonstrated that rauvolfine B inhibited the proliferation of HCT-116 cells and programmed cell death followed by cell cycle arrest.Keywords: apocynacea, indole alkaloid, apoptosis, cell cycle arrest
Procedia PDF Downloads 3341291 Comparative Analysis of Patent Protection between Health System and Enterprises in Shanghai, China
Authors: Na Li, Yunwei Zhang, Yuhong Niu
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The study discussed the patent protections of health system and enterprises in Shanghai. The comparisons of technical distribution and scopes of patent protections between Shanghai health system and enterprises were used by the methods of IPC classification, co-words analysis and visual social network. Results reflected a decreasing order within IPC A61 area, namely A61B, A61K, A61M, and A61F. A61B required to be further investigated. The highest authorized patents A61B17 of A61B of IPC A61 area was found. Within A61B17, fracture fixation, ligament reconstruction, cardiac surgery, and biopsy detection were regarded as common concerned fields by Shanghai health system and enterprises. However, compared with cardiac closure which Shanghai enterprises paid attention to, Shanghai health system was more inclined to blockages and hemostatic tools. The results also revealed that the scopes of patent protections of Shanghai enterprises were relatively centralized. Shanghai enterprises had a series of comprehensive strategies for protecting core patents. In contrast, Shanghai health system was considered to be lack of strategic patent protections for core patents.Keywords: co-words analysis, IPC classification, patent protection, technical distribution
Procedia PDF Downloads 1341290 Glucose Monitoring System Using Machine Learning Algorithms
Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe
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The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning
Procedia PDF Downloads 2031289 Fabrication of Modified Chitosan-Gold Nanoshell with Mercaptopropionic Acid(MPA) for γ-Aminobutyric Acid Detection as a Surface-Enhanced Raman Scattering Substrate
Authors: Bi Wa, Su-Yeon Kwon, Ik-Joong Kang
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Surface-enhanced Raman Scattering (SERS) as the principle for enhancing Raman scattering by molecules adsorbed on rough metal surfaces or by nanostructures is used to detect the concentration change of γ-Aminobutyric Acid (GABA). GABA is the mainly inhibitory neurotransmitter in the mammalian central nervous system in the human body. It plays such significant role in reducing neuronal excitability throughout the nervous system. In this case, the Mercaptopropionic Acid (MPA) is used to modified chitosan –gold nanoshell, which enhances the absorption between GABA and Chitosan-gold nanoshell. The sulfur end of the MPA is linked to gold which is the surface of the chitosan nanoparticles via the very strong S–Au bond, while a functional group (carboxyl group) attached to GABA. The controlling of particles’ size and the surface morphology are also the important factors during the whole experiment. The particle around 100nm is using to link to MPA, and the range of GABA from 1mM to 30mM was detected by the Raman Scattering to obtain the calibrate curve. In this study, DLS, SEM, FT-IR, UV, SERS were used to analyze the products to obtain the conclusion.Keywords: chitosan-gold nanoshell, mercaptopropionic acid, γ-aminobutyric acid, surface-enhanced raman scattering
Procedia PDF Downloads 2441288 Electroactive Ferrocenyl Dendrimers as Transducers for Fabrication of Label-Free Electrochemical Immunosensor
Authors: Sudeshna Chandra, Christian Gäbler, Christian Schliebe, Heinrich Lang
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Highly branched dendrimers provide structural homogeneity, controlled composition, comparable size to biomolecules, internal porosity and multiple functional groups for conjugating reactions. Electro-active dendrimers containing multiple redox units have generated great interest in their use as electrode modifiers for development of biosensors. The electron transfer between the redox-active dendrimers and the biomolecules play a key role in developing a biosensor. Ferrocenes have multiple and electrochemically equivalent redox units that can act as electron “pool” in a system. The ferrocenyl-terminated polyamidoamine dendrimer is capable of transferring multiple numbers of electrons under the same applied potential. Therefore, they can be used for dual purposes: one in building a film over the electrode for immunosensors and the other for immobilizing biomolecules for sensing. Electrochemical immunosensor, thus developed, exhibit fast and sensitive analysis, inexpensive and involve no prior sample pre-treatment. Electrochemical amperometric immunosensors are even more promising because they can achieve a very low detection limit with high sensitivity. Detection of the cancer biomarkers at an early stage can provide crucial information for foundational research of life science, clinical diagnosis and prevention of disease. Elevated concentration of biomarkers in body fluid is an early indication of some type of cancerous disease and among all the biomarkers, IgG is the most common and extensively used clinical cancer biomarkers. We present an IgG (=immunoglobulin) electrochemical immunosensor using a newly synthesized redox-active ferrocenyl dendrimer of generation 2 (G2Fc) as glassy carbon electrode material for immobilizing the antibody. The electrochemical performance of the modified electrodes was assessed in both aqueous and non-aqueous media using varying scan rates to elucidate the reaction mechanism. The potential shift was found to be higher in an aqueous electrolyte due to presence of more H-bond which reduced the electrostatic attraction within the amido groups of the dendrimers. The cyclic voltammetric studies of the G2Fc-modified GCE in 0.1 M PBS solution of pH 7.2 showed a pair of well-defined redox peaks. The peak current decreased significantly with the immobilization of the anti-goat IgG. After the immunosensor is blocked with BSA, a further decrease in the peak current was observed due to the attachment of the protein BSA to the immunosensor. A significant decrease in the current signal of the BSA/anti-IgG/G2Fc/GCE was observed upon immobilizing IgG which may be due to the formation of immune-conjugates that blocks the tunneling of mass and electron transfer. The current signal was found to be directly related to the amount of IgG captured on the electrode surface. With increase in the concentration of IgG, there is a formation of an increasing amount of immune-conjugates that decreased the peak current. The incubation time and concentration of the antibody was optimized for better analytical performance of the immunosensor. The developed amperometric immunosensor is sensitive to IgG concentration as low as 2 ng/mL. Tailoring of redox-active dendrimers provides enhanced electroactivity to the system and enlarges the sensor surface for binding the antibodies. It may be assumed that both electron transfer and diffusion contribute to the signal transformation between the dendrimers and the antibody.Keywords: ferrocenyl dendrimers, electrochemical immunosensors, immunoglobulin, amperometry
Procedia PDF Downloads 3371287 New Insights Into Fog Role In Atmospheric Deposition Using Satellite Images
Authors: Suruchi
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This study aims to examine the spatial and temporal patterns of fog occurrences across Czech Republic. It utilizes satellite imagery and other data sources to achieve this goal. The main objective is to understand the role of fog in atmospheric deposition processes and its potential impact on the environment and ecosystems. Through satellite image analysis, the study will identify and categorize different types of fog, including radiation fog, orographic fog, and mountain fog. Fog detection algorithms and cloud type products will be evaluated to assess the frequency and distribution of fog events throughout the Czech Republic. Furthermore, the regions covered by fog will be classified based on their fog type and associated pollution levels. This will provide insights into the variability in fog characteristics and its implications for atmospheric deposition. Spatial analysis techniques will be used to pinpoint areas prone to frequent fog events and evaluate their pollution levels. Statistical methods will be employed to analyze patterns in fog occurrence over time and its connection with environmental factors. The ultimate goal of this research is to offer fresh perspectives on fog's role in atmospheric deposition processes, enhancing our understanding of its environmental significance and informing future research and environmental management initiatives.Keywords: pollution, GIS, FOG, satellie, atmospheric deposition
Procedia PDF Downloads 221286 Features of Normative and Pathological Realizations of Sibilant Sounds for Computer-Aided Pronunciation Evaluation in Children
Authors: Zuzanna Miodonska, Michal Krecichwost, Pawel Badura
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Sigmatism (lisping) is a speech disorder in which sibilant consonants are mispronounced. The diagnosis of this phenomenon is usually based on the auditory assessment. However, the progress in speech analysis techniques creates a possibility of developing computer-aided sigmatism diagnosis tools. The aim of the study is to statistically verify whether specific acoustic features of sibilant sounds may be related to pronunciation correctness. Such knowledge can be of great importance while implementing classifiers and designing novel tools for automatic sibilants pronunciation evaluation. The study covers analysis of various speech signal measures, including features proposed in the literature for the description of normative sibilants realization. Amplitudes and frequencies of three fricative formants (FF) are extracted based on local spectral maxima of the friction noise. Skewness, kurtosis, four normalized spectral moments (SM) and 13 mel-frequency cepstral coefficients (MFCC) with their 1st and 2nd derivatives (13 Delta and 13 Delta-Delta MFCC) are included in the analysis as well. The resulting feature vector contains 51 measures. The experiments are performed on the speech corpus containing words with selected sibilant sounds (/ʃ, ʒ/) pronounced by 60 preschool children with proper pronunciation or with natural pathologies. In total, 224 /ʃ/ segments and 191 /ʒ/ segments are employed in the study. The Mann-Whitney U test is employed for the analysis of stigmatism and normative pronunciation. Statistically, significant differences are obtained in most of the proposed features in children divided into these two groups at p < 0.05. All spectral moments and fricative formants appear to be distinctive between pathology and proper pronunciation. These metrics describe the friction noise characteristic for sibilants, which makes them particularly promising for the use in sibilants evaluation tools. Correspondences found between phoneme feature values and an expert evaluation of the pronunciation correctness encourage to involve speech analysis tools in diagnosis and therapy of sigmatism. Proposed feature extraction methods could be used in a computer-assisted stigmatism diagnosis or therapy systems.Keywords: computer-aided pronunciation evaluation, sigmatism diagnosis, speech signal analysis, statistical verification
Procedia PDF Downloads 3011285 Integrating AI into Breast Cancer Diagnosis: Aligning Perspectives for Effective Clinical Practice
Authors: Mehrnaz Mostafavi, Mahtab Shabani, Alireza Azani, Fatemeh Ghafari
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Artificial intelligence (AI) can transform breast cancer diagnosis and therapy by providing sophisticated solutions for screening, imaging interpretation, histopathological analysis, and treatment planning. This literature review digs into the many uses of AI in breast cancer treatment, highlighting the need for collaboration between AI scientists and healthcare practitioners. It emphasizes advances in AI-driven breast imaging interpretation, such as computer-aided detection and diagnosis (CADe/CADx) systems and deep learning algorithms. These have shown significant potential for improving diagnostic accuracy and lowering radiologists' workloads. Furthermore, AI approaches such as deep learning have been used in histopathological research to accurately predict hormone receptor status and categorize tumor-associated stroma from regular H&E stains. These AI-powered approaches simplify diagnostic procedures while providing insights into tumor biology and prognosis. As AI becomes more embedded in breast cancer care, it is crucial to ensure its ethical, efficient, and patient-focused implementation to improve outcomes for breast cancer patients ultimately.Keywords: breast cancer, artificial intelligence, cancer diagnosis, clinical practice
Procedia PDF Downloads 681284 Development of a Real-Time Brain-Computer Interface for Interactive Robot Therapy: An Exploration of EEG and EMG Features during Hypnosis
Authors: Maryam Alimardani, Kazuo Hiraki
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This study presents a framework for development of a new generation of therapy robots that can interact with users by monitoring their physiological and mental states. Here, we focused on one of the controversial methods of therapy, hypnotherapy. Hypnosis has shown to be useful in treatment of many clinical conditions. But, even for healthy people, it can be used as an effective technique for relaxation or enhancement of memory and concentration. Our aim is to develop a robot that collects information about user’s mental and physical states using electroencephalogram (EEG) and electromyography (EMG) signals and performs costeffective hypnosis at the comfort of user’s house. The presented framework consists of three main steps: (1) Find the EEG-correlates of mind state before, during, and after hypnosis and establish a cognitive model for state changes, (2) Develop a system that can track the changes in EEG and EMG activities in real time and determines if the user is ready for suggestion, and (3) Implement our system in a humanoid robot that will talk and conduct hypnosis on users based on their mental states. This paper presents a pilot study in regard to the first stage, detection of EEG and EMG features during hypnosis.Keywords: hypnosis, EEG, robotherapy, brain-computer interface (BCI)
Procedia PDF Downloads 2561283 Optimized Simultaneous Determination of Theobromine and Caffeine in Fermented and Unfermented Cacao Beans and in Cocoa Products Using Step Gradient Solvent System in Reverse Phase HPLC
Authors: Ian Marc G. Cabugsa, Kim Ryan A. Won
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Fast, reliable and simultaneous HPLC analysis of theobromine and caffeine in cacao and cocoa products was optimized in this study. The samples tested were raw, fermented, and roasted cacao beans as well as commercially available cocoa products. The HPLC analysis was carried out using step gradient solvent system with acetonitrile and water buffered with H3PO4 as the mobile phase. The HPLC system was optimized using 273 nm wavelength at 35 °C for the column temperature with a flow rate of 1.0 mL/min. Using this method, the theobromine percent recovery mean, Limit of Detection (LOD) and Limit of Quantification (LOQ) is 118.68(±3.38)%, 0.727 and 1.05 respectively. The percent recovery mean, LOD and LOQ for caffeine is 105.53(±3.25)%, 2.42 and 3.50 respectively. The inter-day and intra-day precision for theobromine is 4.31% and 4.48% respectively, while 7.02% and 7.03% was for caffeine respectively. Compared to the standard method in AOAC using methanol in isocratic solvent system, the results of the study produced lesser chromatogram noise with emphasis on theobromine and caffeine. The method is readily usable for cacao and cocoa substances analyses using HPLC with step gradient capability.Keywords: cacao, caffeine, HPLC, step gradient solvent system, theobromine
Procedia PDF Downloads 2811282 Development of Concurrent Engineering through the Application of Software Simulations of Metal Production Processing and Analysis of the Effects of Application
Authors: D. M. Eric, D. Milosevic, F. D. Eric
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Concurrent engineering technologies are a modern concept in manufacturing engineering. One of the key goals in designing modern technological processes is further reduction of production costs, both in the prototype and the preparatory part, as well as during the serial production. Thanks to many segments of concurrent engineering, these goals can be accomplished much more easily. In this paper, we give an overview of the advantages of using modern software simulations in relation to the classical aspects of designing technological processes of metal deformation. Significant savings are achieved thanks to the electronic simulation and software detection of all possible irregularities in the functional-working regime of the technological process. In order for the expected results to be optimal, it is necessary that the input parameters are very objective and that they reliably represent the values of these parameters in real conditions. Since it is a metal deformation treatment here, the particularly important parameters are the coefficient of internal friction between the working material and the tools, as well as the parameters related to the flow curve of the processing material. The paper will give a presentation for the experimental determination of some of these parameters.Keywords: production technologies, metal processing, software simulations, effects of application
Procedia PDF Downloads 2351281 Development of Paper Based Analytical Devices for Analysis of Iron (III) in Natural Water Samples
Authors: Sakchai Satienperakul, Manoch Thanomwat, Jutiporn Seedasama
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A paper based analytical devices (PADs) for the analysis of Fe (III) ion in natural water samples is developed, using reagent from guava leaf extract. The extraction is simply performed in deionized water pH 7, where tannin extract is obtained and used as an alternative natural reagent. The PADs are fabricated by ink-jet printing using alkenyl ketene dimer (AKD) wax. The quantitation of Fe (III) is carried out using reagent from guava leaf extract prepared in acetate buffer at the ratio of 1:1. A color change to gray-purple is observed by naked eye when dropping sample contained Fe (III) ion on PADs channel. The reflective absorption measurement is performed for creating a standard curve. The linear calibration range is observed over the concentration range of 2-10 mg L-1. Detection limited of Fe (III) is observed at 2 mg L-1. In its optimum form, the PADs is stable for up to 30 days under oxygen free conditions. The small dimensions, low volume requirement and alternative natural reagent make the proposed PADs attractive for on-site environmental monitoring and analysis.Keywords: green chemical analysis, guava leaf extract, lab on a chip, paper based analytical device
Procedia PDF Downloads 2411280 Hyperspectral Band Selection for Oil Spill Detection Using Deep Neural Network
Authors: Asmau Mukhtar Ahmed, Olga Duran
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Hydrocarbon (HC) spills constitute a significant problem that causes great concern to the environment. With the latest technology (hyperspectral images) and state of the earth techniques (image processing tools), hydrocarbon spills can easily be detected at an early stage to mitigate the effects caused by such menace. In this study; a controlled laboratory experiment was used, and clay soil was mixed and homogenized with different hydrocarbon types (diesel, bio-diesel, and petrol). The different mixtures were scanned with HYSPEX hyperspectral camera under constant illumination to generate the hypersectral datasets used for this experiment. So far, the Short Wave Infrared Region (SWIR) has been exploited in detecting HC spills with excellent accuracy. However, the Near-Infrared Region (NIR) is somewhat unexplored with regards to HC contamination and how it affects the spectrum of soils. In this study, Deep Neural Network (DNN) was applied to the controlled datasets to detect and quantify the amount of HC spills in soils in the Near-Infrared Region. The initial results are extremely encouraging because it indicates that the DNN was able to identify features of HC in the Near-Infrared Region with a good level of accuracy.Keywords: hydrocarbon, Deep Neural Network, short wave infrared region, near-infrared region, hyperspectral image
Procedia PDF Downloads 1121279 Detection of Total Aflatoxin in Flour of Wheat and Maize Samples in Albania Using ELISA
Authors: Aferdita Dinaku, Jonida Canaj
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Aflatoxins are potentially toxic metabolites produced by certain kinds of fungi (molds) that are found naturally all over the world; they can contaminate food crops and pose a serious health threat to humans by mutagenic and carcinogenic effects. Several types of aflatoxin (14 or more) occur in nature. In Albanian nutrition, cereals (especially wheat and corn) are common ingredients in some traditional meals. This study aimed to investigate the presence of aflatoxins in the flour of wheat and maize that are consumed in Albania’s markets. The samples were collected randomly in different markets in Albania and detected by the ELISA method, measured in 450 nm. The concentration of total aflatoxins was analyzed by enzyme-linked immunosorbent assay (ELISA), and they were ranged between 0.05-1.09 ppb. However, the screened mycotoxin levels in the samples were lower than the maximum permissible limits of European Commission No 1881/2006 (4 μg/kg). The linearity of calibration curves was good for total aflatoxins (B1, B2, G1, G2, M1) (R²=0.99) in the concentration range 0.005-4.05 ppb. The samples were analyzed in two replicated measurements and for each sample, the standard deviation (statistical parameter) is calculated. The results showed that the flour samples are safe, but the necessity of performing such tests is necessary.Keywords: aflatoxins, ELISA technique, food contamination, flour
Procedia PDF Downloads 1571278 Protection System Mis-operations: Fundamental Concepts and Learning from Indian Power Sector
Authors: Pankaj Kumar Jha, Mahendra Singh Hada, Brijendra Singh
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Protection system is an essential feature of the electrical system which helps in detection and removal of faults. Protection system consists of many subsystems like relays, circuit breakers, instrument transformers, auxiliary DC system, auxiliary relays etc. Although the fundamental protective and relay operating concepts are similar throughout the world, there are very significant differences in their implementation. These differences arise through different traditions, operating philosophies, experiences and national standards. Protection system mis-operation due to problem in one or more of its subsystem or inadequate knowledge of numerical relay settings and configuration are very common throughout the world. Protection system mis-operation leads to unstable and unreliable grid operation. In this paper we will discuss about the fundamental concepts of protective relaying and the reasons for protection system mis-operation due to one or more of its subsystems. Many real-world case studies of protection system mis-operation from Indian power sector are discussed in detail in this paper.Keywords: auxiliary trip relays, bus zone, check zone, CT saturation, dead zone protection, DC ground faults, DMT, DR, end fault protection, instrument transformer, SOTF, STUB
Procedia PDF Downloads 761277 Development of a Feedback Control System for a Lab-Scale Biomass Combustion System Using Programmable Logic Controller
Authors: Samuel O. Alamu, Seong W. Lee, Blaise Kalmia, Marc J. Louise Caballes, Xuejun Qian
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The application of combustion technologies for thermal conversion of biomass and solid wastes to energy has been a major solution to the effective handling of wastes over a long period of time. Lab-scale biomass combustion systems have been observed to be economically viable and socially acceptable, but major concerns are the environmental impacts of the process and deviation of temperature distribution within the combustion chamber. Both high and low combustion chamber temperature may affect the overall combustion efficiency and gaseous emissions. Therefore, there is an urgent need to develop a control system which measures the deviations of chamber temperature from set target values, sends these deviations (which generates disturbances in the system) in the form of feedback signal (as input), and control operating conditions for correcting the errors. In this research study, major components of the feedback control system were determined, assembled, and tested. In addition, control algorithms were developed to actuate operating conditions (e.g., air velocity, fuel feeding rate) using ladder logic functions embedded in the Programmable Logic Controller (PLC). The developed control algorithm having chamber temperature as a feedback signal is integrated into the lab-scale swirling fluidized bed combustor (SFBC) to investigate the temperature distribution at different heights of the combustion chamber based on various operating conditions. The air blower rates and the fuel feeding rates obtained from automatic control operations were correlated with manual inputs. There was no observable difference in the correlated results, thus indicating that the written PLC program functions were adequate in designing the experimental study of the lab-scale SFBC. The experimental results were analyzed to study the effect of air velocity operating at 222-273 ft/min and fuel feeding rate of 60-90 rpm on the chamber temperature. The developed temperature-based feedback control system was shown to be adequate in controlling the airflow and the fuel feeding rate for the overall biomass combustion process as it helps to minimize the steady-state error.Keywords: air flow, biomass combustion, feedback control signal, fuel feeding, ladder logic, programmable logic controller, temperature
Procedia PDF Downloads 1291276 Development of a Delivery System for Statin Targeted Spray is a Breakthrough Therapy in Alzheimer’s Prevention
Authors: Fakhr Eddin Alnaal, Angela Dahdal, Duaa Aladib, Sabeen Ibrahim, Ibrahim Ghoraibi, Bissan Ahmed
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Dementia is one of the diseases which had several stages and Alzheimer’s term was selected in respect for the first doctor Alzheimer who defined the first symptoms of this diseases in a woman whom was well treated by him. The fact that this is a type of a silent disease on which you have a long-term process of neurological degradation and suddenly gives symptoms which are most often irreversible, on clinical level likely we can consider it as a malignancy, one in terms of that it is sudden shocking irreversible and on the level of behavior and some mortality beside the lack of early detection tools for diagnosis. Therefore, the goal of our project is to test the concept of the ability of Statin in prevention of such disease and we investigated that both on experimental level and most importantly on clinical one, the clinical part was performed in a recognized house of aged people who had accidently a high cholesterol and were for years given Statin to treat that elevation, however after the symptoms of Alzheimer’s appeared and when diagnosed, they were well treated and rapidly recovered compared to Alzheimer’s patients in the same house who did not receive Statin had a mild improvement in their symptoms after the therapy, on the other hand we confirmed such observation by a well-organized experimental work.Keywords: Alzheimer's, dementia, silent disease, statin
Procedia PDF Downloads 133