Search results for: traditional housing

Authors: Santiago Guerra Fernández

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Abstract—This study is focused on exploring the conditions for the development of Galician music in the communities of Latin America after the massive arrival of Galician immigrants in the late nineteenth and early twentieth centuries, fleeing from hunger and misery in Spain. Migration would be accentuated after 1936 with the arrival of refugees from the Spanish Civil War due to their Republican political militancy fleeing fascism. The aim of this paper is to investigate the part that miscegenation with other local musical traditions has played within Galician expat music, helping to understand the complexity of contemporary Galician identity. Through archival work, the focus is set on examining the different traditional dances (such as the ‘muiñeira’), folk instruments (bagpipes, ‘pandeireta’), and poetic forms (‘cantiga’, ‘copla’) that were exported to Argentina and Cuba. Although research about migrant Galician music has been conducted in Spanish scholarship, there is a gap in the English literature on the topic that this paper intends to fill in. The results show how these musical traditions have played an essential role in shaping the social life and customs of Galician emigrants. By virtue of its malleability and blending properties, music serves here as an indicator of social cohesion.

Keywords: folk, Galicia, migration, identity

Procedia PDF Downloads 73

Authors: Apoorva Vinod, Archana Mathur, Snehanshu Saha

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Though there exists a plethora of Activation Functions (AFs) used in single and multiple hidden layer Neural Networks (NN), their behavior always raised curiosity, whether used in combination or singly. The popular AFs –Sigmoid, ReLU, and Tanh–have performed prominently well for shallow and deep architectures. Most of the time, AFs are used singly in multi-layered NN, and, to the best of our knowledge, their performance is never studied and analyzed deeply when used in combination. In this manuscript, we experiment with multi-layered NN architecture (both on shallow and deep architectures; Convolutional NN and VGG16) and investigate how well the network responds to using two different AFs (Sigmoid-Tanh, Tanh-ReLU, ReLU-Sigmoid) used alternately against a traditional, single (Sigmoid-Sigmoid, Tanh-Tanh, ReLUReLU) combination. Our results show that using two different AFs, the network achieves better accuracy, substantially lower loss, and faster convergence on 4 computer vision (CV) and 15 Non-CV (NCV) datasets. When using different AFs, not only was the accuracy greater by 6-7%, but we also accomplished convergence twice as fast. We present a case study to investigate the probability of networks suffering vanishing and exploding gradients when using two different AFs. Additionally, we theoretically showed that a composition of two or more AFs satisfies Universal Approximation Theorem (UAT).

Keywords: activation function, universal approximation function, neural networks, convergence

Procedia PDF Downloads 158

Authors: Kerstin Grunden, Ann Svensson, Berit Forsman, Christina Karlsson, Ayman Obeid

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The research question of the article is to explore whether the dialogue meetings method could be relevant for reflective learning among researchers and practitioners when welfare technology should be implemented in municipalities, or not. A testbed was planned to be implemented in a retirement home in a Swedish municipality, and the practitioners worked with a pre-study of that testbed. In the article, the dialogue between the researchers and the practitioners in the dialogue meetings is described and analyzed. The potential of dialogue meetings as an arena for learning and reflection among researchers and practitioners is discussed. The research methodology approach is participatory action research with mixed methods (dialogue meetings, focus groups, participant observations). The main findings from the dialogue meetings were that the researchers learned more about the use of traditional research methods, and the practitioners learned more about how they could improve their use of the methods to facilitate change processes in their organization. These findings have the potential both for the researchers and the practitioners to result in more relevant use of research methods in change processes in organizations. It is concluded that dialogue meetings could be relevant for reflective learning among researchers and practitioners when welfare technology should be implemented in a health care organization.

Keywords: dialogue meetings, implementation, reflection, test bed, welfare technology, participatory action research

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Authors: Naveed Ghani

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With the arrival of higher speed communication links and mature application running over the internet, the requirement for reliable, efficient and robust network designs rising day by day. Multi-Protocol Label Switching technology (MPLS) Virtual Private Networks (VPNs) have committed to provide optimal network services. They are gaining popularity in industry day by day. Enterprise customers are moving to service providers that offer MPLS VPNs. The main reason for this shifting is the capability of MPLS VPN to provide built in security features and any-to-any connectivity. MPLS VPNs improved the network performance due to fast label switching as compare to traditional IP Forwarding but traffic classification and policing was still required on per hop basis to enhance the performance of real time traffic which is delay sensitive (particularly voice and video). QoS (Quality of service) is the most important factor to prioritize enterprise networks’ real time traffic such as voice and video. This thesis is focused on the study of QoS parameters (e.g. delay, jitter and MOS (Mean Opinion Score)) for the real time traffic over MPLS VPNs. DiffServ (Differentiated Services) QoS model will be used over MPLS VPN network to get end-to-end service quality.

Keywords: network, MPLS, VPN, DiffServ, MPLS VPN, DiffServ QoS, QoS Model, GNS2

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Authors: Shazmeen Maroof

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The study is motivated by a desire to investigate whether there is substance to claims that, relative to traditional donors, China disregards human rights considerations when allocating overseas aid. While the stated policy of the U.S. is that consideration of potential aid recipients’ respect for human rights is mandatory, some quantitative studies have cast doubt on whether this is reflected in actual allocations. There is a lack of academic literature that formally assesses the extent to which the two countries' aid allocations differ; which is essential to test whether the criticisms of China's aid policy in comparison to that of the U.S. are justified. Using data on two standard human rights measures, 'Political Terror Scale' and 'Civil Liberties', the study analyse the two donors’ aid allocations among 125 countries over the period 2000 to 2014. The bivariate analysis demonstrated that a significant share of China’s aid flow to countries with poor human rights record. At the same time, the U.S. seems little different in providing aid to these countries. The empirical results obtained from the Fractional Logit model also provided some support to the general pessimism regarding China’s provision of aid to countries with poor human rights record, yet challenge the optimists expecting better targeted aid from the U.S. These findings are consistent with the split between humanitarian and non-humanitarian aid and in the sample of countries whose human rights record is below some threshold level.

Keywords: China's aid policy, foreign aid allocation, human rights, United States Foreign Assistance Act

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Authors: William Xiu Shun Wong, Myungsu Lim, Yoonjin Hyun, Chen Liu, Seongi Choi, Dasom Kim, Kee-Young Kwahk, Namgyu Kim

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Recently, many users have begun to frequently share their opinions on diverse issues using various social media. Therefore, numerous governments have attempted to establish or improve national policies according to the public opinions captured from various social media. In this paper, we indicate several limitations of the traditional approaches to analyze public opinion on science and technology and provide an alternative methodology to overcome these limitations. First, we distinguish between the science and technology analysis phase and the social issue analysis phase to reflect the fact that public opinion can be formed only when a certain science and technology is applied to a specific social issue. Next, we successively apply a start list and a stop list to acquire clarified and interesting results. Finally, to identify the most appropriate documents that fit with a given subject, we develop a new logical filter concept that consists of not only mere keywords but also a logical relationship among the keywords. This study then analyzes the possibilities for the practical use of the proposed methodology thorough its application to discover core issues and public opinions from 1,700,886 documents comprising SNS, blogs, news, and discussions.

Keywords: big data, social network analysis, text mining, topic modeling

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Authors: Yoonjeogn Kim

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The concept of flâneur means a walking observer with subjectivity in the urban city and at the same time, an idiomatic and unnamed existence in public. In the modern city, an individual, flâneur walking on the street, observes the street and collects the memories of the past, during which process the individual comes to understand what the past means. However, the concept tends to be narrowly applied to the white middle-class males, thereby excluding females and other marginalized groups. This paper expands the concept to examine black immigrants and black women, who traditionally fall outside the scope of the flâneur. Placing the black immigrants on the trajectory of literary figure of flâneur by reading Tony Morrison's Jazz, this essay revisits the relationship between street and characters in Jazz. In particular, this essay focuses on characters strolling on the street as well as their surroundings. Based on the traditional characteristics of the flâneur, this essay explicates how the black characters in Jazz are reinvented as the flâneur and moving observers with their autonomy to stroll around the city, while the city, which used to be an observer watching and predicting what happens to the characters, takes a position as a mere onlooker. This paper concludes with illustrating the black characters stroll on the street in Harlem and thereby recreating ordinary people living in Harlem as flâneur.

Keywords: jazz, the arcades project, flâneur, flânerie, street, city

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Authors: Ashraf Mohammed M. Eid, Hossam El Badry

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The bored pile friction resistance may be affected by many factors such as the method of construction, pile length and diameter, the soil properties, as well as the depth below ground level. These factors can be represented analytically to study the influence of diameter on the unit skin friction. In this research, the Egyptian Code of soil mechanics is used to assess the skin friction capacity for either the ordinary pile diameter as well as for the large pile diameter. The later is presented in the code and through the work of some researchers based on the results of investigations adopted for a sufficient number of field tests. The comparative results of these researchers with respect to the Egyptian Code are used to check the adequacy of both methods. Based on the results of this study, the traditional static formula adopted for piles of diameter less than 60 cm may be continually used for larger piles by correlating the analyzed formulae. Accordingly, the corresponding modified angle of internal friction is concluded demonstrating a reduction of shear strength due to soil disturbance along the pile shaft. Based on this research the difference between driven piles and bored piles constructed in same soil can be assessed and a better understanding can be evaluated for the effect of different factors on pile skin friction capacity.

Keywords: large piles, static formula, friction piles, sandy soils

Procedia PDF Downloads 500

Authors: T. Heikkinen, J. Oksman, T. Bragge, A. Nurmi, O. Kontkanen, T. Ahtoniemi

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Motor impairment is an inherent phenotypic feature of several chronic neurodegenerative diseases, and pharmacological therapies aimed to counterbalance the motor disability have a great market potential. Animal models of chronic neurodegenerative diseases display a number deteriorating motor phenotype during the disease progression. There is a wide array of behavioral tools to evaluate motor functions in rodents. However, currently existing methods to study motor functions in rodents are often limited to evaluate gross motor functions only at advanced stages of the disease phenotype. The most commonly applied traditional motor assays used in CNS rodent models, lack the sensitivity to capture fine motor impairments or improvements. Fine motor skill characterization in rodents provides a more sensitive tool to capture more subtle motor dysfunctions and therapeutic effects. Importantly, similar approach, kinematic movement analysis, is also used in clinic, and applied both in diagnosis and determination of therapeutic response to pharmacological interventions. The aim of this study was to apply kinematic gait analysis, a novel and automated high precision movement analysis system, to characterize phenotypic deficits in three different chronic neurodegenerative animal models, a transgenic mouse model (SOD1 G93A) for amyotrophic lateral sclerosis (ALS), and R6/2 and Q175KI mouse models for Huntington’s disease (HD). The readouts from walking behavior included gait properties with kinematic data, and body movement trajectories including analysis of various points of interest such as movement and position of landmarks in the torso, tail and joints. Mice (transgenic and wild-type) from each model were analyzed for the fine motor kinematic properties at young ages, prior to the age when gross motor deficits are clearly pronounced. Fine motor kinematic Evaluation was continued in the same animals until clear motor dysfunction with conventional motor assays was evident. Time course analysis revealed clear fine motor skill impairments in each transgenic model earlier than what is seen with conventional gross motor tests. Motor changes were quantitatively analyzed for up to ~80 parameters, and the largest data sets of HD models were further processed with principal component analysis (PCA) to transform the pool of individual parameters into a smaller and focused set of mutually uncorrelated gait parameters showing strong genotype difference. Kinematic fine motor analysis of transgenic animal models described in this presentation show that this method isa sensitive, objective and fully automated tool that allows earlier and more sensitive detection of progressive neuromuscular and CNS disease phenotypes. As a result of the analysis a comprehensive set of fine motor parameters for each model is created, and these parameters provide better understanding of the disease progression and enhanced sensitivity of this assay for therapeutic testing compared to classical motor behavior tests. In SOD1 G93A, R6/2, and Q175KI mice, the alterations in gait were evident already several weeks earlier than with traditional gross motor assays. Kinematic testing can be applied to a wider set of motor readouts beyond gait in order to study whole body movement patterns such as with relation to joints and various body parts longitudinally, providing a sophisticated and translatable method for disseminating motor components in rodent disease models and evaluating therapeutic interventions.

Keywords: Gait analysis, kinematic, motor impairment, inherent feature

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Authors: N. Charoenpokaraj, P. Chitman

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This research aims to study species, abundance, status of birds, the similarities and activity characteristics of birds which reap benefits from the research area in boat touring routes in Tha Ka sub-district, Amphawa District, Samut Songkram Province, Thailand. from October 2012 – September 2013. The data was analyzed to find the abundance, and similarity index of the birds. The results from the survey of birds on all three routes found that there are 33 families and 63 species. Route 3 (traditional coconut sugar making kiln – resort) had the most species; 56 species. There were 18 species of commonly found birds with an abundance level of 5, which calculates to 28.57% of all bird species. In August, 46 species are found, being the greatest number of bird species benefiting from this route. As for the status of the birds, there are 51 resident birds, 7 resident and migratory birds, and 5 migratory birds. On Route 2 and Route 3, the similarity index value is equal to 0.881. The birds are classified by their activity characteristics i.e. insectivore, piscivore, granivore, nectrivore and aquatic invertebrate feeder birds. Some birds also use the area for nesting.

Keywords: bird diversity, boat touring routes, Samut Songkram, similarity index

Procedia PDF Downloads 335

Authors: Marina Shakleina, Konstantin Shaklein, Stanislav Yakiro

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The digitalization of modern human life over the last decade has facilitated the acquisition, storage, and processing of data, which are used to detect changes in consumer preferences and to improve the internal efficiency of the production process. This emerging trend has attracted academic interest in the use of big data in research. The study focuses on modeling the social comfort of the Russian population for the period 2010-2021 using big data. Big data provides enormous opportunities for understanding human interactions at the scale of society with plenty of space and time dynamics. One of the most popular big data sources is Google Trends. The methodology for assessing social comfort using big data involves several steps: 1. 574 words were selected based on the Harvard IV-4 Dictionary adjusted to fit the reality of everyday Russian life. The set of keywords was further cleansed by excluding queries consisting of verbs and words with several lexical meanings. 2. Search queries were processed to ensure comparability of results: the transformation of data to a 10-point scale, elimination of popularity peaks, detrending, and deseasoning. The proposed methodology for keyword search and Google Trends processing was implemented in the form of a script in the Python programming language. 3. Block and summary integral indicators of social comfort were constructed using the first modified principal component resulting in weighting coefficients values of block components. According to the study, social comfort is described by 12 blocks: ‘health’, ‘education’, ‘social support’, ‘financial situation’, ‘employment’, ‘housing’, ‘ethical norms’, ‘security’, ‘political stability’, ‘leisure’, ‘environment’, ‘infrastructure’. According to the model, the summary integral indicator increased by 54% and was 4.631 points; the average annual rate was 3.6%, which is higher than the rate of economic growth by 2.7 p.p. The value of the indicator describing social comfort in Russia is determined by 26% by ‘social support’, 24% by ‘education’, 12% by ‘infrastructure’, 10% by ‘leisure’, and the remaining 28% by others. Among 25% of the most popular searches, 85% are of negative nature and are mainly related to the blocks ‘security’, ‘political stability’, ‘health’, for example, ‘crime rate’, ‘vulnerability’. Among the 25% most unpopular queries, 99% of the queries were positive and mostly related to the blocks ‘ethical norms’, ‘education’, ‘employment’, for example, ‘social package’, ‘recycling’. In conclusion, the introduction of the latent category ‘social comfort’ into the scientific vocabulary deepens the theory of the quality of life of the population in terms of the study of the involvement of an individual in the society and expanding the subjective aspect of the measurements of various indicators. Integral assessment of social comfort demonstrates the overall picture of the development of the phenomenon over time and space and quantitatively evaluates ongoing socio-economic policy. The application of big data in the assessment of latent categories gives stable results, which opens up possibilities for their practical implementation.

Keywords: big data, Google trends, integral indicator, social comfort

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Authors: Yusuf Kaygısız, Necmetti̇n Maraşlı

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Aluminum alloys are produced and used at various areas of industry and especially in the aerospace industry. The advantages of these alloys over traditional iron-based alloys are lightweight, corrosion resistance, and very good thermal and electrical conductivity. The aim of this work is to experimentally investigate the effect of growth rates on the eutectic spacings (λ), microhardness, tensile strength and electrical resistivity in Al–30wt.%Cu–6wt.%Mg eutectic alloy. Al–Cu–Mg eutectic alloy was directionally solidified at a constant temperature gradient (G=8.55 K/mm) with different growth rates, 9.43 to 173.3 µm/s by using a Bridgman-type furnace. The dependency of microstructure, microhardness, tensile strength and electrical resistivity for directionally solidified the Al-Cu-Mg eutectic alloy were investigated. Eutectic microstructure is consisting of regular Al2CuMg lamellar and Al2Cu rod phases with in the α (Al) solid solution matrix. The lamellar eutectic spacings were measured from transverse sections of the samples. It was found that the value of microstructures decrease with the increase the value the growth rates. The microhardness, tensile strength and electrical resistivity of the alloy also were measured from sample and relationships between them were experimentally analyzed by using regression analysis. According to present results, values tensile strength and electrical resistivity increase with increasing growth rates.

Keywords: directional solidification, aluminum alloys, microstructure, electrical properties, hardness test

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Authors: Amir Andria Gad Shehata

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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenanceneural network, LSTM, MLP, forecasting demand, inventory management

Procedia PDF Downloads 63

Authors: N. Chikhi-Chorfi, L. Arbia, S. Zenia, H.Lounici

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Opuntia ficus-indica belongs to the Cactaceae family. The cactus is mainly cultivated for its fruit (prickly pear) that, eaten after pealing, is sweet and juicy, and rich in nutritional compounds, such as ascorbic acid and polyphenols. Different parts of O. ficus-indica are used in the traditional medicine of several countries: the cladodes are utilized to reduce serum cholesterol level and blood pressure, for treatment of ulcers, rheumatic pain, wounds, fatigue, capillary fragility, and liver conditions. This original study, investigate the effect of polyphenols of O. ficus indica (cactus) cladodes against periodontal bacteria collected from patients with periodontitis. The quantitative analysis of total polyphenols (TPP) was determined with Follin-Ciocalteu method. Different concentrations of extracts of O. ficus indica were tested by the disk method on two bacterial strains: Porphyromonas gingivalis and Prevotella intermedia responsible for periodontal disease. The results showed a good correlation between the concentration of total polyphenols and the antibacterial activity of the extracts of Opuntia ficus indica against P. gingivalis and P. intermedia with R² = 0.94 and R² = 0.90 respectively. This observation suggests that these extracts could be used in the treatment and prevention of periodontitis.

Keywords: periodontal disease, P. gingivalis, P. intermedia, polyphenols, Opuntia ficus indica

Procedia PDF Downloads 146

Authors: Lianzhong Zhang, Chao Huang

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Sea-land segmentation is a basic step in many tasks such as sea surface monitoring and ship detection. The existing sea-land segmentation algorithms have poor segmentation accuracy, and the parameter adjustments are cumbersome and difficult to meet actual needs. Also, the current sea-land segmentation adopts traditional deep learning models that use Convolutional Neural Networks (CNN). At present, the transformer architecture has achieved great success in the field of natural images, but its application in the field of radar images is less studied. Therefore, this paper proposes a sea-land segmentation method based on the transformer architecture to strengthen edge supervision. It uses a self-attention mechanism with a gating strategy to better learn relative position bias. Meanwhile, an additional edge supervision branch is introduced. The decoder stage allows the feature information of the two branches to interact, thereby improving the edge precision of the sea-land segmentation. Based on the Gaofen-3 satellite image dataset, the experimental results show that the method proposed in this paper can effectively improve the accuracy of sea-land segmentation, especially the accuracy of sea-land edges. The mean IoU (Intersection over Union), edge precision, overall precision, and F1 scores respectively reach 96.36%, 84.54%, 99.74%, and 98.05%, which are superior to those of the mainstream segmentation models and have high practical application values.

Keywords: SAR, sea-land segmentation, deep learning, transformer

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Authors: Shrey Sharma, Gunjan Kumar Verma

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High density electrical prospecting has been widely used in groundwater investigation, civil engineering and environmental survey. For efficient inversion, the forward modeling routine, sensitivity calculation, and inversion algorithm must be efficient. This paper attempts to provide a brief summary of the past and ongoing developments of the method. It includes reviews of the procedures used for data acquisition, processing and inversion of electrical resistivity data based on compilation of academic literature. In recent times there had been a significant evolution in field survey designs and data inversion techniques for the resistivity method. In general 2-D inversion for resistivity data is carried out using the linearized least-square method with the local optimization technique .Multi-electrode and multi-channel systems have made it possible to conduct large 2-D, 3-D and even 4-D surveys efficiently to resolve complex geological structures that were not possible with traditional 1-D surveys. 3-D surveys play an increasingly important role in very complex areas where 2-D models suffer from artifacts due to off-line structures. Continued developments in computation technology, as well as fast data inversion techniques and software, have made it possible to use optimization techniques to obtain model parameters to a higher accuracy. A brief discussion on the limitations of the electrical resistivity method has also been presented.

Keywords: inversion, limitations, optimization, resistivity

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Authors: Larissa Negris de Souza, Ana Regina Mizrahy Cuperschmid, Daniel de Carvalho Moreira

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Augmented Reality (AR) alters the elaboration of the architectural project, which relates to project cognition: representation, visualization, and perception of information. Understanding these features from the earliest stages of the design can facilitate the study of relationships, zoning, and overall dimensions of the forms. This paper’s goal was to explore a new approach for information visualization during the early stages of architectural design using Augmented Reality (AR). A three-dimensional marker inspired by the Rubik’s Cube was developed, and its performance, evaluated. This investigation interwovens the acquired knowledge of traditional briefing methods and contemporary technology. We considered the concept of patterns (Alexander et al. 1977) to outline geometric forms and associations using visual programming. The Design Science Research was applied to develop the study. An SDK was used in a game engine to generate the AR app. The tool's functionality was assessed by verifying the readability and precision of the reconfigurable 3D marker. The results indicated an inconsistent response. To use AR in the early stages of architectural design the system must provide consistent information and appropriate feedback. Nevertheless, we conclude that our framework sets the ground for looking deep into AR tools for briefing design.

Keywords: augmented reality, cuboid marker, early design stages, graphic representation, patterns

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Authors: Sarah Noaman

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Utilizing renewable resources has become extensive solution for most problems in Egypt nowadays. It plays role in environmental issues such as energy crisis, lake of natural resources and climate change. This paper focuses on the importance of working with the key concepts of creating eco-friendly spaces in Egypt by using traditional perennial plants, such as Guadua bamboo as renewable resources in structures manufacture. Egypt is in critical need to search for alternative raw materials. Thus, this paper focuses on studying the usage of neglected yet affordable materials, such as Guadua bamboo in light weight structures and digital fabrication. Guadua bamboo has been cultivated throughout in tropical and subtropical areas. In Egypt, they exist in many rural areas where people try to control their growth by using pesticides as it serves no economic purpose. This paper aims to discuss the usage of Guadua bamboo either in its original state or after fabrication in the context of interior design and architecture. The results will show the applicability of using perennial plants as complementary materials in the manufacturing processes; also the conclusion will focus the lights on the importance of re-forming shallow water plants in interior design and architecture.

Keywords: digital fabrication, Guadua bamboo, zero-waste material, sustainable material, interior architecture

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Authors: Adel Fatima Zohra, Guendouz Abdelkader

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The solitary sector seems to appear nowadays as a third sector along the private and public ones, because of their ineptitude to take in charge the social exigency of the society regarding the lack in their local assets and the weakness of their financial institutions. The role of this sector is promoting a set of activities in the field of the charity, without aiming neither the individual profit nor a power practice. With the rise in the need of domestic resources, it is possible to count on the Zakat funding to realize some investment projects in order to develop the local society in many sectors as health, agriculture … etc. In the Islamic financial system, the Zakat is likely one of the most important instruments in financing the local development with the respect of the “Charia” rules: the amount of the Zakat is 2.5% of a wealth equivalent of each 85 gr of gold possessed since one year at least. In Algeria a fund of Zakat, was created since 2003 as an alternative to the public finding of development. This fund is a religious and social institution under the supervision of the ministry of religious affairs. This supervision covers two tasks: the first is traditional witch concern the distribution and the forwarding of the zakat to the poor people, and the second is modern concerning the financing of microcredits in the aim to enhance social and economic development. In this paper, we try to highlight the main role of the Zakat fund and its impact on the both social and economic development in Algeria.

Keywords: dogmatic instrument, solidary sector, zakat fund, micro project

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Authors: Han Longxiang

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In the process of treating industrial oil wastewater with complex components, the traditional treatment methods (flotation, coagulation, microwave heating, etc.) often produce high operating costs, secondary pollution, and other problems. In order to solve these problems, the materials with high flux and stability applied to surfactant-stabilized emulsions separation have gained huge attention in the treatment of oily wastewater. Nevertheless, four stable oil-in-water emulsions can be formed due to different surfactants (surfactant-free, anionic surfactant, cationic surfactant, and non-ionic surfactant), and the previous advanced materials can only separate one or several of them, cannot effectively separate in one step. Herein, a facile synthesis method of graphene-based multilevel filter materials (GMFM) can efficiently separate the oil-in-water emulsions stabilized with different surfactants only through its gravity. The prepared materials with high stability of 20 cycles show a high flux of ~ 5000 L m-2 h-1 with a high separation efficiency of > 99.9 %. GMFM can effectively separate the emulsion stabilized by mixed surfactants and oily wastewater from factories. The results indicate that the GMFM has a wide range of applications in oil-in-water emulsions separation in industry and environmental science.

Keywords: emulsion, filtration, graphene, one-step

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Authors: Krithika Kumaragurubaran, Mannu Thareja

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Saving our planet Earth is the responsibility of every human being. Global warming and carbon emissions are killing our planet. We must adopt sustainable practices to give our future generations an equal opportunity to enjoy this planet Earth, our home. One of the most used unsustainable materials is plastic. Plastics are used everywhere. They are cheap, durable, strong, waterproof, non-corrosive with a long life. So longthat it makes plastic unsustainable. With this paper, we want to bring awareness on the usage of plastic in the organizations and how to reduce it by adopting sustainable practices powered by technology. We have taken a case study on the usage of photo ID cards, which are commonly used for authentication and authorization. These ID cards are used by employees or visitors to get access to the restricted areas inside the office buildings. The scale of these plastic cards can be in thousands for a bigger organization. This paper proposes smart alternatives to Identity and Access Management (IAM) which could replace the traditional method of using plastic ID cards. Further, the proposed solution is secure with multi-factor authentication (MFA), cost effective as there is no need to manage the supply chain of ID cards, provides instant IAM with self-service, and has the convenience of smart phone. Smart IAM is not only user friendly however also environment friendly.

Keywords: sustainability, reduce plastic, IAM (Identity and Access Management), multi-factor authentication

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Authors: Jacqueline Rose T. Alipo-on, Francesca Isabelle F. Escobar, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar Al Dahoul

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Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases, which are considered one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis of ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heartbeat types. The dataset used in this work is the synthetic MIT-BIH Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: heartbeat classification, convolutional neural network, electrocardiogram signals, generative adversarial networks, long short-term memory, ResNet-50

Procedia PDF Downloads 128

Authors: Turk Ayman, Ahn Jong Hoon, Khalife K. Hala, Gali-Muhtasib Hala, Lee Mi Kyeong

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Laurus nobilis is an aromatic plant widely distributed in the Mediterranean region. The leaves of this plant are frequently used as a spice and as a traditional medicine for several diseases. In our present study, the methanolic extract of L. nobilis leaves showed antioxidant activity. Chromatographic separations of the EtOAc fraction which had the highest antioxidant activity led to the isolation of 12 compounds. Among them, there was a new phenylpropanoid derivative, which was identified by 1D and 2D NMR experiments, as well as high resolution mass spectrometry. In addition, two major compounds, catechin and epicatechin, which showed strong antioxidant activity may be responsible for the antioxidant activity of L. nobilis leaves. Since different plant parts may contain different types of constituents which contribute to the biological activities, we investigated the antioxidant activity of different parts of L. nobilis such as leaves, stems and fruits. Stems of L. nobilis showed the most potent antioxidant activity, followed by leaves. Further quantitation of total phenol and flavonoids contents revealed a positive correlation between the content of these compounds and antioxidant activity. Taken together, phenolic compounds including flavonoids are responsible for antioxidant activity of L. nobilis. In addition, stem parts of L. nobilis are suggested as good sources for antioxidant activity. Conclusively, L. nobilis might be effective in several free radical mediated diseases.

Keywords: antioxidant activity, different parts, Laurus nobilis, phenolic compound

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Authors: Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang

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Non-intrusive sensor-based human activity recognition (HAR) is utilized in a spectrum of applications, including fitness tracking devices, gaming, health care monitoring, and smartphone applications. Deep learning models such as convolutional neural networks (CNNs) and long short term memory (LSTM) recurrent neural networks (RNNs) provide a way to achieve HAR accurately and effectively. In this paper, we design a multi-layer hybrid architecture with CNN and LSTM and explore a variety of multi-layer combinations. Based on the exploration, we present a lightweight, hybrid, and multi-layer model, which can improve the recognition performance by integrating local features and scale-invariant with dependencies of activities. The experimental results demonstrate the efficacy of the proposed model, which can achieve a 94.7% activity recognition rate on a benchmark human activity dataset. This model outperforms traditional machine learning and other deep learning methods. Additionally, our implementation achieves a balance between recognition rate and training time consumption.

Keywords: deep learning, LSTM, CNN, human activity recognition, inertial sensor

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Authors: Najmuddin Najmuddin

Abstract:

The purpose of this study is to determine whether media usage and change of citizenship norms influence political participation. The focus of this study is to examine citizenship norms in the context of the development of information, and communication technology and how it will impact political participation in the context of Indonesia's transition to democracy. The study use survey method. The main theoretical framework is media and political participation. The results of this study reveal that gender, age and educational background of the respondents did not influence significantly media usage and citizenship norms. The Results also show that educational background is not a factor that distinguishes media usage but it becomes differentiating factor in citizenship norms. The results further show that the media usage has a significant correlation with citizenship norms and citizenship norms has a significant relationship with political participation. In addition, media usage and citizenship norms impact significantly to political participation. The sub-dimensions of citizenship norms (compliance, duty, and engaged citizen) provides a significant contribution to the sub-dimensions of political participation (traditional political participation, modern political participation, civic political participation). Based on the findings it can be concluded that the political euphoria in the era of transition to democracy has changed pattern media usage and citizenship norms of among the young generation.

Keywords: media, citizenship, norms, political, participation, democracy

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Authors: Leah Ghebreberhan, Liya Abraham, John Issac, Atul Kaushik

Abstract:

Medicinal plants are used for various indications in Eritrea according to traditional systems of medicine. Safety concerns, however, are dubious since some medicinal plants have toxic effects indeed. The medicinal plants under study (Commicarpus pedunculosis, Steganotaenia araliaceae, Boscia angustifolia, Solanum incanum, and Calpurnia aurea) are used in the treatment of various diseases. Thus, safety studies must be performed prior to usage since they are rich in phytoconstituents like saponins. Saponns are natural glycosides with several pharmacologic activities including hemolysis. The study was done to assess the level of saponin and toxic effects (hemolysis) of medicinal plants used in folk medicine. The plant extracts were subject to phytochemical analysis, foam test, and hemolytic assay. Regarding the Fh value, Solanam incanum consisted highest Fh value (20mm), whereas Boscia angustifolia showed the lowest Fh value (10mm). The level of hemolysis of all the plant extracts ranged between 9.0 to 20.2 %. All the plant extracts were suitable for treatment with respect to saponin level since they exhibited minimal hemolytic effect against erythrocytes.

Keywords: Boscia angustifolia, Calpurnia aurea, Commicarpus pedunculosis, hemolysis, saponin, Solanum incanum, Steganotaenia araliaceae

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Authors: Marthella Rivera Roidatua

Abstract:

Since the release of Convention on the Rights of Persons with Disabilities in 2006, disability became a mainstreamed global issue. Many developed countries have shown the continuous effort to improve their disability employment policy, for example, the US and the UK with their integrated support system through disability benefits. Relative little recent research on developing country is available. Surprisingly, Indonesia, just enacted the Law No.8/2016 on Disability that bravely highlighted on integrating disabled people into the workforce. It shows a positive progress shifting traditional perspective to what Tom Shakespeare’s concept of a social model of disability. But, the main question is how can this law support the disabled people to access and maintain paid work. Thus, besides the earlier literature reviews, interviews with leading sectors, Ministry of Social Affairs and Ministry of Manpower, was conducted to examine government’s attitude towards the disabled worker. Insights from two local social enterprises on disability were also engaged in building better perspective. The various source of data was triangulated then analysed with a thematic approach. Results were encouraging the Indonesian government to have a better collaboration with other impactful local organisations in promoting the disability employment. In the end, this paper also recommends the government to make a reasonable adjustment and practical guideline for companies in hiring disabled.

Keywords: disability, employment, policy, Indonesia, collaboration, guidelines

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Authors: Shivam Dwivedi, Sumit Prakash Gupta, Durga Toshniwal

Abstract:

It is a challenging task in today’s date to keep defence forces in the highest state of combat readiness with budgetary constraints. A huge amount of time and money is squandered in the unnecessary and expensive traditional maintenance activities. To overcome this limitation Defence Intelligent Mission Readiness and Maintenance Scheduling System has been proposed, which ameliorates the maintenance system by diagnosing the condition and predicting the maintenance requirements. Based on new data mining algorithms, this system intelligently optimises mission readiness for imminent operations and maintenance scheduling in repair echelons. With modified data mining algorithms such as Weighted Feature Ranking Genetic Algorithm and SVM-Random Forest Linear ensemble, it improves the reliability, availability and safety, alongside reducing maintenance cost and Equipment Out of Action (EOA) time. The results clearly conclude that the introduced algorithms have an edge over the conventional data mining algorithms. The system utilizing the intelligent condition-based maintenance approach improves the operational and maintenance decision strategy of the defence force.

Keywords: condition based maintenance, data mining, defence maintenance, ensemble, genetic algorithms, maintenance scheduling, mission capability

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Authors: Subodh Kumar, Amit Varde

Abstract:

Typical on-premises high-performance computing (HPC) environments consist of a fixed number and a fixed set of computing hardware. During the design of the HPC environment, the hardware components, including but not limited to CPU, Memory, GPU, and networking, are carefully chosen from select vendors for optimal performance. High capital cost for building the environment is a prime factor influencing the design environment. A class of software called “Job Schedulers” are critical to maximizing these resources and running multiple workloads to extract the maximum value for the high capital cost. In principle, schedulers work by preventing workloads and users from monopolizing the finite hardware resources by queuing jobs in a workload. A cloud-based HPC environment does not have the limitations of fixed (type of and quantity of) hardware resources. In theory, users and workloads could spin up any number and type of hardware resource. This paper discusses the limitations of using traditional scheduling algorithms for cloud-based HPC workloads. It proposes a new set of features, called “HPC optimizers,” for maximizing the benefits of the elasticity and scalability of the cloud with the goal of cost-performance optimization of the workload.

Keywords: high performance computing, HPC, cloud computing, optimization, schedulers

Procedia PDF Downloads 93

Authors: Jiemiao Chen, Shuoxun Xu

Abstract:

The main goal of our research is to apply the Vine copula measuring dependency between price, temperature, and precipitation indices to calculate a fair crop insurance premium. This research is focused on Worth, Iowa, United States, over the period from 2000 to 2020, where the farmers are dependent on precipitation and average temperature during the growth period of corn. Our proposed insurance considers both the natural risk and the price risk in agricultural production. We first estimate the distributions of crops using parametric methods based on Goodness of Fit tests, and then Vine Copula is applied to model dependence between yield price, crop yield, and weather indices. Once the vine structure and its parameters are determined based on AIC/BIC criteria and forecasting price and yield are obtained from the ARIMA model, we calculate this crop insurance premium using the simulation data generated from the vine copula by the Monte Carlo Simulation method. It is shown that, compared with traditional crop insurance, our proposed insurance is more fair and thus less costly for the farmers and government.

Keywords: vine copula, weather index, crop insurance premium, insurance risk management, Monte Carlo simulation

Procedia PDF Downloads 201