Search results for: Mandarin Chinese processing

Authors: Juliette MacDonald, Jun Li, Wenji Xiang, Mingwei Zhao

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Shanghai International College of Fashion and Innovation (SCF) was created as a result of a collaborative partnership agreement between the University of Edinburgh and Donghua University. The College provides two programmes: Fashion Innovation and Fashion Interior Design and the overarching curriculum has the intention of developing innovation and creativity within an international learning, teaching, knowledge exchange and research context. The research problem presented here focuses on the multi-national/cultural faculty in the team, the challenges arising from difficulties in communication and the associated limitations of management frameworks. The teaching faculty at SCF are drawn from China, Finland, Korea, Singapore and the UK with input from Flying Faculty from Fashion and Interior Design, Edinburgh College of Art (ECA), for 5 weeks each semester. Rather than fully replicating the administrative and pedagogical style of one or other of the institutions within this joint partnership the aim from the outset was to create a third way which acknowledges the quality assurance requirements of both Donghua and Edinburgh, the academic and technical needs of the students and provides relevant development and support for all the SCF-based staff and Flying Academics. It has been well acknowledged by those who are involved in teaching across cultures that there is often a culture shock associated with transnational education but that the experience of being involved in the delivery of a curriculum at a Joint Institution can also be very rewarding for staff and students. It became clear at SCF that if a third way might be achieved which encourages innovative approaches to fashion education whilst balancing the expectations of Chinese and western concepts of education and the aims of two institutions, then it was going to be necessary to construct a framework which developed close working relationships for the entire teaching team, so not only between academics and students but also between technicians and administrators at ECA and SCF. The attempts at co-construction and integration are built on the sharing of cultural and educational experiences and knowledge as well as provision of opportunities for reflection on the pedagogical purpose of the curriculum and its delivery. Methods on evaluating the effectiveness of these aims include a series of surveys and interviews and analysis of data drawn from teaching projects delivered to the students along with graduate successes from the last five years, since SCF first opened its doors. This paper will provide examples of best practice developed by SCF which have helped guide the faculty and embed common core values and aims of co-construction regulations and management, whilst building a pro-active TNE (Trans-National Education) team which enhances the learning experience for staff and students alike.

Keywords: cultural co-construction, educational team management, multi-cultural challenges, TNE integration for teaching teams

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Authors: Natalia Muratova, Dmitry Klimov, Rafail Isemin, Sergey Kuzmin, Aleksandr Mikhalev, Oleg Milovanov

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We investigated the processing of poultry litter into biochar using dry torrefaction methods (DT) in a fixed and fluidized bed of quartz sand blown with nitrogen, as well as wet torrefaction (WT) in a fluidized bed in a medium of water steam at a temperature of 300 °C. Torrefaction technology affects the duration of the heat treatment process and the characteristics of the biochar: the process of separating CO₂, CO, H₂ and CH₄ from a portion of fresh poultry litter during torrefaction in a fixed bed is completed after 2400 seconds, but in a fluidized bed — after 480 seconds. During WT in a fluidized bed of quartz sand, this process ends in 840 seconds after loading a portion of fresh litter, but in a fluidized bed of litter particles previously subjected to torrefaction, the process ends in 350 - 450 seconds. In terms of the ratio between (H/C) and (O/C), the litter obtained after DT and WT treatment corresponds to lignite. WT in a fluidized bed allows one to obtain biochar, in which the specific pore area is two times larger than the specific pore area of biochar obtained after DT in a fluidized bed. Biochar, obtained as a result of the poultry litter treatment in a fluidized bed using DT or WT method, is recommended to be used not only as a biofuel but also as an adsorbent or the soil fertilizer.

Keywords: biochar, poultry litter, dry and wet torrefaction, fixed bed, fluidized bed

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Authors: William Huang

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Retinal prostheses are currently limited to low resolution grayscale images that lack color and spatial information. This study develops a novel real-time image optimization framework and tools to encode maximum information to the prostheses which are constrained by the number of electrodes. One key idea is to localize main objects in images while reducing unnecessary background noise through region-contrast saliency maps. A novel color depth mapping technique was developed through MiniBatchKmeans clustering and color space selection. The resulting image was downsampled using bicubic interpolation to reduce image size while preserving color quality. In comparison to current schemes, the proposed framework demonstrated better visual quality in tested images. The use of the region-contrast saliency map showed improvements in efficacy up to 30%. Finally, the computational speed of this algorithm is less than 380 ms on tested cases, making real-time retinal prostheses feasible.

Keywords: retinal implants, virtual processing unit, computer vision, saliency maps, color quantization

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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Nowadays, wetlands are the subject of contradictory debates opposing scientific, political and administrative meanings. Indeed, given their multiple services (drinking water, irrigation, hydrological regulation, mineral, plant and animal resources...), wetlands concentrate many socio-economic and biodiversity issues. In some regions, they can cover vast areas (>100 thousand ha) of the landscape, such as the Camargue area in the south of France, inside the Rhone delta. The high biological productivity of wetlands, the strong natural selection pressures and the diversity of aquatic environments have produced many species of plants and animals that are found nowhere else. These environments are tremendous carbon sinks and biodiversity reserves depending on their age, composition and surrounding environmental conditions, wetlands play an important role in global climate projections. Covering more than 3% of the earth's surface, wetlands have experienced since the beginning of the 1990s a tremendous revival of interest, which has resulted in the multiplication of inventories, scientific studies and management experiments. The geographical and physical characteristics of the wetlands of the central region conceal a large number of natural habitats that harbour a great biological diversity. These wetlands, one of the natural habitats, are still influenced by human activities, especially agriculture, which affects its layout and functioning. In this perspective, decision-makers need to delimit spatial objects (natural habitats) in a certain way to be able to take action. Thus, wetlands are no exception to this rule even if it seems to be a difficult exercise to delimit a type of environment as whose main characteristic is often to occupy the transition between aquatic and terrestrial environment. However, it is possible to map wetlands with databases, derived from the interpretation of photos and satellite images, such as the European database Corine Land cover, which allows quantifying and characterizing for each place the characteristic wetland types. Scientific studies have shown limitations when using high spatial resolution images (SPOT, Landsat, ASTER) for the identification and characterization of small wetlands (1 hectare). To address this limitation, it is important to note that these wetlands generally represent spatially complex features. Indeed, the use of very high spatial resolution images (>3m) is necessary to map small and large areas. However, with the recent evolution of artificial intelligence (AI) and deep learning methods for satellite image processing have shown a much better performance compared to traditional processing based only on pixel structures. Our research work is also based on spectral and textural analysis on THR images (Spot and IRC orthoimage) using two object-oriented approaches, the nearest neighbour approach (k-NN) and the Super Vector Machine approach (SVM). The k-NN approach gave good results for the delineation of wetlands (wet marshes and moors, ponds, artificial wetlands water body edges, ponds, mountain wetlands, river edges and brackish marshes) with a kappa index higher than 85%.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

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Authors: Sanjeev Kumar Sharma, Arnab Mondal, Ranjit Kumar Upadhyay

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Excitable cells often produce different oscillatory activities that help us to understand the transmitting and processing of signals in the neural system. We consider a FitzHugh-Rinzel (FH-R) model and studied the different dynamics of the model by considering the parameter c as the predominant parameter. The model exhibits different types of neuronal responses such as regular spiking, mixed-mode bursting oscillations (MMBOs), elliptic bursting, etc. Based on the bifurcation diagram, we consider the three regimes (MMBOs, elliptic bursting, and quiescent state). An analytical treatment for the occurrence of the supercritical Hopf bifurcation is studied. Further, we extend our study to a network of a hundred neurons by considering the bi-directional synaptic coupling between them. In this article, we investigate the alternation of spiking propagation and bursting phenomena of an uncoupled and coupled FH-R neurons. We explore that the complete graph of heterogenous desynchronized neurons can exhibit different types of bursting oscillations for certain coupling strength. For higher coupling strength, all the neurons in the network show complete synchronization.

Keywords: excitable neuron model, spiking-bursting, stability and bifurcation, synchronization networks

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Authors: Kemal Polat

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In this paper, three feature weighting methods have been used to improve the classification performance of diabetic retinopathy (DR). To classify the diabetic retinopathy, features extracted from the output of several retinal image processing algorithms, such as image-level, lesion-specific and anatomical components, have been used and fed them into the classifier algorithms. The dataset used in this study has been taken from University of California, Irvine (UCI) machine learning repository. Feature weighting methods including the fuzzy c-means clustering based feature weighting, subtractive clustering based feature weighting, and Gaussian mixture clustering based feature weighting, have been used and compered with each other in the classification of DR. After feature weighting, five different classifier algorithms comprising multi-layer perceptron (MLP), k- nearest neighbor (k-NN), decision tree, support vector machine (SVM), and Naïve Bayes have been used. The hybrid method based on combination of subtractive clustering based feature weighting and decision tree classifier has been obtained the classification accuracy of 100% in the screening of DR. These results have demonstrated that the proposed hybrid scheme is very promising in the medical data set classification.

Keywords: machine learning, data weighting, classification, data mining

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Authors: Maryam Sadeghi, Claude Bazin, Daniel Hodouin, Laura Perez Barnuevo

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The performance of a separation process is usually evaluated using performance indices calculated from elemental assays readily available from the chemical analysis laboratory. However, the separation process performance is essentially related to the properties of the minerals that carry the elements and not those of the elements. Since elements or metals can be carried by valuable and gangue minerals in the ore and that each mineral responds differently to a mineral processing method, the use of only elemental assays could lead to erroneous or uncertain conclusions on the process performance. This paper discusses the advantages of using performance indices calculated from minerals content, such as minerals recovery, for process performance assessments. A method is presented that uses elemental assays to estimate the minerals content of the solids in various process streams. The method combines the stoichiometric composition of the minerals and constraints of mass conservation for the minerals through the concentration process to estimate the minerals content from elemental assays. The advantage of assessing a concentration process using mineral based performance indices is illustrated for an iron ore concentration circuit.

Keywords: data reconciliation, iron ore concentration, mineral composition, process performance assessment

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Authors: Mohammed Adamu Musa, Shehu Saminu Babba

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The technological trend towards waste utilization and cost reduction in industrial processing has attracted use of Rice Husk as a value added material. Both rice husk (RH) and Rice Husk Ash (RHA) has been found suitable for wide range of domestic as well as industrial applications. Therefore, the purpose of this research is to produce high grade sodium silicate from rice husk ash by considering the effect of temperature and time of heating as the process variables. The experiment was performed by heating the rice husk at temperatures 500 °C, 600 °C, 700 °C and 800 °C and time 60min, 90min, 120min and 150min were used to obtain the ash. 1.0M of aqueous sodium hydroxide solution was used to dissolve the silicate from the ash, which contained crude sodium silicate. In addition, the ash was neutralized by adding 5M of HCL until the pH reached 3.5 to give silica gel. At 6000C and 120mins, 94.23% silica was obtained from the RHA. At higher temperatures (700 °C and 800 °C) the percentage yield of silica reduced due to surface melting and carbon fixation in the lattice caused by presence of potassium. For this research, 600 °C is considered to be the optimum temperature for silica production from RHA. Silica produced from RHA can generate aggregate value and can be used in areas such as pulp and paper, plastic and rubber reinforcement industries.

Keywords: burning, rice husk, rice husk ash, silica, silica gel, temperature

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Authors: Dawood Al Chanti, Alice Caplier

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Sparse representations of signals have received a great deal of attention in recent years. In this paper, the interest of using sparse representation as a mean for performing sparse discriminative analysis between spontaneous facial expressions is demonstrated. An automatic facial expressions recognition system is presented. It uses a KSVD-SVM approach which is made of three main stages: A pre-processing and feature extraction stage, which solves the problem of shared subspace distribution based on the random projection theory, to obtain low dimensional discriminative and reconstructive features; A dictionary learning and sparse coding stage, which uses the KSVD model to learn discriminative under or over dictionaries for sparse coding; Finally a classification stage, which uses a SVM classifier for facial expressions recognition. Our main concern is to be able to recognize non-basic affective states and non-acted expressions. Extensive experiments on the JAFFE static acted facial expressions database but also on the DynEmo dynamic spontaneous facial expressions database exhibit very good recognition rates.

Keywords: dictionary learning, random projection, pose and spontaneous facial expression, sparse representation

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Authors: K. A. Gladkova, N. P. Babushkina, E. Y. Bragina

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Purpose: Tuberculosis (TB), caused by Mycobacterium tuberculosis, is one of the major public health problems worldwide. It is clear that the immune response to M. tuberculosis infection is a relationship between inflammatory and anti-inflammatory responses in which Tumour Necrosis Factor-α (TNF-α) plays key roles as a pro-inflammatory cytokine. TNF-α involved in various cell immune responses via binding to its two types of membrane-bound receptors, TNFRSF1A and TNFRSF1B. Importantly, some variants of the TNFRSF1B gene have been considered as possible markers of host susceptibility to TB. However, the possible impact of such TNF-α and its receptor genes polymorphism on TB cases in Tomsk is missing. Thus, the purpose of our study was to investigate polymorphism of TNF-α (rs1800629) and its receptor TNFRSF1B (rs652625 and rs525891) genes in population of Tomsk and to evaluate their possible association with the development of pulmonary TB. Materials and Methods: The population distribution features of genes polymorphisms were investigated and made case-control study based on group of people from Tomsk. Human blood was collected during routine patients examination at Tomsk Regional TB Dispensary. Altogether, 234 TB-positive patients (80 women, 154 men, average age is 28 years old) and 205 health-controls (153 women, 52 men, average age is 47 years old) were investigated. DNA was extracted from blood plasma by phenol-chloroform method. Genotyping was carried out by a single-nucleotide-specific real-time PCR assay. Results: First, interpopulational comparison was carried out between healthy individuals from Tomsk and available data from the 1000 Genomes project. It was found that polymorphism rs1800629 region demonstrated that Tomsk population was significantly different from Japanese (P = 0.0007), but it was similar with the following Europeans subpopulations: Italians (P = 0.052), Finns (P = 0.124) and British (P = 0.910). Polymorphism rs525891 clear demonstrated that group from Tomsk was significantly different from population of South Africa (P = 0.019). However, rs652625 demonstrated significant differences from Asian population: Chinese (P = 0.03) and Japanese (P = 0.004). Next, we have compared healthy individuals versus patients with TB. It was detected that no association between rs1800629, rs652625 polymorphisms, and positive TB cases. Importantly, AT genotype of polymorphism rs525891 was significantly associated with resistance to TB (odds ratio (OR) = 0.61; 95% confidence interval (CI): 0.41-0.9; P < 0.05). Conclusion: To the best of our knowledge, the polymorphism of TNFRSF1B (rs525891) was associated with TB, while genotype AT is protective [OR = 0.61] in Tomsk population. In contrast, no significant correlation was detected between polymorphism TNF-α (rs1800629) and TNFRSF1B (rs652625) genes and alveolar TB cases among population of Tomsk. In conclusion, our data expands the molecular particularities associated with TB. The study was supported by the grant of the Russia for Basic Research #15-04-05852.

Keywords: polymorphism, tuberculosis, TNF-α, TNFRSF1B gene

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Authors: Sitthichai Laisema, Panita Wannapiroon

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This study is a research and development which is intended to: 1) design ubiquitous collaborative learning activities with virtual teams using CPS processes to develop creative thinking and collaboration skills, and 2) assess the suitability of the ubiquitous collaborative learning activities. Its methods are divided into 2 phases. Phase 1 is the design of ubiquitous collaborative learning activities with virtual teams using CPS processes, phase 2 is the assessment of the suitability of the learning activities. The samples used in this study are 5 professionals in the field of learning activity design, ubiquitous learning, information technology, creative thinking, and collaboration skills. The results showed that ubiquitous collaborative learning activities with virtual teams using CPS processes to develop creative thinking and collaboration skills consist of 3 main steps which are: 1) preparation before learning, 2) learning activities processing and 3) performance appraisal. The result of the learning activities suitability assessment from the professionals is in the highest level.

Keywords: ubiquitous learning, collaborative learning, virtual team, creative problem solving

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Authors: Emanuela Zilli, Suana Tikvina, Davide Bonaldo, Monica Varotto, Scilla Rizzardi, Barbara Ruzzante, Raffaele Napolitano, Stefano Bevilacqua, Antonella Ruffatto

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A healthy workplace increases productivity, creativity and decreases absenteeism and turnover. It also contributes to creating a more secure work environment with fewer risks of violence. In the past 3 years, the healthcare system has suffered the psychological, economic and social consequences of the COVID-19 pandemic. On the other hand, the healthcare staff reductions determine high levels of work-related stress that are often unsustainable. The Hospital of Cittadella (in the province of Padua) has 400 beds and serves a territory of 300,000 inhabitants. The hospital itself counts 1.250 healthcare employees (healthcare professionals). This year, the Medical Board of Directors has requested additional staff; however, the economic situation of Italy can not sustain additional hires. At the same time, we have initiated projects that aim to increase well-being, decrease stress and encourage activities that promote self-care. One of the projects that the hospital has organized is the psychomotor practice. It is held by therapists and trainers who operate according to the traditional method. According to the literature, the psychomotor practice is specifically intended for the staff operating in the Intensive Care Unit, Emergency Department and Pneumology Ward. The project consisted of one session of 45 minutes a week for 3 months. This method brings focus to controlled breathing, posture, muscle work and movement that help manage stress and fatigue, creating a more mindful and sustainable lifestyle. In addition, a Qigong course was held every two weeks for 5 months. It is an ancient Chinese practice designed to optimize the energy within the body, reducing stress levels and increasing general well-being. Finally, Tibetan singing crystal bowls sessions, held by a music therapist, consisted of monthly guided meditation sessions using the sounds of the crystal bowls. Sound therapy uses the vibrations created from the crystal bowls to balance the vibrations within the body to promote relaxation. In conclusion, well-being and organizational performance are closely related to each other. It is crucial for any organization to encourage and maintain better physical and mental health of the healthcare staff as it directly affects productivity and, consequently, user satisfaction of the services provided.

Keywords: health promotion, healthcare workers management, Weel being and organizational performance, Psychomotor practice

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Authors: Kazuaki Shiraishi, Narumitsu Asai, Tsukasa Kitahara, Sosuke Mieno, Takaharu Kameoka

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The purpose of this research is to facilitate productivity advances in agriculture. To accomplish this, we developed an automatic three-dimensional (3D) recording system for growth of field crops that consists of a number of inexpensive modules: a very low-cost stereo camera, a couple of ZigBee wireless modules, a Raspberry Pi single-board computer, and a third generation (3G) wireless communication module. Our system uses an inexpensive Web stereo camera in order to keep total costs low. However, inexpensive video cameras record low-resolution images that are very noisy. Accordingly, in order to resolve these problems, we adopted a deep learning method. Based on the results of extended period of time operation test conducted without the use of an external power supply, we found that by using Super-Resolution Convolutional Neural Network method, our system could achieve a balance between the competing goals of low-cost and superior performance. Our experimental results showed the effectiveness of our system.

Keywords: 3D plant data, automatic recording, stereo camera, deep learning, image processing

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Authors: Khan Farhan Rafat, M. Junaid Hussain

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Seamless modification of an entity for the purpose of hiding a message of significance inside its substance in a manner that the embedding remains oblivious to an observer is known as steganography. Together with today's pervasive registering frameworks, steganography has developed into a science that offers an assortment of strategies for stealth correspondence over the globe that must, however, need a critical appraisal from security breach standpoint. Microsoft Word is amongst the preferably used word processing software, which comes as a part of the Microsoft Office suite. With a user-friendly graphical interface, the richness of text editing, and formatting topographies, the documents produced through this software are also most suitable for stealth communication. This research aimed not only to epitomize the fundamental concepts of steganography but also to expound on the utilization of Microsoft Word document as a carrier for furtive message exchange. The exertion is to examine contemporary message hiding schemes from security aspect so as to present the explorative discoveries and suggest enhancements which may serve a wellspring of information to encourage such futuristic research endeavors.

Keywords: hiding information in plain sight, stealth communication, oblivious information exchange, conceal, steganography

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Authors: F. Uriel, M. M. Fernandez Liporace

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In the last decade, academic achievement in higher education has become a topic of agenda in Argentina, regarding the high figures of adjustment problems, academic failure and dropout, and the low graduation rates in the context of massive classes and traditional teaching methods. Psychological variables, such as perceived social support, academic motivation and learning styles and strategies have much to offer since their measurement by tests allows a proper diagnose of their influence on academic achievement. Framed in a major research, several studies analysed multiple samples, totalizing 5135 students attending Argentinean public universities. The first goal was aimed at the identification of statistically significant differences in psychological variables -perceived social support, learning styles, learning strategies, and academic motivation- by age, gender, and degree of academic advance (freshmen versus sophomores). Thus, an inferential group differences study for each psychological dependent variable was developed by means of student’s T tests, given the features of data distribution. The second goal, aimed at examining associations between the four psychological variables on the one hand, and academic achievement on the other, was responded by correlational studies, calculating Pearson’s coefficients, employing grades as the quantitative indicator of academic achievement. The positive and significant results that were obtained led to the formulation of different predictive models of academic achievement which had to be tested in terms of adjustment and predictive power. These models took the four psychological variables above mentioned as predictors, using regression equations, examining predictors individually, in groups of two, and together, analysing indirect effects as well, and adding the degree of academic advance and gender, which had shown their importance within the first goal’s findings. The most relevant results were: first, gender showed no influence on any dependent variable. Second, only good achievers perceived high social support from teachers, and male students were prone to perceive less social support. Third, freshmen exhibited a pragmatic learning style, preferring unstructured environments, the use of examples and simultaneous-visual processing in learning, whereas sophomores manifest an assimilative learning style, choosing sequential and analytic processing modes. Despite these features, freshmen have to deal with abstract contents and sophomores, with practical learning situations due to study programs in force. Fifth, no differences in academic motivation were found between freshmen and sophomores. However, the latter employ a higher number of more efficient learning strategies. Sixth, freshmen low achievers lack intrinsic motivation. Seventh, models testing showed that social support, learning styles and academic motivation influence learning strategies, which affect academic achievement in freshmen, particularly males; only learning styles influence achievement in sophomores of both genders with direct effects. These findings led to conclude that educational psychologists, education specialists, teachers, and universities must plan urgent and major changes. These must be applied in renewed and better study programs, syllabi and classes, as well as tutoring and training systems. Such developments should be targeted to the support and empowerment of students in their academic pathways, and therefore to the upgrade of learning quality, especially in the case of freshmen, male freshmen, and low achievers.

Keywords: academic achievement, academic motivation, coping, learning strategies, learning styles, perceived social support

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Authors: Awatef Hicheur Cairns, Billel Gueni, Hind Hafdi, Christian Joubert, Nasser Khelifa

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Given the ever changing needs of the job markets, education and training centers are increasingly held accountable for student success. Therefore, education and training centers have to focus on ways to streamline their offers and educational processes in order to achieve the highest level of quality in curriculum contents and managerial decisions. Educational process mining is an emerging field in the educational data mining (EDM) discipline, concerned with developing methods to discover, analyze and provide a visual representation of complete educational processes. In this paper, we present our distributed computation platform which allows different education centers and institutions to load their data and access to advanced data mining and process mining services. To achieve this, we present also a comparative study of the different clustering techniques developed in the context of process mining to partition efficiently educational traces. Our goal is to find the best strategy for distributing heavy analysis computations on many processing nodes of our platform.

Keywords: educational process mining, distributed process mining, clustering, distributed platform, educational data mining, ProM

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Authors: Zhihua Cao, Hongfei Zhao, Zhongneng Wu

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The development of polar-based agroforestry was necessary due to the influence of the timber market environment in China, which can promote the coordinated development of forestry and agriculture, and gain remarkable ecological, economic and social benefits. The main agroforestry models of the main poplar planting area in Huaibei plain and along the Yangtze River plain were carried out. 11 typical management models of poplar were selected to sum up: pure poplar forest, poplar-rape-soybean, poplar-wheat-soybean, poplar-rape-cotton, poplar-wheat, poplar-chicken, poplar-duck, poplar-sheep, poplar-Agaricus blazei, poplar-oil peony, poplar-fish, represented by M0-M10, respectively. 12 indexes related with economic, ecological and social benefits (annual average cost, net income, ratio of output to investment, payback period of investment, land utilization ratio, utilization ratio of light energy, improvement and system stability of ecological and production environment, product richness, labor capacity, cultural quality of labor force, sustainability) were screened out to carry on the comprehensive evaluation and analysis to 11 kinds of typical agroforestry models based on analytic hierarchy process (AHP). The results showed that the economic benefit of each agroforestry model was in the order of: M8 > M6 > M9 > M7 > M5 > M10 > M4 > M1 > M2 > M3 > M0. The economic benefit of poplar-A. blazei model was the highest (332, 800 RMB / hm²), followed by poplar-duck and poplar-oil peony model (109, 820RMB /hm², 5, 7226 RMB /hm²). The order of comprehensive benefit was: M8 > M4 > M9 > M6 > M1 > M2 > M3 > M7 > M5 > M10 > M0. The economic benefit and comprehensive benefit of each agroforestry model were higher than that of pure poplar forest. The comprehensive benefit of poplar-A. blazei model was the highest, and that of poplar-wheat model ranked second, while its economic benefit was not high. Next were poplar-oil peony and poplar-duck models. It was suggested that the model of poplar-wheat should be adopted in the plain along the Yangtze River, and the whole cycle mode of poplar-grain, popalr-A. blazei, or poplar-oil peony should be adopted in Huaibei plain, northern Anhui. Furthermore, wheat, rape, and soybean are the main crops before the stand was closed; the agroforestry model of edible fungus or Chinese herbal medicine can be carried out when the stand was closed in order to maximize the comprehensive benefit. The purpose of this paper is to provide a reference for forest farmers in the selection of poplar agroforestry model in the future and to provide the basic data for the sustainable and efficient study of poplar agroforestry in Anhui province, eastern China.

Keywords: agroforestry, analytic hierarchy process (AHP), comprehensive benefit, model, poplar

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Authors: Anurag Jain, Rajneesh Kumar

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Cloud computing is the outcome of rapid growth of internet. Due to elastic nature of cloud computing and unpredictable behavior of user, load balancing is the major issue in cloud computing paradigm. An efficient load balancing technique can improve the performance in terms of efficient resource utilization and higher customer satisfaction. Load balancing can be implemented through task scheduling, resource allocation and task migration. Various parameters to analyze the performance of load balancing approach are response time, cost, data processing time and throughput. This paper demonstrates a two level load balancer approach by combining join idle queue and join shortest queue approach. Authors have used cloud analyst simulator to test proposed two level load balancer approach. The results are analyzed and compared with the existing algorithms and as observed, proposed work is one step ahead of existing techniques.

Keywords: cloud analyst, cloud computing, join idle queue, join shortest queue, load balancing, task scheduling

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Authors: Kelly Danielly Da Silva Alcantara, Daniel Fernando Molina Junqueira, Graziella Colato Antonio

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The Law No. 12,305/10, established by the National Solid Waste Policy (PNRS), provides major changes in the management and managing scenario of solid waste in Brazil. The PNRS established since changes from population behavior as environmental and the consciousness and commitment of the companies with the waste produced. The objective of this project is to conduct a benchmarking study of the management models of Waste Management Municipal Solid (MSW) in national and international levels emphasizing especially in the European Union (Portugal, France and Germany), which are reference countries in energy development, sustainability and consequently recovery of waste generated. The management that encompasses all stages that are included in this sector will be analyzed by benchmarking, as the collection, transportation, processing/treatment and final disposal of waste. Considering the needs to produce clean energy in Brazil, this study will allow the determination to the best treatment of the waste in order to reduce the amount of waste and increase the lifetime of the landfill. Finally, it intends to identify the energy recovery potential through a study analysis of economic viability, energy and sustainable based on a holistic approach.

Keywords: benchmarking, energy recovery, landfill, municipal solid waste

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Authors: Julien Romieux, Fabio Verdicchio

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Wireless Sensor Networks (WSNs), which sense environmental data with battery-powered nodes, require multi-hop communication. This power-demanding task adds an extra workload that is unfairly distributed across the network. As a result, nodes run out of battery at different times: this requires an impractical individual node maintenance scheme. Therefore we investigate a new Cooperative Sensing approach that extends the WSN operational life and allows a more practical network maintenance scheme (where all nodes deplete their batteries almost at the same time). We propose a novel cooperative algorithm that derives a piecewise representation of the sensed signal while controlling approximation accuracy. Simulations show that our algorithm increases WSN operational life and spreads communication workload evenly. Results convey a counterintuitive conclusion: distributing workload fairly amongst nodes may not decrease the network power consumption and yet extend the WSN operational life. This is achieved as our cooperative approach decreases the workload of the most burdened cluster in the network.

Keywords: cooperative signal processing, signal representation and approximation, power management, wireless sensor networks

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Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

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Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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Authors: M. A. Ferhat, M. N. Boukhatem, F. Chemat

Abstract:

Microwave Clevenger or microwave accelerated distillation (MAD) is a combination of microwave heating and distillation, performed at atmospheric pressure without added any solvent or water. Isolation and concentration of volatile compounds are performed by a single stage. MAD extraction of orange essential oil was studied using fresh orange peel from Valencia late cultivar oranges as the raw material. MAD has been compared with a conventional technique, which used a Clevenger apparatus with hydro-distillation (HD). MAD and HD were compared in term of extraction time, yields, chemical composition and quality of the essential oil, efficiency and costs of the process. Extraction of essential oils from orange peels with MAD was better in terms of energy saving, extraction time (30 min versus 3 h), oxygenated fraction (11.7% versus 7.9%), product yield (0.42% versus 0.39%) and product quality. Orange peels treated by MAD and HD were observed by scanning electronic microscopy (SEM). Micrographs provide evidence of more rapid opening of essential oil glands treated by MAD, in contrast to conventional hydro-distillation.

Keywords: clevenger, microwave, extraction; hydro-distillation, essential oil, orange peel

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Authors: J. O. Akinyele, R. W. Salim, K. O. Oikelome, O. T. Olateju

Abstract:

Rice Husk (RH) is the major byproduct in the processing of paddy rice. The management of this waste has become a big challenge to some of the rice producers, some of these wastes are left in open dumps while some are burn in the open space, and these two actions have been contributing to environmental pollution. This study evaluates an alternative waste management of this agricultural product for use as a civil engineering material. The RH was burn in a controlled environment to form Rice Husk Ash (RHA). The RHA was mix with lateritic clay at 0, 2, 4, 6, 8, and 10% proportion by weight. Chemical test was conducted on the open burn and controlled burn RHA with the lateritic clay. Physical test such as particle size distribution, Atterberg limits test, and density test were carried out on the mix material. The chemical composition obtained for the RHA showed that the total percentage compositions of Fe2O3, SiO2 and Al2O3 were found to be above 70% (class “F” pozzolan) which qualifies it as a very good pozzolan. The coefficient of uniformity (Cu) was 8 and coefficient of curvature (Cc) was 2 for the soil sample. The Plasticity Index (PI) for the 0, 2, 4, 6, 8. 10% was 21.0, 18.8, 16.7, 14.4, 12.4 and 10.7 respectively. The work concluded that RHA can be effectively used in hydraulic barriers and as a stabilizing agent in soil stabilization.

Keywords: rice husk ash, pozzolans, paddy rice, lateritic clay

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Authors: David Tresner-Kirsch

Abstract:

Reconciling patient medication lists from multiple sources is a critical task supporting the safe delivery of patient care. Manual reconciliation is a time-consuming and error-prone process, and recently attempts have been made to develop efficiency- and safety-oriented automated support for professionals performing the task. An important capability of any such support system is automated alignment – finding which medications from a list correspond to which medications from a different source, regardless of misspellings, naming differences (e.g. brand name vs. generic), or changes in treatment (e.g. switching a patient from one antidepressant class to another). This work describes a new algorithmic solution to this alignment task, using a greedy matching approach based on string similarity, edit distances, concept extraction and normalization, and synonym search derived from the RxNorm nomenclature. The accuracy of this algorithm was evaluated against a gold-standard corpus of 681 medication records; this evaluation found that the algorithm predicted alignments with 99% precision and 91% recall. This performance is sufficient to support decision support applications for medication reconciliation.

Keywords: clinical decision support, medication reconciliation, natural language processing, RxNorm

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Authors: Jean Marie Tshimula, Atsushi Togashi

Abstract:

We develop a data-science approach for providing an interactive visualization and predictive models to find insights into the projects' historical data in order for stakeholders understand some unseen opportunities in the African market that might escape them behind the online project portfolio of the African Development Bank. This machine learning-based web application identifies the market trend of the fastest growing economies across the continent as well skyrocketing sectors which have a significant impact on the future of business in Africa. Owing to this, the approach is tailored to predict where the investment needs are the most required. Moreover, we create a corpus that includes the descriptions of over more than 1,200 projects that approximately cover 14 sectors designed for some of 53 African countries. Then, we sift out this large amount of semi-structured data for extracting tiny details susceptible to contain some directions to follow. In the light of the foregoing, we have applied the combination of Latent Dirichlet Allocation and Random Forests at the level of the analysis module of our methodology to highlight the most relevant topics that investors may focus on for investing in Africa.

Keywords: machine learning, topic modeling, natural language processing, big data

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Authors: Bing Song, Kexi Han, Xuewei Lv

Abstract:

Titania slag is a high quality raw material containing titanium in the subsequent process of titanium pigment. The effects of cooling approaches of granulating, water cooling, and air cooling on chemical, phases, and acidolysis of Panzhihua titania slag were investigated. Compared to the original slag which was prepared by the conventional processing route, the results show that the titania slag undergoes oxidation of Ti³⁺during different cooling ways. The Ti₂O₃ content is 17.50% in the original slag, but it is 16.55% and 16.84% in water cooled and air-cooled slag, respectively. Especially, the Ti₂O₃ content in granulated slag is decreased about 27.6%. The content of Fe₂O₃ in granulated slag is approximately 2.86% also obviously higher than water (<0.5%) or air-cooled slag (<0.5%). Rutile in cooled titania slag was formed because of the oxidation of Ti³⁺. The rutile phase without a noticeable change in water cooled and air-cooled slag after the titania slag was cooled, but increased significantly in the granulated slag. The rate of sulfuric acid acidolysis of cooled slag is less than the original slag. The rate of acidolysis is 90.61% and 92.46% to the water-cooled slag and air-cooled slag, respectively. However, the rate of acidolysis of the granulated slag is less than that of industry slag about 20%, only 74.72%.

Keywords: cooling approaches, titania slag, granulating, sulfuric acid acidolysis

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Authors: Charn Loong Ng, Mamun Bin Ibne Reaz

Abstract:

As elderly population grows globally, the percentage of people diagnosed with musculoskeletal disorder (MSD) increase proportionally. Electromyography (EMG) is an important biosignal that contributes to MSD’s clinical diagnose and recovery process. Conventional conductive electrode has many disadvantages in the continuous EMG measurement application. This research has design a new surface EMG biosensor based on the parallel-plate capacitive coupling principle. The biosensor is developed by using a double-sided PCB with having one side of the PCB use to construct high input impedance circuitry while the other side of the copper (CU) plate function as biosignal sensing metal plate. The metal plate is insulated using kapton tape for contactless application. The result implicates that capacitive biosensor is capable to constantly capture EMG signal without having galvanic contact to human skin surface. However, there are noticeable noise couple into the measured signal. Post signal processing is needed in order to present a clean and significant EMG signal. A complete design of single ended, non-contact, high input impedance, front end EMG biosensor is presented in this paper.

Keywords: contactless, capacitive, biosensor, electromyography

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Authors: Swati Tyagi, Syed Abbas

Abstract:

Fractional-order Hopfield neural networks are generally used to model the information processing among the interacting neurons. To show the constancy of the processed information, it is required to analyze the stability of these systems. In this work, we perform Mittag-Leffler stability for the corresponding Caputo fractional-order bidirectional associative memory (BAM) neural networks with various time-delays. We derive sufficient conditions to ensure the existence and uniqueness of the equilibrium point by using the theory of topological degree theory. By applying the fractional Lyapunov method and Mittag-Leffler functions, we derive sufficient conditions for the global Mittag-Leffler stability, which further imply the global asymptotic stability of the network equilibrium. Finally, we present two suitable examples to show the effectiveness of the obtained results.

Keywords: bidirectional associative memory neural network, existence and uniqueness, fractional-order, Lyapunov function, Mittag-Leffler stability

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Authors: Pavel Zabrodin

Abstract:

The drawback of magnesium alloys is poor plasticity, which complicates the forming. Effective way of improving the properties of the cast magnesium alloy AZ31 (3 wt. % Al, 0.8 wt. % Zn, 0.2 wt. % Mn)) is to combine hot extrusion at 350°C and equal-channel angular pressing (ECAP) at 180°C. Because of reduced grain sizes, changes in the nature of the grain boundaries, and enhancement of a texture that favors basal dislocation glide, after this kind of processing, increase yield stress and ductility. For study of the effect of microstructure on the mechanisms for plastic deformation, there is some interest in investigating the mechanical properties of the ultrafinegrained (UFG) Mg alloy at low temperatures, before and after annealing. It found that the amplitude and statistics at the low-temperature jump-like deformation the Mg alloy of dependent on microstructure. Reduction of the average density of dislocations and grain growth during annealing causing a reduction in the amplitude of the jump-like deformation and changes in the distribution of surges in amplitude. It found that the amplitude and statistics at the low-temperature jump-like deformation UFG alloy dependent on temperature of deformation. Plastic deformation of UFG alloy at a temperature of 10 K occurs uniformly - peculiarities is not observed. Increasing of the temperature of deformation from 4,2 to 0,5 K is causing a reduction in the amplitude and increasing the frequency of the jump-like deformation.

Keywords: jump-like deformation, low temperature, plasticity, magnesium alloy

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Authors: Swati Bhomia, C. M. Kishtawal, Neeru Jaiswal

Abstract:

Traditionally, monsoon forecasts have encountered many difficulties that stem from numerous issues such as lack of adequate upper air observations, mesoscale nature of convection, proper resolution, radiative interactions, planetary boundary layer physics, mesoscale air-sea fluxes, representation of orography, etc. Uncertainties in any of these areas lead to large systematic errors. Global circulation models (GCMs), which are developed independently at different institutes, each of which carries somewhat different representation of the above processes, can be combined to reduce the collective local biases in space, time, and for different variables from different models. This is the basic concept behind the multi-model superensemble and comprises of a training and a forecast phase. The training phase learns from the recent past performances of models and is used to determine statistical weights from a least square minimization via a simple multiple regression. These weights are then used in the forecast phase. The superensemble forecasts carry the highest skill compared to simple ensemble mean, bias corrected ensemble mean and the best model out of the participating member models. This approach is a powerful post-processing method for the estimation of weather forecast parameters reducing the direct model output errors. Although it can be applied successfully to the continuous parameters like temperature, humidity, wind speed, mean sea level pressure etc., in this paper, this approach is applied to rainfall, a parameter quite difficult to handle with standard post-processing methods, due to its high temporal and spatial variability. The present study aims at the development of advanced superensemble schemes comprising of 1-5 day daily precipitation forecasts from five state-of-the-art global circulation models (GCMs), i.e., European Centre for Medium Range Weather Forecasts (Europe), National Center for Environmental Prediction (USA), China Meteorological Administration (China), Canadian Meteorological Centre (Canada) and U.K. Meteorological Office (U.K.) obtained from THORPEX Interactive Grand Global Ensemble (TIGGE), which is one of the most complete data set available. The novel approaches include the dynamical model selection approach in which the selection of the superior models from the participating member models at each grid and for each forecast step in the training period is carried out. Multi-model superensemble based on the training using similar conditions is also discussed in the present study, which is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional multi-model ensemble (MME) approaches. Further, a variety of methods that incorporate a 'neighborhood' around each grid point which is available in literature to allow for spatial error or uncertainty, have also been experimented with the above mentioned approaches. The comparison of these schemes with respect to the observations verifies that the newly developed approaches provide more unified and skillful prediction of the summer monsoon (viz. June to September) rainfall compared to the conventional multi-model approach and the member models.

Keywords: multi-model superensemble, dynamical model selection, similarity criteria, neighborhood technique, rainfall prediction

Procedia PDF Downloads 139