Search results for: automated teller machines

Authors: Jocelyn B. Barbosa, Angeli L. Magbaril, Mariel T. Sabanal, John Paul T. Galario, Mikka P. Baldovino

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The use of technology has become ubiquitous in different areas of business today. With the advent of digital imaging and database technology, business owners have been motivated to integrate technology to their business operation ranging from small, medium to large enterprises. Technology has been found to have brought many benefits that can make a business grow. Hog or swine raising, for example, is a very popular enterprise in the Philippines, whose challenges in production monitoring can be addressed through technology integration. Swine production monitoring can become a tedious task as the enterprise goes larger. Specifically, problems like delayed and inconsistent reports are most likely to happen if counting of swine per pen of which building is done manually. In this study, we present iCount, which aims to ensure efficient swine detection and counting that hastens the swine production monitoring task. We develop a system that automatically detects and counts swine based on Sobel filter and ellipse fitting model, given the still photos of the group of swine captured in a pen. We improve the Sobel filter detection result through 8-neigbhorhood rule implementation. Ellipse fitting technique is then employed for proper swine detection. Furthermore, the system can generate periodic production reports and can identify the specific consumables to be served to the swine according to schedules. Experiments reveal that our algorithm provides an efficient way for detecting swine, thereby providing a significant amount of accuracy in production monitoring.

Keywords: automatic swine counting, swine detection, swine production monitoring, ellipse fitting model, sobel filter

Procedia PDF Downloads 291

Authors: Soha A. Bahanshal, Vaibhav Verdhan, Bayong Kim

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Graduation rates at six-year colleges are becoming a more essential indicator for incoming fresh students and for university rankings. Predicting student graduation is extremely beneficial to schools and has a huge potential for targeted intervention. It is important for educational institutions since it enables the development of strategic plans that will assist or improve students' performance in achieving their degrees on time (GOT). A first step and a helping hand in extracting useful information from these data and gaining insights into the prediction of students' progress and performance is offered by machine learning techniques. Data analysis and visualization techniques are applied to understand and interpret the data. The data used for the analysis contains students who have graduated in 6 years in the academic year 2017-2018 for science majors. This analysis can be used to predict the graduation of students in the next academic year. Different Predictive modelings such as logistic regression, decision trees, support vector machines, Random Forest, Naïve Bayes, and KNeighborsClassifier are applied to predict whether a student will graduate. These classifiers were evaluated with k folds of 5. The performance of these classifiers was compared based on accuracy measurement. The results indicated that Ensemble Classifier achieves better accuracy, about 91.12%. This GOT prediction model would hopefully be useful to university administration and academics in developing measures for assisting and boosting students' academic performance and ensuring they graduate on time.

Keywords: prediction, decision trees, machine learning, support vector machine, ensemble model, student graduation, GOT graduate on time

Procedia PDF Downloads 55

Authors: Yiping Meng, Yiming Sun

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The traditional construction industry is unable to meet the requirements for novel fabrication and construction. Automated construction and digital design have emerged as industry development trends that compensate for this shortcoming under the backdrop of Industrial Revolution 4.0. Benefitting from more flexible working space and more various end-effector tools compared to CNC methods, robot fabrication and construction techniques have been used in irregular architectural design. However, there is a lack of a systematic and comprehensive design and optimisation workflow considering geometric form, material, and fabrication methods. This paper aims to propose a design optimisation workflow for improving the rationality of a free-form timber structure fabricated by the robotic arm. Firstly, the free-form surface is described by NURBS, while its structure is calculated using the finite element analysis method. Then, by considering the characteristics and limiting factors of robotic timber fabrication, strain energy and robustness are set as optimisation objectives to optimise structural morphology by gradient descent method. As a result, an optimised structure with axial force as the main force and uniform stress distribution is generated after the structure morphology optimisation process. With the decreased strain energy and the improved robustness, the generated structure's bearing capacity and mechanical properties have been enhanced. The results prove the feasibility and effectiveness of the proposed optimisation workflow for free-form timber structure morphology design.

Keywords: robotic fabrication, free-form timber structure, Multi-objective optimisation, Structural morphology, rational design

Procedia PDF Downloads 173

Authors: Michael Zenker, Henrik Prinzhorn, Christian Böning, Tom Strating

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Large-scale products are often assembled according to the job-site principle, meaning that during the assembly the product is located at a fixed position, while the area requirements are constantly changing. On one hand, the product itself is growing with each assembly step, whereas varying areas for storage, machines or working areas are temporarily required. This is an important factor when arranging products to be assembled within the factory. Currently, it is common to reserve a fixed area for each product to avoid overlaps or collisions with the other assemblies. Intending to be large enough to include the product and all adjacent areas, this reserved area corresponds to the superposition of the maximum extents of all required areas of the product. In this procedure, the reserved area is usually poorly utilized over the course of the entire assembly process; instead a large part of it remains unused. If the available area is a limited resource, a systematic arrangement of the products, which complies with the dynamic area requirements, will lead to an increased area utilization and productivity. This paper presents the results of a study on the arrangement of assembly objects assuming dynamic, competing area requirements. First, the problem situation is extensively explained, and existing research on associated topics is described and evaluated on the possibility of an adaptation. Then, a newly developed mathematical optimization model is introduced. This model allows an optimal arrangement of dynamic areas, considering logical and practical constraints. Finally, in order to quantify the potential of the developed method, some test series results are presented, showing the possible increase in area utilization.

Keywords: dynamic area requirements, facility layout problem, optimization model, product assembly

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Authors: Ada Garus

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This paper presents the outcomes of the sustainability assessment of food delivery with a last-mile delivery service introduced in a real-world case study. The methodology used in the sustainability assessment integrates multi-criteria decision-making analysis, sustainability pillars, and scenario analysis to best reflect the conflicting needs of stakeholders involved in the last mile delivery system. The case study provides an application of the framework to the food delivery system of the Joint Research Centre of the European Commission where three alternative solutions were analyzed I) the existent state in which individuals frequent the local cantine or pick up their food, using their preferred mode of transport II) the hypothetical scenario in which individuals can only order their food using the delivery droid system III) a scenario in which the food delivery droid based system is introduced as a supplement to the current system. The environmental indices are calculated using a simulation study in which decision regarding the food delivery is predicted using a multinomial logit model. The vehicle dynamics model is used to predict the fuel consumption of the regular combustion engines vehicles used by the cantine goers and the electricity consumption of the droid. The sustainability assessment allows for the evaluation of the economic, environmental, and social aspects of food delivery, making it an apt input for policymakers. Moreover, the assessment is one of the first studies to investigate automated delivery droids, which could become a frequent addition to the urban landscape in the near future.

Keywords: innovations in transportation technologies, behavioural change and mobility, urban freight logistics, innovative transportation systems

Procedia PDF Downloads 177

Authors: Daudi S. Simbeye, Mbazingwa E. Mkiramweni

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Plant diseases have the potential to drastically diminish the quantity and quality of agricultural products. Guava (Psidium guajava), sometimes known as the apple of the tropics, is one of the most widely cultivated fruits in tropical regions. Monitoring plant health and diagnosing illnesses is an essential matter for sustainable agriculture, requiring the inspection of visually evident patterns on plant leaves and fruits. Due to minor variations in the symptoms of various guava illnesses, a professional opinion is required for disease diagnosis. Due to improper pesticide application by farmers, erroneous diagnoses may result in economic losses. This study proposes a method that uses artificial intelligence (AI) to detect and classify the most widespread guava plant by comparing images of its leaves and fruits to datasets. ESP32 CAM is responsible for data collection, which includes images of guava leaves and fruits. By comparing the datasets, these image formats are used as datasets to help in the diagnosis of plant diseases through the leaves and fruits, which is vital for the development of an effective automated agricultural system. The system test yielded the most accurate identification findings (99 percent accuracy in differentiating four guava fruit diseases (Canker, Mummification, Dot, and Rust) from healthy fruit). The proposed model has been interfaced with a mobile application to be used by smartphones to make a quick and responsible judgment, which can help the farmers instantly detect and prevent future production losses by enabling them to take precautions beforehand.

Keywords: early identification, guava plants, fruit diseases, deep learning

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Authors: John Gibbs, Benjamin Flanders, Dylan Pozorski, Weixuan Liu

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Weight Painting–adjusting the influence a skeletal joint has on a given vertex in a character mesh–is an arduous and time con- suming part of the 3D animation pipeline. This process generally requires a trained technical animator and many hours of work to complete. Our skiNNer plug-in, which works within Autodesk’s Maya 3D animation software, uses Machine Learning and data pro- cessing techniques to create a deep neural network model that can accomplish the weight painting task in seconds rather than hours for bipedal quasi-humanoid character meshes. In order to create a properly trained network, a number of challenges were overcome, including curating an appropriately large data library, managing an arbitrary 3D mesh size, handling arbitrary skeletal architectures, accounting for extreme numeric values (most data points are near 0 or 1 for weight maps), and constructing an appropriate neural network model that can properly capture the high frequency alter- ation between high weight values (near 1.0) and low weight values (near 0.0). The arrived at neural network model is a cross between a traditional CNN, deep residual network, and fully dense network. The resultant network captures the unusually hard-edged features of a weight map matrix, and produces excellent results on many bipedal models.

Keywords: 3d animation, animation, character, rigging, skinning, weight painting, machine learning, artificial intelligence, neural network, deep neural network

Procedia PDF Downloads 245

Authors: Emil F. Khisamutdinov

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Development of functional materials undergoing structural transformations in response to an external stimulus such as environmental changes (pH, temperature, etc.), the presence of particular proteins, or short oligonucleotides are of great interest for a variety of applications ranging from medicine to electronics. The dynamic operations of most nucleic acid (NA) devices, including circuits, nano-machines, and biosensors, rely on networks of NA strand displacement processes in which an external or stimulus strand displaces a target strand from a DNA or RNA duplex. The rate of strand displacement can be greatly increased by the use of “toeholds,” single-stranded regions of the target complex to which the invading strand can bind to initiate the reaction, forming additional base pairs that provide a thermodynamic driving force for transformation. Herein, we developed a highly robust nanoparticle shape transition, sequentially transforming DNA polygons from one shape to another using the toehold-mediated DNA strand displacement technique. The shape transformation was confirmed by agarose gel electrophoresis and atomic force microscopy. Furthermore, we demonstrate that our approach is applicable for RNA shape transformation from triangle to square, which can be detected by fluorescence emission from malachite green binding RNA aptamer. Using gel-shift and fluorescence assays, we demonstrated efficient transformation occurs at isothermal conditions (37°C) that can be implemented within living cells as reporter molecules. This work is intended to provide a simple, cost-effective, and straightforward model for the development of biosensors and regulatory devices in nucleic acid nanotechnology.

Keywords: RNA nanotechnology, bionanotechnology, toehold mediated DNA switch, RNA split fluorogenic aptamers

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Authors: Lucian Capitanu, Virgil Florescu

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Often for the laboratory studies, modeling of specific tribological processes raises special problems. One such problem is the modeling of some temperatures and extremely high contact pressures, allowing modeling of temperatures and pressures at which the injection or extrusion processing of thermoplastic materials takes place. Tribological problems occur mainly in thermoplastics materials reinforced with glass fibers. They produce an advanced wear to the barrels and screws of processing machines, in short time. Obtaining temperatures around 210 °C and higher, as well as pressures around 100 MPa is very difficult in the laboratory. This paper reports a simple and convenient solution to get these conditions, using friction sliding couples with linear contact, cylindrical liner plastic filled with glass fibers on plate steel samples, polished and super-finished. C120 steel, which is a steel for moulds and Rp3 steel, high speed steel for tools, were used. Obtaining the pressure was achieved by continuous request of the liner in rotational movement up to its elasticity limits, when the dry friction coefficient reaches or exceeds the hardness value of 0.5 HB. By dissipation of the power lost by friction on flat steel sample, are reached contact temperatures at the metal surface that reach and exceed 230 °C, being placed in the range temperature values of the injection. Contact pressures (in load and materials conditions used) ranging from 16.3-36.4 MPa were obtained depending on the plastic material used and the glass fibers content.

Keywords: plastics with glass fibers, dry friction, linear contact, contact temperature, contact pressure, experimental simulation

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Authors: Shao Bo Cheng, Yong-Jin Han, Se Young Park, Seong-Bae Park

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Consumer-to-Consumer (C2C) E-commerce has been growing at a very high speed in recent years. Since identical or nearly-same kinds of products compete one another by relying on keyword search in C2C E-commerce, some sellers describe their products with spam keywords that are popular but are not related to their products. Though such products get more chances to be retrieved and selected by consumers than those without spam keywords, the spam keywords mislead the consumers and waste their time. This problem has been reported in many commercial services like e-bay and taobao, but there have been little research to solve this problem. As a solution to this problem, this paper proposes a method to classify whether keywords of a product are spam or not. The proposed method assumes that a keyword for a given product is more reliable if the keyword is observed commonly in specifications of products which are the same or the same kind as the given product. This is because that a hierarchical category of a product in general determined precisely by a seller of the product and so is the specification of the product. Since higher layers of the hierarchical category represent more general kinds of products, a reliable degree is differently determined according to the layers. Hence, reliable degrees from different layers of a hierarchical category become features for keywords and they are used together with features only from specifications for classification of the keywords. Support Vector Machines are adopted as a basic classifier using the features, since it is powerful, and widely used in many classification tasks. In the experiments, the proposed method is evaluated with a golden standard dataset from Yi-han-wang, a Chinese C2C e-commerce, and is compared with a baseline method that does not consider the hierarchical category. The experimental results show that the proposed method outperforms the baseline in F1-measure, which proves that spam keywords are effectively identified by a hierarchical category in C2C e-commerce.

Keywords: spam keyword, e-commerce, keyword features, spam filtering

Procedia PDF Downloads 272

Authors: Walaa Mohammed Saeed

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Studies suggest a crosstalk between bone and metabolism through Osteocalcin (OC), a bone-derived protein that plays an important role in regulating glucose and fat metabolism. Studies relate type II Diabetes Mellitus (DMII) with Homocysteine (Hcy) and cardiovascular diseases (CVD). This study investigates the relationship between levels of OC, Hcy, and DMII in 85 subjects of which 50 were diabetic female patients (29–65 years) and 35 healthy controls. OC and Hcy levels were measured in fasting blood samples using immunoassay analyzer. Fasting serum glucose, glycated hemoglobin, lipid profile, were estimated by automated Siemens Dimension XP auto-analyzer. A significant increase in the frequency of low OC levels (p < 0.001) and high Hcy levels (p < 0.001) was detected in diabetic patients compared to controls (chi-squared test). Using ANOVA test, patients were divided into tertiles based on plasma OC and Hcy levels; fasting serum glucose varied inversely with OC but directly with Hcy tertiles (p=0.049, p=0.033 respectively). Atherogenic Index of Plasma (AIP=Log TG/HDL) predicts that diabetic patients with 36% high and 15% intermediate cardiovascular risk had increased frequency of low OC levels compared to low-risk patients (p=0.047). Another group of diabetic patients with 39% high and 11% intermediate CVD risk had increased frequency of high Hcy levels (p=0.033). A significant negative correlation existed between OC and glucose (r = -0.318; p = 0.035) while correlation between glucose level and Hcy (r = 0.851 p=0.022) was positive. Hence, low serum OC levels and high Hcy levels were associated with impaired glucose metabolism that may increase cardiovascular risk in DMII.

Keywords: osteocalcin, homocysteine, type 2 diabetes, cardiovascular

Procedia PDF Downloads 127

Authors: R. Pravin Kumar, L. Roopa

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Enzymes are molecular machines used in various industries such as pharmaceuticals, cosmetics, food and animal feed, paper and leather processing, biofuel, and etc. Nevertheless, this has been possible only by the breath-taking efforts of the chemists and biologists to evolve/engineer these mysterious biomolecules to work the needful. Main agenda of this enzyme engineering project is to derive screening and selection tools to obtain focused libraries of enzyme variants with desired qualities. The methodologies for this research include the well-established directed evolution, rational redesign and relatively less established yet much faster and accurate insilico methods. This concept was initiated as a Receptor Rependent-4Dimensional Quantitative Structure Activity Relationship (RD-4D-QSAR) to predict kinetic properties of enzymes and extended here to study transaminase by a 7D QSAR approach. Induced-fit scenarios were explored using Quantum Mechanics/Molecular Mechanics (QM/MM) simulations which were then placed in a grid that stores interactions energies derived from QM parameters (QMgrid). In this study, the mutated enzymes were immersed completely inside the QMgrid and this was combined with solvation models to predict descriptors. After statistical screening of descriptors, QSAR models showed > 90% specificity and > 85% sensitivity towards the experimental activity. Mapping descriptors on the enzyme structure revealed hotspots important to enhance the enantioselectivity of the enzyme.

Keywords: QMgrid, QM/MM simulations, RD-4D-QSAR, transaminase

Procedia PDF Downloads 115

Authors: Oluibukun G. Ajayi, Joseph O. Odumosu, Oladimeji T. Babafemi, Azeez Z. Opeyemi, Asaleye O. Samuel

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The need for the complete automation of every procedure of surveying and most especially, its engineering applications cannot be overemphasized due to the many demerits of the conventional manual or analogue approach. This paper presents the summarized details of the development of a Route Information Management (RIM) software. The software, codenamed ‘AutoROUTE’, was encoded using Microsoft visual studio-visual basic package, and it offers complete automation of the computational procedures and plan production involved in route surveying. It was experimented using a route survey data (longitudinal profile and cross sections) of a 2.7 km road which stretches from Dama to Lunko village in Minna, Niger State, acquired with the aid of a Hi-Target DGPS receiver. The developed software (AutoROUTE) is capable of computing the various simple curve parameters, horizontal curve, and vertical curve, and it can also plot road alignment, longitudinal profile, and cross-section with a capability to store this on the SQL incorporated into the Microsoft visual basic software. The plotted plans with AutoROUTE were compared with the plans produced with the conventional AutoCAD Civil 3D software, and AutoROUTE proved to be more user-friendly and accurate because it plots in three decimal places whereas AutoCAD plots in two decimal places. Also, it was discovered that AutoROUTE software is faster in plotting and the stages involved is less cumbersome compared to AutoCAD Civil 3D software.

Keywords: automated systems, cross sections, curves, engineering construction, longitudinal profile, route surveying

Procedia PDF Downloads 111

Authors: Tasneem Halawani, Yamen Khateeb

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With customers’ ever-increasing expectations for fast services provisioning for all their business needs, information technology (IT) organizations, as business partners, have to cope with this demanding environment and deliver their services in the most effective and efficient way. The purpose of this paper is to identify optimization and automation opportunities for the top requested IT services in a heterogenic digital environment and widely spread customer base. In collaboration with systems, processes, and subject matter experts (SMEs), the processes in scope were approached by analyzing four-year related historical data, identifying and surveying stakeholders, modeling the as-is processes, and studying systems integration/automation capabilities. This effort resulted in identifying several pain areas, including standardization, unnecessary customer and IT involvement, manual steps, systems integration, and performance measurement. These pain areas were addressed by standardizing the top five requested IT services, eliminating/automating 43 steps, and utilizing a single platform for end-to-end process execution. In conclusion, the optimization of IT service request processes in a heterogenic digital environment and widely spread customer base is challenging, yet achievable without compromising the service quality and customers’ added value. Further studies can focus on measuring the value of the eliminated/automated process steps to quantify the enhancement impact. Moreover, a similar approach can be utilized to optimize other IT service requests, with a focus on business criticality.

Keywords: automation, customer value, heterogenic, integration, IT services, optimization, processes

Procedia PDF Downloads 88

Authors: ChunYi Peng, Wei Hsuan CHeng, Shyh Kuang Ueng

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This study focuses on the application of self-organizing maps (SOM) technology in analyzing credit card transaction data, aiming to enhance the accuracy and efficiency of fraud detection. Som, as an artificial neural network, is particularly suited for pattern recognition and data classification, making it highly effective for the complex and variable nature of credit card transaction data. By analyzing transaction characteristics with SOM, the research identifies abnormal transaction patterns that could indicate potentially fraudulent activities. Moreover, this study has developed a specialized visualization tool to intuitively present the relationships between SOM analysis outcomes and transaction data, aiding financial institution personnel in quickly identifying and responding to potential fraud, thereby reducing financial losses. Additionally, the research explores the integration of SOM technology with composite intelligent system technologies (including finite state machines, fuzzy logic, and decision trees) to further improve fraud detection accuracy. This multimodal approach provides a comprehensive perspective for identifying and understanding various types of fraud within credit card transactions. In summary, by integrating SOM technology with visualization tools and composite intelligent system technologies, this research offers a more effective method of fraud detection for the financial industry, not only enhancing detection accuracy but also deepening the overall understanding of fraudulent activities.

Keywords: self-organizing map technology, fraud detection, information visualization, data analysis, composite intelligent system technologies, decision support technologies

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Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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The interpretation of medical images benefits from anatomical and physiological priors to optimize computer- aided diagnosis applications. Segmentation of liver and liver lesion is regarded as a major primary step in computer aided diagnosis of liver diseases. Precise liver segmentation in abdominal CT images is one of the most important steps for the computer-aided diagnosis of liver pathology. In this papers, a semi- automated method for medical image data is presented for the liver and liver lesion segmentation data using mathematical morphology. Our algorithm is currency in two parts. In the first, we seek to determine the region of interest by applying the morphological filters to extract the liver. The second step consists to detect the liver lesion. In this task; we proposed a new method developed for the semi-automatic segmentation of the liver and hepatic lesions. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to improve the quality of the original image and image gradient by applying the spatial filter followed by the morphological filters. The second step consists to calculate the internal and external markers of the liver and hepatic lesions. Thereafter we proceed to the liver and hepatic lesions segmentation by the watershed transform controlled by markers. The validation of the developed algorithm is done using several images. Obtained results show the good performances of our proposed algorithm

Keywords: anisotropic diffusion filter, CT images, hepatic lesion segmentation, Liver segmentation, morphological filter, the watershed algorithm

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Authors: M. Mutemwa

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A Cybersecurity Operation Centre (SOC) is a centralized hub for network event monitoring and incident response. SOCs are critical when determining an organization’s cybersecurity posture because they can be used to detect, analyze and report on various malicious activities. For most organizations, a SOC is not part of the initial design and implementation of the Information Technology (IT) environment but rather an afterthought. As a result, it is not natively a plug and play component; therefore, there are integration challenges when a SOC is introduced into an organization. A SOC is an independent hub that needs to be integrated with existing procedures, policies and IT systems of an organization such as the service desk, ticket logging system, reporting, etc. This paper discussed the challenges of integrating a newly developed SOC to an organization’s existing IT environment. Firstly, the paper begins by looking at what data sources should be incorporated into the Security Information and Event Management (SIEM) such as which host machines, servers, network end points, software, applications, web servers, etc. for security posture monitoring. That is which systems need to be monitored first and the order by which the rest of the systems follow. Secondly, the paper also describes how to integrate the organization’s ticket logging system with the SOC SIEM. That is how the cybersecurity related incidents should be logged by both analysts and non-technical employees of an organization. Also the priority matrix for incident types and notifications of incidents. Thirdly, the paper looks at how to communicate awareness campaigns from the SOC and also how to report on incidents that are found inside the SOC. Lastly, the paper looks at how to show value for the large investments that are poured into designing, building and running a SOC.

Keywords: cybersecurity operation centre, incident response, priority matrix, procedures and policies

Procedia PDF Downloads 132

Authors: Peng, Chun-Yi, Chen, Wei-Hsuan, Ueng, Shyh-Kuang

Abstract:

This study focuses on the application of self-organizing maps (SOM) technology in analyzing credit card transaction data, aiming to enhance the accuracy and efficiency of fraud detection. Som, as an artificial neural network, is particularly suited for pattern recognition and data classification, making it highly effective for the complex and variable nature of credit card transaction data. By analyzing transaction characteristics with SOM, the research identifies abnormal transaction patterns that could indicate potentially fraudulent activities. Moreover, this study has developed a specialized visualization tool to intuitively present the relationships between SOM analysis outcomes and transaction data, aiding financial institution personnel in quickly identifying and responding to potential fraud, thereby reducing financial losses. Additionally, the research explores the integration of SOM technology with composite intelligent system technologies (including finite state machines, fuzzy logic, and decision trees) to further improve fraud detection accuracy. This multimodal approach provides a comprehensive perspective for identifying and understanding various types of fraud within credit card transactions. In summary, by integrating SOM technology with visualization tools and composite intelligent system technologies, this research offers a more effective method of fraud detection for the financial industry, not only enhancing detection accuracy but also deepening the overall understanding of fraudulent activities.

Keywords: self-organizing map technology, fraud detection, information visualization, data analysis, composite intelligent system technologies, decision support technologies

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Authors: Erika Duggan

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A Major Hospital had identified that there was no standard process for handling a patient’s medication that they brought with them to the hospital. It was also identified that each floor was handling the patient’s medication differently and storing it in multiple locations. Based on this disconnect many patients were leaving the hospital without their medication. The project team was tasked with creating a cohesive process to send a patient’s unneeded medication home on admission, storing any of the patient’s medication that could not be sent home, storing any of the patient’s medication for inpatient administration, and sending all of the patient’s medication home on discharge. The project team consisted of pharmacists, RNs, LPNs, members from nursing informatics and a project engineer and followed a DMAIC framework. Working together observations were performed to identify what was working and not working on the different floors which resulted in process maps. Using the multidisciplinary team, brainstorming, including affinity diagramming and other lean six sigma techniques, the best process for receiving, storing, and returning the medication was created. It was highlighted that being able to track the medication throughout the patient’s stay would be beneficial and would help make sure the medication left with the patient on discharge. Using an automated medications dispensing system would help store, and track patient’s medications. Also, the use of a specific order that would show up on the discharge instructions would assist the front line staff in retrieving the medication from a set location and sending it home with the patient. This new process will effectively streamline the admission and discharge process for patients who brought their medication with them as well as effectively tracking the medication during the patient’s stay. As well as increasing patient safety as it relates to medication administration.

Keywords: lean six sigma, medication dispensing, process improvement, process mapping

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Authors: S. Ziaran, M. Musil, M. Cekan, O. Chlebo

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The paper analyzes the response of buildings and industrially structures on seismic waves (low frequency mechanical vibration) generated by blasting operations. The principles of seismic analysis can be applied for different kinds of excitation such as: earthquakes, wind, explosions, random excitation from local transportation, periodic excitation from large rotating and/or machines with reciprocating motion, metal forming processes such as forging, shearing and stamping, chemical reactions, construction and earth moving work, and other strong deterministic and random energy sources caused by human activities. The article deals with the response of seismic, low frequency, mechanical vibrations generated by nearby blasting operations on a residential home. The goal was to determine the fundamental natural frequencies of the measured structure; therefore it is important to determine the resonant frequencies to design a suitable modal damping. The article also analyzes the package of seismic waves generated by blasting (Primary waves – P-waves and Secondary waves S-waves) and investigated the transfer regions. For the detection of seismic waves resulting from an explosion, the Fast Fourier Transform (FFT) and modal analysis, in the frequency domain, is used and the signal was acquired and analyzed also in the time domain. In the conclusions the measured results of seismic waves caused by blasting in a nearby quarry and its effect on a nearby structure (house) is analyzed. The response on the house, including the fundamental natural frequency and possible fatigue damage is also assessed.

Keywords: building structure, seismic waves, spectral analysis, structural response

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Authors: Zonglin Yang, Tatsuya Akiyama, Kerry S. Williamson, Michael J. Franklin, Thiruvarangan Ramaraj

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Pseudomonas aeruginosa is an opportunistic pathogen that forms surface-associated microbial communities (biofilms) on artificial implant devices and on human tissue. Biofilm infections are difficult to treat with antibiotics, in part, because the bacteria in biofilms are physiologically heterogeneous. One measure of biological heterogeneity in a population of cells is to quantify the cellular concentrations of ribosomes, which can be probed with fluorescently labeled nucleic acids. The fluorescent signal intensity following fluorescence in situ hybridization (FISH) analysis correlates to the cellular level of ribosomes. The goals here are to provide computationally and statistically robust approaches to automatically quantify cellular heterogeneity in biofilms from a large library of epifluorescent microscopy FISH images. In this work, the initial steps were developed toward these goals by developing an automated biofilm detection approach for use with FISH images. The approach allows rapid identification of biofilm regions from FISH images that are counterstained with fluorescent dyes. This methodology provides advances over other computational methods, allowing subtraction of spurious signals and non-biological fluorescent substrata. This method will be a robust and user-friendly approach which will enable users to semi-automatically detect biofilm boundaries and extract intensity values from fluorescent images for quantitative analysis of biofilm heterogeneity.

Keywords: image informatics, Pseudomonas aeruginosa, biofilm, FISH, computer vision, data visualization

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Authors: Seyedeh Fatemeh Nabavi, Hamid Dalir, Anooshiravan Farshidianfar

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Laser welding is pivotal in modern manufacturing, offering unmatched precision, speed, and efficiency. Its versatility in minimizing heat-affected zones, seamlessly joining dissimilar materials, and working with various metals makes it indispensable for crafting intricate automotive components. Integration into automated systems ensures consistent delivery of high-quality welds, thereby enhancing overall production efficiency. Noteworthy are the safety benefits of laser welding, including reduced fumes and consumable materials, which align with industry standards and environmental sustainability goals. As the automotive sector increasingly demands advanced materials and stringent safety and quality standards, laser welding emerges as a cornerstone technology. A comprehensive model encompassing thermal dynamic and characteristics models accurately predicts geometrical, metallurgical, and mechanical aspects of the laser beam welding process. Notably, Model 2 showcases exceptional accuracy, achieving remarkably low error rates in predicting primary and secondary dendrite arm spacing (PDAS and SDAS). These findings underscore the model's reliability and effectiveness, providing invaluable insights and predictive capabilities crucial for optimizing welding processes and ensuring superior productivity, efficiency, and quality in the automotive industry.

Keywords: laser welding process, geometrical characteristics, mechanical characteristics, metallurgical characteristics, comprehensive model, thermal dynamic

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Authors: Toshifumi Hiramatsu, Satoshi Morita, Manuel Pencelli, Marta Niccolini, Matteo Ragaglia, Alfredo Argiolas

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Automation technologies for agriculture field are needed to promote labor-saving. One of the most relevant problems in automated agriculture is represented by controlling the robot along a predetermined path in presence of rough terrain or incline ground. Unfortunately, disturbances originating from interaction with the ground, such as slipping, make it quite difficult to achieve the required accuracy. In general, it is required to move within 5-10 cm accuracy with respect to the predetermined path. Moreover, lateral velocity caused by gravity on the incline field also affects slipping. In this paper, a path-tracking controller for tracked mobile robots moving on rough terrains of incline field such as vineyard is presented. The controller is composed of a disturbance observer and an adaptive controller based on the kinematic model of the robot. The disturbance observer measures the difference between the measured and the reference yaw rate and linear velocity in order to estimate slip. Then, the adaptive controller adapts “virtual” parameter of the kinematics model: Instantaneous Centers of Rotation (ICRs). Finally, target angular velocity reference is computed according to the adapted parameter. This solution allows estimating the effects of slip without making the model too complex. Finally, the effectiveness of the proposed solution is tested in a simulation environment.

Keywords: the agricultural robot, autonomous control, path-tracking control, tracked mobile robot

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Authors: Philipp Zopf, Franz Haas

Abstract:

Manufacturing of very hard and refractory materials like ceramics, glass or carbide poses particular challenges on tools and machines. The company Sauer GmbH developed especially for this application area ultrasonic tool holders working in a frequency range from 15 to 60 kHz and superimpose the common tool movement in the vertical axis. This technique causes a structural weakening in the contact area and facilitates the machining. The possibility of the force reduction for these special materials especially in drilling of carbide with diamond tools up to 30 percent made the authors try to expand the application range of this method. To make the results evaluable, the authors decide to start with existing processes in which the positive influence of the ultrasonic assistance is proven to understand the mechanism. The comparison of a grinding process the Institute use to machine materials mentioned in the beginning and steel could not be more different. In the first case, the authors use tools with geometrically undefined edges. In the second case, the edges are geometrically defined. To get valid results of the tests, the authors decide to investigate two manufacturing methods, drilling and milling. The main target of the investigation is to reduce the cutting force measured with a force measurement platform underneath the workpiece. Concerning to the direction of the ultrasonic assistance, the authors expect lower cutting forces and longer endurance of the tool in the drilling process. To verify the frequencies and the amplitudes an FFT-analysis is performed. It shows the increasing damping depending on the infeed rate of the tool. The reducing of amplitude of the cutting force comes along.

Keywords: drilling, machining, milling, ultrasonic

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Authors: Nabila Mohamed, Santiago Aparicio, Bahman Tohidi, Mert Atilhan

Abstract:

Qatar's one of the biggest problem in processing its natural resource, which is natural gas, is the often occurring blockage in the pipelines caused due to uncontrolled gas hydrate formation in the pipelines. Several millions of dollars are being spent at the process site to dehydrate the blockage safely by using chemical inhibitors. We aim to establish national database, which addresses the physical conditions that promotes Qatari natural gas to form gas hydrates in the pipelines. Moreover, we aim to design and test novel hydrate inhibitors that are suitable for Qatari natural gas and its processing facilities. From these perspectives we are aiming to provide more effective and sustainable reservoir utilization and processing of Qatari natural gas. In this work, we present the initial findings of a QNRF funded project, which deals with the natural gas hydrate formation characteristics of Qatari type gas in both experimental (PVTx) and computational (molecular simulations) methods. We present the data from the two fully automated apparatus: a gas hydrate autoclave and a rocking cell. Hydrate equilibrium curves including growth/dissociation conditions for multi-component systems for several gas mixtures that represent Qatari type natural gas with and without the presence of well known kinetic and thermodynamic hydrate inhibitors. Ionic liquids were designed and used for testing their inhibition performance and their DFT and molecular modeling simulation results were also obtained and compared with the experimental results. Results showed significant performance of ionic liquids with up to 0.5 % in volume with up to 2 to 4 0C inhibition at high pressures.

Keywords: gas hydrates, natural gas, ionic liquids, inhibition, thermodynamic inhibitors, kinetic inhibitors

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Authors: Devadrita Dey Sarkar

Abstract:

Regardless of the many technologic advances in the past decade, increased training and experience, and the obvious benefits of uniform standards, the false-negative rate in screening mammography remains unacceptably high .A computer aided neural network classification of regions of suspicion (ROS) on digitized mammograms is presented in this abstract which employs features extracted by a new technique based on independent component analysis. CAD is a concept established by taking into account equally the roles of physicians and computers, whereas automated computer diagnosis is a concept based on computer algorithms only. With CAD, the performance by computers does not have to be comparable to or better than that by physicians, but needs to be complementary to that by physicians. In fact, a large number of CAD systems have been employed for assisting physicians in the early detection of breast cancers on mammograms. A CAD scheme that makes use of lateral breast images has the potential to improve the overall performance in the detection of breast lumps. Because breast lumps can be detected reliably by computer on lateral breast mammographs, radiologists’ accuracy in the detection of breast lumps would be improved by the use of CAD, and thus early diagnosis of breast cancer would become possible. In the future, many CAD schemes could be assembled as packages and implemented as a part of PACS. For example, the package for breast CAD may include the computerized detection of breast nodules, as well as the computerized classification of benign and malignant nodules. In order to assist in the differential diagnosis, it would be possible to search for and retrieve images (or lesions) with these CAD systems, which would be reliable and useful method for quantifying the similarity of a pair of images for visual comparison by radiologists.

Keywords: CAD(computer-aided design), lesions, neural network, ROS(region of suspicion)

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Authors: Anja Gräff, Stefan Holzer, Manfred Höld, Jörn Stumpenhausen, Heinz Bernhardt

Abstract:

In view of the increasing quantity of 'green energy' from renewable raw materials and photovoltaic facilities, it is quite conceivable that power supply variations may occur, so that constantly working machines like automatic milking systems (AMS) may break down temporarily. The usage of farm-made energy is steadily increasing in order to keep energy costs as low as possible. As a result, power cuts are likely to happen more frequently. Current work in the framework of the project 'stable 4.0' focuses on possible stress reactions by simulating power cuts up to four hours in dairy farms. Based on heart activity it should be found out whether stress on dairy cows increases under these circumstances. In order to simulate a power cut, 12 random cows out of 2 herds were not admitted to the AMS for at least two hours on three consecutive days. The heart rates of the cows were measured and the collected data evaluated with HRV Program Kubios Version 2.1 on the basis of eight parameters (HR, RMSSD, pNN50, SD1, SD2, LF, HF and LF/HF). Furthermore, stress reactions were examined closely via video analysis, milk yield, ruminant activity, pedometer and measurements of cortisol metabolites. Concluding it turned out, that during the test only some animals were suffering from minor stress symptoms, when they tried to get into the AMS at their regular milking time, but couldn´t be milked because the system was manipulated. However, the stress level during a regular “time-dependent milking rejection” was just as high. So the study comes to the conclusion, that the low psychological stress level in the case of a 2-4 hours failure of an AMS does not have any impact on animal welfare and health.

Keywords: dairy cow, heart activity, power cut, stable 4.0

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Authors: M. Gerasimou, S. Mantzoukis, P. Christodoulou, N. Varsamis, G. Kolliopoulou, N. Zotos

Abstract:

Purpose: Microbial infection of the blood is a serious condition where bacteria invade the bloodstream and cause systemic disease. In such cases, blood cultures are performed. Blood cultures are a key diagnostic test for intensive care unit (ICU) patients. Material and method: The BacT/Alert system, which measures the production of carbon dioxide with metabolic organisms, is used. The positive result in the BacT/Alert system is followed by culture in the following selective media: Blood, Mac Conkey No 2, Chocolate, Mueller Hinton, Chapman and Sabaureaud agar. Gram staining method was used to differentiate bacterial species. The microorganisms were identified by biochemical techniques in the automated Microscan (Siemens) system and followed by a sensitivity test on the same system using the minimum inhibitory concentration MIC technique. The sensitivity test is verified by a Kirby Bauer-based test. Results: In 2017 the Laboratory of Microbiology received 3347 blood cultures. Of these, 170 came from the ICU. 116 found positive. Of these S. epidermidis was identified in 42, A. baumannii in 27, K. pneumoniae in 12 (4 of these KPC ‘Klebsiella pneumoniae carbapenemase’), S. hominis in 8, E. faecium in 7, E. faecalis in 5, P. aeruginosa in 3, C. albicans in 3, S. capitis in 2, K. oxytoca in 2, P. mirabilis in 2, E. coli in 1, S. intermidius in 1 and S. lugdunensis in 1. Conclusions: The study of epidemiological data and microbial resistance phenotypes is essential for the choice of therapeutic regimen for the early treatment and limitation of multivalent strains, while it is a crucial factor to solve diagnostic problems.

Keywords: blood culture, bloodstream, infection, intensive care unit

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Authors: Jun-Ki Choi

Abstract:

The usage of valuable resources and the potential for waste generation at the end of the life cycle of photovoltaic (PV) technologies necessitate a proactive planning for a PV recycling infrastructure. To ensure the sustainability of PV in large scales of deployment, it is vital to develop and institute low-cost recycling technologies and infrastructure for the emerging PV industry in parallel with the rapid commercialization of these new technologies. There are various issues involved in the economics of PV recycling and this research examine those at macro and micro levels, developing a holistic interpretation of the economic viability of the PV recycling systems. This study developed mathematical models to analyze the profitability of recycling technologies and to guide tactical decisions for allocating optimal location of PV take-back centers (PVTBC), necessary for the collection of end of life products. The economic decision is usually based on the level of the marginal capital cost of each PVTBC, cost of reverse logistics, distance traveled, and the amount of PV waste collected from various locations. Results illustrated that the reverse logistics costs comprise a major portion of the cost of PVTBC; PV recycling centers can be constructed in the optimally selected locations to minimize the total reverse logistics cost for transporting the PV wastes from various collection facilities to the recycling center. In the micro- process level, automated recycling processes should be developed to handle the large amount of growing PV wastes economically. The market price of the reclaimed materials are important factors for deciding the profitability of the recycling process and this illustrates the importance of the recovering the glass and expensive metals from PV modules.

Keywords: photovoltaic, recycling, mathematical models, sustainability

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Authors: Mehrnoosh Abouzari, Shahrokh Shahraei

Abstract:

With the development of artificial intelligence in the present age, intelligent machines and systems have proven their actual and potential capabilities and are mindful of increasing their presence in various fields of human life in the fields of industry, financial transactions, marketing, manufacturing, service affairs, politics, economics and various branches of the humanities .Therefore, despite the conservatism and prudence of law enforcement, the traces of artificial intelligence can be seen in various areas of law. Including judicial robotics capability estimation, intelligent judicial decision making system, intelligent defender and attorney strategy adjustment, dissemination and regulation of different and scattered laws in each case to achieve judicial coherence and reduce opinion, reduce prolonged hearing and discontent compared to the current legal system with designing rule-based systems, case-based, knowledge-based systems, etc. are efforts to apply AI in law. In this article, we will identify the ways in which AI is applied in its laws and regulations, identify the dominant concerns in this area and outline the relationship between these two areas in order to answer the question of how artificial intelligence can be used in different areas of law and what the implications of this application will be. The authors believe that the use of artificial intelligence in the three areas of legislative, judiciary and executive power can be very effective in governments' decisions and smart governance, and helping to reach smart communities across human and geographical boundaries that humanity's long-held dream of achieving is a global village free of violence and personalization and human error. Therefore, in this article, we are going to analyze the dimensions of how to use artificial intelligence in the three legislative, judicial and executive branches of government in order to realize its application.

Keywords: artificial intelligence, law, intelligent system, judge

Procedia PDF Downloads 91