Search results for: Learning materials

Authors: M. Beusink, E. W. C. Coenen

Abstract:

The increased application of novel structural materials, such as high grade asphalt, concrete and laminated composites, has sparked the need for a better understanding of the often complex, non-linear mechanical behavior of such materials. The effective macroscopic mechanical response is generally dependent on the applied load path. Moreover, it is also significantly influenced by the microstructure of the material, e.g. embedded fibers, voids and/or grain morphology. At present, multiscale techniques are widely adopted to assess micro-macro interactions in a numerically efficient way. Computational homogenization techniques have been successfully applied over a wide range of engineering cases, e.g. cases involving first order and second order continua, thin shells and cohesive zone models. Most of these homogenization methods rely on Representative Volume Elements (RVE), which model the relevant microstructural details in a confined volume. Imposed through kinematical constraints or boundary conditions, a RVE can be subjected to a microscopic load sequence. This provides the RVE's effective stress-strain response, which can serve as constitutive input for macroscale analyses. Simultaneously, such a study of a RVE gives insight into fine scale phenomena such as microstructural damage and its evolution. It has been reported by several authors that the type of boundary conditions applied to the RVE affect the resulting homogenized stress-strain response. As a consequence, dedicated boundary conditions have been proposed to appropriately deal with this concern. For the specific case of a planar assumption for the analyzed structure, e.g. plane strain, axisymmetric or plane stress, this assumption needs to be addressed consistently in all considered scales. Although in many multiscale studies a planar condition has been employed, the related impact on the multiscale solution has not been explicitly investigated. This work therefore focuses on the influence of the planar assumption for multiscale modeling. In particular the plane stress case is highlighted, by proposing three different implementation strategies which are compatible with a first-order computational homogenization framework. The first method consists of applying classical plane stress theory at the microscale, whereas with the second method a generalized plane stress condition is assumed at the RVE level. For the third method, the plane stress condition is applied at the macroscale by requiring that the resulting macroscopic out-of-plane forces are equal to zero. These strategies are assessed through a numerical study of a thin walled structure and the resulting effective macroscale stress-strain response is compared. It is shown that there is a clear influence of the length scale at which the planar condition is applied.

Keywords: first-order computational homogenization, planar analysis, multiscale, microstrucutures

Procedia PDF Downloads 215

Authors: Anis A. Ansari, Syed Javed Arif

Abstract:

From the last two-three decades, all countries are continuously generating huge quantities of electronic waste in the form of obsolete computers, gadgets and other discarded electronic instruments mainly due to evolution of newer technologies as a result of constant efforts in research and development in this area. This is the primary reason why waste from the electronic industry is increasing exponentially day by day. Thermoset and thermoplastic polymers, which are the major constituents in every electronic waste, may create a new business opportunity if these are recovered and recycled properly. This may reduce our directly dependency on petroleum and petro-products for polymer materials and also create a potential market for recycled polymers to improve economy. The main theme of this paper is to evolve the potential of recovery and recycling of polymers from the waste being generated globally in the form of discarded electronic products.

Keywords: polymer recovery, electronic waste, petroleum, thermoplastics

Procedia PDF Downloads 491

Authors: Rendani Mercy Makhwathana

Abstract:

This paper intends to explore teachers' encounters when teaching English First Additional Language in rural public schools. Teachers are pillars of any education system around the globe. Educational transformations hinge on them as critical role players in the education system. Thus, teachers' encounters are worth consideration, for they impact learners' learning and the well-being of education in general. An exploratory qualitative approach was used in this paper. The population for this paper comprised all Foundation Phase teachers in the district. A purposive sample of 15 Foundation Phase teachers from five rural-based schools was used. Data were collected through classroom observation and individual face-to-face interviews. Data were categorized, analyzed, and interpreted. Amongst the revealed teachers' encounters are learners' inability to read and write and learners' lack of English language background and learners' lack of the vocabulary to express themselves. This paper recommends the provision of relevant resources and support to effectively teach English First Additional Language to enable learners' engagement and effective use of the English language.

Keywords: first additional language, english second language, medium of instruction, teacher professional development

Procedia PDF Downloads 63

Authors: Ahmed Fathi Mohamed, Nasir Shafiq, Muhd Fadhil Nuruddin, Ali Elheber Ahmed

Abstract:

Steel fiber adds to Self-Compacting Concrete (SCC) to enhance it is properties and achieves the requirement. This research work focus on the using of different percentage of steel fiber in SCC mixture contains fly ash and microwave incinerator rice husk ash (MIRHA) as supplementary material. Fibers affect several characteristics of SCC in the fresh and the hardened state. To optimize fiber-reinforced self-compacting concrete (FSCC), The possible fiber content of a given mix composition is an essential input parameter. The aim of the research is to study the properties of fiber reinforced self–compacting (FRSCC) and to develop the expert system/computer program of mix proportion for calculating the steel fiber content and pozzolanic replacement that can be applied to investigate the compressive strength of FSCC mix.

Keywords: self-compacting concrete, silica fume, steel fiber, fresh taste

Procedia PDF Downloads 551

Authors: Margarita S. Tikhonova, Alireza Baniasad, Anton G. Kalmykov, Georgy A. Kalmykov, Ralf Littke

Abstract:

There is a high complexity in the pore structure of organic-rich rocks caused by the combination of inter-particle porosity from inorganic mineral matter and ultrafine intra-particle porosity from both organic matter and clay minerals. Fluids are retained in that pore space, but there are major uncertainties in how and where the fluids are stored and to what extent they are accessible or trapped in 'closed' pores. A large degree of tortuosity may lead to fractionation of organic matter so that the lighter and flexible compounds would diffuse to the reservoir whereas more complicated compounds may be locked in place. Additionally, parts of hydrocarbons could be bound to solid organic matter –kerogen– and mineral matrix during expulsion and migration. Larger compounds can occupy thin channels so that clogging or oil and gas entrapment will occur. Sequential extraction of applying different solvents is a powerful tool to provide more information about the characteristics of trapped organic matter distribution. The Upper Jurassic – Lower Cretaceous Bazhenov shale is one of the most petroliferous source rock extended in West Siberia, Russia. Concerning the variable mineral composition, pore space distribution and thermal maturation, there are high uncertainties in distribution and composition of organic matter in this formation. In order to address this issue geological and geochemical properties of 30 samples including mineral composition (XRD and XRF), structure and texture (thin-section microscopy), organic matter contents, type and thermal maturity (Rock-Eval) as well as molecular composition (GC-FID and GC-MS) of different extracted materials during sequential extraction were considered. Sequential extraction was performed by a Soxhlet apparatus using different solvents, i.e., n-hexane, chloroform and ethanol-benzene (1:1 v:v) first on core plugs and later on pulverized materials. The results indicate that the studied samples are mainly composed of type II kerogen with TOC contents varied from 5 to 25%. The thermal maturity ranged from immature to late oil window. Whereas clay contents decreased with increasing maturity, the amount of silica increased in the studied samples. According to molecular geochemistry, stored hydrocarbons in open and closed pore space reveal different geochemical fingerprints. The results improve our understanding of hydrocarbon expulsion and migration in the organic-rich Bazhenov shale and therefore better estimation of hydrocarbon potential for this formation.

Keywords: Bazhenov formation, bitumen, molecular geochemistry, sequential extraction

Procedia PDF Downloads 155

Authors: Moreblessings Shoko

Abstract:

Polymersomes are materials which are considered as artificial counterparts of natural vesicles. The nanotechnology of such smart nanovesicles is very useful to enhance the efficiency of many therapeutic and diagnostic drugs. Those compounds show a higher stability, flexibility, and mechanical strength to the membrane compared to natural liposomes. Also, they can be designed in detail, the permeability of the membrane can be controlled by different stimuli, and the surface can be functionalized with different biological molecules to facilitate monitoring and target. For this purpose, this study demonstrates the formation of multifunctional and pH sensitive polymersomes and their functionalization with different reactive groups or biomolecules inside and outside of polymersomes´ membrane providing by crossing the membrane and docking/undocking processes for biomedical applications. Overall, they are highly versatile and thus present new opportunities for the design of targeted and selective recognition systems, for example, in mimicking cell functions and in synthetic biology.

Keywords: women, geomatics, challenges, capacity building

Procedia PDF Downloads 553

Authors: S. Biondi, V. Catania, R. Di Natale, A. R. Intilisano, D. Panno

Abstract:

One of the major goals of Spoken Dialog Systems (SDS) is to understand what the user utters. In the SDS domain, the Spoken Language Understanding (SLU) Module classifies user utterances by means of a pre-definite conceptual knowledge. The SLU module is able to recognize only the meaning previously included in its knowledge base. Due the vastity of that knowledge, the information storing is a very expensive process. Updating and managing the knowledge base are time-consuming and error-prone processes because of the rapidly growing number of entities like proper nouns and domain-specific nouns. This paper proposes a solution to the problem of Name Entity Recognition (NER) applied to a SDS domain. The proposed solution attempts to automatically recognize the meaning associated with an utterance by using the PANKOW (Pattern based Annotation through Knowledge On the Web) method at runtime. The method being proposed extracts information from the Web to increase the SLU knowledge module and reduces the development effort. In particular, the Google Search Engine is used to extract information from the Facebook social network.

Keywords: spoken dialog system, spoken language understanding, web semantic, name entity recognition

Procedia PDF Downloads 327

Authors: Yagya Raj Pandeya, Joonwhoan Lee

Abstract:

The dynamic behavior of music and video makes it difficult to evaluate musical instrument playing in a video by computer system. Any television or film video clip with music information are rich sources for analyzing musical instruments using modern machine learning technologies. In this research, we integrate the audio and video information sources using convolutional neural network (CNN) and pass network learned features through recurrent neural network (RNN) to preserve the dynamic behaviors of audio and video. We use different pre-trained CNN for music and video feature extraction and then fine tune each model. The music network use 2D convolutional network and video network use 3D convolution (C3D). Finally, we concatenate each music and video feature by preserving the time varying features. The long short term memory (LSTM) network is used for long-term dynamic feature characterization and then use late fusion with generalized mean. The proposed network performs better performance to recognize the musical instrument using audio-video multimodal neural network.

Keywords: multimodal, 3D convolution, music-video feature extraction, generalized mean

Procedia PDF Downloads 198

Authors: Rio Hirakawa, Christian Gundlach, Sven Hartwig

Abstract:

Aluminium has been used in a wide range of industrial applications due to its numerous advantages, including excellent specific strength, thermal conductivity, corrosion resistance, workability and recyclability. The automotive industry is increasingly adopting multi-materials, including aluminium in structures and components to improve the mechanical usability and performance of individual components. A common method for assembling dissimilar materials is mechanical joining, but mechanical joining requires multiple manufacturing steps, affects the mechanical properties of the base material and increases the weight due to additional metal parts. Fusion bonding is being used in more and more industries as a way of avoiding the above drawbacks. Infusion bonding, and surface pre-treatment of the base material is essential to ensure the long-life durability of the joint. Laser surface treatment of aluminium has been shown to improve the durability of the joint by forming a passive oxide film and roughening the substrate surface. Infusion bonding, the polymer bonds directly to the metal instead of the adhesive, but the sensitivity to interfacial contamination is higher due to the chemical activity and molecular size of the polymer. Laser-treated surfaces are expected to absorb impurities from the storage atmosphere over time, but the effect of such changes in the treated surface over time on the durability of fusion-bonded joints has not yet been fully investigated. In this paper, the effect of the ageing of laser-treated surfaces of aluminum alloys on the corrosion resistance of fusion-bonded joints is therefore investigated. AlMg3 of 1.5 mm thickness was cut using a water-jet cutting machine, cleaned and degreased with isopropanol and surface pre-treated with a pulsed fiber laser at a wavelength of 1060 nm, maximum power of 70 W and repetition rate of 55 kHz. The aluminum surfaces were then stored in air for various periods of time and their corrosion resistance was assessed by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). For the aluminum joints, induction heating was employed as the fusion bonding method and single-lap shear specimens were prepared. The corrosion resistance of the joints was assessed by measuring the lap shear strength before and after neutral salt spray. Cross-sectional observations by scanning electron microscopy (SEM) were also carried out to investigate changes in the microstructure of the bonded interface. Finally, the corrosion resistance of the surface and the joint were compared and the differences in the mechanisms of corrosion resistance enhancement between the two were discussed.

Keywords: laser surface treatment, pre-treatment, bonding, corrosion, durability, interface, automotive, aluminium alloys, joint, fusion bonding

Procedia PDF Downloads 63

Authors: Manana Lobzhanidze

Abstract:

The COVID-19 pandemic has made significant changes in migration processes, notably changes in the study migration process. The constraints caused by the COVID-19 pandemic led to changes in the studying process, which negatively affected its efficiency. The educational process has partially or completely shifted to distance learning; Both labor and study migration have increased significantly in the world. The employment and education market has become global and consequently, a number of challenges have arisen for employers, researchers, and businesses. The role of preparing qualified personnel in achieving high productivity is justified, the benefits for employers and employees are assessed on the one hand, and the role of study migration for the country’s development is examined on the other hand. Research methods. The research is based on methods of analysis and synthesis, quantitative and qualitative, groupings, relative and mean quantities, graphical representation, comparison, analysis and etc. In-depth interviews were conducted with experts to determine quantitative and qualitative indicators. Research findings. Factors affecting study migration are analysed in the paper and the environment that stimulates migration is explored. One of the driving forces of migration is considered to be the desire for receiving higher pay. Levels and indicators of study migration are studied by country. Comparative analysis has found that study migration rates are high in countries where the price of skilled labor is high. The productivity of individuals with low skills is low, which negatively affects the economic development of countries. It has been revealed that students leave the country to improve their skills during study migration. The process mentioned in the article is evaluated as a positive event for a developing country, as individuals are given the opportunity to share the technology of developed countries, gain knowledge, and then introduce it in their own country. The downside of study migration is the return of a small proportion of graduates from developed economies to their home countries. The article concludes that countries with emerging economies devote less resources to research and development, while this is a priority in developed countries, allowing highly skilled individuals to use their skills efficiently. The paper studies the national education system examines the level of competition in the education market and the indicators of educational migration. The level of competition in the education market and the indicators of educational migration are studied. The role of qualified personnel in achieving high productivity is substantiated, the benefits of employers and employees are assessed on the one hand, and the role of study migration in the development of the country is revealed on the other hand. The paper also analyzes the level of competition in the education and labor markets and identifies indicators of study migration. During the pandemic period, there was a great demand for the digital technologies. Open access to a variety of comprehensive platforms will significantly reduce study migration to other countries. As a forecast, it can be said that the intensity of the use of e-learning platforms will be increased significantly in the post-pandemic period. The paper analyzes the positive and negative effects of study migration on economic development, examines the challenges of study migration in light of the COVID-19 pandemic, suggests ways to avoid negative consequences, and develops recommendations for improving the study migration process in the post-pandemic period.

Keywords: study migration, COVID-19 pandemic, factors affecting migration, economic development, post-pandemic migration

Procedia PDF Downloads 114

Authors: Angely Sim Jia Wun, Sasa Arsovski

Abstract:

Numerous studies have been conducted on the segmentation of medical images. Segmenting the lungs is one of the common research topics in those studies. Our research stemmed from the lack of solutions for automatic bone, airway, and vessel segmentation, despite the existence of multiple lung segmentation techniques. Consequently, currently, available software tools used for medical image segmentation do not provide automatic lung, bone, airway, and vessel segmentation. This paper presents segmentation techniques along with an interactive software tool architecture for segmenting bone, lung, airway, and vessel tissues. Additionally, we propose a method for creating binary masks from automatically generated segments. The key contribution of our approach is the technique for automatic image thresholding using adjustable Hounsfield values and binary mask extraction. Generated binary masks can be successfully used as a training dataset for deep-learning solutions in medical image segmentation. In this paper, we also examine the current software tools used for medical image segmentation, discuss our approach, and identify its advantages.

Keywords: lung segmentation, binary masks, U-Net, medical software tools

Procedia PDF Downloads 80

Authors: Scott N. Gerard, Aliza Heching, Susann M. Keohane, Samuel S. Adams

Abstract:

The world-wide population of people over 60 years of age is growing rapidly. The explosion is placing increasingly onerous demands on individual families, multiple industries and entire countries. Current, human-intensive approaches to eldercare are not sustainable, but IoT and AI technologies can help. The Knowledge Reactor (KR) is a contextual, data fusion engine built to address this and other similar problems. It fuses and centralizes IoT and System of Record/Engagement data into a reactive knowledge graph. Cognitive applications and services are constructed with its multiagent architecture. The KR can scale-up and scaledown, because it exploits container-based, horizontally scalable services for graph store (JanusGraph) and pub-sub (Kafka) technologies. While the KR can be applied to many domains that require IoT and AI technologies, this paper describes how the KR specifically supports the challenging domain of cognitive eldercare. Rule- and machine learning-based analytics infer activities of daily living from IoT sensor readings. KR scalability, adaptability, flexibility and usability are demonstrated.

Keywords: ambient sensing, AI, artificial intelligence, eldercare, IoT, internet of things, knowledge graph

Procedia PDF Downloads 157

Authors: Yan Li

Abstract:

Purpose: There is a lack of suitable recommendation systems to assist engineering teaching. The existing traditional engineering pedagogies lack learning interests for postgraduate students. The knowledge graph-based recommender system aims to enhance postgraduate students’ programming skills, with a focus on programming courses. Design/methodology/approach: The case study will be used as a major research method, and the two case studies will be taken in both two teaching styles of the universities (Zhejiang University and the University of Nottingham Ningbo China), followed by the interviews. Quantitative and qualitative research methods will be combined in this study. Research limitations/implications: The case studies were only focused on two teaching styles universities, which is not comprehensive enough. The subject was limited to postgraduate students. Originality/value: The study collected and analyzed the data from two teaching styles of universities’ perspectives. It explored the challenges of Engineering education and tried to seek potential enhancement.

Keywords: knowledge graph and recommender system, engineering pedagogy, programming skills, postgraduate students

Procedia PDF Downloads 57

Authors: M. Mokhtarzadeh, M. Taheri Qomi, M. Nikafrooz, A. Atashafrooz

Abstract:

The purpose of the present study was to investigate the effectiveness of using motion graphics as a learning medium on training hearing aids maintenance skills to hearing-impaired children. The statistical population of this study consisted of all children with hearing loss in Ahvaz city, at age 4 to 7 years old. As the sample, 60, whom were selected by multistage random sampling, were randomly assigned to two groups; experimental (30 children) and control (30 children) groups. The research method was experimental and the design was pretest-posttest with the control group. The intervention consisted of a 2-minute motion graphics clip to train hearing aids maintenance skills. Data were collected using a 9-question researcher-made questionnaire. The data were analyzed by using one-way analysis of covariance. Results showed that the training of hearing aids maintenance skills with motion graphics was significantly effective for those children. The results of this study can be used by educators, teachers, professionals, and parents to train children with disabilities or normal students.

Keywords: hearing aids, hearing aids maintenance skill, hearing impaired children, motion graphics

Procedia PDF Downloads 140

Authors: P. J. Moore-Jones

Abstract:

Emirati students studying at the University of the Emirates, one of three major public institutions of higher learning in the United Arab Emirates (UAE), have a wide demographic of faculty members teaching them an equally wide variety of courses. These faculty members bring with them their own cultural assumptions, methods, expectations, educational practices and use of language. The history of multiculturalism in the UAE coupled with the contemporary multiculturalism that exists in higher education Dubai create intriguing phenomena within the classroom. This study seeks to delve into students’ and faculty members’ perceptions of the social stratification that exist in this context. Data were collected via semi-structured interviews with both and analyzed from an interpretive perspective. Findings suggest the social stratification with is deeply-seeded in the multicultural history of the region and country are reflected in the everyday interworkings of education in modern day Dubai. The relevance of this research lies in that these findings can provide valuable insights into not only the attitudes and perceptions of these Emirati students might also be applicable to any of those student populations may exist.

Keywords: social stratification, intercultural competence, Dubai, United Arab Emirates

Procedia PDF Downloads 226

Authors: Fereshteh Nazeri Bahadori

Abstract:

In today's competitive environment, any company that aims to operate in a market, whether industrial or consumer markets, must know that it cannot address all the tastes and demands of customers at once and serve them all. The study of consumer memory is considered an important subject in marketing research, and many companies have conducted studies on this subject and the factors affecting it due to its importance. Therefore, the current study tries to investigate the relationship between consumers' attention, literacy, and memory. Memory has a very close relationship with learning. Memory is the collection of all the information that we have understood and stored. One of the important subjects in consumer behavior is information processing by the consumer. One of the important factors in information processing is the mental involvement of the consumer, which has attracted a lot of attention in the past two decades. Since consumers are the turning point of all marketing activities, successful marketing begins with understanding why and how consumers behave. Therefore, in the current study, the role of executive attention and literacy on consumers' memory has been investigated. The results showed that executive attention and literacy would play a significant role in the long-term and short-term memory of consumers.

Keywords: literacy, consumer memory, executive attention, psychology of consumer behavior

Procedia PDF Downloads 79

Authors: Imran Ali

Abstract:

General chemotherapy for cancer treatment has many side and toxic effects. A new approach of targeting nano anti-cancer drug is under development stage and only few drugs are available in the market today. The unique features of these drugs are targeted action on cancer cells only without any side effect. Sometimes, these are called magic drugs. The important molecules used for nano anti-cancer drugs are cisplatin, carboplatin, bleomycin, 5-fluorouracil, doxorubicin, dactinomycin, 6-mercaptopurine, paclitaxel, topotecan, vinblastin and etoposide etc. The most commonly used materials for preparing nano particles carriers are dendrimers, polymeric, liposomal, micelles inorganic, organic etc. The proposed lecture will comprise the-of-art of nano drugs in cancer chemo-therapy including preparation, types of drugs, mechanism, future perspectives etc.

Keywords: cancer, nano-anti-cancer drugs, chemo-therapy, mechanism of action, future perspectives

Procedia PDF Downloads 427

Authors: Aileen O'loughlin

Abstract:

‘Is Everybody Going WeLL?’ (IEGW?) is a 33-hour classroom-based initiative created to a) explore values and how they impact on well-being, b) encourage adolescents to connect with their community, and c) provide them with the education to encourage and maintain a lifetime love of physical activity (PA) to ensure beneficial effects on their personal well-being. This initiative is also aimed at achieving sustainable education and aligning with the United Nation’s Sustainable Development Goals numbers 3 and 4. The classroom is a unique setting in which adolescents’ PA participation can be positively influenced through fun PA policies and initiatives. The primary purpose of this research is to evaluate a range of psychosocial and PA outcomes following the 33-hour education programme. This research examined the impact of a PA and well-being programme consisting of either a 60minute or 80minute class, depending on the timetable structure of the school, delivered once a week. Participant outcomes were measured using validated questionnaires regarding Self-esteem, Mental Health Literacy (MHL) and Daily Physical Activity Participation. These questionnaires were administered at three separate time points; baseline, mid-intervention, and post intervention. Semi-structured interviews with participating teachers regarding adherence and participants’ attitudes were completed post-intervention. These teachers were randomly selected for interview. This perspective analytical cohort study included 235 post-primary school students between 11-13 years of age (100 boys and 135 girls) from five public Irish post-primary schools. Three schools received the intervention only; a 33hour interactive well-being learning unit, one school formed a control group and one school had participants in both the intervention and control group. Participating schools were a convenience sample. Data presented outlines baseline data collected pre-participation (0 hours completed). N = 18 junior certificate students returned all three questionnaires fully completed for a 56.3% return rate from 1 school, Intervention School #3. 94.4% (n = 17) of participants enjoy taking part in some form of PA, however only 5.5% (n = 1) of the participants took part in PA every day of the previous 7 days and only 5.5% (n = 1) of those surveyed participated in PA every day during a normal week. 55% (n = 11) had a low level of self-esteem, 50% (n = 9) fall within the normal range of self-esteem, and n = 0 surveyed demonstrated a high level of self-esteem. Female participants’ Mean score was higher than their male counterparts when MHL was compared. Correlation analyses revealed a small association between Self-esteem and Happiness (r = 0.549). Positive correlations were also revealed between MHL and Happiness, MHL and Self-esteem and Self-esteem and 60+ minutes of PA completed daily. IEGW? is a classroom-based with simple methods easy to implement, replicate and financially viable to both public and private schools. It’s unique dataset will allow for the evaluation of a societal approach to the psycho-social well-being and PA participation levels of adolescents. This research is a work in progress and future work is required to learn how to best support the implementation of ‘Is Everybody Going WeLL?’ as part of the school curriculum.

Keywords: education, life-long learning, physical activity, psychosocial well-being

Procedia PDF Downloads 104

Authors: Ana B. Vivas, Antonia Ypsilanti, Aristea I. Ladas, Angeles F. Estevez

Abstract:

Mild Cognitive Impairment (MCI) is considered an intermediate stage between normal and pathological aging, as a substantial percentage of people diagnosed with MCI converts later to dementia of the Alzheimer’s type. Memory is of the first cognitive processes to deteriorate in this condition. In the present study we employed the differential outcomes procedure (DOP) to improve visuospatial memory in a group of participants with MCI. The DOP requires the structure of a conditional discriminative learning task in which a correct choice response to a specific stimulus-stimulus association is reinforced with a particular reinforcer or outcome. A group of 10 participants with MCI, and a matched control group had to learn and keep in working memory four target locations out of eight possible locations where a shape could be presented. Results showed that participants with MCI had a statistically significant better terminal accuracy when a unique outcome was paired with a location (76% accuracy) as compared to a non differential outcome condition (64%). This finding suggests that the DOP is useful in improving working memory in MCI patients, which may delay their conversion to dementia.

Keywords: mild cognitive impairment, working memory, differential outcomes, cognitive process

Procedia PDF Downloads 444

Authors: Hong Lu, Xiong Xiao

Abstract:

Shaft parts are widely used in machinery industry, however, bending deformation often occurred when this kind of parts is being heat treated. This parts needs to be straightened to meet the requirement of straightness. As for the pressure straightening process, a good straightening stroke algorithm is related to the precision and efficiency of straightening process. In this paper, the relationship between straightening load and deflection during the straightening process is analyzed, and the mathematical model of the straightening process has been established. By the mathematical model, the iterative method is used to solve the straightening stroke. Compared to the traditional straightening stroke algorithm, straightening stroke calculated by this method is much more precise; because it can adapt to the change of material performance parameters. Considering that the straightening method is widely used in the mass production of the shaft parts, knowledge base is used to store the data of the straightening process, and a straightening stroke algorithm based on empirical data is set up. In this paper, the straightening process control model which combine the straightening stroke method based on iteration and straightening stroke algorithm based on empirical data has been set up. Finally, an experiment has been designed to verify the straightening process control model.

Keywords: straightness, straightening stroke, deflection, shaft parts

Procedia PDF Downloads 315

Authors: Muhammad A. Nadeem, Shaheed Ullah

Abstract:

The article reports the synthesis of Cr2O3/C nanocomposites obtained by the direct carbonization of PFA/MIL-101(Cr) bulk composite. The nanocomposites were characterized by various instrumental techniques like powder X-ray diffraction (PXRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), transmission electron microscopy (TEM), selected area electron diffraction (SAED) and the surface characterized were investigated via N2 adsorption/desorption analysis. TEM and SAED analysis shows that turbostatic graphitic carbon was obtained with high crystallinity. The nanocomposites were tested for electrochemical supercapacitor and the faradic and non-Faradic processes were checked through cyclic voltammetry (CV). The maximum specific capacitance calculated for Cr2O3/C 900 sample from CV measurement is 301 F g-1 at 2 mV s-1 due to its maximum charge storing capacity as confirm by frequency response analysis.

Keywords: nanocomposites, transmission electron microscopy, non-faradic process

Procedia PDF Downloads 422

Authors: Bin Ji, Kai Xu, Shunyu Yao, Jingjing Liu, Ye Pan

Abstract:

Human pose estimation is a popular research area in computer vision for its important application in human-machine interface. In recent years, 2D human pose estimation based on convolution neural network has got great progress and development. However, in more and more practical applications, people often need to deal with tasks based on video. It’s not far-fetched for us to consider how to combine the spatial and temporal information together to achieve a balance between computing cost and accuracy. To address this issue, this study proposes a new spatiotemporal model, namely Spatiotemporal Net (STNet) to combine both temporal and spatial information more rationally. As a result, the predicted keypoints heatmap is potentially more accurate and spatially more precise. Under the condition of ensuring the recognition accuracy, the algorithm deal with spatiotemporal series in a decoupled way, which greatly reduces the computation of the model, thus reducing the resource consumption. This study demonstrate the effectiveness of our network over the Penn Action Dataset, and the results indicate superior performance of our network over the existing methods.

Keywords: convolutional long short-term memory, deep learning, human pose estimation, spatiotemporal series

Procedia PDF Downloads 133

Authors: Olga Gomez De Miranda, Jose R. Ochoa-Gomez, Stefaan De Wildeman, Luciano Monsegue, Soraya Prieto, Leire Lorenzo, Cristina Dineiro

Abstract:

The chemical industry is facing a new revolution. As long as processes based on the exploitation of fossil resources emerged with force in the XIX century, Society currently demands a new radical change that will lead to the complete and irreversible implementation of a circular sustainable economic model. The implementation of biorefineries will be essential for this. There, renewable raw materials as sugars and other biomass resources are exploited for the development of new materials that will partially replace their petroleum-derived homologs in a safer, and environmentally more benign approach. Isosorbide, (1,4:3,6-dianhydro-d-glucidol) is a primary bio-based derivative obtained from the plant (poly) saccharides and a very interesting example of a useful chemical produced in biorefineries. It can, in turn, be converted to other secondary monomers as isosorbide bis-methyl carbonate (IBMC), whose main field of application can be as a key biodegradable intermediary substitute of bisphenol-A in the manufacture of polycarbonates, or as an alternative to the toxic isocyanates in the synthesis of new polyurethanes (non-isocyanate polyurethanes) both with a huge application market. New products will present advantageous mechanical or optical properties, as well as improved behavior in non-toxicity and biodegradability aspects in comparison to their petro-derived alternatives. A robust production process of IBMC, a biomass-derived chemical, is here presented. It can be used with different raw material qualities using dimethyl carbonate (DMC) as both co-reactant and solvent. It consists of the transesterification of isosorbide with DMC under soft operational conditions, using different basic catalysts, always active with the isosorbide characteristics and purity. Appropriate isolation processes have been also developed to obtain crude IBMC yields higher than 90%, with oligomers production lower than 10%, independently of the quality of the isosorbide considered. All of them are suitable to be used in polycondensation reactions for polymers obtaining. If higher qualities of IBMC are needed, a purification treatment based on nanofiltration membranes has been also developed. The IBMC reaction-isolation conditions established in the laboratory have been successfully modeled using appropriate software programs and moved to a pilot-scale (production of 100 kg of IBMC). It has been demonstrated that a highly efficient IBMC production process able to be up-scaled under suitable market conditions has been obtained. Operational conditions involved the production of IBMC involve soft temperature and energy needs, no additional solvents, and high operational efficiency. All of them are according to green manufacturing rules.

Keywords: biomass, catalyst, isosorbide bis-methyl carbonate, polycarbonate, polyurethane, transesterification

Procedia PDF Downloads 120

Authors: Zhifeng Kong

Abstract:

Over-parameterized neural networks have attracted a great deal of attention in recent deep learning theory research, as they challenge the classic perspective of over-fitting when the model has excessive parameters and have gained empirical success in various settings. While a number of theoretical works have been presented to demystify properties of such models, the convergence properties of such models are still far from being thoroughly understood. In this work, we study the convergence properties of training two-hidden-layer partially over-parameterized fully connected networks with the Rectified Linear Unit activation via gradient descent. To our knowledge, this is the first theoretical work to understand convergence properties of deep over-parameterized networks without the equally-wide-hidden-layer assumption and other unrealistic assumptions. We provide a probabilistic lower bound of the widths of hidden layers and proved linear convergence rate of gradient descent. We also conducted experiments on synthetic and real-world datasets to validate our theory.

Keywords: over-parameterization, rectified linear units ReLU, convergence, gradient descent, neural networks

Procedia PDF Downloads 130

Authors: Aydin Azizi, Ahmed Al. Azizi

Abstract:

Mechanical seals are essential components in centrifugal pumps since they help in controlling leaking out of the liquid that is pumped under pressure. Unlike the common types of packaging, mechanical seals are highly efficient and they reduce leakage by a great extent. However, all multiphase mechanical seals leak and they are subject to failure. Some of the factors that have been recognized to their failure include excessive heating, open seal faces, as well as environment related factors that trigger failure of the materials used to manufacture seals. The proposed research study will explore the failure of multiphase mechanical seal in centrifugal pumps. The objective of the study includes how to reduce the failure in multiphase mechanical seals and to make them more efficient.

Keywords: mechanical seals, centrifugal pumps, multi phase failure, excessive heating

Procedia PDF Downloads 348

Authors: V. Ivanov, J. Chu, V. Stabnikov

Abstract:

Different biotechnological methods for the production of construction materials and for the performance of construction processes in situ are developing within a new scientific discipline of Construction Biotechnology. The aim of this research was to develop and test new biotechnologies and biotechnological grouts for the minimization of the hydraulic conductivity of the fractured rocks and porous soil. This problem is essential to minimize flow rate of groundwater into the construction sites, the tunneling space before and after excavation, inside levies, as well as to stop water seepage from the aquaculture ponds, agricultural channels, radioactive waste or toxic chemicals storage sites, from the landfills or from the soil-polluted sites. The conventional fine or ultrafine cement grouts or chemical grouts have such restrictions as high cost, viscosity, sometime toxicity but the biogrouts, which are based on microbial or enzymatic activities and some not expensive inorganic reagents, could be more suitable in many cases because of lower cost and low or zero toxicity. Due to these advantages, development of biotechnologies for biogrouting is going exponentially. However, most popular at present biogrout, which is based on activity of urease- producing bacteria initiating crystallization of calcium carbonate from calcium salt has such disadvantages as production of toxic ammonium/ammonia and development of high pH. Therefore, the aim of our studies was development and testing of new biogrouts that are environmentally friendly and have low cost suitable for large scale geotechnical, construction, and environmental applications. New microbial biotechnologies have been studied and tested in the sand columns, fissured rock samples, in 1 m3 tank with sand, and in the pack of stone sheets that were the models of the porous soil and fractured rocks. Several biotechnological methods showed positive results: 1) biogrouting using sequential desaturation of sand by injection of denitrifying bacteria and medium following with biocementation using urease-producing bacteria, urea and calcium salt decreased hydraulic conductivity of sand to 2×10-7 ms-1 after 17 days of treatment and consumed almost three times less reagents than conventional calcium-and urea-based biogrouting; 2) biogrouting using slime-producing bacteria decreased hydraulic conductivity of sand to 1x10-6 ms-1 after 15 days of treatment; 3) biogrouting of the rocks with the width of the fissures 65×10-6 m using calcium bicarbonate solution, that was produced from CaCO3 and CO2 under 30 bars pressure, decreased hydraulic conductivity of the fissured rocks to 2×10-7 ms-1 after 5 days of treatment. These bioclogging technologies could have a lot of advantages over conventional construction materials and processes and can be used in geotechnical engineering, agriculture and aquaculture, and for the environmental protection.

Keywords: biocementation, bioclogging, biogrouting, fractured rocks, porous soil, tunneling space

Procedia PDF Downloads 198

Authors: H. Ahmed, A. Persson, L. Sundqvist, B. Biorkman

Abstract:

Numerous amounts of metallurgical dusts and sludge containing iron as well as some other valuable elements such as Zn, Pb and C are annually produced in the steelmaking industry. These alternative iron ore resources (fines) with unsatisfying physical and metallurgical properties are difficult to recycle. However, agglomerating these fines to be further used as a feed stock for existing iron and steel making processes is practiced successfully at several plants but for limited extent. In the present study, briquettes of integrated steelmaking industry waste materials (namely, BF-dust and sludge, BOF-dust and sludge) were used as feed stock to produce direct reduced iron (DRI). Physical and metallurgical properties of produced briquettes were investigated by means of TGA/DTA/QMS in combination with XRD. Swelling, softening and melting behavior were also studied using heating microscope.

Keywords: iron and steel wastes, recycling, self-reducing briquettes, thermogravimetry

Procedia PDF Downloads 383

Authors: S. Bennoud, M. Zergoug

Abstract:

The numerical simulation of electromagnetic interactions is still a challenging problem, especially in problems that result in fully three dimensional mathematical models. The goal of this work is to use mathematical modeling to characterize the reliability and capacity of eddy current technique to detect and characterize defects embedded in aeronautical in-service pieces. The finite element method is used for describing the eddy current technique in a mathematical model by the prediction of the eddy current interaction with defects. However, this model is an approximation of the full Maxwell equations. In this study, the analysis of the problem is based on a three dimensional finite element model that computes directly the electromagnetic field distortions due to defects.

Keywords: eddy current, finite element method, non destructive testing, numerical simulations

Procedia PDF Downloads 430

Authors: M. Chavleishvili

Abstract:

The paper presents the trends of Georgian hazelnut market development and analyses the competitive advantages which will help Georgia to enter international hazelnut market using modern technologies. The history of hazelnut crop development and hazelnut species in Georgia are discussed. For hazelnut supply analysis trends in hazelnut production are considered, trends in export and import development is evaluated, domestic hazelnut market is studied and analysed based on expert interviews and initial accounting materials. In order to achieve and strengthen its position in international market, potential advantages and disadvantages of Georgian hazelnut are revealed, analysis of export and import possibilities of hazelnut is presented. Recommendations are developed based on the conclusions, which are made through identifying the key factors that hinder development of Georgian hazelnut market.

Keywords: hazelnut market, hazelnut export and import, competitiveness of hazelnut

Procedia PDF Downloads 424

Authors: Manar Amayri, Hussain Kazimi, Quoc-Dung Ngo, Stephane Ploix

Abstract:

A general approach is proposed to determine occupant behavior (occupancy and activity) in residential buildings and to use these estimates for improved energy management. Occupant behaviour is modelled with a Bayesian Network in an unsupervised manner. This algorithm makes use of domain knowledge gathered via questionnaires and recorded sensor data for motion detection, power, and hot water consumption as well as indoor CO₂ concentration. Two case studies are presented which show the real world applicability of estimating occupant behaviour in this way. Furthermore, experiments integrating occupancy estimation and hot water production control show that energy efficiency can be increased by roughly 5% over known optimal control techniques and more than 25% over rule-based control while maintaining the same occupant comfort standards. The efficiency gains are strongly correlated with occupant behaviour and accuracy of the occupancy estimates.

Keywords: energy, management, control, optimization, Bayesian methods, learning theory, sensor networks, knowledge modelling and knowledge based systems, artificial intelligence, buildings

Procedia PDF Downloads 357