Search results for: Intrusion Detection System (IDS)

Authors: Mugabe Nzarama Gabriel

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In Rwanda, many healthcare organizations are still using a paper based patients’ data record system although it still present weaknesses to share health patients’ information across different services when necessary. In developed countries, the EHR has been put in place to revolutionize the paper based record system but still the EHR has some challenges related to privacy, security, or interoperability. The purpose of this research was to assess the existing patients’ data record system in healthcare sector in Rwanda, see what an EHR can improve to the system in place and assess the acceptance of EHR as system which is interoperable, very secure and interoperable and see whether stakeholders are ready to adopt the system. The case based methodology was used and TAM theoretical framework to design the questionnaire for the survey. A judgmental sample across two cases, CHUB and Hopital de Nemba, has been selected and SPSS has been used for descriptive statistics. After a qualitative analysis, the findings showed that the paper based record is useful, gives complete information about the patient, protects the privacy of patients but it is still less secure and less interoperable. The respondents shown that they are ready to use the proposed EHR System and want it secure, capable of enforcing the privacy but still they are not all ready for the interoperability. A conclusion has been formulated; recommendations and further research have been proposed.

Keywords: EHR system, healthcare service, TAM, privacy, interoperability

Procedia PDF Downloads 248

Authors: Yixun Shi

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Many interior point methods for convex programming solve an (n+m)x(n+m)linear system in each iteration. Many implementations solve this system in each iteration by considering an equivalent mXm system (4) as listed in the paper, and thus the job is reduced into solving the system (4). However, the system(4) has to be solved exactly since otherwise the error would be entirely passed onto the last m equations of the original system. Often the Cholesky factorization is computed to obtain the exact solution of (4). One Cholesky factorization is to be done in every iteration, resulting in higher computational costs. In this paper, two iterative methods for solving linear systems using vector division are combined together and embedded into interior point methods. Instead of computing one Cholesky factorization in each iteration, it requires only one Cholesky factorization in the entire procedure, thus significantly reduces the amount of computation needed for solving the problem. Based on that, a hybrid algorithm for solving convex programming problems is proposed.

Keywords: convex programming, interior point method, linear systems, vector division

Procedia PDF Downloads 386

Authors: Idris lawal

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The most recent development in the Nigerian payment system is the venture into “electronic payment system”. Electronic payment system is simply a payment or monetary transaction made over the internet or a network of computers. This study was carried out in order to assess how electronic payment system has impacted on banks service delivery, to examine the efficiency of electronic payment system in Nigeria and to determine the level of customer’s satisfaction as a direct result of the deployment of electronic payment systems. The study was conducted using structured questionnaire distributed to 50 bank officials and customers of Access Bank plc. Chi-square(x2) was adopted for the purpose of data analysis. The result of the study showed that the development of electronic payment system offer great benefit to bank customers including; improved services, reduced turn-around time, ease of banking transaction, significant cost saving etc. The study recommend that customer protection laws should be properly put in place to safeguard the interest of end users of e-payment instruments, the banking industry and government should show strong commitment and effort to educate the populace on the benefit of patronizing e-payment system to facilitate economic development.

Keywords: electronic payment system, service delivery, bank, Nigeria

Procedia PDF Downloads 264

Authors: Mohd Sukri Hassan, Ahlam Inayatullah Badrul Munir, M. Husaini A. Rahman

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Halal authentication and verification in supplement capsules are highly required as the gelatine available in the market can be from halal or non-halal sources. It is an obligation for Muslim to consume and use the halal consumer goods. At present, real-time polymerase chain reaction (RT-PCR) is the most common technique being used for the detection of porcine and bovine DNA in gelatine due to high sensitivity of the technique and higher stability of DNA compared to protein. In this study, twenty samples of supplements capsules from different products with different Halal logos were analyzed for porcine and bovine DNA using RT-PCR. Standard bovine and porcine gelatine from eurofins at a range of concentration from 10^-1 to 10^-5 ng/µl were used to determine the linearity range, limit of detection and specificity on RT-PCR (SYBR Green method). RT-PCR detected porcine (two samples), bovine (four samples) and mixture of porcine and bovine (six samples). The samples were also tested using FT-IR technique where normalized peak of IR spectra were pre-processed using Savitsky Golay method before Principal Components Analysis (PCA) was performed on the database. Scores plot of PCA shows three clusters of samples; bovine, porcine and mixture (bovine and porcine). The RT-PCR and FT-IR with chemometrics technique were found to give same results for porcine gelatine samples which can be used for Halal authentication.

Keywords: halal, real-time PCR, gelatine, chemometrics

Procedia PDF Downloads 221

Authors: Ali Kazemi

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The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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Authors: Mohammed Ali

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A flexible manufacturing system has been studied under different manufacturing strategies. The aim of this paper is to test the impact of number of pallets and routing flexibility (design strategy) on system performance operating at different sequencing and dispatching rules (control strategies) at unbalanced load condition (planning strategies). A computer simulation model is developed to evaluate the effects of aforementioned strategies on the make-span time, which is taken as the system performance measure. The impact of number of pallets is shown with the different levels of routing flexibility. In this paper, the same manufacturing system is modeled under different combination of sequencing and dispatching rules. The result of the simulation shows that there is definite range of pallets for each level of routing flexibility at which the systems performs satisfactorily.

Keywords: flexible manufacturing system, manufacturing, strategy, makespan

Procedia PDF Downloads 649

Authors: D. Pinto, L. Castro, M. L. Cruzat, S. Barros, J. Gironás, C. Oberli, M. Torres, C. Escauriaza, A. Cipriano

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Flash floods, together with landslides, are a common natural threat for people living in mountainous regions and foothills. One way to deal with this constant menace is the use of Early Warning Systems, which have become a very important mitigation strategy for natural disasters. In this work, we present our proposal for a pilot Flash Flood Early Warning System for Santiago, Chile, the first stage of a more ambitious project that in a future stage shall also include early warning of landslides. To give a context for our approach, we first analyze three existing Flash Flood Early Warning Systems, focusing on their general architectures. We then present our proposed system, with main focus on the decision support system, a system that integrates empirical models and fuzzy expert systems to achieve reliable risk estimations.

Keywords: decision support systems, early warning systems, flash flood, natural hazard

Procedia PDF Downloads 361

Authors: Valentina Narvaez Gaitan, Laura Valentina Rodriguez Leguizamon, Ruben Dario Hernandez B.

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This work describes a physiological signal emulation system that uses electromyography (EMG) signals obtained from muscle sensors in the first instance. These signals are used to extract their characteristics to model and emulate specific arm movements. The main objective of this effort is to develop a new biomedical software system capable of generating physiological signals through the use of embedded systems by establishing the characteristics of the acquired signals. The acquisition system used was Biosignals, which contains two EMG electrodes used to acquire signals from the forearm muscles placed on the extensor and flexor muscles. Processing algorithms were implemented to classify the signals generated by the arm muscles when performing specific movements such as wrist flexion extension, palmar grip, and wrist pronation-supination. Matlab software was used to condition and preprocess the signals for subsequent classification. Subsequently, the mathematical modeling of each signal is performed to be generated by the embedded system, with a validation of the accuracy of the obtained signal using the percentage of cross-correlation, obtaining a precision of 96%. The equations are then discretized to be emulated in the embedded system, obtaining a system capable of generating physiological signals according to the characteristics of medical analysis.

Keywords: classification, electromyography, embedded system, emulation, physiological signals

Procedia PDF Downloads 79

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

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Authors: Do-Kyu Hwang, Ho-Young Kim, Ho-Hyeoung Choi, Gi-Beom Park, Jae-Hoon Lee

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Currently there are many use of threaded reinforcing bars in construction fields because those do not need additional screw processing when connecting reinforcing bar by threaded coupler. In this study, reinforced concrete bridge piers using threaded rebar coupler system at the plastic hinge area were tested to evaluate seismic performance. The test results showed that threads of the threaded rebar coupler system could be loosened while under tension-compression cyclic loading because tolerance and rib face angle of a threaded rebar coupler system are greater than that of a conventional ribbed rebar coupler system. As a result, cracks were concentrated just outside of the mechanical coupler and stiffness of reinforced concrete bridge pier decreased. Therefore, it is recommended that connection ratio of mechanical couplers in one section shall be below 50% in order that cracks are not concentrated just outside of the mechanical coupler. Also, reduced stiffness of the specimen should be considered when using the threaded rebar coupler system.

Keywords: reinforced concrete column, seismic performance, threaded rebar coupler, threaded reinforcing bar

Procedia PDF Downloads 352

Authors: Nathenal Thomas

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In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.

Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot

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Authors: Yog Raj Sood, Rajnish Shrivastava, Anchal Wadhwa

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Power transformer is one of the electrical equipment that has a central and critical role in the power system. In order to avoid power transformer failure, information system that provides the transformer condition is needed. This paper presents an information system to know the exact situations prevailing within the transformer by declaring its health index. Health index of a transformer is decided by considering several diagnostic tools. The current work deals with UV-Vis, IFT, FP, BDV and Water Content. UV/VIS results have been pre-accessed using separate FL controller for concluding with the Furan contents. It is broadly accepted that the life of a power transformer is the life of the oil/ paper insulating system. The method relies on the use of furan analysis (insulation paper), and other oil analysis results as a means to declare health index. Fuzzy logic system is used to develop the information system. The testing is done on 5 samples of oil of transformers of rating 132/66 KV to obtain the results and results are analyzed using fuzzy logic model.

Keywords: interfacial tension analyzer (ift), flash point (fp), furfuraldehyde (fal), health index

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Authors: Sathapath Kilaso

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Attendance checking in the classroom for student is object to record the student’s attendance in order to support the learning activities in the classroom. Despite the teaching trend in the 21st century is the student-center learning and the lecturer duty is to mentor and give an advice, the classroom learning is still important in order to let the student interact with the classmate and the lecturer or for a specific subject which the in-class learning is needed. The development of the system prototype by applied the microcontroller technology and embedded system with the “internet of thing” trend and the web socket technique will allow the lecturer to be alerted immediately whenever the data is updated.

Keywords: arduino, embedded system, classroom, raspberry PI

Procedia PDF Downloads 356

Authors: Jamilah Halina Abdul Halim, Norsiah Hassan, Azlina Aziz, Norhayati Mat Wajid, Mohd Saipul Asrafi

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There are various types of vertical greenery system (VGS) in Malaysia, but none is installed at government buildings, although the government is looking into energy efficient building design. This is due to lack of technical information that focus on the maintenance and care, issues, and challenges face by vertical greenery system under tropical climate conditions. This research aim to identify issues in implementation of vertical greenery system on existing government building in Malaysia. The methodology used are literature reviews (desktop study), observation on sites, and case studies. Initial findings indicates that design and maintenance issues of vertical greenery system are the main challenges faced mainly by designer, especially those who involved in decision-making process. It can be concluded that orientation, openings, maintenance, performance, longevity, structural load, access, wind resistance, design failure, system failure, and lack of maintenance foresight are the main factors that need to be considered. These factors should be holistically aligned towards the economic cost, effective time, and quality design in implementation of vertical greenery system on existing government building. A comprehensive implementation of vertical greenery system will lead to greater sustainable investment for government buildings and responsive action to climate change.

Keywords: issues, government building, maintenance, vertical greenery system

Procedia PDF Downloads 72

Authors: Andreas Latz, Daniela Heinz, Fatima Hashemi, Melek Baygül

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Introduction: Feline leukemia virus (FeLV), feline immunodeficiency virus (FIV), and feline coronavirus (FCoV) are serious infectious diseases affecting cats worldwide. Transmission of these viruses occurs primarily through close contact with infected cats (via saliva, nasal secretions, faeces, etc.). FeLV, FIV, and FCoV infections can occur in combination and are expressed in similar clinical symptoms. Diagnosis can therefore be challenging: Symptoms are variable and often non-specific. Sick cats show very similar clinical symptoms: apathy, anorexia, fever, immunodeficiency syndrome, anemia, etc. Sample volume for small companion animals for diagnostic purposes can be challenging to collect. In addition, multiplex diagnosis of diseases can contribute to an easier, cheaper, and faster workflow in the lab as well as to the better differential diagnosis of diseases. For this reason, we wanted to develop a new diagnostic tool that utilizes less sample volume, reagents, and consumables than multiplesingleplex ELISA assays Methods: The Multiplier from Dynextechonogies (USA) has been used as platform to develop a Multiplex diagnostic tool for the detection of antibodies against FIV and FCoV/FIP and antigens for FeLV. Multiplex diagnostics. The Dynex®Multiplier®is a fully automated chemiluminescence immunoassay analyzer that significantly simplifies laboratory workflow. The Multiplier®ease-of-use reduces pre-analytical steps by combining the power of efficiently multiplexing multiple assays with the simplicity of automated microplate processing. Plastic beads have been coated with antigens for FIV and FCoV/FIP, as well as antibodies for FeLV. Feline blood samples are incubated with the beads. Read out of results is performed via chemiluminescence Results: Bead coating was optimized for each individual antigen or capture antibody and then combined in the multiplex diagnostic tool. HRP: Antibody conjugates for FIV and FCoV antibodies, as well as detection antibodies for FeLV antigen, have been adjusted and mixed. 3 individual prototyple batches of the assay have been produced. We analyzed for each disease 50 well defined positive and negative samples. Results show an excellent diagnostic performance of the simultaneous detection of antibodies or antigens against these feline diseases in a fully automated system. A 100% concordance with singleplex methods like ELISA or IFA can be observed. Intra- and Inter-Assays showed a high precision of the test with CV values below 10% for each individual bead. Accelerated stability testing indicate a shelf life of at least 1 year. Conclusion: The new tool can be used for multiplex diagnostics of the most important feline infectious diseases. Only a very small sample volume is required. Fully automation results in a very convenient and fast method for diagnosing animal diseases.With its large specimen capacity to process over 576 samples per 8-hours shift and provide up to 3,456 results, very high laboratory productivity and reagent savings can be achieved.

Keywords: Multiplex, FIV, FeLV, FCoV, FIP

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Authors: Seshi Reddy Kasu, Florian Misoc

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The use of hydroelectric pump-storage system at large scale, MW-size systems, is already widespread around the world. Designed for large scale applications, pump-storage station can be scaled-down for small, remote residential applications. Given the cost and complexity associated with installing a substation further than 100 miles from the main transmission lines, a remote, independent and self-sufficient system is by far the most feasible solution. This article is aiming at the design of wind and solar power generating system, by means of pumped-storage to replace the wind and/or solar power systems with a battery bank energy storage. Wind and solar pumped-storage power generating system can reduce the cost of power generation system, according to the user's electricity load and resource condition and also can ensure system reliability of power supply. Wind and solar pumped-storage power generation system is well suited for remote residential applications with intermittent wind and/or solar energy. This type of power systems, installed in these locations, could be a very good alternative, with economic benefits and positive social effects. The advantage of pumped storage power system, where wind power regulation is calculated, shows that a significant smoothing of the produced power is obtained, resulting in a power-on-demand system’s capability, concomitant to extra economic benefits.

Keywords: battery bank, photo-voltaic, pump-storage, wind energy

Procedia PDF Downloads 580

Authors: Dua Hişam, Serhat İkizoğlu

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Identifying the problem behind balance disorder is one of the most interesting topics in the medical literature. This study has considerably enhanced the development of artificial intelligence (AI) algorithms applying multiple machine learning (ML) models to sensory data on gait collected from humans to classify between normal people and those suffering from Vestibular System (VS) problems. Although AI is widely utilized as a diagnostic tool in medicine, AI models have not been used to perform feature extraction and identify VS disorders through training on raw data. In this study, three machine learning (ML) models, the Random Forest Classifier (RF), Extreme Gradient Boosting (XGB), and K-Nearest Neighbor (KNN), have been trained to detect VS disorder, and the performance comparison of the algorithms has been made using accuracy, recall, precision, and f1-score. With an accuracy of 95.28 %, Random Forest Classifier (RF) was the most accurate model.

Keywords: vestibular disorder, machine learning, random forest classifier, k-nearest neighbor, extreme gradient boosting

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Authors: Nabila Louai, Fouad Khaldi, Houria Benharchache

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In this paper, the case of meeting a household’s electrical energy demand with hybrid systems has been examined. The objective is to study technological feasibility and economic viability of the electrification project by a hybrid system (PV/ wind) of a residential home located in Batna-Algeria and to reduce the emissions from traditional power by using renewable energy. An autonomous hybrid wind/photovoltaic (PV)/battery power system and a PV/Wind grid connected system, has been carried out using Hybrid Optimization Model for Electric Renewable (HOMER) simulation software. As a result, it has been found that electricity from the grid can be supplied at a lower price than electricity from renewable energy at this moment.

Keywords: batna, household, hybrid system, renewable energy, techno-economy

Procedia PDF Downloads 582

Authors: Marwa Ahmed Abd El Hamied

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In this paper In this paper, a new technique based on Artificial Immunity System (AIS) technique has been developed to track Maximum Power Point (MPP). AIS system is implemented in a photovoltaic system that is subjected to variable temperature and insulation condition. The proposed novel is simulated using Mat Lab program. The results of simulation have been compared to those who are generated from Observation Controller. The proposed model shows promising results as it provide better accuracy comparing to classical model.

Keywords: component, artificial immunity technique, solar energy, perturbation and observation, power based methods

Procedia PDF Downloads 413

Authors: Marie Bieber, Fabrice Cosson, Olivier Schmitt

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Europe's Global Navigation Satellite System, Galileo, provides worldwide positioning and navigation services. The satellites in space are only one part of the Galileo system. An extensive ground infrastructure is essential to oversee the satellites and ensure accurate navigation signals. High reliability and availability of the entire Galileo system are crucial to continuously provide positioning information of high quality to users. Outages are tracked, and operational availability is regularly assessed. A highly flexible and adaptive tool has been developed to automate the Galileo system availability analysis. Not only does it enable a quick availability consolidation, but it also provides first steps towards improving the data quality of maintenance tickets used for the analysis. This includes data import and data preparation, with a focus on processing strings used for classification and identifying faulty data. Furthermore, the tool allows to handle a low amount of data, which is a major constraint when the aim is to provide accurate statistics.

Keywords: availability, data quality, system performance, Galileo, aerospace

Procedia PDF Downloads 143

Authors: Young-Min Ko, Seung-Jun Yu, Seongjoo Lee, Hyoung-Kyu Song

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The Internet of things (IoT) system has attracted attention. IoT is a technology to connect all the objects to the internet as well as computer. IoT makes it possible for providing more data interoperability methods for an application purpose. Among the IoT technology, the research of devices so that they can communicate without power supply has been actively conducted. Batteryless system permits us to communicate without power supply devices. In this paper, batteryless backscatter system is used as a tag. And mobile devices which are embedded wireless fidelity (Wi-Fi) chipset are used as a reader. The backscatter tag can be obtained Internet connectivity from the reader. Conventional Wi-Fi backscatter system has limitation in the transmission range. In this paper, the proposed algorithm can be obtained improved reliability as well as overcoming the limitation about transmission range.

Keywords: Ambient RF, Backscatter, Batteryless communication, Energy-harvesting, IoT, RFID, Tag, Wi-Fi

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Authors: Leonard Tiong, Sonit Singh, Kevin Ho Shon, Sarah Lewis

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Investigation into the use of artificial intelligence in radiology continues to develop at a rapid rate. During the coronavirus pandemic, the combination of an exponential increase in chest x-rays and unpredictable staff shortages resulted in a huge strain on the department's workload. There is a World Health Organisation estimate that two-thirds of the global population does not have access to diagnostic radiology. Therefore, there could be demand for a program that could detect acute changes in imaging compatible with infection to assist with screening. We generated a conventional neural network and tested its efficacy in recognizing changes compatible with coronavirus infection. Following ethics approval, a deidentified set of 77 normal and 77 abnormal chest x-rays in patients with confirmed coronavirus infection were used to generate an algorithm that could train, validate and then test itself. DICOM and PNG image formats were selected due to their lossless file format. The model was trained with 100 images (50 positive, 50 negative), validated against 28 samples (14 positive, 14 negative), and tested against 26 samples (13 positive, 13 negative). The initial training of the model involved training a conventional neural network in what constituted a normal study and changes on the x-rays compatible with coronavirus infection. The weightings were then modified, and the model was executed again. The training samples were in batch sizes of 8 and underwent 25 epochs of training. The results trended towards an 85.71% true positive/true negative detection rate and an area under the curve trending towards 0.95, indicating approximately 95% accuracy in detecting changes on chest X-rays compatible with coronavirus infection. Study limitations include access to only a small dataset and no specificity in the diagnosis. Following a discussion with our programmer, there are areas where modifications in the weighting of the algorithm can be made in order to improve the detection rates. Given the high detection rate of the program, and the potential ease of implementation, this would be effective in assisting staff that is not trained in radiology in detecting otherwise subtle changes that might not be appreciated on imaging. Limitations include the lack of a differential diagnosis and application of the appropriate clinical history, although this may be less of a problem in day-to-day clinical practice. It is nonetheless our belief that implementing this program and widening its scope to detecting multiple pathologies such as lung masses will greatly assist both the radiology department and our colleagues in increasing workflow and detection rate.

Keywords: artificial intelligence, COVID, neural network, machine learning

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Authors: Mohamed Al-Hazmi, Abdullah Al-Arfaj, Moussa Ihab

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Raw, unpasteurized milk can carry dangerous bacteria such as Salmonella, E. coli, and Listeria, which are responsible for causing numerous foodborne illnesses. The objective of this study was molecular characterization of shiga toxogenic E. coli in raw milk collected from different Egyptian governorates by multiplex PCR. During the period of 25th May to 25th October 2012, a total of 320 bulk-tank milk samples were collected from 10 cow farms located in different Egyptian governorates. Bacteriological examination of milk samples revealed the presence of E. coli organisms in 65 samples (20.3%), serotyping of the E. coli isolates revealed, 35 strains (10.94%) O111, 15 strains (4.69%) O157: H7, 10 strains (3.13%) O128 and 5 strains (1.56%) O119. Multiplex PCR for detection of shiga toxin type 2 and intimin genes revealed positive amplification of 255 bp fragment of shiga toxin type 2 gene and 384 bp fragment of intimin gene from all E. coli serovar O157: H7, while from serovar O111 were 25 (71.43%), 20 (57.14%) and from serovar O128 were 6 (60%), 8 (80%), respectively. The results of multiplex PCR assay are useful for identification of STEC possessing the eaeA and stx2 genes.

Keywords: raw milk, E. coli, multiplex PCR, Shiga toxin type 2, intimin gene

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Authors: Jan Busch, Peter Nyhuis

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Considering the challenges of short product life cycles and growing variant diversity, cost minimization and manufacturing flexibility increasingly gain importance to maintain a competitive edge in today’s global and dynamic markets. In this context, an aerodynamic part feeding system for high-speed industrial assembly applications has been developed at the Institute of Production Systems and Logistics (IFA), Leibniz Universitaet Hannover. The aerodynamic part feeding system outperforms conventional systems with respect to its process safety, reliability, and operating speed. In this paper, a multi-objective optimisation of the aerodynamic feeding system regarding the orientation rate, the feeding velocity and the required nozzle pressure is presented.

Keywords: aerodynamic feeding system, genetic algorithm, multi-objective optimization, workpiece orientation

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Authors: Saeed Vahedikamal, Ian Hepburn

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Microwave Kinetic Inductance Detectors (MKIDs) are considered as one of the most promising photon detectors of the future in many Astronomical applications such as exoplanet detections. The MKID advantages stem from their single photon sensitivity (ranging from UV to optical and near infrared), photon energy resolution and high temporal capability (~microseconds). There has been substantial progress in the development of these detectors and MKIDs with Megapixel arrays is now possible. The unique capability of recording an incident photon and its energy (or wavelength) while also registering its time of arrival to within a microsecond enables an array of MKIDs to produce a four-dimensional data block of x, y, z and t comprising x, y spatial, z axis per pixel spectral and t axis per pixel which is temporal. This offers the possibility that the spectrum and brightness variation for any detected piece of space debris as a function of time might offer a unique identifier or fingerprint. Such a fingerprint signal from any object identified in multiple detections by different observers has the potential to determine the orbital features of the object and be used for their tracking. Modelling performed so far shows that with a 20 cm telescope located at an Astronomical observatory (e.g. La Palma, Canary Islands) we could detect sub cm objects at GEO. By considering a Lambertian sphere with a 10 % reflectivity (albedo of the Moon) we anticipate the following for a GEO object: 10 cm object imaged in a 1 second image capture; 1.2 cm object for a 70 second image integration or 0.65 cm object for a 4 minute image integration. We present details of our modelling and the potential instrument for a dedicated GEO surveillance system.

Keywords: space debris, orbital debris, detection system, observation, microwave kinetic inductance detectors, MKID

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Authors: T. Garba, T. O. Quddus, Y. Y. Babanyara, M. A. Modibbo

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Desertification is define as the changing of productive land into a desert as the result of ruination of land by man-induced soil erosion, which forces famers in the affected areas to move migrate or encourage into reserved areas in search of a fertile land for their farming activities. This study therefore used remote sensing imageries to determine the level of changes in the vegetative areas. To achieve that Normalized Difference of the Vegetative Index (NDVI), classified imageries and image slicing derived from landsat TM 1986, land sat ETM 1999 and Nigeria sat 1 2007 were used to determine changes in vegetations. From the Classified imageries it was discovered that there a more natural vegetation in classified images of 1986 than that of 1999 and 2007. This finding is also future in the three NDVI imageries, it was discovered that there is increased in high positive pixel value from 0.04 in 1986 to 0.22 in 1999 and to 0.32 in 2007. The figures in the three histogram also indicted that there is increased in vegetative areas from 29.15 Km2 in 1986, to 60.58 Km2 in 1999 and then to 109 Km2 in 2007. The study recommends among other things that there is need to restore natural vegetation through discouraging of farming activities in and around the natural vegetation in the study area.

Keywords: vegetative index, classified imageries, change detection, landsat, vegetation

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Authors: Mona Hamdy, Iman Shaheen, Hadeel Seif Eldin, Basma Ali, Omnia Abdeldayem

Abstract:

Summary: Bone involvement of sickle cell disease (SCD) patients varies from acute clinical manifestations of painful vaso-occlusive crises or osteomyelitis to more chronic affection of bone mineral density (BMD) and debilitating osteonecrosis and osteoporosis. Secreted klotho protein is involved in calcium (Ca) reabsorption in the kidney. This study aimed to measure serum klotho levels in children with SCD to determine the possibility of using it as a marker of low BMD in children with SCD in correlation with a dual-energy radiograph absorptiometry scan. This study included 60 sickle disease patients and 30 age-matched and sex-matched control participants without SCD. A highly statistically significant difference was found between patients with normal BMD and those with low BMD, with serum Ca and klotho levels being lower in the latter group. Klotho serum level correlated positively with both serum Ca and BMD. Serum klotho level showed 94.9% sensitivity and 95.2% specificity in the detection of low BMD. Both serum Ca and klotho serum levels may be useful markers for detection of low BMD related to SCD with high sensitivity and specificity; however, klotho may be a better indicator as it is less affected by the nutritional and endocrinal status of patients or by intake of Ca supplements.

Keywords: sickle cell disease, BMD, osteoporosis, DEXA, klotho

Procedia PDF Downloads 85

Authors: M. Amo, A. Alvaro, A. Astudillo, R. Mc Culloch, J. C. del Castillo, M. Gómez, J. M. Martín

Abstract:

Polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) of course comprise a range of highly toxic compounds that may exist as particulates within the air or accumulate within water supplies, soil, or vegetation. They may be created either ubiquitously or naturally within the environment as a product of forest fires or volcanic eruptions. It is only since the industrial revolution, however, that it has become necessary to closely monitor their generation as a byproduct of manufacturing/combustion processes, in an effort to mitigate widespread contamination events. Of course, the environmental concentrations of these toxins are expected to be extremely low, therefore highly sensitive and accurate methods are required for their determination. Since ionization of non-polar compounds through electrospray and APCI is difficult and inefficient, we evaluate the performance of a novel low-flow Atmospheric Pressure Photoionization (APPI) source for the trace detection of various dioxins and furans using rapid Mass Spectrometry workflows. Air, soil and biota (vegetable matter) samples were collected monthly during one year from various locations within the vicinity of an industrial incinerator in Spain. Analytes were extracted and concentrated using soxhlet extraction in toluene and concentrated by rotavapor and nitrogen flow. Various ionization methods as electrospray (ES) and atmospheric pressure chemical ionization (APCI) were evaluated, however, only the low-flow APPI source was capable of providing the necessary performance, in terms of sensitivity, required for detecting all targeted analytes. In total, 10 analytes including 2,3,7,8-tetrachlorodibenzodioxin (TCDD) were detected and characterized using the APPI-MS method. Both PCDDs and PCFDs were detected most efficiently in negative ionization mode. The most abundant ion always corresponded to the loss of a chlorine and addition of an oxygen, yielding [M-Cl+O]- ions. MRM methods were created in order to provide selectivity for each analyte. No chromatographic separation was employed; however, matrix effects were determined to have a negligible impact on analyte signals. Triple Quadrupole Mass Spectrometry was chosen because of its unique potential for high sensitivity and selectivity. The mass spectrometer used was a Sciex´s Qtrap3200 working in negative Multi Reacting Monitoring Mode (MRM). Typically mass detection limits were determined to be near the 1-pg level. The APPI-MS2 technology applied to the detection of PCDD/Fs allows fast and reliable atmospheric analysis, minimizing considerably operational times and costs, with respect other technologies available. In addition, the limit of detection can be easily improved using a more sensitive mass spectrometer since the background in the analysis channel is very low. The APPI developed by SEADM allows polar and non-polar compounds ionization with high efficiency and repeatability.

Keywords: atmospheric pressure photoionization-mass spectrometry (APPI-MS), dioxin, furan, incinerator

Procedia PDF Downloads 189

Authors: Nur Ashida Salim, Muhammad Murtadha Othman, Ismail Musirin, Mohd Salleh Serwan

Abstract:

Over the past few decades, the power system industry in many developing and developed countries has gone through a restructuring process of the industry where they are moving towards a deregulated power industry. This situation will lead to competition among the generation and distribution companies to achieve a certain objective which is to provide quality and efficient production of electric energy, which will reduce the price of electricity. Therefore it is important to obtain an accurate value of the Available Transfer Capability (ATC) and Transmission Reliability Margin (TRM) in order to ensure the effective power transfer between areas during the occurrence of uncertainties in the system. In this paper, the TRM and ATC is determined by taking into consideration the uncertainties of the system operating condition and system cascading collapse by applying the bootstrap technique. A case study of the IEEE RTS-79 is employed to verify the robustness of the technique proposed in the determination of TRM and ATC.

Keywords: available transfer capability, bootstrap technique, cascading collapse, transmission reliability margin

Procedia PDF Downloads 387

Authors: Bahaa Eltahawy, Mikko Ylihärsilä, Reino Virrankoski, Esko Petäjä

Abstract:

Sheet metal processing is automated, but the step from product models to the production machine control still requires human intervention. This may cause time consuming bottlenecks in the production process and increase the risk of human errors. In this paper we present a system, which automatically recognizes features from the CAD-model of the sheet metal product. By using these features, the system produces a complete model of the particular sheet metal product. Then the model is used as an input for the sheet metal processing machine. Currently the system is implemented, capable to recognize more than 11 of the most common sheet metal structural features, and the procedure is fully automated. This provides remarkable savings in the production time, and protects against the human errors. This paper presents the developed system architecture, applied algorithms and system software implementation and testing.

Keywords: feature recognition, automation, sheet metal manufacturing, CAD, CAM

Procedia PDF Downloads 334