Search results for: spatial audio processing

Authors: Ali Essam El Shazly

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The slum survey of 'Sequina' area in Alexandria details the building rooms of twenty-building samples according to the integral measure of space syntax. The essence of room organization sets the most integrative 'visitor' domain between the 'inhabitant' wings of less integrated 'parent' than the 'children' structure with visual ring of 'balcony' space. Despite the collective real relative asymmetry of 'pheno-type' aggregation, the relative asymmetry of individual layouts reveals 'geno-type' structure of spatial diversity. The multifunction of rooms optimizes the integral structure of graph and visibility merge, which contrasts with the deep tailing structure of distinctive social domains. The most integrative layout inverts the geno-type into freed rooms of shallow 'inhabitant' domain against the off-centered 'visitor' space, while the most segregated layout further restricts the pheno-type through isolated 'visitor' from 'inhabitant' domains across the 'staircase' public domain. The catalyst 'kitchen & living' spaces demonstrate multi-structural dimensions among the various social domains. The former ranges from most exposed central integrity to the most hidden 'motherhood' territories. The latter, however, mostly integrates at centrality or at the further ringy 'childern' domain. The study concludes social structure of spatial integrity for redevelopment, which is determined through the micro-level survey of rooms with integral dimensions.

Keywords: Alexandria, Sequina slum, spatial integration, space syntax

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Authors: Khaled M. Alhawiti

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This paper investigates the future of medicine and the use of Natural language processing. The importance of having correct clinical information available online is remarkable; improving patient care at affordable costs could be achieved using automated applications to use the online clinical information. The major challenge towards the retrieval of such vital information is to have it appropriately coded. Majority of the online patient reports are not found to be coded and not accessible as its recorded in natural language text. The use of Natural Language processing provides a feasible solution by retrieving and organizing clinical information, available in text and transforming clinical data that is available for use. Systems used in NLP are rather complex to construct, as they entail considerable knowledge, however significant development has been made. Newly formed NLP systems have been tested and have established performance that is promising and considered as practical clinical applications.

Keywords: clinical information, information retrieval, natural language processing, automated applications

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Authors: Mounir Azzam, Valerie Graw, Andreas Rienow

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The Syrian war, which commenced in 2011, has resulted in significant changes in the real estate market in the Damascus metropolitan area, with rising levels of insecurity and disputes over tenure rights. The quest for spatial justice is, therefore, imperative, and this study performs a spatiotemporal analysis to investigate the impact of the war on real estate differentiation. Using the hedonic price models including 2,411 housing transactions over the period 2010-2022, this study aims to understand the spatial dynamics of the real estate market in wartime. Our findings indicate that war variables have had a significant impact on the differentiation and depreciation of property prices. Notably, property attributes have a more substantial impact on real estate values than district location, with severely damaged buildings in Damascus city resulting in an 89% decline in prices, while prices in Rural Damascus districts have decreased by 50%. Additionally, this study examines the urban texture of Damascus using correlation and homogeneity statistics derived from the gray-level co-occurrence matrix obtained from Google Earth Engine. We monitored 250 samples from hedonic datasets within three different years of the Syrian war (2015, 2019, and 2022). Our findings show that correlation values were highly differentiated, particularly among Rural Damascus districts, with a total decline of 87.2%. While homogeneity values decreased overall between 2015 and 2019, they improved slightly after 2019. The findings have valuable implications, not only for investment prospects in setting up a successful reconstruction strategy but also for spatial justice of property rights in strongly encouraging sustainable real estate development.

Keywords: hedonic price, real estate differentiation, reconstruction strategy, spatial justice, urban texture analysis

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Authors: H. G. C. P. Dinesh, G. Tharshini, M. P. B. Ekanayake, G. M. R. I. Godaliyadda

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This paper presents a new spatial feature extraction method based on principle component analysis (PCA) and Fisher Discernment Analysis (FDA) for facial expression recognition. It not only extracts reliable features for classification, but also reduces the feature space dimensions of pattern samples. In this method, first each gray scale image is considered in its entirety as the measurement matrix. Then, principle components (PCs) of row vectors of this matrix and variance of these row vectors along PCs are estimated. Therefore, this method would ensure the preservation of spatial information of the facial image. Afterwards, by incorporating the spectral information of the eigen-filters derived from the PCs, a feature vector was constructed, for a given image. Finally, FDA was used to define a set of basis in a reduced dimension subspace such that the optimal clustering is achieved. The method of FDA defines an inter-class scatter matrix and intra-class scatter matrix to enhance the compactness of each cluster while maximizing the distance between cluster marginal points. In order to matching the test image with the training set, a cosine similarity based Bayesian classification was used. The proposed method was tested on the Cohn-Kanade database and JAFFE database. It was observed that the proposed method which incorporates spatial information to construct an optimal feature space outperforms the standard PCA and FDA based methods.

Keywords: facial expression recognition, principle component analysis (PCA), fisher discernment analysis (FDA), eigen-filter, cosine similarity, bayesian classifier, f-measure

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Authors: Zhongde Wang, Fanwei Meng, Ling Yang

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Today, social media deeply engages in urban spatial production in a ‘Disembedding’ form, allowing the public to ‘foresight’ physical spaces through online platforms and subsequently engage in corresponding ‘sight’ and visits, thus leading to the emergence of ‘Internet Celebrity Spots’. This paper delves into the laws of action of online media, focusing on experiences. From the perspectives of the public, space, and media, it thoroughly analyzes the experiential design strategies of Chongqing's Liziba Light Rail Station, including the construction of the experiential mainline capturing the matrix of public behavior, the creation of experiential sidelines leveraging spatial advantages, and the deepening of experiential touchpoints to promote media resonance. This analysis aims to provide insights and references for similar urban spaces to transition from ‘internet-famous’ to ‘real-famous’ attractions.

Keywords: online media, urban space, disembedding, internet celebrity spots, experience design

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Authors: Aparna Lal, Ashwin Swaminathan, Teisa Holani

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Background: Clostridium difficile infections (CDIs) have been on the rise globally. In Australia, rates of CDI in all States and Territories have increased significantly since mid-2011. Identifying risk factors for CDI in the community can help inform targeted interventions to reduce infection. Methods: We examine the role of neighbourhood socio-economic status, demography, testing practices and the number of residential aged care facilities on spatial patterns in CDI incidence in the Australian Capital Territory. Data on all tests conducted for CDI were obtained from ACT Pathology by postcode for the period 1st January 2004 through 31 December 2014. Distribution of age groups and the neighbourhood Index of Relative Socio-economic Advantage Disadvantage (IRSAD) were obtained from the Australian Bureau of Statistics 2011 National Census data. A Bayesian spatial conditional autoregressive model was fitted at the postcode level to quantify the relationship between CDI and socio-demographic factors. To identify CDI hotspots, exceedance probabilities were set at a threshold of twice the estimated relative risk. Results: CDI showed a positive spatial association with the number of tests (RR=1.01, 95% CI 1.00, 1.02) and the resident population over 65 years (RR=1.00, 95% CI 1.00, 1.01). The standardized index of relative socio-economic advantage disadvantage (IRSAD) was significantly negatively associated with CDI (RR=0.74, 95% CI 0.56, 0.94). We identified three postcodes with high probability (0.8-1.0) of excess risk. Conclusions: Here, we demonstrate geographic variations in CDI in the ACT with a positive association of CDI with socioeconomic disadvantage and identify areas with a high probability of elevated risk compared with surrounding communities. These findings highlight community-based risk factors for CDI.

Keywords: spatial, socio-demographic, infection, Clostridium difficile

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Authors: Fekadu L. Bayisa, Elvan Ceyhan, Todd D. Steury

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Interaction between individuals within the same species is an important component of population dynamics. An interaction can be either static (based on spatial overlap) or dynamic (based on movement interactions). Using GPS collar data, we can quantify both static and dynamic interactions between black bears. The goal of this work is to determine the level of black bear interactions using the 95% and 50% home ranges, as well as to model black bear spatial interactions, which could be attraction, avoidance/repulsion, or a lack of interaction at all, to gain new insights and improve our understanding of ecological processes. Recent methodological developments in home range estimation, inhomogeneous multitype/cross-type summary statistics, and envelope testing methods are explored to study the nature of black bear interactions. Our findings, in general, indicate that the black bears of one type in our data set tend to cluster around another type.

Keywords: autocorrelated kernel density estimator, cross-type summary function, inhomogeneous multitype Poisson process, kernel density estimator, minimum convex polygon, pointwise and global envelope tests

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Authors: Tianchen Dai

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Shantytowns are special historical products in china, possessing strong particularity and typicality, the theoretical value and the practical significance of which are deemed to hold great importance in the modern development of residential areas in China. The renovation planning of shantytowns can be very challenging in terms of cultural inheritance. The traditional lifestyle, one of the key elements building up residents’ perception of affiliation, should be carried forward in the renovation planning of shantytowns. Mobile vending can be considered as a rare business model survived within modern commercial environment, thanks to the unique spatial characteristics of Chinese shantytowns. This article mainly investigates the unique phenomenon of mobile vending in shantytowns, discussing the operating mechanism and rationality behind this commercial phenomenon. For humanistic concern, the innovative conservation of mobile vending, as a means to preserve the vivacious traditional lifestyle of local residents, can be realized through substantial urban design strategies, including spatial design of public space, height control of the facades, and traffic management around and inside shantytowns.

Keywords: cultural inheritance, mobile vending, renovation planning, shantytowns

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Authors: Sanjay Singh, Sushil Kumar, Rashmi Jain

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Quantum registering is another pattern in computational hypothesis and a quantum mechanical framework has a few helpful properties like Entanglement. We plan to store data concerning the structure and substance of a basic picture in a quantum framework. Consider a variety of n qubits which we propose to use as our memory stockpiling. In recent years classical processing is switched to quantum image processing. Quantum image processing is an elegant approach to overcome the problems of its classical counter parts. Image storage, retrieval and its processing on quantum machines is an emerging area. Although quantum machines do not exist in physical reality but theoretical algorithms developed based on quantum entangled states gives new insights to process the classical images in quantum domain. Here in the present work, we give the brief overview, such that how entangled states can be useful for quantum image storage and retrieval. We discuss the properties of tripartite Greenberger-Horne-Zeilinger and W states and their usefulness to store the shapes which may consist three vertices. We also propose the techniques to store shapes having more than three vertices.

Keywords: Greenberger-Horne-Zeilinger, image storage and retrieval, quantum entanglement, W states

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Authors: Yanjie Zhu, André Jesus, Irwanda Laory

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Structural Health Monitoring (SHM), involving data acquisition, data interpretation and decision-making system aim to continuously monitor the structural performance of civil infrastructures under various in-service circumstances. The main value and purpose of SHM is identifying damages through data interpretation system. Research on SHM has been expanded in the last decades and a large volume of data is recorded every day owing to the dramatic development in sensor techniques and certain progress in signal processing techniques. However, efficient and reliable data interpretation for damage detection under environmental variations is still a big challenge. Structural damages might be masked because variations in measured data can be the result of environmental variations. This research reports a novel method based on single-channel Blind Signal Separation (BSS), which extracts environmental effects from measured data directly without any prior knowledge of the structure loading and environmental conditions. Despite the successful application in audio processing and bio-medical research fields, BSS has never been used to detect damage under varying environmental conditions. This proposed method optimizes and combines Ensemble Empirical Mode Decomposition (EEMD), Principal Component Analysis (PCA) and Independent Component Analysis (ICA) together to separate structural responses due to different loading conditions respectively from a single channel input signal. The ICA is applying on dimension-reduced output of EEMD. Numerical simulation of a truss bridge, inspired from New Joban Line Arakawa Railway Bridge, is used to validate this method. All results demonstrate that the single-channel BSS-based method can recover temperature effects from mixed structural response recorded by a single sensor with a convincing accuracy. This will be the foundation of further research on direct damage detection under varying environment.

Keywords: damage detection, ensemble empirical mode decomposition (EEMD), environmental variations, independent component analysis (ICA), principal component analysis (PCA), structural health monitoring (SHM)

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Authors: Noor Azwa Azreen Binti Abd. Aziz, Muhamad Zaim Bin Mohd Rozi

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Moving towards the 4th Industrial Revolution, artificial intelligence (AI) is now more popular than ever. This subject is gaining significance every day and is continually expanding, often merging with other fields. Instead of merely being passive observers, there are benefits to understanding modern technology by delving into its inner workings. However, in a world teeming with digital information, the impact of AI on the spread of disinformation has garnered significant attention. The dissemination of inaccurate or misleading information is referred to as misinformation, posing a serious threat to democratic society, public debate, and individual decision-making. This article delves deep into the connection between AI and the dissemination of false information, exploring its potential, risks, and ethical issues as AI technology advances. The rise of AI has ushered in a new era in the dissemination of misinformation as AI-driven technologies are increasingly responsible for curating, recommending, and amplifying information on online platforms. While AI holds the potential to enhance the detection and mitigation of misinformation through natural language processing and machine learning, it also raises concerns about the amplification and propagation of false information. AI-powered deepfake technology, for instance, can generate hyper-realistic videos and audio recordings, making it increasingly challenging to discern fact from fiction.

Keywords: artificial intelligence, digital information, disinformation, ethical issues, misinformation

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Authors: Jitka Rychtarikova

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Regional differences in mortality in the Czech Republic (CR) may be moderate from a broader European perspective, but important discrepancies in life expectancy can be found between smaller territorial units. In this study territorial units are based on Administrative Districts of Municipalities with Extended Powers (MEP). This definition came into force January 1, 2003. There are 205 units and the city of Prague. MEP represents the smallest unit for which mortality patterns based on life tables can be investigated and the Czech Statistical Office has been calculating such life tables (every five-years) since 2004. MEP life tables from 2009-2013 for males and females allowed the investigation of three main life cycles with the use of temporary life expectancies between the exact ages of 0 and 35; 35 and 65; and the life expectancy at exact age 65. The results showed regional survival inequalities primarily in adult and older ages. Consequently, only mortality indicators for adult and elderly population were related to census 2011 unlinked data for the same age groups. The most relevant socio-economic factors taken from the census are: having a partner, educational level and unemployment rate. The unemployment rate was measured for adults aged 35-64 completed years. Exploratory spatial data analysis methods were used to detect regional patterns in spatially contiguous units of MEP. The presence of spatial non-stationarity (spatial autocorrelation) of mortality levels for male and female adults (35-64), and elderly males and females (65+) was tested using global Moran’s I. Spatial autocorrelation of mortality patterns was mapped using local Moran’s I with the intention to depict clusters of low or high mortality and spatial outliers for two age groups (35-64 and 65+). The highest Moran’s I was observed for male temporary life expectancy between exact ages 35 and 65 (0.52) and the lowest was among women with life expectancy of 65 (0.26). Generally, men showed stronger spatial autocorrelation compared to women. The relationship between mortality indicators such as life expectancies and socio-economic factors like the percentage of males/females having a partner; percentage of males/females with at least higher secondary education; and percentage of unemployed males/females from economically active population aged 35-64 years, was evaluated using multiple regression (OLS). The results were then compared to outputs from geographically weighted regression (GWR). In the Czech Republic, there are two broader territories North-West Bohemia (NWB) and North Moravia (NM), in which excess mortality is well established. Results of the t-test of spatial regression showed that for males aged 30-64 the association between mortality and unemployment (when adjusted for education and partnership) was stronger in NM compared to NWB, while educational level impacted the length of survival more in NWB. Geographic variation and relationships in mortality of the CR MEP will also be tested using the spatial Durbin approach. The calculations were conducted by means of ArcGIS 10.6 and SAS 9.4.

Keywords: Czech Republic, mortality, municipality, socio-economic factors, spatial analysis

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Authors: Dong Liu

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By sending a high-frequency probe wave and a low-frequency pump wave to a specimen, the vibroacoustic method evaluates the defect’s severity according to the modulation index of the received signal. Many studies experimentally proved the significant sensitivity of the modulation index to the tiny contact type defect. However, it has also been found that the modulation index was highly affected by the frequency of probe or pump waves. Therefore, the chirp signal has been introduced to the VAM method since it can assess multiple frequencies in a relatively short time duration, so the robustness of the VAM method could be enhanced. Consequently, the signal processing method needs to be modified accordingly. Various studies utilized different algorithms or combinations of algorithms for processing the VAM signal method by chirp excitation. These signal process methods were compared and used for processing a VAM signal acquired from the steel samples.

Keywords: vibroacoustic modulation, nonlinear acoustic modulation, nonlinear acoustic NDT&E, signal processing, structural health monitoring

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Authors: Sajed Yaghoubnezhad, Sedygheh Rezai

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Background and Aim: Since currently in Iran, students with learning disabilities are identified after entering school, and with the approach to the gap between IQ and academic achievement, the purpose of this study is to design and calculate the content validity of the pre-school screening checklist (5-7) exposed to learning difficulties. Methods: This research is a fundamental study, and in terms of data collection method, it is quantitative research with a descriptive approach. In order to design this checklist, after reviewing the research background and theoretical foundations, cognitive abilities (visual processing, auditory processing, phonological awareness, executive functions, spatial visual working memory and fine motor skills) are considered the basic variables of school learning. The basic items and worksheets of the screening checklist of pre-school students 5 to 7 years old with learning difficulties were compiled based on the mentioned abilities and were provided to the specialists in order to calculate the content validity ratio index. Results: Based on the results of the table, the validity of the CVR index of the background information checklist is equal to 0.9, and the CVR index of the performance checklist of preschool children (5 to7 years) is equal to 0.78. In general, the CVR index of this checklist is reported to be 0.84. The results of this study provide good evidence for the validity of the pre-school sieve screening checklist (5-7) exposed to learning difficulties.

Keywords: checklist, screening, preschoolers, learning difficulties

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Authors: Huang Hao, Li Weiwen

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Global biodiversity continues to decline as a result of global climate change and various human activities, such as habitat destruction, pollution, introduction of alien species and overfishing. Although there are connections between global marine organisms more or less, it is better to have clear geographical boundaries in order to facilitate the assessment and management of different biogeographical zones. And so area based management tools (ABMT) are considered as the most effective means for the conservation and sustainable use of marine biodiversity. On a large scale, the geographical gap (or barrier) is the main factor to influence the connectivity, diffusion, ecological and evolutionary process of marine organisms, which results in different distribution patterns. On a small scale, these factors include geographical location, geology, and geomorphology, water depth, current, temperature, salinity, etc. Therefore, the analysis on geographic and environmental factors is of great significance in the study of biodiversity characteristics. This paper summarizes the marine spatial classification and ABMTs used in coastal area, open oceans and deep sea. And analysis principles and methods of marine spatial classification based on biogeographic related factors, and take China Near Sea (CNS) area as case study, and select key biogeographic related factors, carry out marine spatial classification at biological region scale, ecological regionals scale and biogeographical scale. The research shows that CNS is divided into 5 biological regions by climate and geographical differences, the Yellow Sea, the Bohai Sea, the East China Sea, the Taiwan Straits, and the South China Sea. And the bioregions are then divided into 12 ecological regions according to the typical ecological and administrative factors, and finally the eco-regions are divided into 98 biogeographical units according to the benthic substrate types, depth, coastal types, water temperature, and salinity, given the integrity of biological and ecological process, the area of the biogeographical units is not less than 1,000 km². This research is of great use to the coastal management and biodiversity conservation for local and central government, and provide important scientific support for future spatial planning and management of coastal waters and sustainable use of marine biodiversity.

Keywords: spatial classification, marine biodiversity, bio-geographical, conservation

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Authors: Kais Ben-Ahmed, Mhamed Ali-El-Aroui

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This paper develops a Local Generalized Linear Spatial Model (LGLSM) to describe the spatial variation of Visceral Leishmaniasis (VL) infection risk in northern and central Tunisia. The response from each region is a number of affected children less than five years of age recorded from 1996 through 2006 from Tunisian pediatric departments and treated as a poison county level data. The model includes climatic factors, namely averages of annual rainfall, extreme values of low temperatures in winter and high temperatures in summer to characterize the climate of each region according to each continentality index, the pluviometric quotient of Emberger (Q2) to characterize bioclimatic regions and component for residual extra-poison variation. The statistical results show the progressive increase in the number of affected children in regions with high continentality index and low mean yearly rainfull. On the other hand, an increase in pluviometric quotient of Emberger contributed to a significant increase in VL incidence rate. When compared with the original GLSM, Bayesian locally modeling is improvement and gives a better approximation of the Tunisian VL risk estimation. According to the Bayesian approach inference, we use vague priors for all parameters model and Markov Chain Monte Carlo method.

Keywords: generalized linear spatial model, local model, extra-poisson variation, continentality index, visceral leishmaniasis, Tunisia

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Authors: Seongsoo Lee

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Motion estimation occupies the heaviest computation in HEVC (high efficiency video coding). Many fast algorithms such as TZS (test zone search) have been proposed to reduce the computation. Still the huge computation of the motion estimation is a critical issue in the implementation of HEVC video codec. In this paper, motion estimator architecture with optimized number of PEs (processing element) is presented by exploiting early termination. It also reduces hardware size by exploiting parallel processing. The presented motion estimator architecture has 8 PEs, and it can efficiently perform TZS with very high utilization of PEs.

Keywords: motion estimation, test zone search, high efficiency video coding, processing element, optimization

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Authors: Jamunarani Appalasamy, Tha Kyi Kyi, Quek Kia Fatt, Joyce Pauline Joseph, Anuar Zaini M. Zain

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Background: The Health Belief Theory had always been associated with chronic disease management. Various health behaviour concepts and perception branching from this Health Belief Theory had involved with medication understanding, use, and self-efficacy which directly link to medication adherence. In a previous quantitative and qualitative study, stroke patients in Malaysia were found to be strongly believing information obtained by various sources such as the internet and social communication. This action leads to lower perception of their stroke preventative medication benefit which in long-term creates non-adherence. Hence, this study intends to pilot an intervention which uses audio-visual concept incorporated with mHealth service to enhance learning and self-reflection among stroke patients to manage their disease. Methods/Design: Twenty patients will be allocated to a proposed intervention whereas another twenty patients are allocated to the usual treatment. The intervention involves a series of developed audio-visual videos sent via mobile phone which later await for responses and feedback from the receiver (patient) via SMS or recorded calls. The primary outcome would be the medication understanding, use and self-efficacy measured over two months pre and post intervention. Secondary outcome is measured from changes of blood parameters and other self-reported questionnaires. Discussion: This study shall also assess uptake/attrition, feasibility, and acceptability of this intervention. Trial Registration: NMRR-15-851-24737 (IIR)

Keywords: health belief, medication understanding, medication use, self-efficacy

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Authors: John Allard, Alex Rich, Iris Aguilar, Zachary Dodds

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With this paper we present several experiences deploying novel, low-cost resources for computing with 3D spatial models. Certainly, computing with 3D models undergirds some of our field’s most important contributions to the human experience. Most often, those are contrived artifacts. This work extends that tradition by focusing on novel resources that deliver uncontrived models of a system’s current surroundings. Atop this new capability, we present several projects investigating the student-accessibility of the computational tools for reasoning about the 3D space around us. We conclude that, with current scaffolding, real-world 3D models are now an accessible and viable foundation for creative computational work.

Keywords: 3D vision, matterport model, real-world 3D models, mathematical and computational methods

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Authors: Shantam Gupta

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The objective of this study is to address the critical need for automation in the domestic food processing sector and study its impact. Food is the one of the most basic physiological needs essential for the survival of a living being. Some of them have the capacity to prepare their own food (like most plants) and henceforth are designated as primary food producers; those who depend on these primary food producers for food form the primary consumers’ class (herbivores). Some of the organisms relying on the primary food are the secondary food consumers (carnivores). There is a third class of consumers called tertiary food consumers/apex food consumers that feed on both the primary and secondary food consumers. Humans form an essential part of the apex predators and are generally at the top of the food chain. But still further disintegration of the food habits of the modern human i.e. Homo sapiens, reveals that humans depend on other individuals for preparing their own food. The old notion of eating raw/brute food is long gone and food processing has become very trenchant in lives of modern human. This has led to an increase in dependence on other individuals for ‘processing’ the food before it can be actually consumed by the modern human. This has led to a further shift of humans in the classification of food chain of consumers. The effects of the shifts shall be systematically investigated in this paper. The processing of food has a direct impact on the economy of the individual (consumer). Also most individuals depend on other processing individuals for the preparation of food. This dependency leads to establishment of a vital link of dependency in the food web which when altered can adversely affect the food web and can have dire consequences on the health of the individual. This study investigates the challenges arising out due to this dependency and the impact of food processing on the economy of the individual. A comparison of Industrial food processing and processing at domestic platforms (households and restaurants) has been made to provide an idea about the present scenario of automation in the food processing sector. A lot of time and energy is also consumed while processing food at home for consumption. The high frequency of consumption of meals (greater than 2 times a day) makes it even more laborious. Through the medium of this study a pressing need for development of an automatic cooking machine is proposed with a mission to reduce the inter-dependency & human effort of individuals required for the preparation of food (by automation of the food preparation process) and make them more self-reliant The impact of development of this product has also further been profoundly discussed. Assumption used: The individuals those who process food also consume the food that they produce. (They are also termed as ‘independent’ or ‘self-reliant’ modern human beings.)

Keywords: automation, food processing, impact on economy, processing individual

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Authors: Samaniego Campoverde José Enrique, Rosero Muñoz Jorge Enrique, Luzcando Narea Lorena Elizabeth

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This paper presents a practical and theoretical model for the operation of the Tesla coil using digital signal processing. The research is based on the analysis of ten scientific papers exploring the development and operation of the Tesla coil. Starting from the Testa coil, several modifications were carried out on the Tesla coil, with the aim of amplifying the digital signal by making use of digital signal processing. To achieve this, an amplifier with a transistor and digital filters provided by MATLAB software were used, which were chosen according to the characteristics of the signals in question.

Keywords: tesla coil, digital signal process, equalizer, graphical environment

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Authors: Qiuyu Chen, Bin Long, Junxi Yang

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Located in the southwest of the "roof of the world", Tibet is the origin center of Tibetan Culture.Lhasa, Shigatse and Gyantse are three famous historical and cultural cities in Tibet. They have always been prominent political, economic and cultural cities, and have accumulated the unique aesthetic orientation and value consciousness of Tibet's urban construction. "Archetype" usually refers to the theoretical origin of things, which is the collective unconscious precipitation. The archetype theory fundamentally explores the dialectical relationship between image expression, original form and behavior mode. By abstracting and describing typical phenomena or imagery of the archetype object can observe the essence of objects, explore ways in which object phenomena arise. Applying archetype theory to the field of urban planning helps to gain insight, evaluation, and restructuring of the complex and ever-changing internal structural units of cities. According to existing field investigations, it has been found that Dzong, Temple, Linka and traditional residential systems are important structural units that constitute the urban space of Lhasa, Shigatse and Gyantse. This article applies the thinking method of archetype theory, starting from the imagery expression of urban spatial pattern, using technologies such as ArcGIS, Depthmap, and Computer Vision to descriptively identify the spatial representation and plane relationship of three cities through remote sensing images and historical maps. Based on historical records, the spatial characteristics of cities in different historical periods are interpreted in a hierarchical manner, attempting to clarify the origin of the formation and evolution of urban pattern imagery from the perspectives of geopolitical environment, social structure, religious theory, etc, and expose the growth laws and key driving forces of cities. The research results can provide technical and material support for important behaviors such as urban restoration, spatial intervention, and promoting transformation in the region.

Keywords: archetype theory, urban spatial imagery, original form and pattern, behavioral driving force, Tibet

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Authors: Morteza Mohri Esfahani, Amir S. H. Rozatian, Morteza Mozaffari

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Single phase magnetite nanoparticles and Bi-substituted ones were prepared by mechanochemical processing (MCP). The effects of Bi-substitution on the structural and magnetic properties of the nanoparticles were studied by X-ray Diffraction (XRD) and magnetometry techniques, respectively. The XRD results showed that all samples have spinel phase and by increasing Bi content, the main diffraction peaks were shifted to higher angles, which means the lattice parameter decreases from 0.843 to 0.838 nm and then increases to 0.841 nm. Also, the results revealed that increasing Bi content lead to a decrease in saturation magnetization (Ms) from 74.9 to 48.8 emu/g and an increase in coercivity (Hc) from 96.8 to 137.1 Oe.

Keywords: bi-substituted magnetite nanoparticles, mechanochemical processing, X-ray diffraction, magnetism

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Authors: Hamza Nejib, Okba Taouali

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This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.

Keywords: online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS

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Authors: Fan Gao, Lior Pachter

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The primary tool currently used to pre-process 10X Chromium single-cell ATAC-seq data is Cell Ranger, which can take very long to run on standard datasets. To facilitate rapid pre-processing that enables reproducible workflows, we present a suite of tools called scATAK for pre-processing single-cell ATAC-seq data that is 15 to 18 times faster than Cell Ranger on mouse and human samples. Our tool can also calculate chromatin interaction potential matrices, and generate open chromatin signal and interaction traces for cell groups. We use scATAK tool to explore the chromatin regulatory landscape of a healthy adult human brain and unveil cell-type specific features, and show that it provides a convenient and computational efficient approach for pre-processing single-cell ATAC-seq data.

Keywords: single-cell, ATAC-seq, bioinformatics, open chromatin landscape, chromatin interactome

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Authors: Shreya Pare, Parvin Akhter

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Remotely sensing image classification becomes a very challenging task owing to the high dimensionality of hyperspectral images. The pixel-wise classification methods fail to take the spatial structure information of an image. Therefore, to improve the performance of classification, spatial information can be integrated into the classification process. In this paper, the multilevel thresholding algorithm based on a modified fuzzy entropy function is used to perform the segmentation of hyperspectral images. The fuzzy parameters of the MFE function have been optimized by using a new meta-heuristic algorithm based on the Tree-Search algorithm. The segmented image is classified by a large distribution machine (LDM) classifier. Experimental results are shown on a hyperspectral image dataset. The experimental outputs indicate that the proposed technique (MFE-TSA-LDM) achieves much higher classification accuracy for hyperspectral images when compared to state-of-art classification techniques. The proposed algorithm provides accurate segmentation and classification maps, thus becoming more suitable for image classification with large spatial structures.

Keywords: classification, hyperspectral images, large distribution margin, modified fuzzy entropy function, multilevel thresholding, tree search algorithm, hyperspectral image classification using tree search algorithm

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Authors: Nattawadee Sinpattanawong, Yaowaret Tharawoot

Abstract:

This is an analytic and descriptive classroom-centered research, the purpose of which is to explore teacher verbal feedback on postgraduate students’ performances in presentations in English in an English for Specific Purposes (ESP) postgraduate classroom. The participants are a Thai female teacher, two Thai female postgraduate students, and two foreign male postgraduate students. The current study draws on both classroom observation and interview data. The class focused on the students’ presentations and the teacher’s providing verbal feedback on them was observed nine times with audio recording and taking notes. For the interviews, the teacher was interviewed about linkages between her verbal feedback and each student’s presentation skills in English. For the data analysis, the audio files from the observations were transcribed and analyzed both quantitatively and qualitatively. The quantitative approach addressed the frequencies and percentages of content of the teacher’s verbal feedback for each student’s performances based on eight presentation factors (content, structure, grammar, coherence, vocabulary, speaking skills, involving the audience, and self-presentation). Based on the quantitative data including the interview data, a qualitative analysis of the transcripts was made to describe the occurrences of several content of verbal feedback for each student’s presentation performances. The study’s findings may help teachers to reflect on their providing verbal feedback based on various students’ performances in presentation in English. They also help students who have similar characteristics to the students in the present study when giving a presentation in English improve their presentation performances by applying the teacher’s verbal feedback content.

Keywords: teacher verbal feedback, presentation factors, presentation in English, presentation performances

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Authors: Atef A. Ata, Sohair F. Rezeka, Ahmed El-Shenawy, Mohammed Diab

Abstract:

Image processing in today’s world grabs massive attentions as it leads to possibilities of broaden application in many fields of high technology. The real challenge is how to improve existing sorting system applications which consists of two integrated stations of processing and handling with a new image processing feature. Existing color sorting techniques use a set of inductive, capacitive, and optical sensors to differentiate object color. This research presents a mechatronics color sorting system solution with the application of image processing. A 5-DOF robot arm is designed and developed with pick and place operation to be main part of the color sorting system. Image processing procedure senses the circular objects in an image captured in real time by a webcam attached at the end-effector then extracts color and position information out of it. This information is passed as a sequence of sorting commands to the manipulator that has pick-and-place mechanism. Performance analysis proves that this color based object sorting system works very accurate under ideal condition in term of adequate illumination, circular objects shape and color. The circular objects tested for sorting are red, green and blue. For non-ideal condition, such as unspecified color the accuracy reduces to 80%.

Keywords: robotics manipulator, 5-DOF manipulator, image processing, color sorting, pick-and-place

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Authors: Liang Sun, Yi He

Abstract:

The origination and development of Chinese traditional villages have a strong link with clan society. Thousands of traditional villages are constituted by one big family who have the same surname. Villages’ basic social relationships are built on the basis of family kinship. Clan power controls family courtyards’ spatial structure and influences their evolvement process. Compared with other countries, research from perspective of clanism is a particular and universally applicable manner to recognize Chinese traditional villages’ space features. This paper takes traditional villages in astern Zhejiang province as examples, especially a single-clan village named Zoumatang. Through combining rural sociology with architecture, it clarifies the coupling relationship between clan structure and village space, reveals spatial composition and evolvement logic of family courtyards. Clan society pays much attention to the patrilineal kinship and genealogy. In astern Zhejiang province, clan is usually divided to ‘clan-branches-families’ three levels. Its structural relationship looks like pyramid, which results in ‘center-margin’ structure when projecting to villages’ space. Due to the cultural tradition of ancestor worship, family courtyards’ space exist similar ‘center-margin’ structure. Ancestor hall and family temple are respectively the space core of village and courtyard. Other parts of courtyard also shows order of superiority and inferiority. Elder and men must be the first. However, along with the disintegration of clan society, family courtyard gradually appears fragmentation trend. Its spatial structure becomes more and more flexible and its scale becomes smaller and smaller. Living conditions rather than ancestor worship turn out to be primary consideration. As a result, there are different courtyard historical prototype in different historic period. To some extent, Chinese present traditional villages’ conservation ignore the impact of clan society. This paper discovers the social significance of courtyard’s spatial texture and rebuilds the connection between society and space. It is expected to promote Chinese traditional villages’ conservation paying more attention to authenticity which defined in the historical process and integrity which built on the basis of social meaning.

Keywords: China, clanism, courtyard, evolvement process, spatial structure, traditional village

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Authors: Cholpassorn Sitthiwarongchai, Chutikarn Sriviboon

Abstract:

The two primary objectives of this research were (1) to examine the current knowledge and actual circumstance of agricultural workers about mangosteen product processing; and (2) to analyze and evaluate ways to develop capacity of mangosteen product processing. The population of this study was 15,125 people who work in the agricultural sector, in this context, mangosteen production, in the eastern part of Thailand that included Chantaburi Province, Rayong Province, Trad Province and Pracheenburi Province. The sample size based on Yamane’s calculation with 95% reliability was therefore 392 samples. Mixed method was employed included questionnaire and focus group discussion with Connoisseurship Model used in order to collect quantitative and qualitative data. Key informants were used in the focus group including agricultural business owners, academic people in agro food processing, local academics, local community development staff, OTOP subcommittee, and representatives of agro processing industry professional organizations. The study found that the majority of the respondents agreed with a high level (in five-rating scale) towards most of variables of knowledge management in agro food processing. The result of the current knowledge and actual circumstance of agricultural human resource in an arena of mangosteen product processing revealed that mostly, the respondents agreed at a high level to establish 7 variables. The guideline to developing the body of knowledge in order to enhance the capacity of the agricultural workers in mangosteen product processing was delivered in the focus group discussion. The discussion finally contributed to an idea to produce manuals for mangosteen product processing methods, with 4 products chosen: (1) mangosteen soap, (2) mangosteen juice, (3) mangosteen toffee, and (4) mangosteen preserves or jam.

Keywords: capacity enhancement, agricultural workers, mangosteen product processing, marketing management

Procedia PDF Downloads 192