Search results for: probability of detection (PD)
2502 The Predictive Significance of Metastasis Associated in Colon Cancer-1 (MACC1) in Primary Breast Cancer
Authors: Jasminka Mujic, Karin Milde-Langosch, Volkmar Mueller, Mirza Suljagic, Tea Becirevic, Jozo Coric, Daria Ler
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MACC1 (metastasis associated in colon cancer-1) is a prognostic biomarker for tumor progression, metastasis, and survival of a variety of solid cancers. MACC1 also causes tumor growth in xenograft models and acts as a master regulator of the HGF/MET signaling pathway. In breast cancer, the expression of MACC1 determined by immunohistochemistry was significantly associated with positive lymph node status and advanced clinical stage. The aim of the present study was to further investigate the prognostic or predictive value of MACC1 expression in breast cancer using western blot analysis and immunohistochemistry. The results of our study have shown that high MACC1 expression in breast cancer is associated with shorter disease-free survival, especially in node-negative tumors. The MACC1 might be a suitable biomarker to select patients with a higher probability of recurrence which might benefit from adjuvant chemotherapy. Our results support a biologic role and potentially open the perspective for the use of MACC1 as predictive biomarker for treatment decision in breast cancer patients.Keywords: breast cancer, biomarker, HGF/MET, MACC1
Procedia PDF Downloads 2332501 Comparing SVM and Naïve Bayes Classifier for Automatic Microaneurysm Detections
Authors: A. Sopharak, B. Uyyanonvara, S. Barman
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Diabetic retinopathy is characterized by the development of retinal microaneurysms. The damage can be prevented if disease is treated in its early stages. In this paper, we are comparing Support Vector Machine (SVM) and Naïve Bayes (NB) classifiers for automatic microaneurysm detection in images acquired through non-dilated pupils. The Nearest Neighbor classifier is used as a baseline for comparison. Detected microaneurysms are validated with expert ophthalmologists’ hand-drawn ground-truths. The sensitivity, specificity, precision and accuracy of each method are also compared.Keywords: diabetic retinopathy, microaneurysm, naive Bayes classifier, SVM classifier
Procedia PDF Downloads 3292500 Nonlinear Power Measurement Algorithm of the Input Mix Components of the Noise Signal and Pulse Interference
Authors: Alexey V. Klyuev, Valery P. Samarin, Viktor F. Klyuev, Andrey V. Klyuev
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A power measurement algorithm of the input mix components of the noise signal and pulse interference is considered. The algorithm efficiency analysis has been carried out for different interference to signal ratio. Algorithm performance features have been explored by numerical experiment results.Keywords: noise signal, pulse interference, signal power, spectrum width, detection
Procedia PDF Downloads 3372499 Application of Raman Spectroscopy for Ovarian Cancer Detection: Comparative Analysis of Fresh, Formalin-Fixed, and Paraffin-Embedded Samples
Authors: Zeinab Farhat, Nicolas Errien, Romuald Wernert, Véronique Verriele, Frédéric Amiard, Philippe Daniel
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Ovarian cancer, also known as the silent killer, is the fifth most common cancer among women worldwide, and its death rate is higher than that of other gynecological cancers. The low survival rate of women with high-grade serous ovarian carcinoma highlights the critical need for the development of new methods for early detection and diagnosis of the disease. The aim of this study was to evaluate if Raman spectroscopy combined with chemometric methods such as Principal Component Analysis (PCA) could differentiate between cancerous and normal tissues from different types of samples, such as paraffin embedding, chemical deparaffinized, formalin-fixed and fresh samples of the same normal and malignant ovarian tissue. The method was applied specifically to two critical spectral regions: the signature region (860-1000 〖cm〗^(-1)) and the high-frequency region (2800-3100 〖cm〗^(-1) ). The mean spectra of paraffin-embedded in normal and malignant tissues showed almost similar intensity. On the other hand, the mean spectra of normal and cancer tissues from chemical deparaffinized, formalin-fixed, and fresh samples show significant intensity differences. These spectral differences reflect variations in the molecular composition of the tissues, particularly lipids and proteins. PCA, which was applied to distinguish between cancer and normal tissues, was performed on whole spectra and on selected regions—the PCA score plot of paraffin-embedded shows considerable overlap between the two groups. However, the PCA score of chemicals deparaffinized, formalin-fixed, and fresh samples showed a good discrimination of tissue types. Our findings were validated by analyses of a set of samples whose status (normal and cancerous) was not previously known. The results of this study suggest that Raman Spectroscopy associated with PCA methods has the capacity to provide clinically significant differentiation between normal and cancerous ovarian tissues.Keywords: Raman spectroscopy, ovarian cancer, signal processing, Principal Component Analysis, classification
Procedia PDF Downloads 252498 The Number of Corona Virus Infections in 2020
Authors: Yasaswi Vengalasetti, Jacob Eisenach, Jay Bhattacharya
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Seroprevalence studies can provide an estimation of the Infection Fatality Rate (IFR), the probability of death given infection. Measuring the seroprevalence and reported deaths of an area within a given time frame an IFR can be estimated. With this IFR calculation, we can then observe COVID-19 death figures in different countries around the world and estimate the number of cases since the onset of the pandemic. There is a large range for estimated COVID-19 infections across different countries. This ranged from 0.659 million infections in Hong Kong to 277 million infections in India. The largest estimated share of the population infected is 63% in Peru and the lowest is 3% in Norway. For younger populations, COVID-19 is most fatal in South America; for older populations, it is most fatal in North America. The Asian regions stand out with significantly lower IFRs in older populations: at 80 years old, COVID-19 is about three times as fatal than in South Asia and about twelve times as fatal than in East Asia. The weighted average for the share of the population infected, the sum of infections divided by the sum of populations across all countries, is 23%.Keywords: epidemiology, seroprevalence, covid-19, infection fatality rate
Procedia PDF Downloads 1232497 Crop Price Variation and Water Saving Technologies in Iran
Authors: Saeed Yazdani, Shahrbanoo Bagheri, Sepideh Nikravesh
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Considering the importance and scarcity of water resources, the efficient management of water resources is of great importance. Adoption of modern irrigation technology is considered to be a key of increasing the efficiency of water used in agriculture. Policy makers have implemented several ways to induce the adoption of new irrigation technology. The empirical studies show that farmers are reluctant to utilize the use of new irrigation methods. This study aims to assess factors affecting on farmer’s decision on the application of water saving technologies with emphasize on crop price variation and water sources. A Logit model was employed to examine the impact of different variables on use of water saving technology. The required data gathered from a sample of 204 farmers in the year 2012. The results indicate that different variables such as crop price variability, water supply source, high-value crops, farm size, income, education, membership in cooperatives have a positive effect and variables such as age and number of plots have a negative impact on the probability of adopting modern water saving technologies.Keywords: irrigation, water, water saving technology, scarcity
Procedia PDF Downloads 2252496 Personal Factors and Career Adaptability in a Call Centre Work Environment: The Mediating Effects of Professional Efficacy
Authors: Nisha Harry
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The study discussed in this article sought to assess whether a sense of professional efficacy mediates the relationship between personal factors and career adaptability. A quantitative cross-sectional survey approach was followed. A non–probability sample of (N = 409) of which predominantly early career and permanently employed black females in call centres in Africa participated in this study. In order to assess personal factors, the participants completed sense of meaningfulness and emotional intelligence measures. Measures of professional efficacy and career adaptability were also completed. The results of the mediational analysis revealed that professional efficacy significantly mediates the meaningfulness (sense of coherence) and career adaptability relationship, but not the emotional intelligence–career adaptability relationship. Call centre agents with professional efficacy are likely to be more work engaged as a result of their sense of meaningfulness and emotional intelligence.Keywords: call centre, professional efficacy, career adaptability, emotional intelligence
Procedia PDF Downloads 3582495 Replacing MOSFETs with Single Electron Transistors (SET) to Reduce Power Consumption of an Inverter Circuit
Authors: Ahmed Shariful Alam, Abu Hena M. Mustafa Kamal, M. Abdul Rahman, M. Nasmus Sakib Khan Shabbir, Atiqul Islam
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According to the rules of quantum mechanics there is a non-vanishing probability of for an electron to tunnel through a thin insulating barrier or a thin capacitor which is not possible according to the laws of classical physics. Tunneling of electron through a thin insulating barrier or tunnel junction is a random event and the magnitude of current flowing due to the tunneling of electron is very low. As the current flowing through a Single Electron Transistor (SET) is the result of electron tunneling through tunnel junctions of its source and drain the supply voltage requirement is also very low. As a result, the power consumption across a Single Electron Transistor is ultra-low in comparison to that of a MOSFET. In this paper simulations have been done with PSPICE for an inverter built with both SETs and MOSFETs. 35mV supply voltage was used for a SET built inverter circuit and the supply voltage used for a CMOS inverter was 3.5V.Keywords: ITRS, enhancement type MOSFET, island, DC analysis, transient analysis, power consumption, background charge co-tunneling
Procedia PDF Downloads 5262494 Development of Micelle-Mediated Sr(II) Fluorescent Analysis System
Authors: K. Akutsu, S. Mori, T. Hanashima
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Fluorescent probes are useful for the selective detection of trace amount of ions and biomolecular imaging in living cells. Various kinds of metal ion-selective fluorescent compounds have been developed, and some compounds have been applied as effective metal ion-selective fluorescent probes. However, because competition between the ligand and water molecules for the metal ion constitutes a major contribution to the stability of a complex in aqueous solution, it is difficult to develop a highly sensitive, selective, and stable fluorescent probe in aqueous solution. The micelles, these are formed in the surfactant aqueous solution, provides a unique hydrophobic nano-environment for stabilizing metal-organic complexes in aqueous solution. Therefore, we focused on the unique properties of micelles to develop a new fluorescence analysis system. We have been developed a fluorescence analysis system for Sr(II) by using a Sr(II) fluorescent sensor, N-(2-hydroxy-3-(1H-benzimidazol-2-yl)-phenyl)-1-aza-18-crown-6-ether (BIC), and studied its complexation behavior with Sr(II) in micellar solution. We revealed that the stability constant of Sr(II)-BIC complex was 10 times higher than that in aqueous solution. In addition, its detection limit value was also improved up to 300 times by this system. However, the mechanisms of these phenomena have remained obscure. In this study, we investigated the structure of Sr(II)-BIC complex in aqueous micellar solution by combining use the extended X-ray absorption fine structure (EXAFS) and neutron reflectivity (NR) method to understand the unique properties of the fluorescence analysis system from the view point of structural chemistry. EXAFS and NR experiments were performed on BL-27B at KEK-PF and on BL17 SHARAKU at J-PARC MLF, respectively. The obtained EXAFS spectra and their fitting results indicated that Sr(II) and BIC formed a Sr(18-crown-6-ether)-like complex in aqueous micellar solution. The EXAFS results also indicated that the hydrophilic head group of surfactant molecule was directly coordinated with Sr(II). In addition, the NR results also indicated that Sr(II)-BIC complex would interact with the surface of micelle molecules. Therefore, we concluded that Sr(II), BIC, and surfactant molecule formed a ternary complexes in aqueous micellar solution, and at least, it is clear that the improvement of the stability constant in micellar solution is attributed to the result of the formation of Sr(BIC)(surfactant) complex.Keywords: micell, fluorescent probe, neutron reflectivity, EXAFS
Procedia PDF Downloads 1832493 A Literature Review of Precision Agriculture: Applications of Diagnostic Diseases in Corn, Potato, and Rice Based on Artificial Intelligence
Authors: Carolina Zambrana, Grover Zurita
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The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence
Procedia PDF Downloads 792492 Operation Strategy of Multi-Energy Storage System Considering Power System Reliability
Authors: Wook-Won Kim, Je-Seok Shin, Jin-O Kim
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As the penetration of Energy Storage System (ESS) increases in the power system due to higher performance and lower cost than ever, ESS is expanding its role to the ancillary service as well as the storage of extra energy from the intermittent renewable energy resources. For multi-ESS with different capacity and SOC level each other, it is required to make the optimal schedule of SOC level use the multi-ESS effectively. This paper proposes the energy allocation method for the multiple battery ESS with reliability constraint, in order to make the ESS discharge the required energy as long as possible. A simple but effective method is proposed in this paper, to satisfy the power for the spinning reserve requirement while improving the system reliability. Modelling of ESS is also proposed, and reliability is evaluated by using the combined reliability model which includes the proposed ESS model and conventional generation one. In the case study, it can be observed that the required power is distributed to each ESS adequately and accordingly, the SOC is scheduled to improve the reliability indices such as Loss of Load Probability (LOLP) and Loss of Load Expectation (LOLE).Keywords: multiple energy storage system (MESS), energy allocation method, SOC schedule, reliability constraints
Procedia PDF Downloads 3682491 Simulation of Performance of LaBr₃ (Ce) Using GEANT4
Authors: Zarana Dave
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Cerium-doped lanthanum bromide, LaBr₃ (Ce), scintillator shows attracting properties for spectroscopy that makes it a suitable solution for security, medical, geophysics and high energy physics applications. Here, the performance parameters of a cylindrical LaBr₃ (Ce) scintillator was investigated. The first aspect is the determination of the efficiency for γ - ray detection, measured with GEANT4 simulation toolkit from 10keV to 10MeV energy range. The second is the detailed study of background radiation of LaBr₃ (Ce). It has relatively high intrinsic radiation background due to naturally occurring ¹³⁸La and ²²⁷Ac radioisotopes.Keywords: LaBr₃(Ce), GEANT4, efficiency, background radiation
Procedia PDF Downloads 2222490 Double Functionalization of Magnetic Colloids with Electroactive Molecules and Antibody for Platelet Detection and Separation
Authors: Feixiong Chen, Naoufel Haddour, Marie Frenea-Robin, Yves MéRieux, Yann Chevolot, Virginie Monnier
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Neonatal thrombopenia occurs when the mother generates antibodies against her baby’s platelet antigens. It is particularly critical for newborns because it can cause coagulation troubles leading to intracranial hemorrhage. In this case, diagnosis must be done quickly to make platelets transfusion immediately after birth. Before transfusion, platelet antigens must be tested carefully to avoid rejection. The majority of thrombopenia (95 %) are caused by antibodies directed against Human Platelet Antigen 1a (HPA-1a) or 5b (HPA-5b). The common method for antigen platelets detection is polymerase chain reaction allowing for identification of gene sequence. However, it is expensive, time-consuming and requires significant blood volume which is not suitable for newborns. We propose to develop a point-of-care device based on double functionalized magnetic colloids with 1) antibodies specific to antigen platelets and 2) highly sensitive electroactive molecules in order to be detected by an electrochemical microsensor. These magnetic colloids will be used first to isolate platelets from other blood components, then to capture specifically platelets bearing HPA-1a and HPA-5b antigens and finally to attract them close to sensor working electrode for improved electrochemical signal. The expected advantages are an assay time lower than 20 min starting from blood volume smaller than 100 µL. Our functionalization procedure based on amine dendrimers and NHS-ester modification of initial carboxyl colloids will be presented. Functionalization efficiency was evaluated by colorimetric titration of surface chemical groups, zeta potential measurements, infrared spectroscopy, fluorescence scanning and cyclic voltammetry. Our results showed that electroactive molecules and antibodies can be immobilized successfully onto magnetic colloids. Application of a magnetic field onto working electrode increased the detected electrochemical signal. Magnetic colloids were able to capture specific purified antigens extracted from platelets.Keywords: Magnetic Nanoparticles , Electroactive Molecules, Antibody, Platelet
Procedia PDF Downloads 2702489 Investigation of Factors Affecting Bangkok Urban Residents’ Behaviour of Bookkeeping for Household Accounts
Authors: Anocha Kimkong
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This research paper, based on demographic variables, is aimed to study the behaviour of bookkeeping for household accounts of residents living in urban communities in Dusit District, Bangkok and to investigate factors that affected the behavior of bookkeeping. By use of non proportional stratified sampling technique of probability sampling, the research had a total of 247 samples. The systematic sampling technique was also utilized by selecting one household out of every 3 households. The demographic findings reported female respondents as the majority with an average age between 26-35 years old, having married status and having children. The respondents earn a living by selling, with an average income per month of between 5,001-15,000 Baht. Most of the families rent a house and each family have approximately 3-4 members. Furthermore, most of the household respondents used to be trained to do bookkeeping for household accounts. In addition, the factors in affecting the residents’ behaviour of doing household account bookkeeping included a dislike of numbers, inaccuracy of recording, availability of accounting counselors in the communities, people’s participation in trainings arranged by outside organizations.Keywords: household account, bookkeeping, urban community, demographic variables
Procedia PDF Downloads 2702488 Red-Tide Detection and Prediction Using MODIS Data in the Arabian Gulf of Qatar
Authors: Yasir E. Mohieldeen
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Qatar is one of the most water scarce countries in the World. In 2014, the average per capita rainfall was less than 29 m3/y/ca, while the global average is 6,000 m3/y/ca. However, the per capita water consumption in Qatar is among the highest in the World: more than 500 liters per person per day, whereas the global average is 160 liters per person per day. Since the early 2000s, Qatar has been relying heavily on desalinated water from the Arabian Gulf as the main source of fresh water. In 2009, about 99.9% of the total potable water produced was desalinated. Reliance on desalinated water makes Qatar very vulnerable to water related natural disasters, such as the red-tide phenomenon. Qatar’s strategic water reserve lasts for only 7 days. In case of red-tide outbreak, the country would not be able to desalinate water for days, let alone the months that this disaster would bring about (as it clogs the desalination equipment). The 2008-09 red-tide outbreak, for instance, lasted for more than eight months and forced the closure of desalination plants in the region for weeks. This study aims at identifying favorite conditions for red-tide outbreaks, using satellite data along with in-situ measurements. This identification would allow the prediction of these outbreaks and their hotspots. Prediction and monitoring of outbreaks are crucial to water security in the country, as different measures could be put in place in advance to prevent an outbreak and mitigate its impact if it happened. Red-tide outbreaks are detected using different algorithms for chlorophyll concentration in the Gulf waters. Vegetation indices, such as Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were used along with Surface Algae Bloom Index (SABI) to detect known outbreaks. MODIS (or Moderate Resolution Imaging Spectroradiometer) bands are used to calculate these indices. A red-tide outbreaks atlas in the Arabian Gulf is being produced. Prediction of red-tide outbreaks ahead of their occurrences would give critical information on possible water-shortage in the country. Detecting known outbreaks in the past few decades and related parameters (e.g. water salinity, water surface temperature, nutrition, sandstorms, … etc) enables the identification of favorite conditions of red-tide outbreak that are key to the prediction of these outbreaks.Keywords: Arabian Gulf, MODIS, red-tide detection, strategic water reserve, water desalination
Procedia PDF Downloads 1072487 Socio-Economic Inequality in Breastfeeding Patterns in India
Authors: Ankita Shukla
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The promotion and support of breastfeeding is a global priority with benefits for maternal and infant health, especially in low income and middle-income countries where the probability of child survival is still very low. In India too it has been well established that breastfeeding increases the survival of the child. However, the breastfeeding levels are quite low in the country. Examining the socio-economic inequality in breastfeeding pattern can help to the causal pathways responsible for early breastfeeding termination. This paper tries to understand the socio-economic differential in breastfeeding patterns among Indian women. Data is used from nationally representative National Family Health Survey-3. Using Cox regression modelling techniques, the analysis found that the likelihood of having small breastfeeding duration increased with increasing household wealth status similarly education also has negative effect on breastfeeding duration. The considerable gender difference is also visible in India, likelihood of stopping breastfeeding was significantly higher among female children compared with male children. To understand the cultural factors or norms responsible for the early termination of breastfeeding more in depth/qualitative studies are needed.Keywords: breastfeeding, India, socio-economic inequality, women education
Procedia PDF Downloads 2362486 Securing Mobile Ad-Hoc Network Utilizing OPNET Simulator
Authors: Tariq A. El Shheibia, Halima Mohamed Belhamad
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This paper is considered securing data based on multi-path protocol (SDMP) in mobile ad hoc network utilizing OPNET simulator modular 14.5, including the AODV routing protocol at the network as based multi-path algorithm for message security in MANETs. The main idea of this work is to present a way that is able to detect the attacker inside the MANETs. The detection for this attacker will be performed by adding some effective parameters to the network.Keywords: MANET, AODV, malicious node, OPNET
Procedia PDF Downloads 2952485 Conformance to Spatial Planning between the Kampala Physical Development Plan of 2012 and the Existing Land Use in 2021
Authors: Brendah Nagula, Omolo Fredrick Okalebo, Ronald Ssengendo, Ivan Bamweyana
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The Kampala Physical Development Plan (KPDP) was developed in 2012 and projected both long term and short term developments within the City .The purpose of the plan was to not only shape the city into a spatially planned area but also to control the urban sprawl trends that had expanded with pronounced instances of informal settlements. This plan was approved by the National Physical Planning Board and a signature was appended by the Minister in 2013. Much as the KPDP plan has been implemented using different approaches such as detailed planning, development control, subdivision planning, carrying out construction inspections, greening and beautification, there is still limited knowledge on the level of conformance towards this plan. Therefore, it is yet to be determined whether it has been effective in shaping the City into an ideal spatially planned area. Attaining a clear picture of the level of conformance towards the KPDP 2012 through evaluation between the planned and the existing land use in Kampala City was performed. Methods such as Supervised Classification and Post Classification Change Detection were adopted to perform this evaluation. Scrutiny of findings revealed Central Division registered the lowest level of conformance to the planning standards specified in the KPDP 2012 followed by Nakawa, Rubaga, Kawempe, and Makindye. Furthermore, mixed-use development was identified as the land use with the highest level of non-conformity of 25.11% and institutional land use registered the highest level of conformance of 84.45 %. The results show that the aspect of location was not carefully considered while allocating uses in the KPDP whereby areas located near the Central Business District have higher land rents and hence require uses that ensure profit maximization. Also, the prominence of development towards mixed-use denotes an increased demand for land towards compact development that was not catered for in the plan. Therefore in order to transform Kampala city into a spatially planned area, there is need to carefully develop detailed plans especially for all the Central Division planning precincts indicating considerations for land use densification.Keywords: spatial plan, post classification change detection, Kampala city, landuse
Procedia PDF Downloads 922484 Renewable Energy Trends Analysis: A Patents Study
Authors: Sepulveda Juan
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This article explains the elements and considerations taken into account when implementing and applying patent evaluation and scientometric study in the identifications of technology trends, and the tools that led to the implementation of a software application for patent revision. Univariate analysis helped recognize the technological leaders in the field of energy, and steered the way for a multivariate analysis of this sample, which allowed for a graphical description of the techniques of mature technologies, as well as the detection of emerging technologies. This article ends with a validation of the methodology as applied to the case of fuel cells.Keywords: patents, scientometric, renewable energy, technology maps
Procedia PDF Downloads 3082483 A Simple Olfactometer for Odour and Lateralization Thresholds of Chemical Vapours
Authors: Lena Ernstgård, Aishwarya M. Dwivedi, Johan Lundström, Gunnar Johanson
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A simple inexpensive olfactometer was constructed to enable valid measures of detection threshold of low concentrations of vapours of chemicals. The delivery system consists of seven syringe pumps, each connected to a Tedlar bag containing a predefined concentration of the test chemical in the air. The seven pumps are connected to a 8-way mixing valve which in turn connects to a birhinal nose piece. Chemical vapor of known concentration is generated by injection of an appropriate amount of the test chemical into a Tedlar bag with a known volume of clean air. Complete vaporization is assured by gentle heating of the bag from the outside with a heat flow. The six test concentrations are obtained by adding different volumes from the starting bag to six new Tedlar bags with known volumes of clean air. One bag contains clean air only. Thus, six different test concentrations and clean air can easily be tested in series by shifting the valve to new positions. Initial in-line measurement with a photoionization detector showed that the delivery system quickly responded to a shift in valve position. Thus 90% of the desired concentration was reached within 15 seconds. The concentrations in the bags are verified daily by gas chromatography. The stability of the system in terms of chemical concentration is monitored in real time by means of a photo-ionization detector. To determine lateralization thresholds, an additional pump supplying clean air is added to the delivery system in a way so that the nostrils can be separately and interchangeably be exposed to clean air and test chemical. Odor and lateralization thresholds were determined for three aldehydes; acrolein, crotonaldehyde, and hexanal in 20 healthy naïve individuals. Aldehydes generally have a strong odour, and the selected aldehydes are also considered to be irritating to mucous membranes. The median odor thresholds of the three aldehydes were 0.017, 0.0008, and 0.097 ppm, respectively. No lateralization threshold could be identified for acrolein, whereas the medians for crotonaldehyde and hexanal were 0.003 and 0.39 ppm, respectively. In conclusion, we constructed a simple, inexpensive olfactometer that allows for stable and easily measurable concentrations of vapors of the test chemical. Our test with aldehydes demonstrates that the system produces valid detection among volunteers in terms of odour and lateralization thresholds.Keywords: irritation, odour delivery, olfactometer, smell
Procedia PDF Downloads 2162482 An Automatic Large Classroom Attendance Conceptual Model Using Face Counting
Authors: Sirajdin Olagoke Adeshina, Haidi Ibrahim, Akeem Salawu
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large lecture theatres cannot be covered by a single camera but rather by a multicamera setup because of their size, shape, and seating arrangements. Although, classroom capture is achievable through a single camera. Therefore, a design and implementation of a multicamera setup for a large lecture hall were considered. Researchers have shown emphasis on the impact of class attendance taken on the academic performance of students. However, the traditional method of carrying out this exercise is below standard, especially for large lecture theatres, because of the student population, the time required, sophistication, exhaustiveness, and manipulative influence. An automated large classroom attendance system is, therefore, imperative. The common approach in this system is face detection and recognition, where known student faces are captured and stored for recognition purposes. This approach will require constant face database updates due to constant changes in the facial features. Alternatively, face counting can be performed by cropping the localized faces on the video or image into a folder and then count them. This research aims to develop a face localization-based approach to detect student faces in classroom images captured using a multicamera setup. A selected Haar-like feature cascade face detector trained with an asymmetric goal to minimize the False Rejection Rate (FRR) relative to the False Acceptance Rate (FAR) was applied on Raspberry Pi 4B. A relationship between the two factors (FRR and FAR) was established using a constant (λ) as a trade-off between the two factors for automatic adjustment during training. An evaluation of the proposed approach and the conventional AdaBoost on classroom datasets shows an improvement of 8% TPR (output result of low FRR) and 7% minimization of the FRR. The average learning speed of the proposed approach was improved with 1.19s execution time per image compared to 2.38s of the improved AdaBoost. Consequently, the proposed approach achieved 97% TPR with an overhead constraint time of 22.9s compared to 46.7s of the improved Adaboost when evaluated on images obtained from a large lecture hall (DK5) USM.Keywords: automatic attendance, face detection, haar-like cascade, manual attendance
Procedia PDF Downloads 722481 Implementation of a Non-Poissonian Model in a Low-Seismicity Area
Authors: Ludivine Saint-Mard, Masato Nakajima, Gloria Senfaute
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In areas with low to moderate seismicity, the probabilistic seismic hazard analysis frequently uses a Poisson approach, which assumes independence in time and space of events to determine the annual probability of earthquake occurrence. Nevertheless, in countries with high seismic rate, such as Japan, it is frequently use non-poissonian model which assumes that next earthquake occurrence depends on the date of previous one. The objective of this paper is to apply a non-poissonian models in a region of low to moderate seismicity to get a feedback on the following questions: can we overcome the lack of data to determine some key parameters?, and can we deal with uncertainties to apply largely this methodology on an industrial context?. The Brownian-Passage-Time model was applied to a fault located in France and conclude that even if the lack of data can be overcome with some calculations, the amount of uncertainties and number of scenarios leads to a numerous branches in PSHA, making this method difficult to apply on a large scale of low to moderate seismicity areas and in an industrial context.Keywords: probabilistic seismic hazard, non-poissonian model, earthquake occurrence, low seismicity
Procedia PDF Downloads 622480 Artificial Intelligence for Traffic Signal Control and Data Collection
Authors: Reggie Chandra
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Trafficaccidents and traffic signal optimization are correlated. However, 70-90% of the traffic signals across the USA are not synchronized. The reason behind that is insufficient resources to create and implement timing plans. In this work, we will discuss the use of a breakthrough Artificial Intelligence (AI) technology to optimize traffic flow and collect 24/7/365 accurate traffic data using a vehicle detection system. We will discuss what are recent advances in Artificial Intelligence technology, how does AI work in vehicles, pedestrians, and bike data collection, creating timing plans, and what is the best workflow for that. Apart from that, this paper will showcase how Artificial Intelligence makes signal timing affordable. We will introduce a technology that uses Convolutional Neural Networks (CNN) and deep learning algorithms to detect, collect data, develop timing plans and deploy them in the field. Convolutional Neural Networks are a class of deep learning networks inspired by the biological processes in the visual cortex. A neural net is modeled after the human brain. It consists of millions of densely connected processing nodes. It is a form of machine learning where the neural net learns to recognize vehicles through training - which is called Deep Learning. The well-trained algorithm overcomes most of the issues faced by other detection methods and provides nearly 100% traffic data accuracy. Through this continuous learning-based method, we can constantly update traffic patterns, generate an unlimited number of timing plans and thus improve vehicle flow. Convolutional Neural Networks not only outperform other detection algorithms but also, in cases such as classifying objects into fine-grained categories, outperform humans. Safety is of primary importance to traffic professionals, but they don't have the studies or data to support their decisions. Currently, one-third of transportation agencies do not collect pedestrian and bike data. We will discuss how the use of Artificial Intelligence for data collection can help reduce pedestrian fatalities and enhance the safety of all vulnerable road users. Moreover, it provides traffic engineers with tools that allow them to unleash their potential, instead of dealing with constant complaints, a snapshot of limited handpicked data, dealing with multiple systems requiring additional work for adaptation. The methodologies used and proposed in the research contain a camera model identification method based on deep Convolutional Neural Networks. The proposed application was evaluated on our data sets acquired through a variety of daily real-world road conditions and compared with the performance of the commonly used methods requiring data collection by counting, evaluating, and adapting it, and running it through well-established algorithms, and then deploying it to the field. This work explores themes such as how technologies powered by Artificial Intelligence can benefit your community and how to translate the complex and often overwhelming benefits into a language accessible to elected officials, community leaders, and the public. Exploring such topics empowers citizens with insider knowledge about the potential of better traffic technology to save lives and improve communities. The synergies that Artificial Intelligence brings to traffic signal control and data collection are unsurpassed.Keywords: artificial intelligence, convolutional neural networks, data collection, signal control, traffic signal
Procedia PDF Downloads 1692479 Determinants of Child Anthropometric Indicators: A Case Study of Mali in 2015
Authors: Davod Ahmadigheidari
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The main objective of this study was to explore prevalence of anthropometric indicators as well the factors associated with the anthropometric indications in Mali. Data on 2015, downloaded from the website of Unicef, were analyzed. A total of 16,467 women (ages 15-49 years) and 16,467 children (ages 0-59 months) were selected for the sample. Different statistical analyses, such as descriptive, crosstabs and binary logistic regression form the basis of this study. Child anthropometric indicators (i.e., wasting, stunting, underweight and BMI for age) were used as the dependent variables. SPSS Syntax from WHO was used to create anthropometric indicators. Different factors, such as child’s sex, child’s age groups, child’s diseases symptoms (i.e., diarrhea, cough and fever), maternal education, household wealth index and area of residence were used as independent variables. Results showed more than forty percent of Malian households were in nutritional crises (stunting (42%) and underweight (34%). Findings from logistic regression analyses indicated that low score of wealth index, low maternal education and experience of diarrhea in last two weeks increase the probability of child malnutrition.Keywords: Mali, wasting, stunting, underweight, BMI for age and wealth index
Procedia PDF Downloads 1552478 Impact of Water Interventions under WASH Program in the South-west Coastal Region of Bangladesh
Authors: S. M. Ashikur Elahee, Md. Zahidur Rahman, Md. Shofiqur Rahman
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This study evaluated the impact of different water interventions under WASH program on access of household's to safe drinking water. Following survey method, the study was carried out in two Upazila of South-west coastal region of Bangladesh namely Koyra from Khulna and Shymnagar from Satkhira district. Being an explanatory study, a total of 200 household's selected applying random sampling technique were interviewed using a structured interview schedule. The predicted probability suggests that around 62 percent household's are out of year-round access to safe drinking water whereby, only 25 percent household's have access at SPHERE standard (913 Liters/per person/per year). Besides, majority (78 percent) of the household's have not accessed at both indicators simultaneously. The distance from household residence to the water source varies from 0 to 25 kilometer with an average distance of 2.03 kilometers. The study also reveals that the increase in monthly income around BDT 1,000 leads to additional 11 liters (coefficient 0.01 at p < 0.1) consumption of safe drinking water for a person/year. As expected, lining up time has significant negative relationship with dependent variables i.e., for higher lining up time, the probability of getting access for both SPHERE standard and year round access variables becomes lower. According to ordinary least square (OLS) regression results, water consumption decreases at 93 liters for per person/year of a household if one member is added to that household. Regarding water consumption intensity, ordered logistic regression (OLR) model shows that one-minute increase of lining up time for water collection tends to reduce water consumption intensity. On the other hand, as per OLS regression results, for one-minute increase of lining up time, the water consumption decreases by around 8 liters. Considering access to Deep Tube Well (DTW) as a reference dummy, in OLR, the household under Pond Sand Filter (PSF), Shallow Tube Well (STW), Reverse Osmosis (RO) and Rainwater Harvester System (RWHS) are respectively 37 percent, 29 percent, 61 percent and 27 percent less likely to ensure year round access of water consumption. In line of health impact, different type of water born diseases like diarrhea, cholera, and typhoid are common among the coastal community caused by microbial impurities i.e., Bacteria, Protozoa. High turbidity and TDS in pond water caused by reduction of water depth, presence of suspended particle and inorganic salt stimulate the growth of bacteria, protozoa, and algae causes affecting health hazard. Meanwhile, excessive growth of Algae in pond water caused by excessive nitrate in drinking water adversely effects on child health. In lieu of ensuring access at SPHERE standard, we need to increase the number of water interventions at reasonable distance, preferably a half kilometer away from the dwelling place, ensuring community peoples involved with its installation process where collectively owned water intervention is found more effective than privately owned. In addition, a demand-responsive approach to supply of piped water should be adopted to allow consumer demand to guide investment in domestic water supply in future.Keywords: access, impact, safe drinking water, Sphere standard, water interventions
Procedia PDF Downloads 2192477 A Strategic Partner Evaluation Model for the Project Based Enterprises
Authors: Woosik Jang, Seung H. Han
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The optimal partner selection is one of the most important factors to pursue the project’s success. However, in practice, there is a gaps in perception of success depending on the role of the enterprises for the projects. This frequently makes a relations between the partner evaluation results and the project’s final performances, insufficiently. To meet this challenges, this study proposes a strategic partner evaluation model considering the perception gaps between enterprises. A total 3 times of survey was performed; factor selection, perception gap analysis, and case application. After then total 8 factors are extracted from independent sample t-test and Borich model to set-up the evaluation model. Finally, through the case applications, only 16 enterprises are re-evaluated to “Good” grade among the 22 “Good” grade from existing model. On the contrary, 12 enterprises are re-evaluated to “Good” grade among the 19 “Bad” grade from existing model. Consequently, the perception gaps based evaluation model is expected to improve the decision making quality and also enhance the probability of project’s success.Keywords: partner evaluation model, project based enterprise, decision making, perception gap, project performance
Procedia PDF Downloads 1572476 Housing Security System and Household Entrepreneurship: Evidence from China
Authors: Wangshi Yong, Wei Shi, Jing Zou, Qiang Li, Yilin Tian
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With the advancement of the reform of China’s housing security system, the impact is becoming increasingly profound. This paper explores the relationship between the housing security system and household entrepreneurship on the 2017 China Household Finance Survey (CHFS) and conducts a large number of robustness checks, including PSM and IV estimation. The results show that the assistance of the housing security system will significantly promote family entrepreneurship, increasing the probability of entrepreneurship by 2%. Its internal mechanism is mainly achieved by relaxing liquidity constraints and increasing household social capital. However, the risk preference effect has not existed. Heterogeneity analysis shows that the positive impact of the housing security system on family entrepreneurship is mainly reflected in areas with high housing prices and incomes, as well as households with long-term security and social or commercial insurance. Meanwhile, it also verifies that the positive externalities of the housing security system will also positively affect active entrepreneurial motivation, entrepreneurial intensity, and entrepreneurial innovation.Keywords: the housing security system, household entrepreneurship, social capital, liquidity constraints, risk preference
Procedia PDF Downloads 842475 KAP Study on Breast Cancer Among Women in Nirmala Educational Institutions-A Prospective Observational Study
Authors: Shaik Asha Begum, S. Joshna Rani, Shaik Abdul Rahaman
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INTRODUCTION: Breast cancer is a disease that creates in breast cells. "KAP" study estimates the Knowledge, Attitude, and Practices of a local area. More than 1.5 million ladies (25% of all ladies with malignancy) are determined to have bosom disease consistently all through the world. Understanding the degrees of Knowledge, Attitude and Practice will empower a more effective cycle of mindfulness creation as it will permit the program to be custom-made all the more properly to the necessities of the local area. OBJECTIVES: The objective of this study is to assess the knowledge on signs and symptoms, risk factors, provide awareness on the practicing of the early detection techniques of breast cancer and provide knowledge on the overall breast cancer including preventive techniques. METHODOLOGY: This is an expressive cross-sectional investigation. This investigation of KAP was done in the Nirmala Educational Institutions from January to April 2021. A total of 300 participants are included from women students in pharmacy graduates & lecturers, and also from graduates other than the pharmacy. The examiners are taken from the BCAM (Breast Cancer Awareness Measure), tool compartment (Version 2). RESULT: According to the findings of the study, the majority of the participants were not well informed about breast cancer. A lump in the breast was the most commonly mentioned sign of breast cancer, followed by pain in the breast or nipple. The percentage of knowledge related to the breast cancer risk factors was also very less. The correct answers for breast cancer risk factors were radiation exposure (58.20 percent), a positive family history (47.6 percent), obesity (46.9 percent), a lack of physical activity (43.6 percent), and smoking (43.2 percent). Breast cancer screening, on the other hand, was uncommon (only 30 and 11.3 percent practiced clinical breast examination and mammography respectively). CONCLUSION: In this study, the knowledge on the signs and symptoms, risk factors of breast cancer - pharmacy graduates have more knowledge than the non-pharmacy graduates but in the preventive techniques and early detective tools of breast cancer -had poor knowledge in the pharmacy and non-pharmacy graduate. After the awareness program, pharmacy and non-pharmacy graduates got supportive knowledge on the preventive techniques and also practiced the early detective techniques of breast cancer.Keywords: breast cancer, mammography, KAP study, early detection
Procedia PDF Downloads 1382474 Effective Training System for Riding Posture Using Depth and Inertial Sensors
Authors: Sangseung Kang, Kyekyung Kim, Suyoung Chi
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A good posture is the most important factor in riding. In this paper, we present an effective posture correction system for a riding simulator environment to provide position error detection and customized training functions. The proposed system detects and analyzes the rider's posture using depth data and inertial sensing data. Our experiments show that including these functions will help users improve their seat for a riding.Keywords: posture correction, posture training, riding posture, riding simulator
Procedia PDF Downloads 4762473 A Comprehensive Framework for Fraud Prevention and Customer Feedback Classification in E-Commerce
Authors: Samhita Mummadi, Sree Divya Nagalli, Harshini Vemuri, Saketh Charan Nakka, Sumesh K. J.
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One of the most significant challenges faced by people in today’s digital era is an alarming increase in fraudulent activities on online platforms. The fascination with online shopping to avoid long queues in shopping malls, the availability of a variety of products, and home delivery of goods have paved the way for a rapid increase in vast online shopping platforms. This has had a major impact on increasing fraudulent activities as well. This loop of online shopping and transactions has paved the way for fraudulent users to commit fraud. For instance, consider a store that orders thousands of products all at once, but what’s fishy about this is the massive number of items purchased and their transactions turning out to be fraud, leading to a huge loss for the seller. Considering scenarios like these underscores the urgent need to introduce machine learning approaches to combat fraud in online shopping. By leveraging robust algorithms, namely KNN, Decision Trees, and Random Forest, which are highly effective in generating accurate results, this research endeavors to discern patterns indicative of fraudulent behavior within transactional data. Introducing a comprehensive solution to this problem in order to empower e-commerce administrators in timely fraud detection and prevention is the primary motive and the main focus. In addition to that, sentiment analysis is harnessed in the model so that the e-commerce admin can tailor to the customer’s and consumer’s concerns, feedback, and comments, allowing the admin to improve the user’s experience. The ultimate objective of this study is to ramp up online shopping platforms against fraud and ensure a safer shopping experience. This paper underscores a model accuracy of 84%. All the findings and observations that were noted during our work lay the groundwork for future advancements in the development of more resilient and adaptive fraud detection systems, which will become crucial as technologies continue to evolve.Keywords: behavior analysis, feature selection, Fraudulent pattern recognition, imbalanced classification, transactional anomalies
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