Search results for: medical image processing

Authors: Qingsheng Qi, Cuijuan Gao, Carol Sze Ki Lin

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Food waste can be defined as a by-product of food processing by industries and consumers, which has not been recycled or used for other purposes. Stringent waste regulations worldwide are pushing local companies and sectors towards higher sustainability standards. The development of novel strategies for food waste re-use is economically and environmentally sound, as it solves a waste management issue and represents an inexpensive nutrient source for biotechnological processes. For example, Yarrowia lipolytica is a yeast which can utilize hydrophobic substrates, such as fatty acids, lipids, and alkanes and simple carbon sources, such as glucose and glycerol, which can all be found in food waste. This broad substrate range makes Y. lipolytica a promising candidate for the degradation and valorisation of food waste, and for the production of organic acids, such as citric and α-ketoglutaric acids. Current research conducted in our group demonstrated that Y. lipolytica was shown to be able to produce succinic acid. In this talk, we will focus on the application of genetically modified yeast Y. lipolytica for fermentative succinic acid production with an aim to increase productivity and yield.

Keywords: food waste, succinic acid, Yarrowia lipolytica, bioplastic

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Authors: Vrajesh Chokshi

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In last three decades, the global economy is substantially changed. Today, we are living in highly inter-connected world. The global markets are more open and consumers are well informed about products and services. The information technology revolution has broken all barriers in global business. The E-commerce has given opportunities of global trades to corporate. The IT is extensively used in almost all industries. After liberalization in 1992, the Indian economy is also significantly changed. The IT (information technology) and ITES (IT enable services) are extensively used in supply chain management. In India, previously car rental service business was dominated by local organization and operated through local contact. This industry is very lucrative and to catch this opportunity, many new corporate have ventured into e-commerce car rental service business in India. As the market is very competitive, branding is also very important part of marketing strategy. Now, the E-commerce portals those are in car rental business in India have realized the importance of the same and have started usage of all types of communication channel to promote their brand in different Indian markets. At consumer side, the awareness is also being considerably increased due to marketing communication campaign run by these companies. This paper aims to understand effectiveness of branding strategies in car rental business in India and also tries to identify unique promotional strategies to consolidate brand image of this business in different Indian markets.

Keywords: branding strategies, car rental business, CRM (customer relationship management), ITES (information technology enabled services)

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Authors: Harisudha Kuresan, Dhanalakshmi Samiappan, T. Rama Rao

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In modern telecommunication applications, Glottal Closure Instants location finding is important and is directly evaluated from the speech waveform. Here, we study the GCI using Speech Event Detection using Residual Excitation and the Mean Based Signal (SEDREAMS) algorithm. Speech coding uses parameter estimation using audio signal processing techniques to model the speech signal combined with generic data compression algorithms to represent the resulting modeled in a compact bit stream. This paper proposes a sub-band coder SBC, which is a type of transform coding and its performance for GCI detection using SEDREAMS are evaluated. In SBCs code in the speech signal is divided into two or more frequency bands and each of these sub-band signal is coded individually. The sub-bands after being processed are recombined to form the output signal, whose bandwidth covers the whole frequency spectrum. Then the signal is decomposed into low and high-frequency components and decimation and interpolation in frequency domain are performed. The proposed structure significantly reduces error, and precise locations of Glottal Closure Instants (GCIs) are found using SEDREAMS algorithm.

Keywords: SEDREAMS, GCI, SBC, GOI

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Authors: Tarantino E., Disciglio G., Gagliardi A., Gatta G., Tarantino A.

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Fertilizer is a critical input for improving production and increasing crop yields. Consecutive experimental trials during six years (from 2010-2015) were carried out in Apulia region (south-eastern Italy) on seven crops grown in cylinder pots. The aim was to determinate the effects of chemical and organic fertilizer on marketable yield and other parameters of processing tomato (Lycopersicum esculentum L., cv Docet), lettuce (Lactuca sativa L., cv Canasta), cauliflower (Brassica oleracea L., cv Casper), pepper (Capsicum annum L., cv Akron), fennel (Foeniculum vulgare L., cv Tarquinia), eggplant (Solanum melongena L. cv Primato F1) and chard (Beta vulgaris L., Argentata). At harvest the quail-quantitative yield characteristics of each crop were determined. All of the experimental data were subjected to analysis of variance (ANOVA). Results showed that the yields for all of these crops were greater under the chemical system than the organic system whereas quite variable results were generally observed for the other characteristics of the yield.

Keywords: fertilizers, herbaceous crops, yield characteristics, succession

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Authors: F. Massri, M. Shkarneh, B. Almassri

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Water scarcity and increasing water demand especially for residential use are major challenges facing Palestine. The need to accurately forecast water consumption is useful for the planning and management of this natural resource. The main objective of this paper is to (i) study the major factors influencing the water consumption in Palestine, (ii) understand the general pattern of Household water consumption, (iii) assess the possible changes in household water consumption and suggest appropriate remedies and (iv) develop prediction model based on the Artificial Neural Network to the water consumption in Palestinian cities. The paper is organized in four parts. The first part includes literature review of household water consumption studies. The second part concerns data collection methodology, conceptual frame work for the household water consumption surveys, survey descriptions and data processing methods. The third part presents descriptive statistics, multiple regression and analysis of the water consumption in the two Palestinian cities. The final part develops the use of Artificial Neural Network for modeling the water consumption in Palestinian cities.

Keywords: water management, demand forecasting, consumption, ANN, Ramallah

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Authors: Angsumalin Puntho

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Disruptive technology has had a great influence on our everyday lives and the existence of an organization. Geologists in the public sector need to keep up with digital technology and be able to work and collaborate in a more effective manner. The result from SWOT and 7S McKinsey analyses suggest that there are inadequate IT personnel, no individual digital literacy development plan, and a misunderstanding of management policies. The Office of Civil Service Commission develops digital literacy skills that civil servants and government officers should possess in order to work effectively; it consists of nine dimensions, including computer skills, internet skills, cyber security awareness, word processing, spreadsheets, presentation programs, online collaboration, graphics editors and cyber security practices; and six steps of digital literacy development including self-assessment, individual development plan, self-learning, certified test, learning reflection, and practices. Geologists can use digital literacy as a learning tool to develop themselves for better career opportunities.

Keywords: disruptive technology, digital technology, digital literacy, computer skills

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Authors: Leyli Khavari, Javad Yousefian

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The aim of this study was to investigate the effect of physical biorhythm cycle on health-related fitness factors. For this purpose, 120 athlete and non-athlete male and female students were selected randomly and based on the level of physical activity divided into athletic and non-athletic groups. The exact date of birth and also when the subjects were in the positive, negative and critical physical biorhythm cycle was determined by calculation software biorhythm. The physical fitness factors tests, including Queens College Step Test, AAHPERD sit-ups; Wells stretch test and hand dynamometer. Students in three stages in positive, negative and critical physical cycle were tested. Data processing using SPSS software and statistical tests ANOVA with repeated measures and student t test was used for dependent. The results of this study showed that changes in physical fitness and physical biorhythm were not affected by changes in the 23-day physical cycle.

Keywords: AAHPERD test, biorhythm, physical cycle, Queens College Step Test

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Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores

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Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.

Keywords: SAR, generalized gamma distribution, detection curves, radar detection

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Authors: Budi Nurani Ruchjana, Atje Setiawan Abdullah, I. Gede Nyoman Mindra Jaya, Eddy Hermawan

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In this paper, we propose the application package to estimate parameters of spatiotemporal model based on the multivariate time series analysis using the R open-source software. We build packages mainly to estimate the parameters of the Generalized Space Time Autoregressive (GSTAR) model. GSTAR is a combination of time series and spatial models that have parameters vary per location. We use the method of Ordinary Least Squares (OLS) and use the Mean Average Percentage Error (MAPE) to fit the model to spatiotemporal real phenomenon. For case study, we use oil production data from volcanic layer at Jatibarang Indonesia or climate data such as rainfall in Indonesia. Software R is very user-friendly and it is making calculation easier, processing the data is accurate and faster. Limitations R script for the estimation of model parameters spatiotemporal GSTAR built is still limited to a stationary time series model. Therefore, the R program under windows can be developed either for theoretical studies and application.

Keywords: GSTAR Model, MAPE, OLS method, oil production, R software

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Authors: Abdelhadi Adel, Kadri Ouahab

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This paper proposes an improved approach based on MAS Architecture and Heuristic Algorithm for systematic maintenance to minimize makespan. We have implemented a problem-solving approach for optimizing the processing time, methods based on metaheuristics. The proposed approach is inspired by the behavior of the human body. This hybridization is between a multi-agent system and inspirations of the human body, especially genetics. The effectiveness of our approach has been demonstrated repeatedly in this paper. To solve such a complex problem, we proposed an approach which we have used advanced operators such as uniform crossover set and single point mutation. The proposed approach is applied to three preventive maintenance policies. These policies are intended to maximize the availability or to maintain a minimum level of reliability during the production chain. The results show that our algorithm outperforms existing algorithms. We assumed that the machines might be unavailable periodically during the production scheduling.

Keywords: multi-agent systems, emergence, genetic algorithm, makespan, systematic maintenance, scheduling, hybrid flow shop scheduling

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Authors: G. R. Constantine, M.C.K. Thilakasiri, V.S. Mohottala, T.V. Soundaram, D.S. Rathnayake, E.G.H.E. De Silva, A.L.S. Mohamed, V.R. Weerasekara

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Orthostatic hypotension is prevalent in the elderly population, and it is an important risk factor contributing to falls in the elderly. This study aims to evaluate the prevalence of orthostatic hypotension in hospitalized elderly patients, changes in blood pressure during the hospital stay, morbidities associated with it and its association with falls in the elderly. A cross-sectional descriptive study was conducted in the National Hospital of Sri Lanka (NHSL) in a sample of 120 patients of age 65 years or above who were admitted to the medical wards. The demographic, clinical data was obtained by an interviewer-administered questionnaire. Two validated questionnaires were used to assess symptoms and effects of orthostatic hypotension and risk factors associated with falls. Orthostatic hypotension on admission and after 3 days of hospital stay was measured by bed-side mercury sphygmomanometer. Prevalence of orthostatic hypotension among the study population was 63.3%(76 patients). But no significant change in the orthostatic hypotension noted after 3 days of hospital admission (SND 0.61, SE= 5.59, p=0.27). There was no significant association found between orthostatic hypotension and its symptoms (dizziness and vertigo, vision problems, malaise, fatigue, poor concentration, neck stiffness), impact on standing or walking and non-communicable diseases. Falls were experienced by 27.5 % (33 patients) of the study population and prevalence of patients with orthostatic hypotension who had experienced falls was 25.9% (28 patients). In conclusions, orthostatic hypotension is more prevalent among elderly patients, but It wasn’t associated with symptoms, and non-communicable diseases, or as a risk factor for falls in elderly.

Keywords: orthostatic hypotension, elderly falls, emergency geriatric, Sri Lanka

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Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: Antonia Stanojević, Agnes Akkerman

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In contemporary society, economically active people typically spend most of their waking hours doing their job. Having that in mind, this research examines how socialization at the workplace shapes political preferences. Innovatively, it examines, in particular, the possible relationship between employees’ voice suppression by the employer and the formation of their political preferences. Since the employer is perceived as an authority figure, their behavior might induce spillovers to attitudes about political authorities and authoritarian governance. Therefore, a positive effect of suppression of voice by employers on employees' preference for authoritarian governance is expected. Furthermore, this relation is expected to be mediated by two mechanisms: system justification and power distance. Namely, it is expected that suppression of voice would create a power distance organizational climate and increase employees’ acceptance of unequal distribution of power, as well as evoke attempts of oppression rationalization through system justification. The hypotheses will be tested on the data gathered within the first wave of Work and Politics Dataset 2017 (N=6000), which allows for a wide range of demographic and psychological control variables. Although a cross-sectional analysis to be used at this point does not allow for causal inferences, the confirmation of expected relationships would encourage and justify further longitudinal research on the same panel dataset, in order to get a clearer image of the causal relationship between employers' suppression of voice and workers' political preferences.

Keywords: authoritarian values, political preferences, power distance, system justification, voice suppression

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Authors: H. Maachou, A. Chagnes, G. Cote

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The present work reports the properties of chitosan/hydroxyapatite (Cs/HA: 100/00, 70/30 and 30/70) composite microspheres obtained by emulsification processing route. The morphology of chitosane microspheres was observed by a scanning electron microscope (SEM) which shows an aggregate of spherical microspheres with a particle size, determined by optical microscope, ranged from 4 to 10 µm. Thereafter, a biomimetic approach was used to study the in vitro biomineralization of these composites. It concerns the composites immersion in simulated body fluid (SBF) for different times. The deposited calcium phosphate was studied using X-ray diffraction analysis (XRD), FTIR spectroscopy and ICP analysis of phosphorus. In fact, the mineral formed on Cs/HA microspheres was a mixture of carbonated HA and β-TCP as showed by FTIR peaks at 1419,5 and 871,8 cm-1 and XRD peak at 29,5°. This formation was induced by the presence of HA in chitosan microspheres. These results are confirmed by SEM micrographs which chow the Ca-P crystals growth in form of cauliflowers. So, these materials are of great interest for bone regeneration applications due to their ability to nucleate calcium phosphates in presence of simulated body fluid (SBF).

Keywords: hydroxyapatite, chitosan, microsphere, composite, bone regeneration

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Authors: M. A. Askari, M. A. Nazari, P. Perrier, Y. Payan

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Growth and remodeling of biological structures have gained lots of attention over the past decades. Determining the response of living tissues to mechanical loads is necessary for a wide range of developing fields such as prosthetics design or computerassisted surgical interventions. It is a well-known fact that biological structures are never stress-free, even when externally unloaded. The exact origin of these residual stresses is not clear, but theoretically, growth is one of the main sources. Extracting body organ’s shapes from medical imaging does not produce any information regarding the existing residual stresses in that organ. The simplest cause of such stresses is gravity since an organ grows under its influence from birth. Ignoring such residual stresses might cause erroneous results in numerical simulations. Accounting for residual stresses due to tissue growth can improve the accuracy of mechanical analysis results. This paper presents an original computational framework based on gradual growth to determine the residual stresses due to growth. To illustrate the method, we apply it to a finite element model of a healthy human face reconstructed from medical images. The distribution of residual stress in facial tissues is computed, which can overcome the effect of gravity and maintain tissues firmness. Our assumption is that tissue wrinkles caused by aging could be a consequence of decreasing residual stress and thus not counteracting gravity. Taking into account these stresses seems therefore extremely important in maxillofacial surgery. It would indeed help surgeons to estimate tissues changes after surgery.

Keywords: finite element method, growth, residual stress, soft tissue

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Authors: Rihab Idoudi, Karim Saheb Ettabaa, Basel Solaiman, Kamel Hamrouni

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Medical association rules induction is used to discover useful correlations between pertinent concepts from large medical databases. Nevertheless, ARs algorithms produce huge amount of delivered rules and do not guarantee the usefulness and interestingness of the generated knowledge. To overcome this drawback, we propose an ontology based interestingness measure for ARs ranking. According to domain expert, the goal of the use of ARs is to discover implicit relationships between items of different categories such as ‘clinical features and disorders’, ‘clinical features and radiological observations’, etc. That’s to say, the itemsets which are composed of ‘similar’ items are uninteresting. Therefore, the dissimilarity between the rule’s items can be used to judge the interestingness of association rules; the more different are the items, the more interesting the rule is. In this paper, we design a distinct approach for ranking semantically interesting association rules involving the use of an ontology knowledge mining approach. The basic idea is to organize the ontology’s concepts into a hierarchical structure of conceptual clusters of targeted subjects, where each cluster encapsulates ‘similar’ concepts suggesting a specific category of the domain knowledge. The interestingness of association rules is, then, defined as the dissimilarity between corresponding clusters. That is to say, the further are the clusters of the items in the AR, the more interesting the rule is. We apply the method in our domain of interest – mammographic domain- using an existing mammographic ontology called Mammo with the goal of deriving interesting rules from past experiences, to discover implicit relationships between concepts modeling the domain.

Keywords: association rule, conceptual clusters, interestingness measures, ontology knowledge mining, ranking

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Authors: Jingting Luo, Yong Wang, Ying Wang

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Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

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Authors: Frantisek Bozek, Pavel Budinsky, Ignac Hoza, Alexandr Bozek, Magdalena Naplavova

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A cleaner production project was implemented in a bakery. The project is based on the substitution of the best available technique for an obsolete leaven production technology. The new technology enables production of durable, high-quality leavens. Moreover, 25% of flour as the original raw material can be replaced by pastry from the previous day production which has not been sold. That pastry was previously disposed in a waste incineration plant. Besides the environmental benefits resulting from less waste, lower consumption of energy, reduction of sewage waters quantity and floury dustiness there are also significant economic benefits. Payback period of investment was calculated with help of static method of financial analysis about 2.6 years, using dynamic method 3.5 years and an internal rate of return more than 29%. The supposed annual average profit after taxation in the second year of operation was incompliance with the real profit.

Keywords: bakery, best available technology, cleaner production, costs, economic benefit, efficiency, energy, environmental benefit, investment, savings

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Authors: Ramim Tanver Rahman, Muhammad Mahbub Sobhan, M. A. Alim

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This study reports on processing of biscuits using skinned, treated and dried cassava flour. Five samples of biscuits S2, S3, S4, S5, and S6 containing 8, 16, 24, 32, and 40% cassava flour with wheat flour and a control sample (S1) containing no cassava flour were processed. The weights of all the biscuit samples were higher than that of control biscuit. The biscuit containing cassava flour was lower width than the control biscuit. The spread ratio of biscuits with 16% cassava flour was higher than other combinations of cassava flour. No remarkable changes in moisture content, peroxide value, fatty acid value, texture, and flavor were observed up to 4 months of storage in ambient conditions (27° to 35°C). A decreasing trend in color, flavor, texture and overall acceptability was observed with the increased incorporation of cassava flour. The sample S1 (no cassava flour) secured the highest overall acceptability and sample S6 (40% cassava flour) obtained the lowest overall acceptability. It is recommended that good quality cassava flour fortified biscuits may be processed in industrial-scale substituting the wheat flour by cassava flour up to 24% levels.

Keywords: cassava flour, wheat flour, shelf life, spread ratio, storage, biscuit

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Authors: Marco Castagna

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Proposed paper is aimed to inquire about the relation between text and reader, focusing on the concept of ‘attestation’. Indeed, despite being widely accepted in semiotic research, even today the concept of text remains uncertainly defined. So, it seems to be undeniable that what is called ‘text’ offers an image of internal cohesion and coherence, that makes it possible to analyze it as an object. Nevertheless, this same object remains problematic when it is pragmatically activated by the act of reading. In fact, as for the T.A.R:D.I.S., that is the unique space-temporal vehicle used by the well-known BBC character Doctor Who in his adventures, every text appears to its own readers not only “bigger inside than outside”, but also offering spaces that change according to the different traveller standing in it. In a few words, as everyone knows, this singular condition raises the questions about the gnosiological relation between text and reader. How can a text be considered the ‘same’, even if it can be read in different ways by different subjects? How can readers can be previously provided with knowledge required for ‘understanding’ a text, but at the same time learning something more from it? In order to explain this singular condition it seems useful to start thinking about text as a device more than an object. In other words, this unique status is more clearly understandable when ‘text’ ceases to be considered as a box designed to move meaning from a sender to a recipient (marking the semiotic priority of the “code”) and it starts to be recognized as performative meaning hypothesis, that is discursively configured by one or more forms and empirically perceivable by means of one or more substances. Thus, a text appears as a “semantic hanger”, potentially offered to the “unending deferral of interpretant", and from time to time fixed as “instance of Discourse”. In this perspective, every reading can be considered as an answer to the continuous request for confirming or denying the meaning configuration (the meaning hypothesis) expressed by text. Finally, ‘attestation’ is exactly what regulates this dynamic of request and answer, through which the reader is able to confirm his previous hypothesis on reality or maybe acquire some new ones.Proposed paper is aimed to inquire about the relation between text and reader, focusing on the concept of ‘attestation’. Indeed, despite being widely accepted in semiotic research, even today the concept of text remains uncertainly defined. So, it seems to be undeniable that what is called ‘text’ offers an image of internal cohesion and coherence, that makes it possible to analyze it as an object. Nevertheless, this same object remains problematic when it is pragmatically activated by the act of reading. In fact, as for the T.A.R:D.I.S., that is the unique space-temporal vehicle used by the well-known BBC character Doctor Who in his adventures, every text appears to its own readers not only “bigger inside than outside”, but also offering spaces that change according to the different traveller standing in it. In a few words, as everyone knows, this singular condition raises the questions about the gnosiological relation between text and reader. How can a text be considered the ‘same’, even if it can be read in different ways by different subjects? How can readers can be previously provided with knowledge required for ‘understanding’ a text, but at the same time learning something more from it? In order to explain this singular condition it seems useful to start thinking about text as a device more than an object. In other words, this unique status is more clearly understandable when ‘text’ ceases to be considered as a box designed to move meaning from a sender to a recipient (marking the semiotic priority of the “code”) and it starts to be recognized as performative meaning hypothesis, that is discursively configured by one or more forms and empirically perceivable by means of one or more substances. Thus, a text appears as a “semantic hanger”, potentially offered to the “unending deferral of interpretant", and from time to time fixed as “instance of Discourse”. In this perspective, every reading can be considered as an answer to the continuous request for confirming or denying the meaning configuration (the meaning hypothesis) expressed by text. Finally, ‘attestation’ is exactly what regulates this dynamic of request and answer, through which the reader is able to confirm his previous hypothesis on reality or maybe acquire some new ones.

Keywords: attestation, meaning, reader, text

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Authors: Zhehao Zhang

Abstract:

Walking has become an indispensable and sustainable way of travel for college students in their daily lives; campus street is an important carrier for students to walk and take part in a variety of activities, improving the walkability of campus streets plays an important role in optimizing the quality of campus space environment, promoting the campus walking system and inducing multiple walking behaviors. The purpose of this paper is to explore the effect of campus layout, facility distribution, and location site selection on the walkability of campus streets, and assess the street design qualities from the elements of imageability, enclosure, complexity, transparency, and human scale, and further examines the relationship between street-level urban design perceptual qualities and walkability and its effect on walking behavior in the campus. Taking Tianjin University as the research object, this paper uses the optimized walk score method based on walking frequency, variety, and distance to evaluate the walkability of streets from a macro perspective and measures the urban design qualities in terms of the calculation of street physical environment characteristics, as well as uses behavior annotation and street image data to establish temporal and spatial behavior database to analyze walking activity from the microscopic view. In addition, based on the conclusions, the improvement and design strategy will be presented from the aspects of the built walking environment, street vitality, and walking behavior.

Keywords: walkability, streetscapes, pedestrian activity, walk score

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Authors: Harshkumar K. Desai, Anuj K. Desai, Jay P. Patel, Snehal V. Trivedi, Yogendrasinh Parmar

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The need of continuous improvement in a product or process in this era of global competition leads to apply value engineering for functional and aesthetic improvement in consideration with economic aspect too. Solar industries located at G.I.D.C., Makarpura, Vadodara, Gujarat, India; a manufacturer of variety of CNC Machines had a challenge to analyze the structural design of column, base, carriage and table of CNC Milling Machine in the account of reduction of overall weight of a machine without affecting the rigidity and accuracy at the time of operation. The identified task is the first attempt to validate and optimize the proposed design of ribbed structure statically using advanced modeling and analysis tools in a systematic way. Results of stress and deformation obtained using analysis software are validated with theoretical analysis and found quite satisfactory. Such optimized results offer a weight reduction of the final assembly which is desired by manufacturers in favor of reduction of material cost, processing cost and handling cost finally.

Keywords: CNC milling machine, optimization, finite element analysis (FEA), weight reduction

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Authors: Heramb Somthankar, Anujoy Chakraborty

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This paper presents a classification study on yield prediction in semiconductor production using machine learning approaches. A complicated semiconductor production process is generally monitored continuously by signals acquired from sensors and measurement sites. A monitoring system contains a variety of signals, all of which contain useful information, irrelevant information, and noise. In the case of each signal being considered a feature, "Feature Selection" is used to find the most relevant signals. The open-source UCI SECOM Dataset provides 1567 such samples, out of which 104 fail in quality assurance. Feature extraction and selection are performed on the dataset, and useful signals were considered for further study. Afterward, common machine learning algorithms were employed to predict whether the signal yields pass or fail. The most relevant algorithm is selected for prediction based on the accuracy and loss of the ML model.

Keywords: deep learning, feature extraction, feature selection, machine learning classification algorithms, semiconductor production monitoring, signal processing, time-series analysis

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Authors: A. Hamma, A. Pegoretti

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The paper focuses on the evaluation of mechanical performances and viscoelastic behaviour of starch-grafted-PP reinforced with kenaf fibres. Investigations were carried out on composites prepared by melt compounding and compression molding. Two aspects have been taken into account, the effects of various fibres loading rates (10, 20 and 30 wt.%) and the fibres aspect ratios (L/D=30 and 160). Good fibres/matrix interaction has been evidenced by SEM observations. However, processing induced variation of fibre length quantified by optical microscopy observations. Tensile modulus and ultimate properties, hardness and tensile impact stress, were found to remarkably increase with fibre loading. Moreover, short term tensile creep tests have proven that kenaf fibres improved considerably the creep stability. Modelling of creep behaviour by a four parameter Burger model was successfully used. An empirical equation involving Halpin-Tsai semi empirical model was also used to predict the elastic modulus of composites.

Keywords: mechanical properties, creep, fibres, thermoplastic composites, starch-grafted-PP

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Authors: Tuyuan Cheng

Abstract:

As we age, many things become more difficult. Among the abilities are the linguistic and cognitive ones. Competing theories have shown that these two functions could diminish together or that one is selectively affected by the other. In other words, some proposes aging affects sentence production in the same way it affects sentence comprehension and other cognitive functions, while some argues it does not.To address this question, the current investigation is conducted into the critical aspect of sentences as well as cognitive abilities – the syntactic complexity and the number of perspective shifts being contained in the elicited production. Healthy non-pathological aging is often characterized by a cognitive and neural decline in a number of cognitive abilities. Although the language is assumed to be of the more stable domain, a variety of findings in the cognitive aging literature would suggest otherwise. Older adults often show deficits in language production and multiple aspects of comprehension. Nevertheless, while some age differences likely reflect cognitive decline, others might reflect changes in communicative goals, and some even display cognitive advantages. In the domain of language processing, research efforts have been made in tests that probed a variety of communicative abilities. In general, there exists a distinction: Comprehension seems to be selectively unaffected, while production does not. The current study raises a novel question and investigates whether aging affects the production of relative clauses (RCs) under the cognitive factor of perspective shifts. Based on Perspective Hypothesis (MacWhinney, 2000, 2005), our cognitive processes build upon a fundamental system of perspective-taking, and language provides a series of cues to facilitate the construction and shifting of perspectives. These cues include a wide variety of constructions, including RCs structures. In this regard, linguistic complexity can be determined by the number of perspective shifts, and the processing difficulties of RCs can be interpreted within the theory of perspective shifting. Two experiments were conducted to study language production under controlled conditions. In Experiment 1, older healthy participants were tested on standard measures of cognitive aging, including MMSE (Mini-Mental State Examination), ToMI-2 (a simplified Theory of Mind Inventory-2), and a perspective-shifting comprehension task programmed with E-Prime. The results were analyzed to examine if/how they are correlated with aging people’s subsequent production data. In Experiment 2, the production profile of differing RCs, SRC vs. ORC, were collected with healthy aging participants who perform a picture elicitation task. Variable containing 0, 1, or 2 perspective shifts were juxtaposed respectively to the pictures and counterbalanced presented for elicitation. In parallel, a controlled group of young adults were recruited to examine the linguistic and cognitive abilities in question. The results lead us to the discussion whetheraging affects RCs production in a manner determined by its semantic structure or the number of perspective shifts it contains or the status of participants’ mental understanding. The major findingsare: (1) Elders’ production on Chinese RCtypes did not display intrinsic difficulty asymmetry. (2) RC types (the linguistic structural features) and the cognitiveperspective shifts jointly play important roles in the elders’ RCproduction. (3) The production of RC may defy the aging in the case offlexibly preserved cognitive ability.

Keywords: cognition aging, perspective hypothesis, perspective shift, relative clauses, sentence complexity

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Authors: Miroslav Popelka, Jakub Nozicka

Abstract:

The whole work is based on possibility to use Lego Mindstorms robotics systems to reduce costs. Lego Mindstorms consists of a wide variety of hardware components necessary to simulate, programme and test of robotics systems in practice. To programme algorithm, which simulates space using the ultrasonic sensor, was used development environment supplied with kit. Software Matlab was used to render values afterwards they were measured by ultrasonic sensor. The algorithm created for this paper uses theoretical knowledge from area of signal processing. Data being processed by algorithm are collected by ultrasonic sensor that scans 2D space in front of it. Ultrasonic sensor is placed on moving arm of robot which provides horizontal moving of sensor. Vertical movement of sensor is provided by wheel drive. The robot follows map in order to get correct positioning of measured data. Based on discovered facts it is possible to consider Lego Mindstorm for low-cost and capable kit for real-time modelling.

Keywords: LEGO Mindstorms, ultrasonic sensor, real-time modeling, 2D object, low-cost robotics systems, sensors, Matlab, EV3 Home Edition Software

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Authors: Youngjae Jin, Daeshik Kim

Abstract:

This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in Verilog HDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.

Keywords: auto-encoder, behavior model simulation, digital hardware design, pre-route simulation, Unsupervised feature learning

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Authors: A. Belayadi, A. Mougari, L. Ait-Gougam, F. Mekideche-Chafa

Abstract:

The artificial neural network is one of the interesting techniques that have been advantageously used to deal with modeling problems. In this study, the computing with artificial neural network (CANN) is proposed. The model is applied to modulate the information processing of one-dimensional task. We aim to integrate a new method which is based on a new coding approach of generating the input-output mapping. The latter is based on increasing the neuron unit in the last layer. Accordingly, to show the efficiency of the approach under study, a comparison is made between the proposed method of generating the input-output set and the conventional method. The results illustrated that the increasing of the neuron units, in the last layer, allows to find the optimal network’s parameters that fit with the mapping data. Moreover, it permits to decrease the training time, during the computation process, which avoids the use of computers with high memory usage.

Keywords: neural network computing, continuous functions generating the input-output mapping, decreasing the training time, machines with big memories

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Authors: Qianxi Lv, Junying Liang

Abstract:

Among the various modes of interpreting, simultaneous interpreting (SI) is regarded as a ‘complex’ and ‘extreme condition’ of cognitive tasks while consecutive interpreters (CI) do not have to share processing capacity between tasks. Given that SI exerts great cognitive demand, it makes sense to posit that the output of SI may be more compromised than that of CI in the linguistic features. The bulk of the research has stressed the varying cognitive demand and processes involved in different modes of interpreting; however, related empirical research is sparse. In keeping with our interest in investigating the quantitative linguistic factors discriminating between SI and CI, the current study seeks to examine the potential lexical simplification, syntactic complexity and sequential organization mechanism with a self-made inter-model corpus of transcribed simultaneous and consecutive interpretation, translated speech and original speech texts with a total running word of 321960. The lexical features are extracted in terms of the lexical density, list head coverage, hapax legomena, and type-token ratio, as well as core vocabulary percentage. Dependency distance, an index for syntactic complexity and reflective of processing demand is employed. Frequency motif is a non-grammatically-bound sequential unit and is also used to visualize the local function distribution of interpreting the output. While SI is generally regarded as multitasking with high cognitive load, our findings evidently show that CI may impose heavier or taxing cognitive resource differently and hence yields more lexically and syntactically simplified output. In addition, the sequential features manifest that SI and CI organize the sequences from the source text in different ways into the output, to minimize the cognitive load respectively. We reasoned the results in the framework that cognitive demand is exerted both on maintaining and coordinating component of Working Memory. On the one hand, the information maintained in CI is inherently larger in volume compared to SI. On the other hand, time constraints directly influence the sentence reformulation process. The temporal pressure from the input in SI makes the interpreters only keep a small chunk of information in the focus of attention. Thus, SI interpreters usually produce the output by largely retaining the source structure so as to relieve the information from the working memory immediately after formulated in the target language. Conversely, CI interpreters receive at least a few sentences before reformulation, when they are more self-paced. CI interpreters may thus tend to retain and generate the information in a way to lessen the demand. In other words, interpreters cope with the high demand in the reformulation phase of CI by generating output with densely distributed function words, more content words of higher frequency values and fewer variations, simpler structures and more frequently used language sequences. We consequently propose a revised effort model based on the result for a better illustration of cognitive demand during both interpreting types.

Keywords: cognitive demand, corpus-based, dependency distance, frequency motif, interpreting types, lexical simplification, sequential units distribution, syntactic complexity

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Authors: Yu Liang, Wei Wei

Abstract:

Spatial representation of numbers and numerical magnitude are important for preschoolers’ mathematical ability. Mental number line, a typical index to measure numbers spatial representation, and numerical comparison are both related to arithmetic obviously. However, they seem to rely on different mechanisms and probably influence arithmetic through different mechanisms. In line with this idea, preschool children were trained with two tasks to investigate which one is more important for approximate arithmetic. The training of numerical processing and number line estimation were proved to be effective. They both improved the ability of approximate arithmetic. When the difficulty of approximate arithmetic was taken into account, the performance in number line training group was not significantly different among three levels. However, two harder levels achieved significance in numerical comparison training group. Thus, comparing spatial representation ability, symbolic approximation arithmetic relies more on numerical magnitude. Educational implications of the study were discussed.

Keywords: approximate arithmetic, mental number line, numerical magnitude, preschooler

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