Search results for: accident database

Authors: Mumtaz Begum Mustafa, Siti Salwah Salim, Feizal Dani Rahman

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Recently, Automatic Speech Recognition (ASR) systems were used to assist children in language acquisition as it has the ability to detect human speech signal. Despite the benefits offered by the ASR system, there is a lack of ASR systems for Malay-speaking children. One of the contributing factors for this is the lack of continuous speech database for the target users. Though cross-lingual adaptation is a common solution for developing ASR systems for under-resourced language, it is not viable for children as there are very limited speech databases as a source model. In this research, we propose a two-stage adaptation for the development of ASR system for Malay-speaking children using a very limited database. The two stage adaptation comprises the cross-lingual adaptation (first stage) and cross-age adaptation. For the first stage, a well-known speech database that is phonetically rich and balanced, is adapted to the medium-sized Malay adults using supervised MLLR. The second stage adaptation uses the speech acoustic model generated from the first adaptation, and the target database is a small-sized database of the target users. We have measured the performance of the proposed technique using word error rate, and then compare them with the conventional benchmark adaptation. The two stage adaptation proposed in this research has better recognition accuracy as compared to the benchmark adaptation in recognizing children’s speech.

Keywords: Automatic Speech Recognition System, children speech, adaptation, Malay

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Authors: W. A. Gonçalves, E. P. Souza, C. R. Alcântara

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The ISCCP-Tracking database offers an opportunity to study physical and morphological characteristics of Convective Systems based on geostationary meteorological satellites. This database contains 26 years of tracking of Convective Systems for the entire globe. Then, Tropical Squall Lines which occur in Brazil are certainly within the database. In this study, we propose a methodology for identification of these systems based on the ISCCP-Tracking database. A physical and morphological characterization of these systems is also shown. The proposed methodology is firstly based on the year of 2007. The Squall Lines were subjectively identified by visually analyzing infrared images from GOES-12. Based on this identification, the same systems were identified within the ISCCP-Tracking database. It is known, and it was also observed that the Squall Lines which occur on the north coast of Brazil develop parallel to the coast, influenced by the sea breeze. In addition, it was also observed that the eccentricity of the identified systems was greater than 0.7. Then, a methodology based on the inclination (based on the coast) and eccentricity (greater than 0.7) of the Convective Systems was applied in order to identify and characterize Tropical Squall Lines in Brazil. These thresholds were applied back in the ISCCP-Tracking database for the year of 2007. It was observed that other systems, which were not Squall Lines, were also identified. Then, we decided to call all systems identified by the inclination and eccentricity thresholds as Linear Convective Systems, instead of Squall Lines. After this step, the Linear Convective Systems were identified and characterized for the entire database, from 1983 to 2008. The physical and morphological characteristics of these systems were compared to those systems which did not have the required inclination and eccentricity to be called Linear Convective Systems. The results showed that the convection associated with the Linear Convective Systems seems to be more intense and organized than in the other systems. This affirmation is based on all ISCCP-Tracking variables analyzed. This type of methodology, which explores 26 years of satellite data by an objective analysis, was not previously explored in the literature. The physical and morphological characterization of the Linear Convective Systems based on 26 years of data is of a great importance and should be used in many branches of atmospheric sciences.

Keywords: squall lines, convective systems, linear convective systems, ISCCP-Tracking

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Authors: M. Belén Prendes-Gero, Celestino González-Nicieza, M. Inmaculada Alvarez-Fernández

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Roof collapse is one of the problems with a higher frequency in most of the mines of all countries, even now. There are many reasons that may cause the roof to collapse, namely the mine stress activities in the mining process, the lack of vigilance and carelessness or the complexity of the geological structure and irregular operations. This work is the result of the analysis of one accident produced in the “Mary” coal exploitation located in northern Spain. In this accident, the roof of a crossroad of excavated galleries to exploit the “Morena” Layer, 700 m deep, collapsed. In the paper, the work done by the forensic team to determine the causes of the incident, its conclusions and recommendations are collected. Initially, the available documentation (geology, geotechnics, mining, etc.) and accident area were reviewed. After that, laboratory and on-site tests were carried out to characterize the behaviour of the rock materials and the support used (metal frames and shotcrete). With this information, different hypotheses of failure were simulated to find the one that best fits reality. For this work, the software of finite differences in three dimensions, FLAC 3D, was employed. The results of the study confirmed that the detachment was originated as a consequence of one sliding in the layer wall, due to the large roof span present in the place of the accident, and probably triggered as a consequence of the existence of a protection pillar insufficient. The results allowed to establish some corrective measures avoiding future risks. For example, the dimensions of the protection zones that must be remained unexploited and their interaction with the crossing areas between galleries, or the use of more adequate supports for these conditions, in which the significant deformations may discourage the use of rigid supports such as shotcrete. At last, a grid of seismic control was proposed as a predictive system. Its efficiency was tested along the investigation period employing three control equipment that detected new incidents (although smaller) in other similar areas of the mine. These new incidents show that the use of explosives produces vibrations which are a new risk factor to analyse in a next future.

Keywords: forensic analysis, hypothesis modelling, roof failure, seismic monitoring

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Authors: Satoshi Furukawa, Satomu Morita, Katsuji Nishi, Masahito Hitosugi

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Coronary artery dissection leading to acute myocardial infarction after blunt chest trauma is extremely rare. A 67-year-old woman suffered blunt chest trauma following a traffic accident. The electrocardiogram revealed acute posterior ST-segment elevation and myocardial infarction and coronary angiography demonstrated acute right coronary artery dissection. Following the death of the victim an autopsy was performed after cardiopulmonary support had been carried out. In this case report, we describe the case of a woman with blunt chest trauma, who developed an acute myocardial infarction secondary to right coronary artery dissection. Although there was additional the blunt chest trauma due to chest compression, we confirmed the injury at autopsy and by histological findings.

Keywords: blunt chest trauma, right coronary artery dissection, coronary angiography, autopsy, histological examination

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Authors: Hamed Nafar, Sajad Rezaei, Hamid Behbahani

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Safety analysis of the roads through the accident rates which is one of the widely used tools has been resulted from the direct exposure method which is based on the ratio of the vehicle-kilometers traveled and vehicle-travel time. However, due to some fundamental flaws in its theories and difficulties in gaining access to the data required such as traffic volume, distance and duration of the trip, and various problems in determining the exposure in a specific time, place, and individual categories, there is a need for an algorithm for prioritizing the road safety so that with a new exposure method, the problems of the previous approaches would be resolved. In this way, an efficient application may lead to have more realistic comparisons and the new method would be applicable to a wider range of time, place, and individual categories. Therefore, an algorithm was introduced to prioritize the safety of roads using the quasi-induced exposure method and utilizing the analytical hierarchy process. For this research, 11 provinces of Iran were chosen as case study locations. A rural accidents database was created for these provinces, the validity of quasi-induced exposure method for Iran’s accidents database was explored, and the involvement ratio for different characteristics of the drivers and the vehicles was measured. Results showed that the quasi-induced exposure method was valid in determining the real exposure in the provinces under study. Results also showed a significant difference in the prioritization based on the new and traditional approaches. This difference mostly would stem from the perspective of the quasi-induced exposure method in determining the exposure, opinion of experts, and the quantity of accidents data. Overall, the results for this research showed that prioritization based on the new approach is more comprehensive and reliable compared to the prioritization in the traditional approach which is dependent on various parameters including the driver-vehicle characteristics.

Keywords: road safety, prioritizing, Quasi-induced exposure, Analytical Hierarchy Process

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Authors: Fatima Akhmedova, Simon Liao

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One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work, we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due to their invariance, non-redundancy and the ability to extract features either globally and locally. To assess the applicability of Hahn moments to Face Recognition we conduct two experiments on the Olivetti Research Laboratory (ORL) database and University of Notre-Dame (UND) X1 biometric collection. Fusion of the global features along with the features from local facial regions are used as an input for the conventional k-NN classifier. The method reaches an accuracy of 93% of correctly recognized subjects for the ORL database and 94% for the UND database.

Keywords: face recognition, Hahn moments, recognition-by-parts, time-lapse

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Authors: Peris Wanjiku

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The objective of this paper is to describe the development and implications of a national nursing workforce analytical system in Kenya. Findings: Creating a national electronic nursing workforce analytical system provides more reliable information on nurses ‘national demographics, migration patterns, and workforce capacity and efficiency. Data analysis is most useful for human resources for health (HRH) planning when workforce capacity data can be linked to worksite staffing requirements. As a result of establishing this database, the Kenya Ministry of Health has improved its capability to assess its nursing workforce and document important workforce trends, such as out-migration. Current data identify the United States as the leading recipient country of Kenyan nurses. The overwhelming majority of Kenyan nurses who decide to out-migrate are amongst Kenya’s most qualified. Conclusions: The Kenya nursing database is a first step toward facilitating evidence-based decision-making in HRH. This database is unique to developing countries in sub-Saharan Africa. Establishing an electronic workforce database requires long-term investment and sustained support by national and global stakeholders.

Keywords: analytical, information, health, migration

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Authors: Iftikhar A. Tayubi, Tabrej Khan, Mansoor M. Alsubei, Fahad A. Alsaferi

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LIZTOXD provides a single source of high-quality information about proteinaceous lizard toxins that will be an invaluable resource for pharmacologists, neuroscientists, toxicologists, medicinal chemists, ion channel scientists, clinicians, and structural biologists. We will provide an intuitive, well-organized and user-friendly web interface that allows users to explore the detail information of Lizard and toxin proteins. It includes common name, scientific name, entry id, entry name, protein name and length of the protein sequence. The utility of this database is that it can provide a user-friendly interface for users to retrieve the information about Lizard, toxin and toxin protein of different Lizard species. These interfaces created in this database will satisfy the demands of the scientific community by providing in-depth knowledge about Lizard and its toxin. In the next phase of our project we will adopt methodology and by using A MySQL and Hypertext Preprocessor (PHP) which and for designing Smart Draw. A database is a wonderful piece of equipment for storing large quantities of data efficiently. The users can thus navigate from one section to another, depending on the field of interest of the user. This database contains a wealth of information on species, toxins, toxins, clinical data etc. LIZTOXD resource that provides comprehensive information about protein toxins from lizard toxins. The combination of specific classification schemes and a rich user interface allows researchers to easily locate and view information on the sequence, structure, and biological activity of these toxins. This manually curated database will be a valuable resource for both basic researchers as well as those interested in potential pharmaceutical and agricultural applications of lizard toxins.

Keywords: LIZTOXD, MySQL, PHP, smart draw

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Authors: Ivana Kašparová, Emilie Pecharová

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The experience of radiological contamination of land, especially after the Chernobyl and Fukushima disasters have shown the need to explore possibilities to the capture of radionuclides in the area affected and to adapt the landscape management to this purpose ex –ante the considered accident in terms of prevention. The project‚ Minimizing the impact of radiation contamination on land in the emergency zone of Temelin NPP‘ (2012-2015), dealt with the possibility of utilization of wetlands as retention sites for water carrying radionuclides in the case of a radiation accident. A model artificial wetland was designed and adopted as a utility model by the Ministry of Industry and Trade of the Czech Republic. The article shows the conditions of construction of designed wetlands in the landscape with regard to minimizing the negative effect on agricultural production and enhancing the hydrological functionality of the landscape.

Keywords: artificial wetland, land use/ land cover, old maps, surface-to-water transport of radionuclides

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Authors: Romeo Botes, Imelda Smit

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In today’s modern age of technology vast amounts of data needs to be processed in real-time to keep users satisfied. This data comes from various sources and in many formats, including electronic and mobile devices such as GPRS modems and GPS devices. They make use of different protocols including TCP, UDP, and HTTP/s for data communication to web servers and eventually to users. The data obtained from these devices may provide valuable information to users, but are mostly in an unreadable format which needs to be processed to provide information and business intelligence. This data is not always current, it is mostly historical data. The data is not subject to implementation of consistency and redundancy measures as most other data usually is. Most important to the users is that the data are to be pre-processed in a readable format when it is entered into the database. To accomplish this, programmers build processing programs and scripts to decode and process the information stored in databases. Programmers make use of various techniques in such programs to accomplish this, but sometimes neglect the effect some of these techniques may have on database performance. One of the techniques generally used,is to pull data from the database server, process it and push it back to the database server in one single step. Since the processing of the data usually takes some time, it keeps the database busy and locked for the period of time that the processing takes place. Because of this, it decreases the overall performance of the database server and therefore the system’s performance. This paper follows on a paper discussing the performance increase that may be achieved by utilizing array lists along with a pull-process-push data processing technique split in three steps. The purpose of this paper is to expand the number of clients when comparing the two techniques to establish the impact it may have on performance of the CPU storage and processing time.

Keywords: performance measures, algorithm techniques, data processing, push data, process data, array list

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Authors: Natalia Ortega

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Safety Culture (SCU) involves various perceptual, psychological, behavioral, and managerial factors. It has been shown that creating and maintaining an SCU is one way to reduce and prevent accidents and fatalities. In the construction sector, safety attitude, knowledge, and a supportive environment are predictors of safety behavior. The highest possible proportion of safety behavior among employees can be achieved by improving their safety attitude and knowledge. Accordingly, top management's commitment to safety is vital in shaping employees' safety attitude; therefore, the first step to improving employees' safety attitude is the genuine commitment of top management to safety. One of the factors affecting the successful implementation of health and safety promotion programs is the construction industry's subcontracting model. The contractual model's complexity, combined with the need for coordination among diverse stakeholders, makes it challenging to implement, manage, and follow up on health and well-being initiatives. The Systems theoretic accident model and process (STAMP) concept has expanded global consideration in recent years, increasing research attention. STAMP focuses attention on the role of constraints in safety management. The findings discover a growth of the research field from the definition in 2004 by Leveson and is being used across multiple domains. A systematic literature review of this novel model aims to meet the safety goals for human space exploration with a powerful and different approach to safety management, safety-driven design, and decision-making. Around two hundred studies have been published about applying the model. However, every single model for safety requires time to transform into research and practice, be tested and debated, and grow further and mature.

Keywords: stamp, risk management, accident prevention, safety culture, systems thinking, construction industry, safety

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Authors: Chhaya Gangwal, R. N. Bhaumik, Shishir Kumar

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Handling uncertainty and impreciseness of knowledge appears to be a challenging task in Information Systems. Intuitionistic fuzzy (IF) and rough set theory enhances databases by allowing it for the management of uncertainty and impreciseness. This paper presents a new efficient query optimization technique for the multi-valued or imprecise IF rough database. The usefulness of this technique was illustrated on malaria knowledge from the rural tribal communities of Tripura where most of the information is multi-valued and imprecise. Then, the querying about knowledge on malaria is executed into SQL server to make the implementation of IF rough data querying simpler.

Keywords: intuitionistic fuzzy set, rough set, relational database, IF rough relational database

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Authors: Hung Lin-Zin, Lai Mei-Yen

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Prostate cancer is the most commonly diagnosed male cancer in the U.S. The prevalence is around 1 in 8. The etiology of prostate cancer is still unknown, but some predisposing factors, such as age, black race, family history, and obesity, may increase the risk of the disease. In 2020, a total of 7,178 Taiwanese people were nearly diagnosed with prostate cancer, accounting for 5.88% of all cancer cases, and the incidence rate ranked fifth among men. In that year, the total number of deaths from prostate cancer was 1,730, accounting for 3.45% of all cancer deaths, and the death rate ranked 6th among men, accounting for 94.34% of the cases of male reproductive organs. Looking for domestic and foreign literature on the use of OMOP (Observational Medical Outcomes Partnership, hereinafter referred to as OMOP) database analysis, there are currently nearly a hundred literature published related to nursing-related health problems and nursing measures built in the OMOP general data model database of medical institutions are extremely rare. The OMOP common data model construction analysis platform is a system developed by the FDA in 2007, using a common data model (common data model, CDM) to analyze and monitor healthcare data. It is important to build up relevant nursing information from the OMOP- CDM database to assist our daily practice. Therefore, we choose prostate cancer patients who are our popular care objects and use the OMOP- CDM database to explore the common associated health problems. With the assistance of OMOP-CDM database analysis, we can expect early diagnosis and prevention of prostate cancer patients' comorbidities to improve patient care.

Keywords: OMOP, nursing diagnosis, health problem, prostate cancer

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Authors: Andressa dos Santos Nicolau, João P. da S.C Algusto, Claudio Márcio do N. A. Pereira, Roberto Schirru

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In case of abnormal situations, the nuclear power plant (NPP) operators must follow written procedures to check the condition of the plant and to classify the type of emergency. In this paper, we proposed a Real Time Expert System in order to improve operator’s performance in case of transient or accident with reactor shutdown. The expert system’s knowledge is based on the sequence of events (SoE) of known accident and two emergency procedures of the Brazilian Pressurized Water Reactor (PWR) NPP and uses two kinds of knowledge representation: rule and logic trees. The results show that the system was able to classify the response of the automatic protection systems, as well as to evaluate the conditions of the plant, diagnosing the type of occurrence, recovery procedure to be followed, indicating the shutdown root cause, and classifying the emergency level.

Keywords: emergence procedure, expert system, operator support, PWR nuclear power plant

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Authors: Wing Kam Fung, Kexin Yu

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Child trafficking has been a serious problem in modern China. The Chinese government has established a national anti-trafficking DNA database to help reunite missing children with their families. The database collects DNA information from missing children's parents, trafficked and homeless children, then conducts paternity tests to find matched pairs. This paper considers the matching accuracy in such cases by looking into the exclusion probability in paternity testing. First, the situation of child trafficking in China is introduced. Next, derivations of the exclusion probability for both one-parent and two-parents cases are given, followed by extension to allow for 1 or 2 mutations. The accuracy of paternity testing of child trafficking cases is then assessed using the exclusion probabilities and available data. Finally, the number of loci that should be used to ensure a correct match is investigated.

Keywords: child trafficking, DNA database, exclusion probability, paternity testing

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Authors: Tetyana Baydyk, Ernst Kussul, Sandra Bonilla Meza

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There are many articles that attempt to establish the role of different facial fragments in face recognition. Various approaches are used to estimate this role. Frequently, authors calculate the entropy corresponding to the fragment. This approach can only give approximate estimation. In this paper, we propose to use a more direct measure of the importance of different fragments for face recognition. We propose to select a recognition method and a face database and experimentally investigate the recognition rate using different fragments of faces. We present two such experiments in the paper. We selected the PCNC neural classifier as a method for face recognition and parts of the LFW (Labeled Faces in the Wild) face database as training and testing sets. The recognition rate of the best experiment is comparable with the recognition rate obtained using the whole face.

Keywords: face recognition, labeled faces in the wild (LFW) database, random local descriptor (RLD), random features

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Authors: Simon Arunga, Teddy Kwaga, Rita Kageni, Michael Gichangi, Nyawira Mwangi, Fred Kagwa, Rogers Mwavu, Amos Baryashaba, Luis F. Nakayama, Katharine Morley, Michael Morley, Leo A. Celi, Jessica Haberer, Celestino Obua

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Purpose: The main aim for creating the Multimodal Database of Retinal Images for Africa (MoDRIA) was to provide a publicly available repository of retinal images for responsible researchers to conduct algorithm development in a bid to curb the challenges of ophthalmic artificial intelligence (AI) in Africa. Methods: Data and retina images were ethically sourced from sites in Uganda and Kenya. Data on medical history, visual acuity, ocular examination, blood pressure, and blood sugar were collected. Retina images were captured using fundus cameras (Foru3-nethra and Canon CR-Mark-1). Images were stored on a secure online database. Results: The database consists of 7,859 retinal images in portable network graphics format from 1,988 participants. Images from patients with human immunodeficiency virus were 18.9%, 18.2% of images were from hypertensive patients, 12.8% from diabetic patients, and the rest from normal’ participants. Conclusion: Publicly available data repositories are a valuable asset in the development of AI technology. Therefore, is a need for the expansion of MoDRIA so as to provide larger datasets that are more representative of Sub-Saharan data.

Keywords: retina images, MoDRIA, image repository, African database

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Authors: Moohyun Lee, Soojung Hur, Yongwan Park

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In this paper is proposed a method uses only LIDAR system to classification an obstacle and determine its type by establishing database for classifying obstacles based on LIDAR. The existing LIDAR system, in determining the recognition of obstruction in an autonomous vehicle, has an advantage in terms of accuracy and shorter recognition time. However, it was difficult to determine the type of obstacle and therefore accurate path planning based on the type of obstacle was not possible. In order to overcome this problem, a method of classifying obstacle type based on existing LIDAR and using the width of obstacle materials was proposed. However, width measurement was not sufficient to improve accuracy. In this research, the width data was used to do the first classification; database for LIDAR intensity data by four major obstacle materials on the road were created; comparison is made to the LIDAR intensity data of actual obstacle materials; and determine the obstacle type by finding the one with highest similarity values. An experiment using an actual autonomous vehicle under real environment shows that data declined in quality in comparison to 3D LIDAR and it was possible to classify obstacle materials using 2D LIDAR.

Keywords: obstacle, classification, database, LIDAR, segmentation, intensity

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Authors: D. S. Gomes, A. T. Silva

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Analysis of the uncertainty quantification related to nuclear safety margins applied to the nuclear reactor is an important concept to prevent future radioactive accidents. The nuclear fuel performance code may involve the tolerance level determined by traditional deterministic models producing acceptable results at burn cycles under 62 GWd/MTU. The behavior of nuclear fuel can simulate applying a series of material properties under irradiation and physics models to calculate the safety limits. In this study, theoretical predictions of nuclear fuel failure under transient conditions investigate extended radiation cycles at 75 GWd/MTU, considering the behavior of fuel rods in light-water reactors under reactivity accident conditions. The fuel pellet can melt due to the quick increase of reactivity during a transient. Large power excursions in the reactor are the subject of interest bringing to a treatment that is known as the Fuchs-Hansen model. The point kinetic neutron equations show similar characteristics of non-linear differential equations. In this investigation, the multivariate logistic regression is employed to a probabilistic forecast of fuel failure. A comparison of computational simulation and experimental results was acceptable. The experiments carried out use the pre-irradiated fuels rods subjected to a rapid energy pulse which exhibits the same behavior during a nuclear accident. The propagation of uncertainty utilizes the Wilk's formulation. The variables chosen as essential to failure prediction were the fuel burnup, the applied peak power, the pulse width, the oxidation layer thickness, and the cladding type.

Keywords: logistic regression, reactivity-initiated accident, safety margins, uncertainty propagation

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Authors: Bagul Abhijeet

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Background: Client-Server model is the backbone of today’s internet communication. In which normal user can not have control over particular website or server? By using the same processing model one can have unauthorized access to particular server. In this paper, we discussed about application scenario of hacking for simple website or server consist of unauthorized way to access the server database. This application emerges to autonomously take direct access of simple website or server and retrieve all essential information maintain by administrator. In this system, IP address of server given as input to retrieve user-id and password of server. This leads to breaking administrative security of server and acquires the control of server database. Whereas virus helps to escape from server security by crashing the whole server. Objective: To control malicious attack and preventing all government website, and also find out illegal work to do hackers activity. Results: After implementing different hacking as well as non-hacking techniques, this system hacks simple web sites with normal security credentials. It provides access to server database and allow attacker to perform database operations from client machine. Above Figure shows the experimental result of this application upon different servers and provides satisfactory results as required. Conclusion: In this paper, we have presented a to view to hack the server which include some hacking as well as non-hacking methods. These algorithms and methods provide efficient way to hack server database. By breaking the network security allow to introduce new and better security framework. The terms “Hacking” not only consider for its illegal activities but also it should be use for strengthen our global network.

Keywords: Hacking, Vulnerabilities, Dummy request, Virus, Server monitoring

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Authors: Samuel Kaspi, Sitalakshmi Venkatraman

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In-memory database systems are becoming popular due to the availability and affordability of sufficiently large RAM and processors in modern high-end servers with the capacity to manage large in-memory database transactions. While fast and reliable in-memory systems are still being developed to overcome cache misses, CPU/IO bottlenecks and distributed transaction costs, disk-based data stores still serve as the primary persistence. In addition, with the recent growth in multi-tenancy cloud applications and associated security concerns, many organisations consider the trade-offs and continue to require fast and reliable transaction processing of disk-based database systems as an available choice. For these organizations, the only way of increasing throughput is by improving the performance of disk-based concurrency control. This warrants a hybrid database system with the ability to selectively apply an enhanced disk-based data management within the context of in-memory systems that would help improve overall throughput. The general view is that in-memory systems substantially outperform disk-based systems. We question this assumption and examine how a modified variation of access invariance that we call enhanced memory access, (EMA) can be used to allow very high levels of concurrency in the pre-fetching of data in disk-based systems. We demonstrate how this prefetching in disk-based systems can yield close to in-memory performance, which paves the way for improved hybrid database systems. This paper proposes a novel EMA technique and presents a comparative study between disk-based EMA systems and in-memory systems running on hardware configurations of equivalent power in terms of the number of processors and their speeds. The results of the experiments conducted clearly substantiate that when used in conjunction with all concurrency control mechanisms, EMA can increase the throughput of disk-based systems to levels quite close to those achieved by in-memory system. The promising results of this work show that enhanced disk-based systems facilitate in improving hybrid data management within the broader context of in-memory systems.

Keywords: in-memory database, disk-based system, hybrid database, concurrency control

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Authors: Manuela Nayantara Jeyaraj

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PostgreSQL is an Object-Relational Database Management System (ORDBMS) with an architecture that ensures optimal quality data management. But due to the shading growth of similar ORDBMS, PostgreSQL has not been renowned among the database user community. Despite having its features and in-built functionalities shadowed, PostgreSQL renders a vast range of utilities for data manipulation and hence calling for it to be upheld more among users. But introducing PostgreSQL in order to stimulate its advantageous features among users, mandates endorsing learn-ability as an add-on as the target groups considered consist of both amateur as well as professional PostgreSQL users. The scope of this paper deliberates providing easy contemplation of query formulations and flows through a visual editor designed according to user interface principles that standby to support every aspect of making PostgreSQL learn-able by self-operation and creation of queries within the visual editor. This paper tends to scrutinize the importance of choosing PostgreSQL as the working database environment, the visual perspectives that influence human behaviour and ultimately learning, the modes in which learn-ability can be provided via visualization and the advantages reaped by the implementation of the proposed system features.

Keywords: database, learn-ability, PostgreSQL, query, visual-editor

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Authors: U. Waqas, M. F. Ahmed, A. Mehmood, M. A. Rashid

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In geophysical exploration surveys, the quality of acquired data holds significant importance before executing the data processing and interpretation phases. In this study, 2D seismic reflection survey data of Fort Abbas area, Cholistan Desert, Pakistan was taken as test case in order to assess its quality on statistical bases by using normalized root mean square error (NRMSE), Cronbach’s alpha test (α) and null hypothesis tests (t-test and F-test). The analysis challenged the quality of the acquired data and highlighted the significant errors in the acquired database. It is proven that the study area is plain, tectonically least affected and rich in oil and gas reserves. However, subsurface 3D modeling and contouring by using acquired database revealed high degrees of structural complexities and intense folding. The NRMSE had highest percentage of residuals between the estimated and predicted cases. The outcomes of hypothesis testing also proved the biasness and erraticness of the acquired database. Low estimated value of alpha (α) in Cronbach’s alpha test confirmed poor reliability of acquired database. A very low quality of acquired database needs excessive static correction or in some cases, reacquisition of data is also suggested which is most of the time not feasible on economic grounds. The outcomes of this study could be used to assess the quality of large databases and to further utilize as a guideline to establish database quality assessment models to make much more informed decisions in hydrocarbon exploration field.

Keywords: Data quality, Null hypothesis, Seismic lines, Seismic reflection survey

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Authors: Nassim Salmi

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Postoperative mobilization is an important part of fundamental care. Increased mobilization has a positive effect on recovery, but immobilization is still a challenge in postoperative care. Aims: To report how the establishment of a national nursing database was used to measure postoperative mobilization in patients undergoing surgery for ovarian cancer. Mobilization was defined as at least 3 hours out of bed on postoperative day 1, with the goal set at achieving this in 60% of patients. Clinical nurses on 4400 patients with ovarian cancer performed data entry. Findings: 46.7% of patients met the goal for mobilization on the first postoperative day, but variations in duration and type of mobilization were observed. Of those mobilized, 51.8% had been walking in the hallway. A national nursing database creates opportunities to optimize fundamental care. By comparing nursing data with oncological, surgical, and pathology data, it became possible to study mobilization in relation to cancer stage, comorbidity, treatment, and extent of surgery.

Keywords: postoperative care, gynecology, nursing documentation, database

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Authors: Teja Koduru

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Untreated Lyme disease can lead to neurological, cardiac, and dermatological complications. Rapid diagnosis of the erythema migrans (EM) rash, a characteristic symptom of Lyme disease is therefore crucial to early diagnosis and treatment. In this study, we aim to utilize deep learning frameworks including Tensorflow and Keras to create deep convolutional neural networks (DCNN) to detect images of acute Lyme Disease from images of erythema migrans. This study uses a custom database of erythema migrans images of varying quality to train a DCNN capable of classifying images of EM rashes vs. non-EM rashes. Images from publicly available sources were mined to create an initial database. Machine-based removal of duplicate images was then performed, followed by a thorough examination of all images by a clinician. The resulting database was combined with images of confounding rashes and regular skin, resulting in a total of 683 images. This database was then used to create a DCNN with an accuracy of 93% when classifying images of rashes as EM vs. non EM. Finally, this model was converted into a web and mobile application to allow for rapid diagnosis of EM rashes by both patients and clinicians. This tool could be used for patient prescreening prior to treatment and lead to a lower mortality rate from Lyme disease.

Keywords: Lyme, untreated Lyme, erythema migrans rash, EM rash

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Authors: Nguyen Chi Quang, Nguyen Duong Tri Nguyen

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This article is the first step to research and outline the structure of the geotechnical database in the geological survey of a power project; in the context of this report creating the database that has been carried out for the Bac Ai pumped storage hydropower project. For the purpose of providing a method of organizing and storing geological and topographic survey data and experimental results in a spatial database, the RockWorks software is used to bring optimal efficiency in the process of exploiting, using, and analyzing data in service of the design work in the power engineering consulting. Three-dimensional (3D) geotechnical models are created from the survey data: such as stratigraphy, lithology, porosity, etc. The results of the 3D geotechnical model in the case of Bac Ai pumped storage hydropower project include six closely stacked stratigraphic formations by Horizons method, whereas modeling of engineering geological parameters is performed by geostatistical methods. The accuracy and reliability assessments are tested through error statistics, empirical evaluation, and expert methods. The three-dimensional model analysis allows better visualization of volumetric calculations, excavation and backfilling of the lake area, tunneling of power pipelines, and calculation of on-site construction material reserves. In general, the application of engineering geological modeling makes the design work more intuitive and comprehensive, helping construction designers better identify and offer the most optimal design solutions for the project. The database always ensures the update and synchronization, as well as enables 3D modeling of geological and topographic data to integrate with the designed data according to the building information modeling. This is also the base platform for BIM & GIS integration.

Keywords: database, engineering geology, 3D Model, RockWorks, Bac Ai pumped storage hydropower project

Procedia PDF Downloads 134

Authors: Ässia Boukhatmi, Roger Nyffenegger

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The expansion of solar energy as a means to address the climate crisis is undisputed, but the increasing number of new photovoltaic (PV) modules being put on the market is simultaneously leading to increased challenges in terms of managing the growing waste stream. Many of the discarded modules are still fully functional but are often damaged by improper handling after disassembly or not properly tested to be considered for a second life. In addition, the collection rate for dismantled PV modules in several European countries is only a fraction of previous projections, partly due to the increased number of illegal exports. The underlying problem for those market imperfections is an insufficient data exchange between the different actors along the PV value chain, as well as the limited traceability of PV panels during their lifetime. As part of the Horizon 2020 project CIRCUSOL, an asset database prototype was developed to tackle the described problems. In an iterative process applying the design science research methodology, different business models, as well as the technical implementation of the database, were established and evaluated. To explore the requirements of different stakeholders for the development of the database, surveys and in-depth interviews were conducted with various representatives of the solar industry. The proposed database prototype maps the entire value chain of PV modules, beginning with the digital product passport, which provides information about materials and components contained in every module. Product-related information can then be expanded with performance data of existing installations. This information forms the basis for the application of data analysis methods to forecast the appropriate end-of-life strategy, as well as the circular economy potential of PV modules, already before they arrive at the recycling facility. The database prototype could already be enriched with data from different data sources along the value chain. From a business model perspective, the database offers opportunities both in the area of reuse as well as with regard to the certification of sustainable modules. Here, participating actors have the opportunity to differentiate their business and exploit new revenue streams. Future research can apply this approach to further industry and product sectors, validate the database prototype in a practical context, and can serve as a basis for standardization efforts to strengthen the circular economy.

Keywords: business model, circular economy, database, design science research, solar industry

Procedia PDF Downloads 79

Authors: Stacy Jarvis

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Databases such as JSTOR, RILM and WorldCat have been the main source and storage of literature in the music orb. The Reference Index to Music Literature is a bibliographic database of over 2.6 million citations to writings about music from over 70 countries. The Research Institute produces RILM for the Study of Music at the University of Buffalo. JSTOR is an e-library of academic journals, books, and primary sources. Database JSTOR helps scholars find, utilise, and build upon a vast range of literature through a powerful teaching and research platform. Another database, WorldCat, is the world's biggest library catalogue, assisting scholars in finding library materials online. An evaluation of these databases in the music sphere is conducted by looking into the description and intended use and finding similarities and differences among them. Through comparison, it is found that these aim to serve different purposes, though they have the same goal of providing and storing literature. Also, since each database has different parts of literature that it majors on, the intended use of the three databases is evaluated. This can be found in the description, scope, and intended uses section. These areas are crucial to the research as it addresses the functional or literature differences among the three databases. It is also found that these databases have different quantitative potentials. This is determined by addressing the year each database began collecting literature and the number of articles, periodicals, albums, conference proceedings, music, dissertations, digital media, essays collections, journal articles, monographs, online resources, reviews, and reference materials that can be found in each one of them. This can be found in the sections- description, scope and intended uses and the importance of the database in identifying literature on different topics. To compare the delivery of services to the users, the importance of databases in identifying literature on different topics is also addressed in the section -the importance of databases in identifying literature on different topics. Even though these databases are used in research, they all have disadvantages and advantages. This is addressed in the sections on advantages and disadvantages. This will be significant in determining which of the three is the best. Also, it will help address how the shortcomings of one database can be addressed by utilising two databases together while conducting research. It is addressed in the section- a combination of RILM and JSTOR. All this information revolves around the idea that a huge amount of quantitative and qualitative data can be found in the presented databases on music and digital content; however, each of the given databases has a different construction and material features contributing to the musical scholarship in its way.

Keywords: RILM, JSTOR, WorldCat, database, literature, research

Procedia PDF Downloads 59

Authors: Lee Yan Nian

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Safety investigation is different from an administrative investigation in that the former is conducted by an independent agency and the purpose of such investigation is to prevent accidents in the future and not to apportion blame or determine liability. Before October 2018, Taiwan railway occurrences were investigated by local supervisory authority. Characteristics of this kind of investigation are that enforcement actions, such as administrative penalty, are usually imposed on those persons or units involved in occurrence. On October 21, 2018, due to a Taiwan Railway accident, which caused 18 fatalities and injured another 267, establishing an agency to independently investigate this catastrophic railway accident was quickly decided. The Taiwan Transportation Safety Board (TTSB) was then established on August 1, 2019 to take charge of investigating major aviation, marine, railway and highway occurrences. The objective of this study is to assess the effectiveness of safety investigations conducted by the TTSB. In this study, the major railway occurrence investigation reports published by the TTSB are used for modeling and analysis. According to the classification of railway occurrences investigated by the TTSB, accident types of Taiwan railway occurrences can be categorized into: derailment, fire, Signal Passed at Danger and others. A Causal Factor Analysis System (CFAS) developed by the TTSB is used to identify the influencing causal factors and their causal relationships in the investigation reports. All terminologies used in the CFAS are equivalent to the Human Factors Analysis and Classification System (HFACS) terminologies, except for “Technical Events” which was added to classify causal factors resulting from mechanical failure. Accordingly, the Bayesian network structure of each occurrence category is established based on the identified causal factors in the CFAS. In the Bayesian networks, the prior probabilities of identified causal factors are obtained from the number of times in the investigation reports. Conditional Probability Table of each parent node is determined from domain experts’ experience and judgement. The resulting networks are quantitatively assessed under different scenarios to evaluate their forward predictions and backward diagnostic capabilities. Finally, the established Bayesian network of derailment is assessed using investigation reports of the same accident which was investigated by the TTSB and the local supervisory authority respectively. Based on the assessment results, findings of the administrative investigation is more closely tied to errors of front line personnel than to organizational related factors. Safety investigation can identify not only unsafe acts of individual but also in-depth causal factors of organizational influences. The results show that the proposed methodology can identify differences between safety investigation and administrative investigation. Therefore, effective intervention strategies in associated areas can be better addressed for safety improvement and future accident prevention through safety investigation.

Keywords: administrative investigation, bayesian network, causal factor analysis system, safety investigation

Procedia PDF Downloads 86

Authors: Archana Singh, Jyoti Agarwal, Ajay Rana

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Data Mining is an efficient technology to discover patterns in large databases. Association Rule Mining techniques are used to find the correlation between the various item sets in a database, and this co-relation between various item sets are used in decision making and pattern analysis. In recent years, the problem of finding association rules from large datasets has been proposed by many researchers. Various research papers on association rule mining (ARM) are studied and analyzed first to understand the existing algorithms. Apriori algorithm is the basic ARM algorithm, but it requires so many database scans. In DIC algorithm, less amount of database scan is needed but complex data structure lattice is used. The main focus of this paper is to propose a new optimized algorithm (Friendly Algorithm) and compare its performance with the existing algorithms A data set is used to find out frequent itemsets and association rules with the help of existing and proposed (Friendly Algorithm) and it has been observed that the proposed algorithm also finds all the frequent itemsets and essential association rules from databases as compared to existing algorithms in less amount of database scan. In the proposed algorithm, an optimized data structure is used i.e. Graph and Adjacency Matrix.

Keywords: association rules, data mining, dynamic item set counting, FP-growth, friendly algorithm, graph

Procedia PDF Downloads 389