• Parasites, Hosts and Diseases
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• v.51 no.2
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• pp.177-182
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• 2013

The purpose of the present study was to evaluate the potential role of the 27-Kilodalton (KDa) antigen versus Fasciola gigantica adult worm regurge antigens in a DOT-Blot assay and to assess this assay as a practical tool for diagnosis fascioliasis in Egyptian patients. Fasciola gigantica antigen of an approximate molecular mass 27- (KDa) was obtained from adult worms by a simple elution SDS-PAGE. A Dot-Blot was developed comparatively to adult worm regurge antigens for the detection of specific antibodies from patients infected with F. gigantica in Egypt. Control sera were obtained from patients with other parasitic infections and healthy volunteers to assess the test and compare between the antigens. The sensitivity, specificity, positive and negative predictive values of Dot-Blot using the adult worm regurge were 80%, 90%, 94.1%, and 69.2% respectively, while those using 27-KDa were 100% which confirms the diagnostic potential of this antigen. All patients infected with Fasciola were positive, with cross reactivity reported with Schistosoma mansoni serum samples. This 27-KDa Dot-Blot assay showed to be a promising test which can be used for serodiagnosis of fascioliasis in Egyptian patients especially, those presenting with hepatic disease. It is specific, sensitive and easy to perform method for the rapid diagnosis particularly when more complex laboratory tests are unavailable.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.333-339
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• 2022

The purpose of the article is to identify priority trends of technological innovations and strategic opportunities for using the smart potential to the benefit of the Russian industrial production development in the context of digital transformation. The article substantiates the demand for technological process automation at industrial enterprises in Russia and considers the possibilities of using artificial intelligence and the implementation of smart manufacturing in the industry. The article reveals the priorities of the leading Russian industrial companies in the field of digitalization, namely, an expansion of the use of cloud technologies, predictive analysis, IaaS services (virtual data storage and processing centers), supervisory control, and data acquisition (SCADA), etc. The authors give the characteristics of the monitoring of the smart manufacturing systems development indicators in the Russian Federation, conducted by Rosstat since 2020; presents projected data on the assessment of the required resources in relation to the instruments of state support for the development of smart manufacturing technologies for the period until 2024. The article determines targets for the development of smart technologies within the framework of the Federal Project "Digital Technologies".

• Asia Marketing Journal
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• v.20 no.2
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• pp.65-83
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• 2018

Technological advances are bringing autonomous vehicles to the ever-evolving transportation system. Anticipating adoption of these technologies by users is essential to vehicle manufacturers for making more precise production and marketing strategies. The research investigates regulatory focus and consumer innovativeness with consumers' adoption of autonomous vehicles (AVs) and to consumers' subsequent willingness to pay for AVs. An online questionnaire was fielded to confirm predictions, and regression analysis was conducted to verify the model's validity. The results show that a promotion focus does not have a significantly positive effect on the automation level at which consumers will adopt AVs, but a prevention focus has a significantly positive effect on conditional AV adoption. Consumer innovativeness, consumers' novelty-seeking have a significantly positive relationship with high and full AV adoption, and consumers' independent decision-making has a significantly positive effect on full AV adoption. The higher the level of automation at which a consumer adopts AVs, the higher the willingness to pay for them. Finally, using a neural network and decision tree analyses, we show methods with which to describe three categories for potential adopters of AVs.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.6
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• pp.319-325
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• 2023

In this study, we proposed a method for hyperparameter optimization in the building and training of a deep learning model designed to process point cloud data collected by a millimeter-wave radar system. The primary aim of this study is to facilitate the deployment of a baseline model in resource-constrained IoT devices. We evaluated a RadHAR baseline deep learning model trained on a public dataset composed of point clouds representing five distinct human activities. Additionally, we introduced a coarse-to-fine hyperparameter optimization procedure, showing substantial potential to enhance model efficiency without compromising predictive performance. Experimental results show the feasibility of significantly reducing model size without adversely impacting performance. Specifically, the optimized model demonstrated a 3.3% improvement in classification accuracy despite a 16.8% reduction in number of parameters compared th the baseline model. In conclusion, this research offers valuable insights for the development of deep learning models for resource-constrained IoT devices, underscoring the potential of hyperparameter optimization and model size reduction strategies. This work contributes to enhancing the practicality and usability of deep learning models in real-world environments, where high levels of accuracy and efficiency in data processing and classification tasks are required.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.187-194
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• 2014

We consider a Bayesian nonignorable selection model to accommodate the selection bias. Markov chain Monte Carlo methods is known to be very useful to fit the nonignorable selection model. However, sensitivity to prior assumptions on parameters for selection mechanism is a potential problem. To quantify the sensitivity to prior assumption, the deviance information criterion and the conditional predictive ordinate are used to compare the goodness-of-fit under two different prior specifications. It turns out that the 'MLE' prior gives better fit than the 'uniform' prior in viewpoints of goodness-of-fit measures.

• International Journal of Automotive Technology
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• v.5 no.3
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• pp.145-153
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• 2004

Potential fuel economy improvements and environmental legislation have renewed interest in Gasoline Direct Injection (GDI) engines. Computational models of fuel injection and mixing processes pre-ignition are being developed for engine optimisation. These highly transient thermofluid models require verification against temporally and spatially resolved data-sets. The authors have previously established the capability of PDA to provide suitable temporally and spatially resolved spray characteristics such as mean droplet size, velocity components and qualitative mass distribution. This paper utilises this data-set to assess the predictive capability of a numerical model for GDI spray prediction. After a brief description of the two-phase model and discretisation sensitivity, the influence of initial spray conditions is discussed. A minimum of 5 initial global spray characteristics are required to model the downstream spray characteristics adequately under isothermal, atmospheric conditions. Verification of predicted transient spray characteristics such as the hollow-cone, cone collapse, head vortex, stratification and penetration are discussed, and further improvements to modelling GDI sprays proposed.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.136-138
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• 2006

Recently, network systems are widely used in several areas, and some considerable attentions have been directed to the Networked Control System(NCS). In NCS, network-induced delays are inevitable, and they sometimes degrade the performance of networked control systems to be a source of potential instability. In this paper, We proposes a compensation method for networked control system subject to network-induced delays by using a simple method, which is based on a sort of predictive strategy. To evaluate its feasibility and effectiveness, a real-time NCS for a rotary inverted pendulum is implemented via an Ethernet. Based on the experimental results. we show that the proposed simple method can be a practical and feasible solution to NCS design.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.206-212
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• 2004

This paper is application of System Assurance(SA) for the rolling stock. As railway systems become more complex, design teams are increasingly under pressure to deliver, design solutions, which integrate both technical and Systems Assurance(SA). Systems Assurance is the application of management methods and analysis techniques to ensure that a design meets Reliability, Availability, Maintainability and Safety (RAMS) criteria. It should be clearly understood that the intent of System Assurance is not just to provide analytical techniques as a metric on performance, but more importantly it should provide a management tool with which to co-ordinate and assure the whole design. System Assurance encompasses the ongoing requirement to consider safety, and RAM through each stage of a Project, from feasibility study through to commissioning and operation. If System Assurance is undertaken properly at feasibility study at the design stages of a Project, the benefits of such analyses can be significant in identifying potential problems early enough for action to be taken before manufacture or installation. At commissioning, RAMS demonstration activities are undertaken to validate the predictive and analytical techniques undertaken during the design.

• International Journal of Control, Automation, and Systems
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• v.5 no.5
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• pp.508-514
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• 2007

Properties and potential applications of the block pulse response circulant matrix (PRCM) and its singular value decomposition (SVD) are investigated in relation to MIMO control and identification. The SVD of the PRCM is found to provide complete directional as well as frequency decomposition of a MIMO system in a real matrix form. Three examples were considered: design of MIMO FIR controller, design of robust reduced-order model predictive controller, and input design for MIMO identification. The examples manifested the effectiveness and usefulness of the PRCM in the design of MIMO control and identification. irculant matrix, SVD, MIMO control, identification.

• Journal of Advanced Marine Engineering and Technology
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• v.32 no.5
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• pp.791-797
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• 2008

The officer of the deck(OOD) may sometimes have to carry out lookout as well as handling of auto pilot without a quartermaster at sea. The purpose of this paper is to develop the ship's auto pilot control module using speech recognition in order to reduce the potential risk of one man bridge system. The feature parameters predicting the OOD's intention was extracted from the sample wheel orders written in SMCP(IMO Standard Marine Communication Phrases). We designed a pre-recognition procedure which could make some candidate words using DTW(Dynamic Time Warping) algorithm, a post-recognition procedure which made a final decision from the candidate words using the feature parameters. To evaluate the effectiveness of these procedures the experiment was conducted with 500 wheel orders.