Search results for: metallurgical image processing

Authors: Syed Mahbubuz Zaman, A. B. M. Abrar Haque, Mehedi Hassan Nayeem, Misbah Uddin Sagor

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Everyday e-mails are being used by millions of people as an effective form of communication over the Internet. Although e-mails allow high-speed communication, there is a constant threat known as spam. Spam e-mail is often called junk e-mails which are unsolicited and sent in bulk. These unsolicited emails cause security concerns among internet users because they are being exposed to inappropriate content. There is no guaranteed way to stop spammers who use static filters as they are bypassed very easily. In this paper, a smart system is proposed that will be using neural networks to approach spam in a different way, and meanwhile, this will also detect the most relevant features that will help to design the spam filter. Also, a comparison of different parameters for different neural network models has been shown to determine which model works best within suitable parameters.

Keywords: long short-term memory, bidirectional long short-term memory, gated recurrent unit, natural language processing, natural language processing

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Authors: Bo Wang

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The geometric processing of multi-source remote sensing data using control data of different scale and different accuracy is an important research direction of multi-platform system for earth observation. In the existing block bundle adjustment methods, as the controlling information in the adjustment system, the approach using single observation scale and precision is unable to screen out the control information and to give reasonable and effective corresponding weights, which reduces the convergence and adjustment reliability of the results. Referring to the relevant theory and technology of quotient space, in this project, several subjects are researched. Multi-layer quotient space of multi-geometric features is constructed to describe and filter control data. Normalized granularity merging mechanism of multi-layer control information is studied and based on the normalized scale factor, the strategy to optimize the weight selection of control data which is less relevant to the adjustment system can be realized. At the same time, geometric positioning experiment is conducted using multi-source remote sensing data, aerial images, and multiclass control data to verify the theoretical research results. This research is expected to break through the cliché of the single scale and single accuracy control data in the adjustment process and expand the theory and technology of photogrammetry. Thus the problem to process multi-source remote sensing data will be solved both theoretically and practically.

Keywords: multi-source image geometric process, high precision geometric positioning, quotient space of multi-geometric features, optimized weight selection

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Authors: Liu Jia’nan

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The default accounts hold the view that there exists a kind of scalar implicature which can be processed without context and own a psychological privilege over other scalar implicatures which depend on context. In contrast, the Relevance Theorist regards context as a must because all the scalar implicatures have to meet the need of relevance in discourse. However, in Katsos, the experimental results showed: Although quantitatively the adults rejected under-informative utterance with lexical scales (context-independent) and the ad hoc scales (context-dependent) at almost the same rate, adults still regarded the violation of utterance with lexical scales much more severe than with ad hoc scales. Neither default account nor Relevance Theory can fully explain this result. Thus, there are two questionable points to this result: (1) Is it possible that the strange discrepancy is due to other factors instead of the generation of scalar implicature? (2) Are the ad hoc scales truly formed under the possible influence from mental context? Do the participants generate scalar implicatures with ad hoc scales instead of just comparing semantic difference among target objects in the under- informative utterance? In my Experiment 1, the question (1) will be answered by repetition of Experiment 1 by Katsos. Test materials will be showed by PowerPoint in the form of pictures, and each procedure will be done under the guidance of a tester in a quiet room. Our Experiment 2 is intended to answer question (2). The test material of picture will be transformed into the literal words in DMDX and the target sentence will be showed word-by-word to participants in the soundproof room in our lab. Reading time of target parts, i.e. words containing scalar implicatures, will be recorded. We presume that in the group with lexical scale, standardized pragmatically mental context would help generate scalar implicature once the scalar word occurs, which will make the participants hope the upcoming words to be informative. Thus if the new input after scalar word is under-informative, more time will be cost for the extra semantic processing. However, in the group with ad hoc scale, scalar implicature may hardly be generated without the support from fixed mental context of scale. Thus, whether the new input is informative or not does not matter at all, and the reading time of target parts will be the same in informative and under-informative utterances. People’s mind may be a dynamic system, in which lots of factors would co-occur. If Katsos’ experimental result is reliable, will it shed light on the interplay of default accounts and context factors in scalar implicature processing? We might be able to assume, based on our experiments, that one single dominant processing paradigm may not be plausible. Furthermore, in the processing of scalar implicature, the semantic interpretation and the pragmatic interpretation may be made in a dynamic interplay in the mind. As to the lexical scale, the pragmatic reading may prevail over the semantic reading because of its greater exposure in daily language use, which may also lead the possible default or standardized paradigm override the role of context. However, those objects in ad hoc scale are not usually treated as scalar membership in mental context, and thus lexical-semantic association of the objects may prevent their pragmatic reading from generating scalar implicature. Only when the sufficient contextual factors are highlighted, can the pragmatic reading get privilege and generate scalar implicature.

Keywords: scalar implicature, ad hoc scale, dynamic interplay, default account, Mandarin Chinese processing

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Authors: K. A. Ghazaryan, T. H. Derdzyan

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For assessment of the soils pollution level of the open mine and tailing dump of surrounding territories of Akhtala ore processing combine by heavy metals in 2013 collected soil samples and analyzed for different heavy metals, such as Cu, Zn, Pb, Ni and Cd. The main soil type in the study sites was the mountain cambisol. To classify soil pollution level contamination indices like Contamination factors (Cf), Degree of contamination (Cd), Pollution load index (PLI) and Geoaccumulation index (I-geo) are calculated. The distribution pattern of trace metals in the soil profile according to I geo, Cf and Cd values shows that the soil is very polluted. And also the PLI values for the 19 sites were >1, which indicates deterioration of site quality.

Keywords: soils pollution, heavy metal, geoaccumulation index, pollution load index, contamination factor

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Authors: O. Hinrichs, H. Franz, G. Reiter

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Electron guns have a key function in a series of thermal processes, like EB (electron beam) melting, evaporation or welding. These techniques need a high-intensity continuous electron beam that defocuses itself due to high space charge forces. A proper beam transport throughout the magnetic focusing system can be ensured by a space charge compensation via residual gas ions. The different pressure stages in the EB gun cause various degrees of compensation. A numerical model was installed to simulate realistic charge distributions within the beam by using CST-Particle Studio code. We will present current status of beam dynamic simulations. This contribution will focus on the creation of space charge ions and their influence on beam and gun components. Furthermore, the beam transport in the gun will be shown for different beam parameters. The electron source allows to produce beams with currents of 3 A to 15 A and energies of 40 keV to 45 keV.

Keywords: beam dynamic simulation, space charge compensation, thermionic electron source, EB melting, EB thermal processing

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Authors: Chan Kwong Tung

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Since Baddeley and Hitch’s seminal research in 1974 on working memory (WM), this topic has been of great interest to language educators. Although there are some variations in the definitions of WM, recent findings in WM have contributed vastly to our understanding of language learning, especially its effects on second language acquisition (SLA). For example, the phonological component of WM (PWM) and the executive component of WM (EWM) have been found to be positively correlated with language learning. This paper discusses two general, yet highly relevant WM findings that could directly affect the effectiveness of Chinese Language (CL) vocabulary teaching and learning, as well as the quality of its assessment. First, PWM is found to be critical for the long-term learning of phonological forms of new words. Second, EWM is heavily involved in interpreting the semantic characteristics of new words, which consequently affects the quality of learners’ reading comprehension. These two ideas are hardly discussed in the Chinese literature, both conceptual and empirical. While past vocabulary acquisition studies have mainly focused on the cognitive-processing approach, active processing, ‘elaborate processing’ (or lexical elaboration) and other effective learning tasks and strategies, it is high time to balance the spotlight to the WM (particularly PWM and EWM) to ensure an optimum control on the teaching and learning effectiveness of such approaches, as well as the validity of this language assessment. Given the unique phonological, orthographical and morphological properties of the CL, this discussion will shed some light on the vocabulary acquisition of this Sino-Tibetan language family member. Together, these two WM concepts could have crucial implications for the design, development, and planning of vocabularies and ultimately reading comprehension teaching and assessment in language education. Hopefully, this will raise an awareness and trigger a dialogue about the meaning of these findings for future language teaching, learning, and assessment.

Keywords: Chinese Language, working memory, vocabulary assessment, vocabulary teaching

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Authors: Chunyue Liu, Hongxing Jiang

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Traditional water depth survey of wetland habitats used by waterbirds needs intensive labor, time and money. The optical remote sensing image relies on passive multispectral scanner data has been widely employed to study estimate water depth. This paper presents an innovative method for developing the water depth model based on the characteristics of visible and thermal infrared spectra of Landsat ETM+ image, combing with 441 field water depth data at Etoupao shallow wetland. The wetland is located at Momoge National Nature Reserve of Northeast China, where the largest stopover habitat along the eastern flyway of globally, critically-endangered Siberian Cranes are. The cranes mainly feed on the tubers of emergent aquatic plants such as Scirpus planiculmis and S. nipponicus. The effective water control is a critical step for maintaining the production of tubers and food availability for this crane. The model employing multi-band approach can effectively simulate water depth for this shallow wetland. The model parameters of NDVI and GREEN indicated the vegetation growth and coverage affecting the reflectance from water column change are uneven. Combining with the field-observed water level at the same date of image acquisition, the digital elevation model (DEM) for the underwater terrain was generated. The wetland area and water volume of different water levels were then calculated from the DEM using the function of Area and Volume Statistics under the 3D Analyst of ArcGIS 10.0. The findings provide good references to effectively monitor changes in water level and water demand, develop practical plan for water level regulation and water management, and to create best foraging habitats for the cranes. The methods here can be adopted for the bottom topography simulation and water management in waterbirds’ habitats, especially in the shallow wetlands.

Keywords: remote sensing, water depth reversion, shallow wetland habitat management, siberian crane

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Authors: Christian Röling, Elena Y. Poimanova, Vladimir V. Bruevich

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Here we demonstrate a non-destructive optical technique to localize and characterize single crystals of semiconductive organic materials – Spectroscopic Imaging Ellipsometry. With a combination of microscopy and ellipsometry, it is possible to characterize even micro-sized thin film crystals on plane surface regarding anisotropy, optical properties, crystalline domains and thickness. The semiconducting thiophene-phenylene co-oligomer 1,4-bis(5'-hexyl-[2,2'-bithiophen]-5-yl)benzene (dHex-TTPTT) crystals were grown by solvent based self-assembly technique on silicon substrate with 300 nm thermally silicon dioxide. The ellipsometric measurements were performed with an Ep4-SE (Accurion). In an ellipsometric high-contrast image of the complete sample, we have localized high-quality single crystals. After demonstrating the uniaxial anisotropy of the crystal by using Müller-Matrix imaging ellipsometry, we determined the optical axes by rotating the sample and performed spectroscopic measurements (λ = 400-700 nm) in 5 nm intervals. The optical properties were described by using a Lorentz term in the Ep4-Model. After determining the dispersion of the crystals, we converted a recorded Delta and Psi-map into a 2D thickness image. Based on a quantitative analysis of the resulting thickness map, we have calculated the height of a molecular layer (3.49 nm).

Keywords: anisotropy, ellipsometry, SCFET, thin film

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Authors: Diana Mariz Catangay, Irish-Ann Montano, Frances Janine Suyat

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As an active pedestal for student’s interaction with both issues happening inside the school and out; may it be political, societal, international, or other current events, a school paper should at least meet the standard of providing a representation of the school’s morals and values and help the institution uplift its image. The researchers seek to ascertain how the two student publications from the Philippines’ two prime state universities, the University of the Philippines’ Philippine Collegian, and the Polytechnic University of the Philippines’ the Catalyst, presents iii their school through balanced journalism and objective documentation. The objectives include determining the number of school-related articles published versus those articles that are concerned outside the school’s jurisdiction, analyzing the insight it provides on the image of the university, assessing the similarities and/or differences between the two publications, and, finally, coming up with the conclusion of how the two newspapers uses their medium to present their respective schools. The research used the quantitative method of research in order to further analyze the articles that will serve as bases in coming up with the right conclusion based on the objectives of the study. Coding sheets and coding guides are utilized for the chosen research method. The gathered findings will then be interpreted as fitting to the goal of the research.

Keywords: content analysis, journalistic presentation, student publications, state universities

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Authors: O. Alelweet, S. Pavia

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In order to face current compelling environmental problems affecting the planet, the construction industry needs to adapt. It is widely acknowledged that there is a need for durable, high-performance, low-greenhouse gas emission binders that can be used as an alternative to Portland cement (PC) to lower the environmental impact of construction. Alkali activated materials (AAMs) are considered a more sustainable alternative to PC materials. The binders of AAMs result from the reaction of an alkali metal source and a silicate powder or precursor which can be a calcium silicate or an aluminosilicate-rich material. This paper evaluates the particle size, specific surface area, chemical and mineral composition and amorphousness of silicate materials (most industrial waste locally produced in Ireland and Saudi Arabia) to develop alkali-activated binders that can replace PC resources in specific applications. These include recycled ceramic brick, bauxite, illitic clay, fly ash and metallurgical slag. According to the results, the wastes are reactive and comply with building standards requirements. The study also evidenced that the reactivity of the Saudi bauxite (with significant kaolinite) can be enhanced on thermal activation; and high calcium in the slag will promote reaction; which should be possible with low alkalinity activators. The wastes evidenced variable water demands that will be taken into account for mixing with the activators. Finally, further research is proposed to further determine the reactive fraction of the clay-based precursors.

Keywords: alkali activated materials, alkali-activated binders, sustainable building materials, recycled ceramic brick, bauxite, red mud, clay, fly ash, metallurgical slags, particle size, chemical and mineral composition and amorphousness, water demand, particle density

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Authors: Hyojin Lim, Cuong Nguyen Khac, Ho-Youl Jung

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In this paper, we propose moving object detection method which is helpful for driver to safely take his/her car out of parking lot. When moving objects such as motorbikes, pedestrians, the other cars and some obstacles are detected at the rear-side of host vehicle, the proposed algorithm can provide to driver warning. We assume that the host vehicle is just before departure. Gaussian Mixture Model (GMM) based background subtraction is basically applied. Pre-processing such as smoothing and post-processing as morphological filtering are added.We examine “which color space has better performance for detection of moving objects?” Three color spaces including RGB, YCbCr, and Y are applied and compared, in terms of detection rate. Through simulation, we prove that RGB space is more suitable for moving object detection based on background subtraction.

Keywords: gaussian mixture model, background subtraction, moving object detection, color space, morphological filtering

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Authors: Nizar Caraka Trihanasia, Suparwoko

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The purpose of this paper is to analyze the design model of city gates on arterial roads as Yogyakarta’s “Istimewa” (special) identity. City marketing has become a trend among cities in the past few years. It began to compete with each other in promoting their identity to the world. One of the easiest ways to recognize the identity is by knowing the image of the city which can be seen through architectural buildings or urban elements. The idea is to recognize how the image of the city can represent Yogyakarta’s identity, which is limited to the contribution of the city gates distinctiveness on Yogyakarta urban area. This study has concentrated on the aspect of city gates as built environment that provides a diversity, configuration and scale of development that promotes a sense of place and community. The visual analysis will be conducted to interpreted the existing Yogyakarta city gates (as built environment) focussing on some variables of 1) character and pattern, 2) circulation system establishment, and 3) open space utilisation. Literature review and site survey are also conducted to understand the relationship between the built environment and the sense of place in the community. This study suggests that visually the Yogyakarta city gate model has strong visual characters and pattern by using the concept of a sense of place of Yogyakarta community value.

Keywords: visual analysis, model, Yogyakarta “Istimewa”, citygates

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Authors: Rosa Sobreira, Paula Arriscado

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Marketers are aware that media relations is an important touch point, which is also cheaper, to bring their products and their brands to the consumer. They recognize the role of journalists as moderators and transformers of public opinion, and they realize their influence on brand image. And also, they know that readers, listeners, viewers and internet users "believe" more what they read, hear and see in the news than in an advertisement. The study is focused on the automotive industry and analyses the news published about three brands that share industrial facilities and components. We wanted to understand the role of the information created by the brand`s media team in the journalists’ work, and the impact on management, activation and differentiation of brands and their products` attributes and benefits. Based on a qualitative methodology, the analysis focused on press news, making comparison between media coverage and their “narratives” about the three cars from different brands. The results point to the fact that journalists easily integrate speech from the marks on their products. In the case of this study, we found that apart from the description of the many similarities between the three cars, the average speech also "struggled" for revealing the attributes that differentiate them. This interpretation of the results helps us to understand the "marriage" between branding and media. We believe also this paper let us to understand how journalists, through news, join the speech of the brands.

Keywords: brand management, media relations, differentiation, positioning

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Authors: Arnab Majumdar, Sanjoy Sadhukhan

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Although gun barrel steels are an important variety from defense view point, available literatures are very limited. In the present work, an IF grade Ni-Cr-Mo-V high strength low alloy steel is produced in Electric Earth Furnace-ESR Route. Ingot was hot forged to desired dimension with a reduction ratio of 70-75% followed by homogenization, hardening and tempering treatment. Sample chemistry, NMIR, macro and micro structural analyses were done. Mechanical properties which include tensile, impact, and fracture toughness were studied. Ultrasonic testing was done to identify internal flaws. The existing high strength low alloy Ni-Cr-Mo-V steel shows improved properties in modified processing route and heat treatment schedule in comparison to properties noted earlier for manufacturing of gun barrels. The improvement in properties seems to withstand higher explosive loads with the same amount of steel in gun barrel application.

Keywords: gun barrel steels, IF grade, chemistry, physical properties, thermal and mechanical processing, mechanical properties, ultrasonic testing

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Authors: Faisal Alshammari, Abdulmajid Addali, Mosab Alrashed, Taihiret Alhashan

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The application of acoustic emission techniques is gaining popularity, as it can monitor the condition of gears and bearings and detect early symptoms of a defect in the form of pitting, wear, and flaking of surfaces. Early detection of these defects is essential as it helps to avoid major failures and the associated catastrophic consequences. Signal processing techniques are required for early defect detection – in this article, a time domain technique called the Energy Index (EI) is used. This article presents an investigation into the Energy Index’s effectiveness to detect early-stage defect initiation and deterioration, and compares it with the common r.m.s. index, Kurtosis, and the Kolmogorov-Smirnov statistical test. It is concluded that EI is a more effective technique for monitoring defect initiation and development than other statistical parameters.

Keywords: acoustic emission, signal processing, kurtosis, Kolmogorov-Smirnov test

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Authors: Ravneet Kaur, Joydeep Acharya, Sudhanshu Gaur

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Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

Keywords: human machine interface, industrial internet of things, internet of things, optical character recognition, video analytics

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Authors: Yongxin Chen, Min Zhang

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As industrial enterprises are the primary source of national pollution, environmental information disclosure is a crucial way to demonstrate to stakeholders the work they have done in fulfilling their environmental responsibilities and accepting social supervision. In the era of the digital economy, many companies, actively embracing the opportunities that come with digital transformation, have begun to apply digital technology to information collection and disclosure within the enterprise. However, less is known about the relationship between digital transformation and environmental disclosure. This study investigates how enterprise digital transformation affects environmental disclosure in 643 Chinese industrial companies, according to information processing theory. What is intriguing is that the depth (size) and breadth (diversity) of environmental disclosure linearly increase with the rise in the collection, processing, and analytical capabilities in the digital transformation process. However, the volume of data will grow exponentially, leading to a marginal increase in the economic and environmental costs of utilizing, storing, and managing data. In our empirical findings, linearly increasing benefits and marginal costs create a unique inverted U-shaped relationship between the degree of digital transformation and environmental disclosure in the Chinese industrial sector. Besides, based on the upper echelons theory, we also propose that the top management team with high stability and managerial capabilities will invest more effort and expense into improving environmental disclosure quality, lowering the carbon footprint caused by digital technology, maintaining data security etc. In both these contexts, the increasing marginal cost curves would become steeper, weakening the inverted U-shaped slope between DT and ED.

Keywords: digital transformation, environmental disclosure, the top management team, information processing theory, upper echelon theory

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Authors: Amandeep Singh, Niraj Bala

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In the last decades, light-weight materials such as magnesium matrix composites have become hot topic for material research due to their excellent mechanical and physical properties. However, relatively very less work has been done related to the wear behavior of these composites. Magnesium matrix composites have wide applications in automobile and aerospace sector. In this review, attempt has been done to collect the literature related to wear behavior of magnesium matrix composites fabricated through various processing techniques such as stir casting, powder metallurgy, friction stir processing etc. Effect of different reinforcements, reinforcement content, reinforcement size, wear load, sliding speed and time have been studied by different researchers in detail. Wear mechanism under different experimental condition has been reviewed in detail. The wear resistance of magnesium and its alloys can be enhanced with the addition of different reinforcements. Wear resistance can further be enhanced by increasing the percentage of added reinforcements. Increase in applied load during wear test leads to increase in wear rate of magnesium composites.

Keywords: hardness, magnesium matrix composites, reinforcement, wear

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Authors: Anaam H. Al-ShaikhAli, Mansour A. Al-Herz

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The research leverages the proven HS-FCC technology to directly crack crude oils into petrochemical building blocks. Crude oils were subjected to an optimized hydro-processing process where metal contaminants and sulfur were reduced to an acceptable level for feeding the crudes into the HS-FCC technology. The hydro-processing is achieved through a fixed-bed reactor which is composed of 3 layers of catalysts. The crude oil is passed through a dementalization catalyst followed by a desulfurization catalyst and finally a de-aromatization catalyst. The hydroprocessing was conducted at an optimized liquid hourly space velocity (LHSV), temperature, and pressure for an optimal reduction of metals and sulfur from the crudes. The hydro-processed crudes were then fed into a micro activity testing (MAT) unit to simulate the HS-FCC technology. The catalytic cracking of crude oils was conducted over tailored catalyst formulations under an optimized catalyst/oil ratio and cracking temperature for optimal production of total light olefins.

Keywords: petrochemical, catalytic cracking, catalyst synthesis, HS-FCC technology

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Authors: Chia-Chi Chang, Chuan-Bi Lin, Chia-Min Chan

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Most ZigBee sensor networks to date make use of nodes with limited processing, communication, and energy capabilities. Energy consumption is of great importance in wireless sensor applications as their nodes are commonly battery-driven. Once ZigBee nodes are deployed outdoors, limited power may make a sensor network useless before its purpose is complete. At present, there are two strategies for long node and network lifetime. The first strategy is saving energy as much as possible. The energy consumption will be minimized through switching the node from active mode to sleep mode and routing protocol with ultra-low energy consumption. The second strategy is to evaluate the energy consumption of sensor applications as accurately as possible. Erroneous energy model may render a ZigBee sensor network useless before changing batteries. In this paper, we present a ZigBee wireless sensor node with four key modules: a processing and radio unit, an energy harvesting unit, an energy storage unit, and a sensor unit. The processing unit uses CC2530 for controlling the sensor, carrying out routing protocol, and performing wireless communication with other nodes. The harvesting unit uses a 2W solar panel to provide lasting energy for the node. The storage unit consists of a rechargeable 1200 mAh Li-ion battery and a battery charger using a constant-current/constant-voltage algorithm. Our solution to extend node lifetime is implemented. Finally, a long-term sensor network test is used to exhibit the functionality of the solar powered system.

Keywords: ZigBee, Li-ion battery, solar panel, CC2530

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Authors: Yao-Hong Tsai

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Due to the sensor technology, video surveillance has become the main way for security control in every big city in the world. Surveillance is usually used by governments for intelligence gathering, the prevention of crime, the protection of a process, person, group or object, or the investigation of crime. Many surveillance systems based on computer vision technology have been developed in recent years. Moving target tracking is the most common task for Unmanned Aerial Vehicle (UAV) to find and track objects of interest in mobile aerial surveillance for civilian applications. The paper is focused on vision-based collision avoidance for UAVs by recurrent neural networks. First, images from cameras on UAV were fused based on deep convolutional neural network. Then, a recurrent neural network was constructed to obtain high-level image features for object tracking and extracting low-level image features for noise reducing. The system distributed the calculation of the whole system to local and cloud platform to efficiently perform object detection, tracking and collision avoidance based on multiple UAVs. The experiments on several challenging datasets showed that the proposed algorithm outperforms the state-of-the-art methods.

Keywords: unmanned aerial vehicle, object tracking, deep learning, collision avoidance

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Authors: Katerina Nerantzaki, Panayiota Metallidou, Anastasia Efklides

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The aim of the study was to investigate: (a) changes in the intensity of various epistemic emotions during cognitive processing in a decision-making task and (b) their associations with metacognitive feelings of difficulty and confidence. One hundred and fifty-two undergraduate university students were asked individually to read in the e-prime environment decision-making scenarios about moral dilemmas concerning self-driving cars, which differed in the level of conflict they produced, and then to make a choice between two options. Further, the participants were asked to rate on a four-point scale four epistemic emotions (surprise, curiosity, confusion, and wonder) and two metacognitive feelings (feeling of difficulty and feeling of confidence) after making their choice in each scenario. Changes in cognitive processing due to the level of conflict affected differently the intensity of the specific epistemic emotions. Further, there were interrelations of epistemic emotions with metacognitive feelings.

Keywords: confusion, curiosity, epistemic emotions, metacognitive experiences, surprise

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Authors: Wei Zhang, Yan He, Yan Wang, Yufeng Li, Chuanpeng Hao

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Surface roughness is an important index for evaluating surface quality, needs to be accurately measured to ensure the performance of the workpiece. The roughness measurement based on machine vision involves various image features, some of which are redundant. These redundant features affect the accuracy and speed of the visual approach. Previous research used correlation analysis methods to select the appropriate features. However, this feature analysis is independent and cannot fully utilize the information of data. Besides, blindly reducing features lose a lot of useful information, resulting in unreliable results. Therefore, the focus of this paper is on providing a redundant feature removal approach for visual roughness measurement. In this paper, the statistical methods and gray-level co-occurrence matrix(GLCM) are employed to extract the texture features of machined images effectively. Then, the principal component analysis(PCA) is used to fuse all extracted features into a new one, which reduces the feature dimension and maintains the integrity of the original information. Finally, the relationship between new features and roughness is established by the support vector machine(SVM). The experimental results show that the approach can effectively solve multi-feature information redundancy of machined surface images and provides a new idea for the visual evaluation of surface roughness.

Keywords: feature analysis, machine vision, PCA, surface roughness, SVM

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Authors: Mostefa Hamrat, Bensaid Boulekbache, Mohamed Chemrouk, Sofiane Amziane

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The paper presents the results of an experimental work on the flexural behaviour of two types of concrete in terms of the progressive cracking process until failure and the crack opening, and beam deflection, using Digital Image Correlation (DIC) technique. At serviceability limit states, comparisons of the building code equations and the equations developed by some researchers for the short-term deflections and crack widths have been made using the reinforced concrete test beams. The experimental results show that the addition of steel fibers increases the first cracking load and amplify the number of cracks that conducts to a remarkable decreasing in the crack width with an increasing in ductility. This study also shows that there is a good agreement between the deflection values for RC beams predicted by the major codes (Eurocode2, ACI 318, and the CAN/CSA-S806) and the experimental results for beams with steel fibers at service load. The most important added benefit of the DIC technique is that it allows detecting the first crack with a high precision easily measures the crack opening and follows the progressive cracking process until failure of reinforced concrete members.

Keywords: beams, digital image correlation (DIC), deflection, crack width, serviceability, codes provisions

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Authors: Yao Lu, Xiuguo Zhang, Zhiying Cao

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In this paper, Load Balancing idea is used in the Web service mobile host. The main idea of Load Balancing is to establish a one-to-many mapping mechanism: An entrance-mapping request to plurality of processing node in order to realize the dividing and assignment processing. Because the mobile host is a resource constrained environment, there are some Web services which cannot be completed on the mobile host. When the mobile host resource is not enough to complete the request, Load Balancing scheduler will divide the request into a plurality of sub-requests and transfer them to different auxiliary mobile hosts. Auxiliary mobile host executes sub-requests, and then, the results will be returned to the mobile host. Service request integrator receives results of sub-requests from the auxiliary mobile host, and integrates the sub-requests. In the end, the complete request is returned to the client. Experimental results show that this technology adopted in this paper can complete requests and have a higher efficiency.

Keywords: Dinic, load balancing, mobile host, web service

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Authors: Ben Soltane Cheima, Ittansa Yonas Kelbesa

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Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: feature extraction, speaker modeling, feature matching, Mel frequency cepstrum coefficient (MFCC), Gaussian mixture model (GMM), vector quantization (VQ), Linde-Buzo-Gray (LBG), expectation maximization (EM), pre-processing, voice activity detection (VAD), short time energy (STE), background noise statistical modeling, closed-set tex-independent speaker identification system (CISI)

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Authors: Simon Caba, Raja Abou Ackl, Svend Rasmussen, Nicholas E. Pedersen

Abstract:

It is a challenge to directly monitor cavitation in a pump application during operation because of a lack of visual access to validate the presence of cavitation and its form of appearance. In this work, experimental investigations are carried out in an inline single-stage centrifugal pump with optical access. Hence, it gives the opportunity to enhance the value of CFD tools and standard cavitation measurements. Experiments are conducted using two impellers running in the same volute at 3000 rpm and the same flow rate. One of the impellers used is optimized for lower NPSH₃% by its blade design, whereas the other one is manufactured using a standard casting method. The cavitation is detected by pump performance measurements, vibration measurements and high-speed image recordings. The head drop and the pump casing vibration caused by cavitation are correlated with the visual appearance of the cavitation. The vibration data is recorded in an axial direction of the impeller using accelerometers recording at a sample rate of 131 kHz. The vibration frequency domain data (up to 20 kHz) and the time domain data are analyzed as well as the root mean square values. The high-speed recordings, focusing on the impeller suction side, are taken at 10,240 fps to provide insight into the flow patterns and the cavitation behavior in the rotating impeller. The videos are synchronized with the vibration time signals by a trigger signal. A clear correlation between cloud collapses and abrupt peaks in the vibration signal can be observed. The vibration peaks clearly indicate cavitation, especially at higher NPSHA values where the hydraulic performance is not affected. It is also observed that below a certain NPSHA value, the cavitation started in the inlet bend of the pump. Above this value, cavitation occurs exclusively on the impeller blades. The impeller optimized for NPSH₃% does show a lower NPSH₃% than the standard impeller, but the head drop starts at a higher NPSHA value and is more gradual. Instabilities in the head drop curve of the optimized impeller were observed in addition to a higher vibration level. Furthermore, the cavitation clouds on the suction side appear more unsteady when using the optimized impeller. The shape and location of the cavitation are compared to 3D fluid flow simulations. The simulation results are in good agreement with the experimental investigations. In conclusion, these investigations attempt to give a more holistic view on the appearance of cavitation by comparing the head drop, vibration spectral data, vibration time signals, image recordings and simulation results. Data indicates that a criterion for cavitation detection could be derived from the vibration time-domain measurements, which requires further investigation. Usually, spectral data is used to analyze cavitation, but these investigations indicate that the time domain could be more appropriate for some applications.

Keywords: cavitation, centrifugal pump, head drop, high-speed image recordings, pump vibration

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Authors: V. E. Messerle, O. A. Lavrichshev, A. B. Ustimenko

Abstract:

Currently and in the foreseeable future (up to 2100), the global economy is oriented to the use of organic fuel, mostly, solid fuels, the share of which constitutes 40% in the generation of electric power. Therefore, the development of technologies for their effective and environmentally friendly application represents a priority problem nowadays. This work presents the results of thermodynamic and experimental investigations of plasma technology for processing of low-grade coals. The use of this technology for producing target products (synthesis gas, hydrogen, technical carbon, and valuable components of mineral mass of coals) meets the modern environmental and economic requirements applied to basic industrial sectors. The plasma technology of coal processing for the production of synthesis gas from the coal organic mass (COM) and valuable components from coal mineral mass (CMM) is highly promising. Its essence is heating the coal dust by reducing electric arc plasma to the complete gasification temperature, when the COM converts into synthesis gas, free from particles of ash, nitrogen oxides and sulfur. At the same time, oxides of the CMM are reduced by the carbon residue, producing valuable components, such as technical silicon, ferrosilicon, aluminum and carbon silicon, as well as microelements of rare metals, such as uranium, molybdenum, vanadium, titanium. Thermodynamic analysis of the process was made using a versatile computation program TERRA. Calculations were carried out in the temperature range 300 - 4000 K and a pressure of 0.1 MPa. Bituminous coal with the ash content of 40% and the heating value 16,632 kJ/kg was taken for the investigation. The gaseous phase of coal processing products includes, basically, a synthesis gas with a concentration of up to 99 vol.% at 1500 K. CMM components completely converts from the condensed phase into the gaseous phase at a temperature above 2600 K. At temperatures above 3000 K, the gaseous phase includes, basically, Si, Al, Ca, Fe, Na, and compounds of SiO, SiH, AlH, and SiS. The latter compounds dissociate into relevant elements with increasing temperature. Complex coal conversion for the production of synthesis gas from COM and valuable components from CMM was investigated using a versatile experimental plant the main element of which was plug and flow plasma reactor. The material and thermal balances helped to find the integral indicators for the process. Plasma-steam gasification of the low-grade coal with CMM processing gave the synthesis gas yield 95.2%, the carbon gasification 92.3%, and coal desulfurization 95.2%. The reduced material of the CMM was found in the slag in the form of ferrosilicon as well as silicon and iron carbides. The maximum reduction of the CMM oxides was observed in the slag from the walls of the plasma reactor in the areas with maximum temperatures, reaching 47%. The thusly produced synthesis gas can be used for synthesis of methanol, or as a high-calorific reducing gas instead of blast-furnace coke as well as power gas for thermal power plants. Reduced material of CMM can be used in metallurgy.

Keywords: gasification, mineral mass, organic mass, plasma, processing, solid fuel, synthesis gas, valuable components

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Authors: Gemma García López

Abstract:

The goal of this study is to analyze if search queries carried out in search engines such as Google, can offer emotional information about the user that performs them. Knowing the emotional state in which the Internet user is located can be a key to achieve the maximum personalization of content and the detection of worrying behaviors. For this, two studies were carried out using tools with advanced natural language processing techniques. The first study determines if a query can be classified as positive, negative or neutral, while the second study extracts emotional content from words and applies the categorical and dimensional models for the representation of emotions. In addition, we use search queries in Spanish and English to establish similarities and differences between two languages. The results revealed that text search queries performed by users on the Internet can be classified emotionally. This allows us to better understand the emotional state of the user at the time of the search, which could involve adapting the technology and personalizing the responses to different emotional states.

Keywords: emotion classification, text search queries, emotional analysis, sentiment analysis in text, natural language processing

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Authors: Kazunori Nomura, Hiromichi Ogi, Masaumi Nakahara, Sou Watanabe, Atsuhiro Shibata

Abstract:

Chemical Processing Facility of Japan Atomic Energy Agency is a basic research field for advanced back-end technology developments with using actual high-level radioactive materials such as irradiated fuels from the fast reactor, high-level liquid waste from reprocessing plant. In the nature of a research facility, various kinds of chemical reagents have been offered for fundamental tests. Most of them were treated properly and stored in the liquid waste vessel equipped in the facility, but some were not treated and remained at the experimental space as a kind of legacy waste. It is required to treat the waste in safety. On the other hand, we formulated the Medium- and Long-Term Management Plan of Japan Atomic Energy Agency Facilities. This comprehensive plan considers Chemical Processing Facility as one of the facilities to be decommissioned. Even if the plan is executed, treatment of the “legacy” waste beforehand must be a necessary step for decommissioning operation. Under this circumstance, we launched a collaborative research project called the STRAD project, which stands for Systematic Treatment of Radioactive liquid waste for Decommissioning, in order to develop the treatment processes for wastes of the nuclear research facility. In this project, decomposition methods of chemicals causing a troublesome phenomenon such as corrosion and explosion have been developed and there is a prospect of their decomposition in the facility by simple method. And solidification of aqueous or organic liquid wastes after the decomposition has been studied by adding cement or coagulants. Furthermore, we treated experimental tools of various materials with making an effort to stabilize and to compact them before the package into the waste container. It is expected to decrease the number of transportation of the solid waste and widen the operation space. Some achievements of these studies will be shown in this paper. The project is expected to contribute beneficial waste management outcome that can be shared world widely.

Keywords: chemical processing facility, medium- and long-term management plan of JAEA facilities, STRAD project, treatment of radioactive waste

Procedia PDF Downloads 142