Search results for: document detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4132

Search results for: document detection

1672 miR-200c as a Biomarker for 5-FU Chemosensitivity in Colorectal Cancer

Authors: Rezvan Najafi, Korosh Heydari, Massoud Saidijam

Abstract:

5-FU is a chemotherapeutic agent that has been used in colorectal cancer (CRC) treatment. However, it is usually associated with the acquired resistance, which decreases the therapeutic effects of 5-FU. miR-200c is involved in chemotherapeutic drug resistance, but its mechanism is not fully understood. In this study, the effect of inhibition of miR-200c in sensitivity of HCT-116 CRC cells to 5-FU was evaluated. HCT-116 cells were transfected with LNA-anti- miR-200c for 48 h. mRNA expression of miR-200c was evaluated using quantitative real- time PCR. The protein expression of phosphatase and tensin homolog (PTEN) and E-cadherin were analyzed by western blotting. Annexin V and propidium iodide staining assay were applied for apoptosis detection. The caspase-3 activation was evaluated by an enzymatic assay. The results showed LNA-anti-miR-200c inhibited the expression of PTEN and E-cadherin protein, apoptosis and activation of caspase 3 compared with control cells. In conclusion, these results suggest that miR-200c as a prognostic marker can overcome to 5-FU chemoresistance in CRC.

Keywords: colorectal cancer, miR-200c, 5-FU resistance, E-cadherin, PTEN

Procedia PDF Downloads 161
1671 The Evaluation of the Re-Construction Project Hamamönü, Ankara in Turkey as a Case from Socio-Cultural Perspective

Authors: Tuğçe Kök, Gözen Güner Aktaş, Nur Ayalp

Abstract:

In a global world, Social and cultural sustainability are subjects which have gained significant importance in recent years. The concept of sustainability was included in the document of the World Conservation Union (IUCN) by World Charter for Nature, adopted in 1982 for the first time. However, merged with urban sustainability a new phenomenon has emerged. Sustainability is an essential fact, This fact is discussed via the socio-cultural field of sustainability. Together with central government and local authorities, conservation activities have been intensified on the protection of values on an area scale. Today, local authorities play an important role in the urban historic site rehabilitation and re-construction of traditional houses projects in Ankara, Turkey. Many conservative acts have occurred after 1980’s. To give a remarkable example about the conservation implementations of traditional Turkish houses is ‘Hamamönü, Ankara Re-Construction Project which is one of the historical parts that has suffered from deterioration and unplanned urban development. In this region, preexisting but unused historic fibre of the site has been revised and according to result of this case-study, the relationship between users and re-construction were discussed. Most of the houses were re-constructed in order to build a new tourist attraction area. This study discusses the socio-cultural relations between the new built environment and the visitors, from the point of cultural sustainability. This study questions the transmission of cultural stimulations. A case study was conducted to discuss the perception of cultural aspects of the visitors in the site. The relationship between the real cultural identities and existent ones after the re-constructed project, Which has been transmitted through the visitors and the users of those spaces will be discussed. The aim of the study is to analyze the relation between the cultural identities, which have been tried to be protected with the re-construction project and the users. The purposes of this study are to evaluate the implementations of Altındağ Municipality in Hamamönü and examine the socio-cultural sustainability with the user responses. After the assessment of implementation under socio-cultural sustainability, some proposals for the future of Hamamönü were introduced.

Keywords: social sustainability, cultural sustainability, Hamamönü, Turkey, re-construction

Procedia PDF Downloads 474
1670 Impact of Flavor on Food Product Quality, A Case Study of Vanillin Stability during Biscuit Preparation

Authors: N. Yang, R. Linforth, I. Fisk

Abstract:

The influence of food processing and choice of flavour solvent was investigated using biscuits prepared with vanillin flavour as an example. Powder vanillin either was added directly into the dough or dissolved into flavour solvent then mixed into the dough. The impact of two commonly used flavour solvents on food quality was compared: propylene glycol (PG) or triacetin (TA). The analytical approach for vanillin detection was developed by chromatography (HPLC-PDA), and the standard extraction method for vanillin was also established. The results indicated the impact of solvent choice on vanillin level during biscuit preparation. After baking, TA as a more heat resistant solvent retained more vanillin than PG, so TA is a better solvent for products that undergo a heating process. The results also illustrated the impact of mixing and baking on vanillin stability in the matrices. The average loss of vanillin was 33% during mixing and 13% during baking, which indicated that the binding of vanillin to fat or flour before baking might cause larger loss than evaporation loss during baking.

Keywords: biscuit, flavour stability, food quality, vanillin

Procedia PDF Downloads 507
1669 Microbiological Analysis, Cytotoxic and Genotoxic Effects from Material Captured in PM2.5 and PM10 Filters Used in the Aburrá Valley Air Quality Monitoring Network (Colombia)

Authors: Carmen E. Zapata, Juan Bautista, Olga Montoya, Claudia Moreno, Marisol Suarez, Alejandra Betancur, Duvan Nanclares, Natalia A. Cano

Abstract:

This study aims to evaluate the diversity of microorganisms in filters PM2.5 and PM10; and determine the genotoxic and cytotoxic activity of the complex mixture present in PM2.5 filters used in the Aburrá Valley Air Quality Monitoring Network (Colombia). The research results indicate that particulate matter PM2.5 of different monitoring stations are bacteria; however, this study of detection of bacteria and their phylogenetic relationship is not complete evidence to connect the microorganisms with pathogenic or degrading activities of compounds present in the air. Additionally, it was demonstrated the damage induced by the particulate material in the cell membrane, lysosomal and endosomal membrane and in the mitochondrial metabolism; this damage was independent of the PM2.5 concentrations in almost all the cases.

Keywords: cytotoxic, genotoxic, microbiological analysis, PM10, PM2.5

Procedia PDF Downloads 339
1668 Detection of Respiratory Syncytial Virus (hRSV) by PCR Technique in Lower Respiratory Tract Infection (LRTI) in Babylon City

Authors: Amal Raqib Shameran, Ghanim Aboud Al-Mola

Abstract:

Respiratory syncytial virus (hRSV) is the major pathogens of respiratory tract infections (RTI) among infants and children in the world. They are classified in family Paramyxoviridae and sub-family Pneumovirinae. The current work aimed to detect the role of RSV in the lower respiratory tract infection (LRTI) in Hilla, Iraq. The samples were collected from 50 children who were admitted to hospital suffering from lower respiratory tract infections (LRTI). 50 nasal and pharyngeal swabs were taken from patients at the period from January 2010 till April 2011, hospitalized in Hilla Maternity and Children Hospital. The results showed that the proportion of children infected with hRSV accounted for 24% 12/50 with lower respiratory tract infections (LRTI) when they tested by polymerase chain reaction (RT-PCR).

Keywords: respiratory syncytial virus, respiratory tract infections, infants, polymerase chain reaction (PCR)

Procedia PDF Downloads 342
1667 Risk Management Approach for a Secure and Performant Integration of Automated Drug Dispensing Systems in Hospitals

Authors: Hind Bouami, Patrick Millot

Abstract:

Medication dispensing system is a life-critical system whose failure may result in preventable adverse events leading to longer patient stays in hospitals or patient death. Automation has led to great improvements in life-critical systems as it increased safety, efficiency, and comfort. However, critical risks related to medical organization complexity and automated solutions integration can threaten drug dispensing security and performance. Knowledge about the system’s complexity aspects and human machine parameters to control for automated equipment’s security and performance will help operators to secure their automation process and to optimize their system’s reliability. In this context, this study aims to document the operator’s situation awareness about automation risks and parameters involved in automation security and performance. Our risk management approach has been deployed in the North Luxembourg hospital center’s pharmacy, which is equipped with automated drug dispensing systems since 2009. With more than 4 million euros of gains generated, North Luxembourg hospital center’s success story was enabled by the management commitment, pharmacy’s involvement in the implementation and improvement of the automation project, and the close collaboration between the pharmacy and Sinteco’s firm to implement the necessary innovation and organizational actions for automated solutions integration security and performance. An analysis of the actions implemented by the hospital and the parameters involved in automated equipment’s integration security and performance has been made. The parameters to control for automated equipment’s integration security and performance are human aspects (6.25%), technical aspects (50%), and human-machine interaction (43.75%). The implementation of an anthropocentric analysis system before automation would have prevented and optimized the control of risks related to automation.

Keywords: Automated drug delivery systems, Hospitals, Human-centered automated system, Risk management

Procedia PDF Downloads 133
1666 Detection of COVID-19 Cases From X-Ray Images Using Capsule-Based Network

Authors: Donya Ashtiani Haghighi, Amirali Baniasadi

Abstract:

Coronavirus (COVID-19) disease has spread abruptly all over the world since the end of 2019. Computed tomography (CT) scans and X-ray images are used to detect this disease. Different Deep Neural Network (DNN)-based diagnosis solutions have been developed, mainly based on Convolutional Neural Networks (CNNs), to accelerate the identification of COVID-19 cases. However, CNNs lose important information in intermediate layers and require large datasets. In this paper, Capsule Network (CapsNet) is used. Capsule Network performs better than CNNs for small datasets. Accuracy of 0.9885, f1-score of 0.9883, precision of 0.9859, recall of 0.9908, and Area Under the Curve (AUC) of 0.9948 are achieved on the Capsule-based framework with hyperparameter tuning. Moreover, different dropout rates are investigated to decrease overfitting. Accordingly, a dropout rate of 0.1 shows the best results. Finally, we remove one convolution layer and decrease the number of trainable parameters to 146,752, which is a promising result.

Keywords: capsule network, dropout, hyperparameter tuning, classification

Procedia PDF Downloads 72
1665 Improving Detection of Illegitimate Scores and Assessment in Most Advantageous Tenders

Authors: Hao-Hsi Tseng, Hsin-Yun Lee

Abstract:

The Most Advantageous Tender (MAT) has been criticized for its susceptibility to dictatorial situations and for its processing of same score, same rank issues. This study applies the four criteria from Arrow's Impossibility Theorem to construct a mechanism for revealing illegitimate scores in scoring methods. While commonly be used to improve on problems resulting from extreme scores, ranking methods hide significant defects, adversely affecting selection fairness. To address these shortcomings, this study relies mainly on the overall evaluated score method, using standardized scores plus normal cumulative distribution function conversion to calculate the evaluation of vender preference. This allows for free score evaluations, which reduces the influence of dictatorial behavior and avoiding same score, same rank issues. Large-scale simulations confirm that this method outperforms currently used methods using the Impossibility Theorem.

Keywords: Arrow’s impossibility theorem, cumulative normal distribution function, most advantageous tender, scoring method

Procedia PDF Downloads 459
1664 Assessing Musculoskeletal Disorder Prevalence and Heat-Related Symptoms: A Cross-sectional Comparison in Indian Farmers

Authors: Makkhan Lal Meena, R. C. Bairwa, G. S. Dangayach, Rahul Jain

Abstract:

The current study looked at the frequency of chronic illness conditions, accidents, health complaints, and ergonomic issues among 100 conventional and 100 greenhouse farmers. Data related to the health symptoms and ergonomic problems were collected through questionnaires by conducting direct interviews of farmers. According to the findings, symptoms of heat exposure (skin rashes, headache, dizziness, and lack of appetite) were substantially higher among conventional farmers than greenhouse farmers. The greenhouse farmers reported much more pain, numbness, or weakness in wrists/hands, fingers, upper back, hips, and ankles/feet than conventional farmers. The findings of the study suggest that suitable ergonomic knowledge and awareness campaign programs concentrating on safety at work, particularly low back pain, should be implemented in workplaces to allow for earlier detection of symptoms among the greenhouse farmers.

Keywords: accident, conventional farmer, ergonomics, health symptoms, greenhouse farmers, pesticide

Procedia PDF Downloads 264
1663 Crystallography Trials of Escherichia coli Nitrate Transporter, NarU

Authors: Naureen Akhtar

Abstract:

The stability of the protein in detergent-containing solution is the key for its successful crystallisation. Fluorescence-detection size-exclusion chromatography (FSEC) is a potential approach for screening monodispersity as well as the stability of protein in a detergent-containing-solution. In this present study, covalently linked Green Fluorescent Protein (GFP) to bacterial nitrate transporter, NarU from Escherichia coli was studied for pre-crystallisation trials by FSEC. Immobilised metal ion affinity chromatography (IMAC) and gel filtration were employed for their purification. The main objectives of this study were over-expression, detergent screening and crystallisation of nitrate transporter proteins. This study could not produce enough proteins that could realistically be taken forward to achieve the objectives set for this particular research. In future work, different combinations of variables like vectors, tags, creation of mutant proteins, host cells, position of GFP (N- or C-terminal) and/or membrane proteins would be tried to determine the best combination as the principle of technique is still promising.

Keywords: transporters, detergents, over-expression, crystallography

Procedia PDF Downloads 469
1662 3D Building Model Utilizing Airborne LiDAR Dataset and Terrestrial Photographic Images

Authors: J. Jasmee, I. Roslina, A. Mohammed Yaziz & A.H Juazer Rizal

Abstract:

The need of an effective building information collection method is vital to support a diversity of land development activities. At present, advances in remote sensing such as airborne LiDAR (Light Detection and Ranging) is an established technology for building information collection, location, and elevation of the reflecting laser points towards the construction of 3D building models. In this study, LiDAR datasets and terrestrial photographic images of buildings towards the construction of 3D building models is explored. It is found that, the quantitative accuracy of the constructed 3D building model, namely in the horizontal and vertical components were ± 0.31m (RMSEx,y) and ± 0.145m (RMSEz) respectively. The accuracies were computed based on sixty nine (69) horizontal and twenty (20) vertical surveyed points. As for the qualitative assessment, it is shown that the appearance of the 3D building model is adequate to support the requirements of LOD3 presentation based on the OGC (Open Geospatial Consortium) standard CityGML.

Keywords: LiDAR datasets, DSM, DTM, 3D building models

Procedia PDF Downloads 314
1661 Efficient Feature Fusion for Noise Iris in Unconstrained Environment

Authors: Yao-Hong Tsai

Abstract:

This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.

Keywords: image fusion, iris recognition, local binary pattern, wavelet

Procedia PDF Downloads 364
1660 Empowering a New Frontier in Heart Disease Detection: Unleashing Quantum Machine Learning

Authors: Sadia Nasrin Tisha, Mushfika Sharmin Rahman, Javier Orduz

Abstract:

Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases.

Keywords: quantum machine learning, SVM, QSVM, matrix product state

Procedia PDF Downloads 91
1659 A Facile and Room Temperature Growth of Pd-Pt Decorated Hexagonal-ZnO Framework and Their Selective H₂ Gas Sensing Properties

Authors: Gaurav Malik, Satyendra Mourya, Jyoti Jaiswal, Ramesh Chandra

Abstract:

The attractive and multifunctional properties of ZnO make it a promising material for the fabrication of highly sensitive and selective efficient gas sensors at room temperature. This presented article focuses on the development of highly selective and sensitive H₂ gas sensor based on the Pd-Pt decorated ZnO framework and its sensing mechanisms. The gas sensing performance of sputter made Pd-Pt/ZnO electrode on anodized porous silicon (PSi) substrate toward H₂ gas is studied under low detection limit (2–500 ppm) of H₂ in the air. The chemiresistive sensor demonstrated sublimate selectivity, good sensing response, and fast response/recovery time with excellent stability towards H₂ at low temperature operation under ambient environment. The elaborate selective measurement of Pd-Pt/ZnO/PSi structure was performed towards different oxidizing and reducing gases. This structure exhibited advance and reversible response to H₂ gas, which revealed that the acquired architecture with ZnO framework is a promising candidate for H₂ gas sensor.

Keywords: sputtering, porous silicon, ZnO framework, XPS spectra, gas sensor

Procedia PDF Downloads 387
1658 The Effect of Closed Circuit Television Image Patch Layout on Performance of a Simulated Train-Platform Departure Task

Authors: Aaron J. Small, Craig A. Fletcher

Abstract:

This study investigates the effect of closed circuit television (CCTV) image patch layout on performance of a simulated train-platform departure task. The within-subjects experimental design measures target detection rate and response latency during a CCTV visual search task conducted as part of the procedure for safe train dispatch. Three interface designs were developed by manipulating CCTV image patch layout. Eye movements, perceived workload and system usability were measured across experimental conditions. Task performance was compared to identify significant differences between conditions. The results of this study have not been determined.

Keywords: rail human factors, workload, closed circuit television, platform departure, attention, information processing, interface design

Procedia PDF Downloads 165
1657 Statistical Modeling of Mobile Fading Channels Based on Triply Stochastic Filtered Marked Poisson Point Processes

Authors: Jihad S. Daba, J. P. Dubois

Abstract:

Understanding the statistics of non-isotropic scattering multipath channels that fade randomly with respect to time, frequency, and space in a mobile environment is very crucial for the accurate detection of received signals in wireless and cellular communication systems. In this paper, we derive stochastic models for the probability density function (PDF) of the shift in the carrier frequency caused by the Doppler Effect on the received illuminating signal in the presence of a dominant line of sight. Our derivation is based on a generalized Clarke’s and a two-wave partially developed scattering models, where the statistical distribution of the frequency shift is shown to be consistent with the power spectral density of the Doppler shifted signal.

Keywords: Doppler shift, filtered Poisson process, generalized Clark’s model, non-isotropic scattering, partially developed scattering, Rician distribution

Procedia PDF Downloads 369
1656 Breast Cancer Detection Using Machine Learning Algorithms

Authors: Jiwan Kumar, Pooja, Sandeep Negi, Anjum Rouf, Amit Kumar, Naveen Lakra

Abstract:

In modern times where, health issues are increasing day by day, breast cancer is also one of them, which is very crucial and really important to find in the early stages. Doctors can use this model in order to tell their patients whether a cancer is not harmful (benign) or harmful (malignant). We have used the knowledge of machine learning in order to produce the model. we have used algorithms like Logistic Regression, Random forest, support Vector Classifier, Bayesian Network and Radial Basis Function. We tried to use the data of crucial parts and show them the results in pictures in order to make it easier for doctors. By doing this, we're making ML better at finding breast cancer, which can lead to saving more lives and better health care.

Keywords: Bayesian network, radial basis function, ensemble learning, understandable, data making better, random forest, logistic regression, breast cancer

Procedia PDF Downloads 48
1655 Investigation of Stoneley Waves in Multilayered Plates

Authors: Bing Li, Tong Lu, Lei Qiang

Abstract:

Stoneley waves are interface waves that propagate at the interface between two solid media. In this study, the dispersion characteristics and wave structures of Stoneley waves in elastic multilayered plates are displayed and investigated. With a perspective of bulk wave, a reasonable assumption of the potential function forms of the expansion wave and shear wave in nth layer medium is adopted, and the characteristic equation of Stoneley waves in a three-layered plate is given in a determinant form. The dispersion curves and wave structures are solved and presented in both numerical and simulation results. It is observed that two Stoneley wave modes exist in a three-layered plate, that conspicuous dispersion occurs on low frequency band, that the velocity of each Stoneley wave mode approaches the corresponding Stoneley wave velocity at interface between two half infinite spaces. The wave structures reveal that the in-plane displacement of Stoneley waves are relatively high at interfaces, which shows great potential for interface defects detection.

Keywords: characteristic equation, interface waves, potential function, Stoneley waves, wave structure

Procedia PDF Downloads 313
1654 Fault Diagnosis and Fault-Tolerant Control of Bilinear-Systems: Application to Heating, Ventilation, and Air Conditioning Systems in Multi-Zone Buildings

Authors: Abderrhamane Jarou, Dominique Sauter, Christophe Aubrun

Abstract:

Over the past decade, the growing demand for energy efficiency in buildings has attracted the attention of the control community. Failures in HVAC (heating, ventilation and air conditioning) systems in buildings can have a significant impact on the desired and expected energy performance of buildings and on the user's comfort as well. FTC is a recent technology area that studies the adaptation of control algorithms to faulty operating conditions of a system. The application of Fault-Tolerant Control (FTC) in HVAC systems has gained attention in the last two decades. The objective is to maintain the variations in system performance due to faults within an acceptable range with respect to the desired nominal behavior. This paper considers the so-called active approach, which is based on fault and identification scheme combined with a control reconfiguration algorithm that consists in determining a new set of control parameters so that the reconfigured performance is "as close as possible, "in some sense, to the nominal performance. Thermal models of buildings and their HVAC systems are described by non-linear (usually bi-linear) equations. Most of the works carried out so far in FDI (fault diagnosis and isolation) or FTC consider a linearized model of the studied system. However, this model is only valid in a reduced range of variation. This study presents a new fault diagnosis (FD) algorithm based on a bilinear observer for the detection and accurate estimation of the magnitude of the HVAC system failure. The main contribution of the proposed FD algorithm is that instead of using specific linearized models, the algorithm inherits the structure of the actual bilinear model of the building thermal dynamics. As an immediate consequence, the algorithm is applicable to a wide range of unpredictable operating conditions, i.e., weather dynamics, outdoor air temperature, zone occupancy profile. A bilinear fault detection observer is proposed for a bilinear system with unknown inputs. The residual vector in the observer design is decoupled from the unknown inputs and, under certain conditions, is made sensitive to all faults. Sufficient conditions are given for the existence of the observer and results are given for the explicit computation of observer design matrices. Dedicated observer schemes (DOS) are considered for sensor FDI while unknown input bilinear observers are considered for actuator or system components FDI. The proposed strategy for FTC works as follows: At a first level, FDI algorithms are implemented, making it also possible to estimate the magnitude of the fault. Once the fault is detected, the fault estimation is then used to feed the second level and reconfigure the control low so that that expected performances are recovered. This paper is organized as follows. A general structure for fault-tolerant control of buildings is first presented and the building model under consideration is introduced. Then, the observer-based design for Fault Diagnosis of bilinear systems is studied. The FTC approach is developed in Section IV. Finally, a simulation example is given in Section V to illustrate the proposed method.

Keywords: bilinear systems, fault diagnosis, fault-tolerant control, multi-zones building

Procedia PDF Downloads 166
1653 Dynamical Models for Enviromental Effect Depuration for Structural Health Monitoring of Bridges

Authors: Francesco Morgan Bono, Simone Cinquemani

Abstract:

This research aims to enhance bridge monitoring by employing innovative techniques that incorporate exogenous factors into the modeling of sensor signals, thereby improving long-term predictability beyond traditional static methods. Using real datasets from two different bridges equipped with Linear Variable Displacement Transducer (LVDT) sensors, the study investigates the fundamental principles governing sensor behavior for more precise long-term forecasts. Additionally, the research evaluates performance on noisy and synthetically damaged data, proposing a residual-based alarm system to detect anomalies in the bridge. In summary, this novel approach combines advanced modeling, exogenous factors, and anomaly detection to extend prediction horizons and improve preemptive damage recognition, significantly advancing structural health monitoring practices.

Keywords: structural health monitoring, dynamic models, sindy, railway bridges

Procedia PDF Downloads 31
1652 Small Target Recognition Based on Trajectory Information

Authors: Saad Alkentar, Abdulkareem Assalem

Abstract:

Recognizing small targets has always posed a significant challenge in image analysis. Over long distances, the image signal-to-noise ratio tends to be low, limiting the amount of useful information available to detection systems. Consequently, visual target recognition becomes an intricate task to tackle. In this study, we introduce a Track Before Detect (TBD) approach that leverages target trajectory information (coordinates) to effectively distinguish between noise and potential targets. By reframing the problem as a multivariate time series classification, we have achieved remarkable results. Specifically, our TBD method achieves an impressive 97% accuracy in separating target signals from noise within a mere half-second time span (consisting of 10 data points). Furthermore, when classifying the identified targets into our predefined categories—airplane, drone, and bird—we achieve an outstanding classification accuracy of 96% over a more extended period of 1.5 seconds (comprising 30 data points).

Keywords: small targets, drones, trajectory information, TBD, multivariate time series

Procedia PDF Downloads 39
1651 Quality Assurance in Higher Education: Doha Institute for Graduate Studies as a Case Study

Authors: Ahmed Makhoukh

Abstract:

Quality assurance (QA) has recently become a common practice, which is endorsed by most Higher Education (HE) institutions worldwide, due to the pressure of internal and external forces. One of the aims of this quality movement is to make the contribution of university education to socio-economic development highly significant. This entails that graduates are currently required have a high-quality profile, i.e., to be competent and master the 21st-century skills needed in the labor market. This wave of change, mostly imposed by globalization, has the effect that university education should be learner-centered in order to satisfy the different needs of students and meet the expectations of other stakeholders. Such a shift of focus on the student learning outcomes has led HE institutions to reconsider their strategic planning, their mission, the curriculum, the pedagogical competence of the academic staff, among other elements. To ensure that the overall institutional performance is on the right way, a QA system should be established to assume this task of checking regularly the extent to which the set of standards of evaluation are strictly respected as expected. This operation of QA has the advantage of proving the accountability of the institution, gaining the trust of the public with transparency and enjoying an international recognition. This is the case of Doha Institute (DI) for Graduate Studies, in Qatar, the object of the present study. The significance of this contribution is to show that the conception of quality has changed in this digital age, and the need to integrate a department responsible for QA in every HE institution to ensure educational quality, enhance learners and achieve academic leadership. Thus, to undertake the issue of QA in DI for Graduate Studies, an elite university (in the academic sense) that focuses on a small and selected number of students, a qualitative method will be adopted in the description and analysis of the data (document analysis). In an attempt to investigate the extent to which QA is achieved in Doha Institute for Graduate Studies, three broad indicators will be evaluated (input, process and learning outcomes). This investigation will be carried out in line with the UK Quality Code for Higher Education represented by Quality Assurance Agency (QAA).

Keywords: accreditation, higher education, quality, quality assurance, standards

Procedia PDF Downloads 145
1650 Advanced Real-Time Fluorescence Imaging System for Rat's Femoral Vein Thrombosis Monitoring

Authors: Sang Hun Park, Chul Gyu Song

Abstract:

Artery and vein occlusion changes observed in patients and experimental animals are unexplainable symptoms. As the fat accumulated in cardiovascular ruptures, it causes vascular blocking. Likewise, early detection of cardiovascular disease can be useful for treatment. In this study, we used the mouse femoral occlusion model to observe the arterial and venous occlusion changes without darkroom. We observed the femoral arterial flow pattern changes by proposed fluorescent imaging system using an animal model of thrombosis. We adjusted the near-infrared light source current in order to control the intensity of the fluorescent substance light. We got the clear fluorescent images and femoral artery flow pattern were measured by a 5-minute interval. The result showed that the fluorescent substance flowing in the femoral arteries were accumulated in thrombus as time passed, and the fluorescence of other vessels gradually decreased.

Keywords: thrombus, fluorescence, femoral, arteries

Procedia PDF Downloads 336
1649 Towards Learning Query Expansion

Authors: Ahlem Bouziri, Chiraz Latiri, Eric Gaussier

Abstract:

The steady growth in the size of textual document collections is a key progress-driver for modern information retrieval techniques whose effectiveness and efficiency are constantly challenged. Given a user query, the number of retrieved documents can be overwhelmingly large, hampering their efficient exploitation by the user. In addition, retaining only relevant documents in a query answer is of paramount importance for an effective meeting of the user needs. In this situation, the query expansion technique offers an interesting solution for obtaining a complete answer while preserving the quality of retained documents. This mainly relies on an accurate choice of the added terms to an initial query. Interestingly enough, query expansion takes advantage of large text volumes by extracting statistical information about index terms co-occurrences and using it to make user queries better fit the real information needs. In this respect, a promising track consists in the application of data mining methods to extract dependencies between terms, namely a generic basis of association rules between terms. The key feature of our approach is a better trade off between the size of the mining result and the conveyed knowledge. Thus, face to the huge number of derived association rules and in order to select the optimal combination of query terms from the generic basis, we propose to model the problem as a classification problem and solve it using a supervised learning algorithm such as SVM or k-means. For this purpose, we first generate a training set using a genetic algorithm based approach that explores the association rules space in order to find an optimal set of expansion terms, improving the MAP of the search results. The experiments were performed on SDA 95 collection, a data collection for information retrieval. It was found that the results were better in both terms of MAP and NDCG. The main observation is that the hybridization of text mining techniques and query expansion in an intelligent way allows us to incorporate the good features of all of them. As this is a preliminary attempt in this direction, there is a large scope for enhancing the proposed method.

Keywords: supervised leaning, classification, query expansion, association rules

Procedia PDF Downloads 319
1648 Monitoring of Pesticide Content in Biscuits Available on the Vojvodina Market, Serbia

Authors: Ivana Loncarevic, Biljana Pajin, Ivana Vasiljevic, Milana Lazovic, Danica Mrkajic, Aleksandar Fises, Strahinja Kovacevic

Abstract:

Biscuits belong to a group of flour-confectionery products that are considerably consumed worldwide. The basic raw material for their production is wheat flour or integral flour as a nutritionally highly valuable component. However, this raw material is also a potential source of contamination since it may contain the residues of biochemical compounds originating from plant and soil protection agents. Therefore, it is necessary to examine the health safety of both raw materials and final products. The aim of this research was to examine the content of undesirable residues of pesticides (mostly organochlorine pesticides, organophosphorus pesticides, carbamate pesticides, triazine pesticides, and pyrethroid pesticides) in 30 different biscuit samples of domestic origin present on the Vojvodina market using Gas Chromatograph Thermo ISQ/Trace 1300. The results showed that all tested samples had the limit of detection of pesticide content below 0.01 mg/kg, indicating that this type of confectionary products is not contaminated with pesticides.

Keywords: biscuits, pesticides, contamination, quality

Procedia PDF Downloads 173
1647 Experimental Set-Up for Investigation of Fault Diagnosis of a Centrifugal Pump

Authors: Maamar Ali Saud Al Tobi, Geraint Bevan, K. P. Ramachandran, Peter Wallace, David Harrison

Abstract:

Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated.

Keywords: centrifugal pump setup, vibration analysis, artificial intelligence, genetic algorithm

Procedia PDF Downloads 405
1646 Content and Language Integrated Instruction: An Investigation of Oral Corrective Feedback in the Chinese Immersion Classroom

Authors: Qin Yao

Abstract:

Content and language integrated instruction provides second language learners instruction in subject matter and language, and is greatly valued, particularly in the language immersion classroom where a language other than students’ first language is the vehicle for teaching school curriculum. Corrective feedback is an essential instructional technique for teachers to integrate a focus on language into their content instruction. This study aims to fill a gap in the literature on immersion—the lack of studies examining corrective feedback in Chinese immersion classrooms, by studying learning opportunities brought by oral corrective feedback in a Chinese immersion classroom. Specifically, it examines what is the distribution of different types of teacher corrective feedback and how students respond to each feedback type, as well as how the focus of the teacher-student interactional exchanges affect the effect of feedback. Two Chinese immersion teachers and their immersion classes were involved, and data were collected through classroom observations interviews. Observations document teachers’ provision of oral corrective feedback and students’ responses following the feedback in class, and interviews with teachers collected teachers’ reflective thoughts about their teaching. A primary quantitative and qualitative analysis of the data revealed that, among different types of corrective feedback, recast occurred most frequently. Metalinguistic clue and repetition were the least occurring feedback types. Clarification request lead to highest percentage of learner uptake manifested by learners’ oral production immediately following the feedback, while explicit correction came the second and recast the third. In addition, the results also showed the interactional context played a role in the effectiveness of the feedback: teachers were most likely to give feedback in conversational exchanges that focused on explicit language and content, while students were most likely to use feedback in exchanges that focused on explicit language. In conclusion, the results of this study indicate recasts are preferred by Chinese immersion teachers, confirming results of previous studies on corrective feedback in non-Chinese immersion classrooms; and clarification request and explicit language instruction elicit more target language production from students and are facilitative in their target language development, thus should not be overlooked in immersion and other content and language integrated classrooms.

Keywords: Chinese immersion, content and language integrated instruction, corrective feedback, interaction

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1645 An Investigative Study into Good Governance in the Non-Profit Sector in South Africa: A Systems Approach Perspective

Authors: Frederick M. Dumisani Xaba, Nokuthula G. Khanyile

Abstract:

There is a growing demand for greater accountability, transparency and ethical conduct based on sound governance principles in the developing world. Funders, donors and sponsors are increasingly demanding more transparency, better value for money and adherence to good governance standards. The drive towards improved governance measures is largely influenced by the need to ‘plug the leaks’, deal with malfeasance, engender greater levels of accountability and good governance and to ultimately attract further funding or investment. This is the case with the Non-Profit Organizations (NPOs) in South Africa in general, and in the province of KwaZulu-Natal in particular. The paper draws from the good governance theory, stakeholder theory and systems thinking to critically examine the requirements for good governance for the NPO sector from a theoretical and legislative point and to systematically looks at the contours of governance currently among the NPOs. The paper did this through the rigorous examination of the vignettes of cases of governance among selected NPOs based in KwaZulu-Natal. The study used qualitative and quantitative research methodologies through document analysis, literature review, semi-structured interviews, focus groups and statistical analysis from the various primary and secondary sources. It found some good cases of good governance but also found frightening levels of poor governance. There was an exponential growth of NPOs registered during the period under review, equally so there was an increase in cases of non-compliance to good governance practices. NPOs operate in an increasingly complex environment. There is contestation for influence and access to resources. Stakeholder management is poorly conceptualized and executed. Recognizing that the NPO sector operates in an environment characterized by complexity, constant changes, unpredictability, contestation, diversity and divergent views of different stakeholders, there is a need to apply legislative and systems thinking approaches to strengthen governance to withstand this turbulence through a capacity development model that recognizes these contextual and environmental challenges.

Keywords: good governance, non-profit organizations, stakeholder theory, systems theory

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1644 Subject Teachers’ Perception of the Changing Role of Language in the Curriculum of Secondary Education

Authors: Moldir Makenova

Abstract:

Alongside the implementation of trilingual education in schools, the Ministry of Education and Science of the Republic of Kazakhstan innovated the school curriculum in 2013 to include a Content and Language Integrated Learning (CLIL) approach. In this regard, some transition issues have arisen, such as unprepared teachers, a need for more awareness of the CLIL approach, and teaching resources. Some teachers view it as a challenge due to its combination of both content and language. This often creates anxiety among teachers who are knowledgeable about their subject areas in Kazakh or Russian but are deficient in delivering the subject’s content in English. Thus, with this new teaching approach, teachers encounter to choose the role of language and answer how language works in the CLIL classroom. This study aimed to explore how teachers experience the changing role of language in the curriculum and to find out what challenges teachers face related to CLIL implementation and how their language proficiency influences their teaching practices. A qualitative comparative case study was conducted in an X Lyceum and a mainstream school piloting CLIL. Data collection procedures were conducted via semi-structured interviews, classroom observations, and document analysis. Eight content teachers were chosen from these two schools as the target group of this study. Subject teachers, rather than language teachers, were chosen as the target group to grasp how the language-related issues in the new curriculum are interpreted by educators who do not necessarily identify themselves as language experts at the outset. The findings showed that mainstream teachers prioritize content over language because, as content teachers, the knowledge of content is more essential for them rather than the language. In contrast, most X Lyceum teachers balance language and content and additionally showed their preferences to support the ‘English language only' policy among 10-11 graders. Moreover, due to the low-level English proficiency, mainstream teachers did highlight the necessity of CLIL training and further collaboration with language teachers. This study will be beneficial for teachers and policy-makers to enable them to solve the issues mentioned above related to the implementation of CLIL. Larger-scale research conducted in the future would further inform its successful deployment country-wide.

Keywords: role of language, trilingual education, updated curriculum, teacher practices

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1643 Research of Acoustic Propagation within Marine Riser in Deepwater Drilling

Authors: Xiaohui Wang, Zhichuan Guan, Roman Shor, Chuanbin Xu

Abstract:

Early monitoring and real-time quantitative description of gas intrusion under the premise of ensuring the integrity of the drilling fluid circulation system will greatly improve the accuracy and effectiveness of deepwater gas-kick monitoring. Therefore, in order to study the propagation characteristics of ultrasonic waves in the gas-liquid two-phase flow within the marine riser, in this paper, a numerical simulation method of ultrasonic propagation in the annulus of the riser was established, and the credibility of the numerical analysis was verified by the experimental results of the established gas intrusion monitoring simulation experimental device. The numerical simulation can solve the sound field in the gas-liquid two-phase flow according to different physical models, and it is easier to realize the single factor control. The influence of each parameter on the received signal can be quantitatively investigated, and the law with practical guiding significance can be obtained.

Keywords: gas-kick detection, ultrasonic, void fraction, coda wave velocity

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