Search results for: accuracy improvement

Authors: Davide Fuscà, Kanan Rahimli, Roberto Leuzzi

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Preventing abuse and illegal activities in a given area of the sea is a very difficult and expensive task. Artificial intelligence offers the possibility to implement new methods to identify the vessel class type from the kinematic features of the vessel itself. The task strictly depends on the quality of the data. This paper explores the application of a deep, long short-term memory model by using AIS flow only with a relatively low quality. The proposed model reaches high accuracy on detecting nine vessel classes representing the most common vessel types in the Ionian-Adriatic Sea. The model has been applied during the Adriatic-Ionian trial period of the international EU ANDROMEDA H2020 project to identify vessels performing behaviors far from the expected one depending on the declared type.

Keywords: maritime surveillance, artificial intelligence, behavior analysis, LSTM

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Authors: Zheng Lulin, Xiong Guoping

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In recent years, agriculture, rural development, and peasants are among the top concerns and priorities of the Chinese Government. Several related issues have been paid many attentions by academic communities, including the impacts of corresponding policies on the rural villages, the mechanisms of these impacts, and the future development of rural society. However, most of the researchers focus on single rural policy instead of integral rural policy system. Hence, this dissertation focused on the mechanisms of policies’ influence on rural changes through a case study from Changfu Village in central Guangxi Province, China, to propose the optimized suggestions for rural development. Forty-three relevant pivotal policies of significant influence on rural development are summarized from literature and documents, covering five aspects of agricultural production, rural living security, open rural markets, rural household registration systems, and farmland transferring. Besides, having been live in this area for more than 20 years, researchers obtain the basic information about changing the social connection between citizens and villagers, the habitat of villagers by years of informal interviews. Furthermore, more than 200 questionnaires are given to villagers to analyze the changing of their personal and family information. The summary of rural policies revealed that the development trend of public rural policies followed the U-shape curve and these policies are characterized by economic intentions and operative economy. Report of questionnaires and interviews show that the development of rural economy was promoted greatly by public policies. Firstly, Social communication and rural culture were affected to a certain extent. Secondly, the educational level of rural individuals was significantly enhanced, whereas the quality of population had limited progress. Finally, the freedom of occupational choice for rural individuals into cities was greater than before, but still restricted by the class solidification of social background, resulting in more obstacles for rural individuals to settle down in cities. From what we discuss about, we may reach the conclusion on several perspectives: Firstly, the impact of the rural policies has a significant role in promoting the economy development of the rural area. However, separations between rural and urban area are still a major problem since rural policy contributed little to improve the rural population quality. Therefore, in the future, providing high quality educational facilities including teachers, libraries, and opportunities of broadening their knowledge base are key issues of future rural policy. Secondly, the development of rural economy would be a lack of driving force for further improvement owning to the fact that working hard couldn’t get more improvement. In the future, public policies should support the rural development of culture, technology, and personal qualities to create favorable social environment for the free increase of rural population.

Keywords: changing of rural area, rural development of China, rural policy, social environment

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Authors: Samart Rungjarean, Benchalak Muangmeesri, Dechrit Maneetham

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Monks' and Novices' chimes may have some restrictions, such as during the rain when a structure or location chimes or at a certain period. Alternately, certain temple bells may be found atop a tall, difficult-to-reach bell tower. As a result, the concept of designing a brass bell for use with a mobile phone over great distances was proposed. The Internet of Things (IoT) system will be used to regulate the bell by testing each of the three beatings with a wooden head. A stone-beating head and a steel beater. The sound resonates nicely, with the distance and rhythm of the hit contributing to this. An ESP8266 microcontroller is used by the control system to manage its operations and will communicate with the pneumatic system to convey a signal. Additionally, a mobile phone will be used to operate the entire system. In order to precisely direct and regulate the rhythm, There is a resonance of roughly 50 dB for this test, and the operating distance can be adjusted. Timing and accuracy were both good.

Keywords: automatic ring-bell, microcontroller, ring-bell, iot

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Authors: Shreeyam, Ranjan Kumar Sah, Shivangi

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Recognizing and solving handwritten mathematical expressions can be a challenging task, particularly when certain characters are segmented and classified. This project proposes a solution that uses Convolutional Neural Network (CNN) and image processing techniques to accurately solve various types of equations, including arithmetic, quadratic, and trigonometric equations, as well as logical operations like logical AND, OR, NOT, NAND, XOR, and NOR. The proposed solution also provides a graphical solution, allowing users to visualize equations and their solutions. In addition to equation solving, the platform, called CNNCalc, offers a comprehensive learning experience for students. It provides educational content, a quiz platform, and a coding platform for practicing programming skills in different languages like C, Python, and Java. This all-in-one solution makes the learning process engaging and enjoyable for students. The proposed methodology includes horizontal compact projection analysis and survey for segmentation and binarization, as well as connected component analysis and integrated connected component analysis for character classification. The compact projection algorithm compresses the horizontal projections to remove noise and obtain a clearer image, contributing to the accuracy of character segmentation. Experimental results demonstrate the effectiveness of the proposed solution in solving a wide range of mathematical equations. CNNCalc provides a powerful and user-friendly platform for solving equations, learning, and practicing programming skills. With its comprehensive features and accurate results, CNNCalc is poised to revolutionize the way students learn and solve mathematical equations. The platform utilizes a custom-designed Convolutional Neural Network (CNN) with image processing techniques to accurately recognize and classify symbols within handwritten equations. The compact projection algorithm effectively removes noise from horizontal projections, leading to clearer images and improved character segmentation. Experimental results demonstrate the accuracy and effectiveness of the proposed solution in solving a wide range of equations, including arithmetic, quadratic, trigonometric, and logical operations. CNNCalc features a user-friendly interface with a graphical representation of equations being solved, making it an interactive and engaging learning experience for users. The platform also includes tutorials, testing capabilities, and programming features in languages such as C, Python, and Java. Users can track their progress and work towards improving their skills. CNNCalc is poised to revolutionize the way students learn and solve mathematical equations with its comprehensive features and accurate results.

Keywords: AL, ML, hand written equation solver, maths, computer, CNNCalc, convolutional neural networks

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Authors: Drago Bratkovic, Curtis Gravance, David Ketteridge, Ravi Krishnan, Michael Imperiale

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The mucopolysaccharidoses (MPSs) are a group of lysosomal storage diseases that have a common defect in the catabolism of glycosaminoglycans (GAGs). MPS I is the most common of the MPS diseases. Manifestations of MPS I include coarsening of facial features, corneal clouding, developmental delay, short stature, skeletal manifestations, hearing loss, cardiac valve disease, hepatosplenomegaly, and umbilical and inguinal hernias. Treatments for MPS I restore or activate the missing or deficient enzyme in the case of enzyme replacement therapy (ERT) and haematopoietic stem cell transplantation (HSCT). Pentosan polysulfate sodium (PPS) is a potential treatment to improve bone and joint manifestations of MPS I. The mechanisms of action of PPS that are relevant to the treatment of MPS I are the ability to: (i) Reduce systemic and accumulated GAG, (ii) Reduce inflammatory effects via the inhibition of NF-kB, resulting in the reduction in pro-inflammatory mediators. (iii) Reduce the expression of the pain mediator nerve growth factor in osteocytes from degenerating joints. (iv) Inhibit the cartilage degrading enzymes related to joint dysfunction in MPS I. PPS is being evaluated as an adjunctive therapy to ERT and/or HSCT in an open-label, single-centre, phase 2 study. Patients are ≥ 5 years of age with a diagnosis of MPS I and previously received HSCT and/or ERT. Three white, female, patients with MPS I-Hurler, ages 14, 15, and 19 years, and one, white male patient aged 15 years are enrolled. All were diagnosed at ≤2 years of age. All patients received HSCT ≤ 6 months after diagnosis. Two of the patients were treated with ERT prior to HSCT, and 1 patient received ERT commencing 3 months prior to HSCT. Two patients received 0.75mg/kg and 2 patients received 1.5mg/kg of PPS. PPS was well tolerated at doses of 0.75 and 1.5 mg/kg to 47 weeks of continuous dosing. Of the 19 adverse events (AEs), 2 were related to PPS. One AE was moderate (pre-syncope) and 1 was mild (injection site bruising), experienced in the same patient. All AEs were reported as mild or moderate. There have been no SAEs. One subject experienced a COVID-19 infection and PPS was interrupted. The MPS I signature GAG fragments, sulfated disaccharide and UA-HNAc S, tended to decrease in 3 patients from baseline through Week 25. Week 25 GAG data are pending for the 4th patient. Overall, most biomarkers (inflammatory, cartilage degeneration, and bone turnover) evaluated in the 3 patients with 25-week assessments have indicated either no change or a reduction in levels compared to baseline. In 3 patients, there was a trend toward improvement in the 2MWT from baseline to Week 48 with > 100% increase in 1 patient (01-201). In the 3 patients that had Week 48 assessments, patients and proxies reported improvement in PGIC, including “worthwhile difference” (n=1), or “made all the difference” (n=2).

Keywords: MPS I, pentosan polysulfate sodium, clinical study, 2MWT, QoL

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Authors: Jaci Mastrandrea

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Background: The National Comprehensive Cancer Network (NCCN) recommends that healthcare institutions have established processes for integrating palliative care (PC) into cancer treatment and that all cancer patients be screened for PC needs upon initial diagnosis as well as throughout the entire continuum of care (National Comprehensive Cancer Network, 2021). Early PC screening is directly correlated with improved patient outcomes. The Sky Lakes Cancer Treatment Center (SLCTC) is an institution that has access to PC services yet does not have protocols in place for identifying patients with palliative needs or a standardized referral process. The aim of this quality improvement project is to improve early access to PC services by establishing a standardized screening and referral process for outpatient oncology patients. Method: The sample population included all adult patients with an oncology diagnosis who presented to the SLCTC for treatment during the project timeline from March 15th, 2022, to April 29th, 2022. The “Palliative and Supportive Needs Assessment'' (PSNA) screening tool was developed from validated and evidence-based PC referral criteria. The tool was initially implemented using paper forms and later was integrated into the Epic-Beacon EHR system. Patients were screened by registered nurses on the SLCTC treatment team. Nurses responsible for screening patients received an educational inservice prior to implementation. Patients with a PSNA score of three or higher were considered to be a positive screen. Scores of five or higher triggered a PC referral order in the patient’s EHR for the oncologist to review and approve. All patients with a positive screen received an educational handout on the topic of PC, and the EHR was flagged for follow-up. Results: Prior to implementation of the PSCNA screening tool, the SLCTC had zero referrals to PC in the past year, excluding referrals to hospice. Data was collected from the first 100 patient screenings completed within the eight-week data collection period. Seventy-three percent of patients met criteria for PC referral with a score greater than or equal to three. Of those patients who met referral criteria, 53.4% (39 patients) were referred for a palliative and supportive care consultation. Patients that were not referred to PC upon meeting the criteria were flagged in the EHR for re-screening within one to three months. Patients with lung cancer, chronic hematologic malignancies, breast cancer, and gastrointestinal malignancy most frequently met criteria for PC referral and scored highest overall on the scale of 0-12. Conclusion: The implementation of a standardized PC screening tool at the SLCTC significantly increased awareness of PC needs among cancer patients in the outpatient setting. Additionally, data derived from this quality improvement project supports the national recommendation for PC to be an integral component of cancer treatment across the entire continuum of care.

Keywords: oncology, palliative care, symptom management, symptom screening, ambulatory oncology, cancer, supportive care

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Authors: S. H. Arnaud Kanga, O. Hili, S. Dabo-Niang

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Spatial prediction is an issue appealing and attracting several fields such as agriculture, environmental sciences, ecology, econometrics, and many others. Although multiple non-parametric prediction methods exist for spatial data, those are based on the conditional expectation. This paper took a different approach by examining a non-parametric spatial predictor of the conditional quantile. The study especially observes the stationary multidimensional spatial process over a rectangular domain. Indeed, the proposed quantile is obtained by inverting the conditional distribution function. Furthermore, the proposed estimator of the conditional distribution function depends on three kernels, where one of them controls the distance between spatial locations, while the other two control the distance between observations. In addition, the almost complete convergence and the convergence in mean order q of the kernel predictor are obtained when the sample considered is alpha-mixing. Such approach of the prediction method gives the advantage of accuracy as it overcomes sensitivity to extreme and outliers values.

Keywords: conditional quantile, kernel, nonparametric, stationary

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Authors: V. Paployan, K. Madoyan, A. Melikyan, H. Minassian

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Resonant two-photon ionization (TPI) is a valuable technique for the study of clusters due to its ultrahigh sensitivity. The comparison of the observed TPI spectra with results of calculations allows to deduce important information on the shape, rotational and vibrational temperatures of the clusters with high accuracy. In this communication we calculate the TPI cross-section for pump-probe scheme in Ag neutral cluster. The pump photon energy is chosen to be close to the surface plasmon (SP) energy of cluster in dielectric media. Since the interband transition energy in Ag exceeds the SP resonance energy, the main contribution into the TPI comes from the latter. The calculations are performed by separating the coordinates of electrons corresponding to the collective oscillations and the individual motion that allows to take into account the resonance contribution of excited SP oscillations. It is shown that the ionization cross section increases by two orders of magnitude if the energy of the pump photon matches the surface plasmon energy in the cluster.

Keywords: resonance enhancement, silver clusters, surface plasmon, two-photon ionization

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Authors: Byung Cheol Kim

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This study explores a method for the signal-noise separation challenge in project control, focusing on the limitations of traditional deterministic approaches that use single-point performance metrics to predict project outcomes. We detail how traditional methods often overlook future uncertainties, resulting in tracking biases when reliance is placed solely on immediate data without adjustments for predictive accuracy. Our investigation led to the development of the Predictive Tracking Project Control (PTPC) framework, which incorporates network simulation and Bayesian control models to adapt more effectively to project dynamics. The PTPC introduces controlled disturbances to better identify and separate tracking biases from useful predictive signals. We will demonstrate the efficacy of the PTPC with examples, highlighting its potential to enhance real-time project monitoring and decision-making, marking a significant shift towards more accurate project management practices.

Keywords: predictive tracking, project control, signal-noise separation, Bayesian inference

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Authors: Elżbieta Cygan-Bączek, Piotr Wyżga, Sławomir Cygan

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In the presented work, the main goal was to investigate the retention properties, defined as the ability of the matrix material to hold diamond particles in relation to metallized (Ti, Si, Cr, Co, Cu, Ni) and non-metallized diamond crystals. For this purpose, diamond-impregnated specimens were tested for wear rate on abrasive sandstone using a test rig specially designed to simulate tool application conditions. The tests that involved 3- and 2-body abrasion ranked the alloys in different orders. The ability of the matrix to retain diamond crystals was determined using the electron microskopy (SEM, TEM). The specimens were also characterized by X-ray diffraction (XRD) and hardness. The conducted research has shown that Si and Ti metallized diamonds, apart from mechanical jamming in the matrix, are also connected in a metallurgical manner, ensuring the improvement of the retention properties of the matrix material.

Keywords: diamond, metallic-diamond segments, retention, abrasive wear resistance

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Authors: Sharmeelee Subramaniam, Muhd Harris Ramli, Fauziah Ahmad

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The application of vacuum pressure to accelerate ground consolidation has been growing significantly in recent years. This ground improvement technique has its advantages, especially in areas where suitable fill is scarce, as it minimizes the surcharge fill height required for the preloading. A study was carried out to examine the response of soft subsoil subjected to vacuum consolidation in combination with embankment loading, surcharge preloading and PVD with two-way drainage. This paper shall describe a procedure to determine the optimum surcharge height and penetration depth of prefabricated vertical drains (PVD) where vacuum consolidation is combined with the use of PVD in soft clay deposits with two-way drainage.

Keywords: prefabricated vertical drain, soft soil, surcharge preload, vacuum consolidation

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Authors: S. Ghorbani, N. I. Polushin

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In this study, an approach to identify factors affecting on surface roughness in a machining process is presented. This study is based on 81 data about surface roughness over a wide range of cutting tools (conventional, cutting tool with holes, cutting tool with composite material), workpiece materials (AISI 1045 Steel, AA2024 aluminum alloy, A48-class30 gray cast iron), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev), depth of cut (0.05-0.15 mm) and tool overhang (41-65 mm). A single decision tree (SDT) analysis was done to identify factors for predicting a model of surface roughness, and the CART algorithm was employed for building and evaluating regression tree. Results show that a single decision tree is better than traditional regression models with higher rate and forecast accuracy and strong value.

Keywords: cutting condition, surface roughness, decision tree, CART algorithm

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Authors: Song Zhiyong, Zhao Bo, Du Li, Wang Wei

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Aircraft structures generally have complex surface. Because of constantly switching postures of motion axis, five-axis CNC machine’s composite stiffness changes during CNC machining. It gives rise to different amplitude of vibration of processing system, which further leads to the different effects on surface waviness. In order to provide a solution for this problem, we take the “S” shape test specimen’s CNC machining for the object, through calculate the five axis CNC machine’s composite stiffness and establish vibration model, we analysis of the influence mechanism between vibration amplitude and surface waviness. Through carry out the surface quality measurement experiments, verify the validity and accuracy of the theoretical analysis. This paper’s research results provide a theoretical basis for surface waviness control.

Keywords: five axis CNC machine, “S” shape test specimen, composite stiffness, surface waviness

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Authors: Bency Jacob, S.B. Waykar

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Degradations in historical document images appear due to aging of the documents. It is very difficult to understand and retrieve text from badly degraded documents as there is variation between the document foreground and background. Thresholding of such document images either result in broken characters or detection of false texts. Numerous algorithms exist that can separate text and background efficiently in the textual regions of the document; but portions of background are mistaken as text in areas that hardly contain any text. This paper presents a way to overcome these problems by a robust binarization technique that recovers the text from a severely degraded document images and thereby increases the accuracy of optical character recognition systems. The proposed document recovery algorithm efficiently removes degradations from document images. Here we are using the ostus method ,local thresholding and global thresholding and after the binarization training and recognizing the characters in the degraded documents.

Keywords: binarization, denoising, global thresholding, local thresholding, thresholding

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Authors: Alireza Mirrashid, Mohammad Khoshbin, Ali Atghaei, Hassan Shahbazi

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In various industries, smoke and fire are two of the most important threats in the workplace. One of the common methods for detecting smoke and fire is the use of infrared thermal and smoke sensors, which cannot be used in outdoor applications. Therefore, the use of vision-based methods seems necessary. The problem of smoke and fire detection is spatiotemporal and requires spatiotemporal solutions. This paper presents a method that uses spatial features along with temporal-based features to detect smoke and fire in the scene. It consists of three main parts; the task of each part is to reduce the error of the previous part so that the final model has a robust performance. This method also uses transformer modules to increase the accuracy of the model. The results of our model show the proper performance of the proposed approach in solving the problem of smoke and fire detection and can be used to increase workplace safety.

Keywords: attention, fire detection, smoke detection, spatio-temporal

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Authors: Wang Xingjuan, Qian Dongming

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As a common thinking ability, spatial thinking ability plays an increasingly important role in the information age. The key to cultivating students' spatial thinking ability is to cultivate students' ability to process and transform graphics. The 3D printing course enables students to constantly touch the rotation and movement of objects during the modeling process and to understand spatial graphics from different views. To this end, this article combines the classic PSVT: R test to explore the impact of 3D printing courses on the spatial thinking ability of middle school students. The results of the study found that: (1) Through the study of the 3D printing course, the students' spatial ability test scores have been significantly improved, which indirectly reflects the improvement of the spatial thinking ability level. (2) The student's spatial thinking ability test results are influenced by the parent's occupation.

Keywords: 3D printing, middle school students, spatial thinking ability, influence

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Authors: Baobao Li

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Operational risk covers all operations of commercial banks and has a close relationship with the bank’s internal control. But in the commercial banks' management practice, internal control is always separated from the operational risk measurement. With the increasing of operational risk events in recent years, operational risk is paid more and more attention by regulators and banks’ managements. The paper first discussed the relationship between internal control and operational risk management and used CVaR-POT model to measure operational risk, and then put forward a modified measurement method (to use operational risk assessment results to modify the measurement results of the CVaR-POT model). The paper also analyzed the necessity and rationality of this method. The method takes into consideration the influence of internal control, improves the accuracy and effectiveness of operational risk measurement and save the economic capital for commercial banks, avoiding the drawbacks of using some mainstream models one-sidedly.

Keywords: commercial banks, internal control, operational risk, risk measurement

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Authors: Ratnawati Mohd Asraf, Hazlina Abdullah

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Numerous studies on boys’ performance relative to girls’ have been conducted around the globe. However, little has been done in relation to the literacy of primary school boys in the Malaysian context. This paper discusses the results of a study that sought to determine the literacy performance of Grades 1, 2, and 3 primary school students in the state of Selangor, Malaysia. Data on approximately 85,000 students from each grade level were obtained from the Ministry of Education Malaysia, which conducts national screening on literacy and numeracy, or LINUS, in all government primary schools. Teachers’ views were also sought through focus group interviews and journal entries. The results show that although there is an overall improvement in literacy performance in the Malay language among the students as they go into Grades 2 and 3, girls are found to outperform boys in every screening for all grade levels.

Keywords: boys’ underperformance, literacy, literacy performance, reading

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Authors: Deepika Bhalla, Raj Kumar Bansal, Hari Om Gupta

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Dissolved Gas Analysis (DGA) has been widely used for fault diagnosis in a transformer. Artificial neural networks (ANN) have high accuracy but are regarded as black boxes that are difficult to interpret. For many problems it is desired to extract knowledge from trained neural networks (NN) so that the user can gain a better understanding of the solution arrived by the NN. This paper applies a pedagogical approach for rule extraction from function approximating neural networks (REFANN) with application to incipient fault diagnosis using the concentrations of the dissolved gases within the transformer oil, as the input to the NN. The input space is split into subregions and for each subregion there is a linear equation that is used to predict the type of fault developing within a transformer. The experiments on real data indicate that the approach used can extract simple and useful rules and give fault predictions that match the actual fault and are at times also better than those predicted by the IEC method.

Keywords: artificial neural networks, dissolved gas analysis, rules extraction, transformer

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Authors: G. Erkomaishvili

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The paper discusses economic policy of Georgia aiming to increase national competitiveness as well as the tools and means which will help to improve the competitiveness of the country. The sectors of the economy, in which the country can achieve the competitive advantage, are studied. It is noted that the country’s economic policy plays an important role in obtaining and maintaining the competitive advantage - authority should take measures to ensure high level of education; scientific and research activities should be funded by the state; foreign direct investments should be attracted mainly in science-intensive industries; adaptation with the latest scientific achievements of the modern world and deepening of scientific and technical cooperation. Stable business environment and export oriented strategy is the basis for the country’s economic growth. As the outcome of the research, the paper suggests the strategy for improving competitiveness in Georgia; recommendations are provided based on relevant conclusions.

Keywords: competitive advantage, competitiveness, competitiveness improvement strategy, competitiveness of Georgia

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Authors: J. R. Wang, H. C. Chang, A. L. Ho, J. H. Yang, S. W. Chen, C. Shih

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The purpose of the study is to analyze the load rejection transient of ABWR by using TRACE, PARCS, and SNAP codes. This study has some steps. First, using TRACE, PARCS, and SNAP codes establish the model of ABWR. Second, the key parameters are identified to refine the TRACE/PARCS/SNAP model further in the frame of a steady state analysis. Third, the TRACE/PARCS/SNAP model is used to perform the load rejection transient analysis. Finally, the FSAR data are used to compare with the analysis results. The results of TRACE/PARCS are consistent with the FSAR data for the important parameters. It indicates that the TRACE/PARCS/SNAP model of ABWR has a good accuracy in the load rejection transient.

Keywords: ABWR, TRACE, PARCS, SNAP

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Authors: Adnan H. M. Al-Helali, Hamza A. Ali

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Growth of censorship and pervasive monitoring on the Internet, Steganography arises as a new means of achieving secret communication. Steganography is the art and science of embedding information within electronic media used by common applications and systems. Generally, hiding information of multimedia within images will change some of their properties that may introduce few degradation or unusual characteristics. This paper presents a new image steganography approach for hiding information of multimedia (images, text, and audio) using generated Mandelbrot Fractal image as a cover. The proposed technique has been extensively tested with different images. The results show that the method is a very secure means of hiding and retrieving steganographic information. Experimental results demonstrate that an effective improvement in the values of the Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Normalized Cross Correlation (NCC) and Image Fidelity (IF) over the previous techniques.

Keywords: fractal image, information hiding, Mandelbrot et fractal, steganography

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Authors: K. Matušínská, Z. Bednarčík, M. Klepek

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This paper examines international marketing in business practice of Czech exporting small and medium-sized enterprises (SMEs) with regard to the strategic perspectives. Research was focused on Czech exporting SMEs from Moravian-Silesia region and their behaviour on international markets. For purpose of collecting data, a questionnaire was given to 262 SMEs involved in international business. Statistics utilized in this research included frequency, mean, percentage, and chi-square test. Data were analysed by Statistical Package for the Social Sciences software. The research analysis disclosed that there is certain space for improvement in strategic marketing especially in marketing research, perception of cultural and social differences, product adaptation and usage of marketing communication tools.

Keywords: international marketing, marketing mix, marketing research, small and medium-sized enterprises, strategic marketing

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Authors: Issam Derkaoui, Mohammed Khenfouch, Bakang M. Mothudi, Malik Maaza, Izeddine Zorkani, Anouar Jorio

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Transition metal oxides nanoparticles with different morphologies have attracted a lot of attention recently owning to their distinctive geometries, and demonstrated promising electrical properties for various applications. In this paper, we discuss the time and annealing effects on the structural and electrical properties of vanadium oxides nanoparticles (VO-NPs) prepared by microwave method. In this sense, transmission electron microscopy (TEM), X-ray diffraction (XRD), Raman Spectroscopy, Ultraviolet-visible absorbance spectra (Uv-Vis) and electrical conductivity were investigated. Hence, the annealing state and the time are two crucial parameters for the improvement of the optoelectronic properties. The use of these nanostructures is promising way for the development of technological applications especially for energy storage devices.

Keywords: Vanadium oxide, Microwave, Electrical conductivity, Optoelectronic properties

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Authors: N. Malatji, A. P. I. Popoola

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Zn-Al2O3 and Cr2O3 nanocomposite coatings were successfully produced by electrodeposition technique from chloride acidic bath. Particle loading of Al2O3 (50nm) particles were varied from 5-10 g/L and for Cr2O3(100nm) was 10-20 g/L. Scanning electron microscope (SEM) affixed with energy dispersive spectrometry was used to study the surface morphology and content of the nanoparticles incorporated into the coatings. Microhardness, thermal stability, wear and corrosion behavior of the coatings were also evaluated to study the effect of these nanoparticles on these properties. Zn-Al2O3 nanocomposite was found to exhibit good surface properties especially corrosion resistance. On the other side, Cr2O3 incorporation resulted in the improvement of only mechanical properties. Therefore, Zn-Al2O3 proved to be a better coating for most industrial applications where both chemical and mechanical properties are required.

Keywords: electrodeposition, nanocomposite coatings, corrosion, thermal stability, tribology

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Authors: Chaima Babi, Said Gadri

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The rapid increase in fake news continues to grow at a very fast rate; this requires implementing efficient techniques that allow testing the re-liability of online content. For that, the current research strives to illuminate the fake news problem using deep learning DL and machine learning ML ap-proaches. We have developed the traditional LSTM (Long short-term memory), and the bidirectional BiLSTM model. A such process is to perform a training task on almost of samples of the dataset, validate the model on a subset called the test set to provide an unbiased evaluation of the final model fit on the training dataset, then compute the accuracy of detecting classifica-tion and comparing the results. For the programming stage, we used Tensor-Flow and Keras libraries on Python to support Graphical Processing Units (GPUs) that are being used for developing deep learning applications.

Keywords: machine learning, deep learning, natural language, fake news, Bi-LSTM, LSTM, multiclass classification

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Authors: Rwei-Ching Chang, Bo-Yu Su

Abstract:

Adhesion of copper thin films deposited on polyethylene terephthAdhesion of copper thin films deposited on polyethylene terephthalate substrate by direct current sputtering with different sputtering parameters is discussed in this work. The effects of plasma treatment with 0, 5, and 10 minutes on the thin film properties are investigated first. Various argon flow rates at 40, 50, 60 standard cubic centimeters per minute (sccm), deposition power at 30, 40, 50 W, and film thickness at 100, 200, 300 nm are also discussed. The 3-dimensional surface profilometer, micro scratch machine, and optical microscope are used to characterize the thin film properties. The results show that the increase of the plasma treatment time on the polyethylene terephthalate surface affects the roughness and critical load of the films. The critical load increases as the plasma treatment time increases. When the plasma treatment time was adjusted from 5 minutes to 10 minutes, the adhesion increased from 8.20 mN to 13.67 mN. When the argon flow rate is decreased from 60 sccm to 40 sccm, the adhesion increases from 8.27 mN to 13.67 mN. The adhesion is also increased by the condition of higher power, where the adhesion increased from 13.67 mN to 25.07 mN as the power increases from 30 W to 50 W. The adhesion of the film increases from 13.67 mN to 21.41mN as the film thickness increases from 100 nm to 300 nm. Comparing all the deposition parameters, it indicates the change of the power and thickness has much improvement on the film adhesion.alate substrate by direct current sputtering with different sputtering parameters is discussed in this work. The effects of plasma treatment with 0, 5, and 10 minutes on the thin film properties are investigated first. Various argon flow rates at 40, 50, 60 standard cubic centimeters per minute (sccm), deposition power at 30, 40, 50 W, and film thickness at 100, 200, 300 nm are also discussed. The 3-dimensional surface profilometer, micro scratch machine, and optical microscope are used to characterize the thin film properties. The results show that the increase of the plasma treatment time on the polyethylene terephthalate surface affects the roughness and critical load of the films. The critical load increases as the plasma treatment time increases. When the plasma treatment time was adjusted from 5 minutes to 10 minutes, the adhesion increased from 8.20 mN to 13.67 mN. When the argon flow rate is decreased from 60 sccm to 40 sccm, the adhesion increases from 8.27 mN to 13.67 mN. The adhesion is also increased by the condition of higher power, where the adhesion increased from 13.67 mN to 25.07 mN as the power increases from 30 W to 50 W. The adhesion of the film increases from 13.67 mN to 21.41mN as the film thickness increases from 100 nm to 300 nm. Comparing all the deposition parameters, it indicates the change of the power and thickness has much improvement on the film adhesion.

Keywords: flexible substrate, sputtering, adhesion, copper thin film

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Authors: Dimitrios Triantakonstantis, Demetris Stathakis

Abstract:

Urban areas have been expanded throughout the globe. Monitoring and modeling urban growth have become a necessity for a sustainable urban planning and decision making. Urban prediction models are important tools for analyzing the causes and consequences of urban land use dynamics. The objective of this research paper is to analyze and model the urban change, which has been occurred from 1990 to 2000 using CORINE land cover maps. The model was developed using drivers of urban changes (such as road distance, slope, etc.) under an Artificial Neural Network modeling approach. Validation was achieved using a prediction map for 2006 which was compared with a real map of Urban Atlas of 2006. The accuracy produced a Kappa index of agreement of 0,639 and a value of Cramer's V of 0,648. These encouraging results indicate the importance of the developed urban growth prediction model which using a set of available common biophysical drivers could serve as a management tool for the assessment of urban change.

Keywords: artificial neural networks, CORINE, urban atlas, urban growth prediction

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Authors: Corentin Jankowiak, Aggelos Zacharopoulos, Caterina Brandoni

Abstract:

In a context of increasing stress put on the electricity network by the decarbonization of many sectors, energy storage is likely to be the key mitigating element, by acting as a buffer between production and demand. In particular, the highest potential for storage is when connected closer to the loads. Yet, low voltage storage struggles to penetrate the market at a large scale due to the novelty and complexity of the solution, and the competitive advantage of fossil fuel-based technologies regarding regulations. Strong and reliable numerical simulations are required to show the benefits of storage located near loads and promote its development. The present study was restrained from excluding aggregated control of storage: it is assumed that the storage units operate independently to one another without exchanging information – as is currently mostly the case. A computationally light battery model is presented in detail and validated by direct comparison with a domestic battery operating in real conditions. This model is then used to develop Peak-Shaving (PS) control strategies as it is the decentralized service from which beneficial impacts are most likely to emerge. The aggregation of flatter, peak- shaved consumption profiles is likely to lead to flatter and arbitraged profile at higher voltage layers. Furthermore, voltage fluctuations can be expected to decrease if spikes of individual consumption are reduced. The crucial part to achieve PS lies in the charging pattern: peaks depend on the switching on and off of appliances in the dwelling by the occupants and are therefore impossible to predict accurately. A performant PS strategy must, therefore, include a smart charge recovery algorithm that can ensure enough energy is present in the battery in case it is needed without generating new peaks by charging the unit. Three categories of PS algorithms are introduced in detail. First, using a constant threshold or power rate for charge recovery, followed by algorithms using the State Of Charge (SOC) as a decision variable. Finally, using a load forecast – of which the impact of the accuracy is discussed – to generate PS. A performance metrics was defined in order to quantitatively evaluate their operating regarding peak reduction, total energy consumption, and self-consumption of domestic photovoltaic generation. The algorithms were tested on load profiles with a 1-minute granularity over a 1-year period, and their performance was assessed regarding these metrics. The results show that constant charging threshold or power are far from optimal: a certain value is not likely to fit the variability of a residential profile. As could be expected, forecast-based algorithms show the highest performance. However, these depend on the accuracy of the forecast. On the other hand, SOC based algorithms also present satisfying performance, making them a strong alternative when the reliable forecast is not available.

Keywords: decentralised control, domestic integrated batteries, electricity network performance, peak-shaving algorithm

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Authors: Y. T. Lee, J. H. Na, S. H. Kim, S. U. Hong

Abstract:

In this study, an experimental research for estimation of slab depth, column size and location of rebar of concrete specimen is conducted using the Impact Echo Method (IE) based on stress wave among non-destructive test methods. Estimation of slab depth had total length of 1800×300 and 6 different depths including 150 mm, 180 mm, 210 mm, 240 mm, 270 mm and 300 mm. The concrete column specimen was manufactured by differentiating the size into 300×300×300 mm, 400×400×400 mm and 500×500×500 mm. In case of the specimen for estimation of rebar, rebar of ∅22 mm was used in a specimen of 300×370×200 and arranged at 130 mm and 150 mm from the top to the rebar top. As a result of error rate of slab depth was overall mean of 3.1%. Error rate of column size was overall mean of 1.7%. Mean error rate of rebar location was 1.72% for top, 1.19% for bottom and 1.5% for overall mean showing relative accuracy.

Keywords: impact echo method, estimation, slab depth, column size, rebar location, concrete

Procedia PDF Downloads 354