Search results for: space and cost
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9487

Search results for: space and cost

5647 Acceleration of Adsorption Kinetics by Coupling Alternating Current with Adsorption Process onto Several Adsorbents

Authors: A. Kesraoui, M. Seffen

Abstract:

Applications of adsorption onto activated carbon for water treatment are well known. The process has been demonstrated to be widely effective for removing dissolved organic substances from wastewaters, but this treatment has a major drawback is the high operating cost. The main goal of our research work is to improve the retention capacity of Tunisian biomass for the depollution of industrial wastewater and retention of pollutants considered toxic. The biosorption process is based on the retention of molecules and ions onto a solid surface composed of biological materials. The evaluation of the potential use of these materials is important to propose as an alternative to the adsorption process generally expensive, used to remove organic compounds. Indeed, these materials are very abundant in nature and are low cost. Certainly, the biosorption process is effective to remove the pollutants, but it presents a slow kinetics. The improvement of the biosorption rates is a challenge to make this process competitive with respect to oxidation and adsorption onto lignocellulosic fibers. In this context, the alternating current appears as a new alternative, original and a very interesting phenomenon in the acceleration of chemical reactions. Our main goal is to increase the retention acceleration of dyes (indigo carmine, methylene blue) and phenol by using a new alternative: alternating current. The adsorption experiments have been performed in a batch reactor by adding some of the adsorbents in 150 mL of pollutants solution with the desired concentration and pH. The electrical part of the mounting comprises a current source which delivers an alternating current voltage of 2 to 15 V. It is connected to a voltmeter that allows us to read the voltage. In a 150 mL capacity cell, we plunged two zinc electrodes and the distance between two Zinc electrodes has been 4 cm. Thanks to alternating current, we have succeeded to improve the performance of activated carbon by increasing the speed of the indigo carmine adsorption process and reducing the treatment time. On the other hand, we have studied the influence of the alternating current on the biosorption rate of methylene blue onto Luffa cylindrica fibers and the hybrid material (Luffa cylindrica-ZnO). The results showed that the alternating current accelerated the biosorption rate of methylene blue onto the Luffa cylindrica and the Luffa cylindrica-ZnO hybrid material and increased the adsorbed amount of methylene blue on both adsorbents. In order to improve the removal of phenol, we performed the coupling between the alternating current and the biosorption onto two adsorbents: Luffa cylindrica and the hybrid material (Luffa cylindrica-ZnO). In fact, the alternating current has succeeded to improve the performance of adsorbents by increasing the speed of the adsorption process and the adsorption capacity and reduce the processing time.

Keywords: adsorption, alternating current, dyes, modeling

Procedia PDF Downloads 159
5646 Gender: Schooling and Social Condition’s Women in Brazil

Authors: Simone Tamires Vieira

Abstract:

This paper aims to investigate the history of women's schooling in Brazil and to reflect on the condition and social space of women today. Therefore, the following question arises as a research problem: how does the history of the school in/exclusion of women in Brazil relate to the occupations occupied today? As for the objectives, we seek to collect data on the education of women and girls in Brazil, analyze some institutionalized educational legislation and policies, reflect on issues of opportunity and deprivation in order to problematize the female condition through the review of qualitative literature. The results showed that gender and symbolic violence are powerful categories to analyze this theme since the trajectories, choices, and opportunities given to women are permeated by veiled mechanisms perpetuated by a structurally patriarchal society, focused on the interests of the elite, which denies diversity to maintain its status. The aim of this research is to contribute to reflections on the potential of dialogical action, as it highlights the forces that act and permeate the trajectories of women to empower current and future generations.

Keywords: gender, school in/exclusion symbolic violence, women, symbolic violence, women

Procedia PDF Downloads 156
5645 Portrayal of Foreign Culture in Pakistani Newspapers

Authors: Ghulam Shabir, Masood Nadeem

Abstract:

The research work has been done on the Portrayal of Foreign Culture including Film, Art, and Drama in Pakistani English newspapers (Dawn and The News). For this purpose the weekly newspapers of three months (January to March) of the years 1990, 1995, 2000, 2005, and 2010 were analyzed. Content Analysis was employed for data interpretation and to draw the inferences. It was explored that to what extent the Foreign Culture has been depicted in our print media in the form of Film, Art, and Drama in comparison to Pakistani cultural context. The qualitative analysis revealed that Pakistani English newspapers gave more coverage to Foreign Culture. Pakistani film, art, and drama related issues have been less portrayed in the form of stories, columns, pictures, and news about music, fashion, ceremonies, programs, and shows. However, most of the space has been occupied by Western and Indian pictures, and news about music, fashion, ceremonies, programs and shows on the Cultural Page of these English newspapers.

Keywords: newspapers, portrayal of foreign culture, qualitative analysis, Pakistani English newspapers

Procedia PDF Downloads 508
5644 Cortex-M3 Based Virtual Platform Implementation for Software Development

Authors: Jun Young Moon, Hyeonggeon Lee, Jong Tae Kim

Abstract:

In this paper, we present Cortex-M3 based virtual platform which can virtualize wearable hardware platform and evaluate hardware performance. Cortex-M3 is very popular microcontroller in wearable devices, hardware sensors and display devices. This platform can be used to implement software layer for specific hardware architecture. By using the proposed platform the software development process can be parallelized with hardware development process. We present internal mechanism to implement the proposed virtual platform and describe how to use the proposed platform to develop software by using case study which is low cost wearable device that uses Cortex-M3.

Keywords: electronic system level design, software development, virtual platform, wearable device

Procedia PDF Downloads 373
5643 A Simple Low-Cost 2-D Optical Measurement System for Linear Guideways

Authors: Wen-Yuh Jywe, Bor-Jeng Lin, Jing-Chung Shen, Jeng-Dao Lee, Hsueh-Liang Huang, Tung-Hsien Hsieh

Abstract:

In this study, a simple 2-D measurement system based on optical design was developed to measure the motion errors of the linear guideway. Compared with the transitional methods about the linear guideway for measuring the motion errors, our proposed 2-D optical measurement system can simultaneously measure horizontal and vertical running straightness errors for the linear guideway. The performance of the 2-D optical measurement system is verified by experimental results. The standard deviation of the 2-D optical measurement system is about 0.4 μm in the measurement range of 100 mm. The maximum measuring speed of the proposed automatic measurement instrument is 1 m/sec.

Keywords: 2-D measurement, linear guideway, motion errors, running straightness

Procedia PDF Downloads 489
5642 Modeling Food Popularity Dependencies Using Social Media Data

Authors: DEVASHISH KHULBE, MANU PATHAK

Abstract:

The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-temporal popularity of various cuisines can be analyzed. Tracking the popularity of food types and retail locations across space and time can also be useful for business owners and restaurant investors. In this work, we present an approach using off-the shelf machine learning techniques to identify trends and popularity of cuisine types in an area using geo-tagged data from social media, Google images and Yelp. After adjusting for time, we use the Kernel Density Estimation to get hot spots across the location and model the dependencies among food cuisines popularity using Bayesian Networks. We consider the Manhattan borough of New York City as the location for our analyses but the approach can be used for any area with social media data and information about retail businesses.

Keywords: Web Mining, Geographic Information Systems, Business popularity, Spatial Data Analyses

Procedia PDF Downloads 115
5641 Key Aroma Compounds as Predictors of Pineapple Sensory Quality

Authors: Jenson George, Thoa Nguyen, Garth Sanewski, Craig Hardner, Heather Eunice Smyth

Abstract:

Pineapple (Ananas comosus), with its unique sweet flavour, is one of the most popular tropical, non-climacteric fruits consumed worldwide. It is also the third most important tropical fruit in world production. In Australia, 99% of the pineapple production is from the Queensland state due to the favourable subtropical climatic conditions. The flavourful fruit is known to contain around 500 volatile organic compounds (VOC) at varying concentrations and greatly contribute to the flavour quality of pineapple fruit by providing distinct aroma sensory properties that are sweet, fruity, tropical, pineapple-like, caramel-like, coconut-like, etc. The aroma of pineapple is one of the important factors attracting consumers and strengthening the marketplace. To better understand the aroma of Australian-grown pineapples, the matrix-matched Gas chromatography–mass spectrometry (GC-MS), Head Space - Solid-phase microextraction (HS-SPME), Stable-isotope dilution analysis (SIDA) method was developed and validated. The developed method represents a significant improvement over current methods with the incorporation of multiple external reference standards, multiple isotopes labeled internal standards, and a matching model system of pineapple fruit matrix. This method was employed to quantify 28 key aroma compounds in more than 200 genetically diverse pineapple varieties from a breeding program. The Australian pineapple cultivars varied in content and composition of free volatile compounds, which were predominantly comprised of esters, followed by terpenes, alcohols, aldehydes, and ketones. Using selected commercial cultivars grown in Australia, and by employing the sensorial analysis, the appearance (colour), aroma (intensity, sweet, vinegar/tang, tropical fruits, floral, coconut, green, metallic, vegetal, fresh, peppery, fermented, eggy/sulphurous) and texture (crunchiness, fibrousness, and juiciness) were obtained. Relationships between sensory descriptors and volatiles were explored by applying multivariate analysis (PCA) to the sensorial and chemical data. The key aroma compounds of pineapple exhibited a positive correlation with corresponding sensory properties. The sensory and volatile data were also used to explore genetic diversity in the breeding population. GWAS was employed to unravel the genetic control of the pineapple volatilome and its interplay with fruit sensory characteristics. This study enhances our understanding of pineapple aroma (flavour) compounds, their biosynthetic pathways and expands breeding option for pineapple cultivars. This research provides foundational knowledge to support breeding programs, post-harvest and target market studies, and efforts to optimise the flavour of commercial pineapple varieties and their parent lines to produce better tasting fruits for consumers.

Keywords: Ananas comosus, pineapple, flavour, volatile organic compounds, aroma, Gas chromatography–mass spectrometry (GC-MS), Head Space - Solid-phase microextraction (HS-SPME), Stable-isotope dilution analysis (SIDA).

Procedia PDF Downloads 55
5640 Effects of Daily Temperature Changes on Transient Heat and Moisture Transport in Unsaturated Soils

Authors: Davood Yazdani Cherati, Ali Pak, Mehrdad Jafarzadeh

Abstract:

This research contains the formulation of a two-dimensional analytical solution to transient heat, and moisture flow in a semi-infinite unsaturated soil environment under the influence of daily temperature changes. For this purpose, coupled energy conservation and mass fluid continuity equations governing hydrothermal behavior of unsaturated soil media are presented in terms of temperature and volumetric moisture content. In consideration of the soil environment as an infinite half-space and by linearization of the governing equations, Laplace–Fourier transformation is conducted to convert differential equations with partial derivatives (PDEs) to ordinary differential equations (ODEs). The obtained ODEs are solved, and the inverse transformations are calculated to determine the solution to the system of equations. Results indicate that heat variation induces moisture transport in both horizontal and vertical directions.

Keywords: analytical solution, heat conduction, hydrothermal analysis, laplace–fourier transformation, two-dimensional

Procedia PDF Downloads 214
5639 A Compilation of Nanotechnology in Thin Film Solar Cell Devices

Authors: Nurul Amziah Md Yunus, Izhal Abdul Halin, Nasri Sulaiman, Noor Faezah Ismail, Nik Hasniza Nik Aman

Abstract:

Nanotechnology has become the world attention in various applications including the solar cells devices due to the uniqueness and benefits of achieving low cost and better performances of devices. Recently, thin film solar cells such as cadmium telluride (CdTe), copper-indium-gallium-diSelenide (CIGS), copper-zinc-tin-sulphide (CZTS), and dye-sensitized solar cells (DSSC) enhanced by nanotechnology have attracted much attention. Thus, a compilation of nanotechnology devices giving the progress in the solar cells has been presented. It is much related to nanoparticles or nanocrystallines, carbon nanotubes, and nanowires or nanorods structures.

Keywords: nanotechnology, nanocrystalline, nanowires, carbon nanotubes, nanorods, thin film solar cells

Procedia PDF Downloads 626
5638 Application of Nanoparticles on Surface of Commercial Carbon-Based Adsorbent for Removal of Contaminants from Water

Authors: Ahmad Kayvani Fard, Gordon Mckay, Muataz Hussien

Abstract:

Adsorption/sorption is believed to be one of the optimal processes for the removal of heavy metals from water due to its low operational and capital cost as well as its high removal efficiency. Different materials have been reported in literature as adsorbent for heavy metal removal in waste water such as natural sorbents, organic polymers (synthetic) and mineral materials (inorganic). The selection of adsorbents and development of new functional materials that can achieve good removal of heavy metals from water is an important practice and depends on many factors, such as the availability of the material, cost of material, and material safety and etc. In this study we reported the synthesis of doped Activated carbon and Carbon nanotube (CNT) with different loading of metal oxide nanoparticles such as Fe2O3, Fe3O4, Al2O3, TiO2, SiO2 and Ag nanoparticles and their application in removal of heavy metals, hydrocarbon, and organics from waste water. Commercial AC and CNT with different loadings of mentioned nanoparticle were prepared and effect of pH, adsorbent dosage, sorption kinetic, and concentration effects are studied and optimum condition for removal of heavy metals from water is reported. The prepared composite sorbent is characterized using field emission scanning electron microscopy (FE-SEM), high transmission electron microscopy (HR-TEM), thermogravimetric analysis (TGA), X-ray diffractometer (XRD), the Brunauer, Emmett and Teller (BET) nitrogen adsorption technique, and Zeta potential. The composite materials showed higher removal efficiency and superior adsorption capacity compared to commercially available carbon based adsorbent. The specific surface area of AC increased by 50% reaching up to 2000 m2/g while the CNT specific surface area of CNT increased by more than 8 times reaching value of 890 m2/g. The increased surface area is one of the key parameters along with surface charge of the material determining the removal efficiency and removal efficiency. Moreover, the surface charge density of the impregnated CNT and AC have enhanced significantly where can benefit the adsorption process. The nanoparticles also enhance the catalytic activity of material and reduce the agglomeration and aggregation of material which provides more active site for adsorbing the contaminant from water. Some of the results for treating wastewater includes 100% removal of BTEX, arsenic, strontium, barium, phenolic compounds, and oil from water. The results obtained are promising for the use of AC and CNT loaded with metal oxide nanoparticle in treatment and pretreatment of waste water and produced water before desalination process. Adsorption can be very efficient with low energy consumption and economic feasibility.

Keywords: carbon nanotube, activated carbon, adsorption, heavy metal, water treatment

Procedia PDF Downloads 233
5637 Hierarchical Piecewise Linear Representation of Time Series Data

Authors: Vineetha Bettaiah, Heggere S. Ranganath

Abstract:

This paper presents a Hierarchical Piecewise Linear Approximation (HPLA) for the representation of time series data in which the time series is treated as a curve in the time-amplitude image space. The curve is partitioned into segments by choosing perceptually important points as break points. Each segment between adjacent break points is recursively partitioned into two segments at the best point or midpoint until the error between the approximating line and the original curve becomes less than a pre-specified threshold. The HPLA representation achieves dimensionality reduction while preserving prominent local features and general shape of time series. The representation permits course-fine processing at different levels of details, allows flexible definition of similarity based on mathematical measures or general time series shape, and supports time series data mining operations including query by content, clustering and classification based on whole or subsequence similarity.

Keywords: data mining, dimensionality reduction, piecewise linear representation, time series representation

Procedia PDF Downloads 273
5636 A Review of Urban Placemaking Assessment Frameworks

Authors: Amal Abdou, Yasser ElSayed, Nora Selim

Abstract:

Public urban spaces are an essential component in any urban settlement. They are quite important in enhancing the quality of urban life while offering social, health, environmental and economic benefits to a city and its residents. Place-making assessment of public urban spaces has been one of the major guiding principles for urban planning and policymaking, of which the definition and evaluation have become the crucial research topic. It is increasingly being essential to mitigate the undesirable impacts of urbanization in cities while improving public urban space’s resilience to environmental, social, and economic changes. Globally, several place-making assessment tools (PATs) have been developed to make such informed decision-making. They act as a catalyst to increase market demand for sustainable products and services by providing a mechanism for recognizing excellence. Assessing how placemaking can positively contribute to urban environments is critical to inform both the continued development of the place and the way placemaking is done as a practice. Therefore, this study aims to review different themes for assessing urban placemaking in public urban spaces.

Keywords: urban placemaking, public urban spaces, placemaking assessment, literature review

Procedia PDF Downloads 97
5635 A Machine Learning-Based Approach to Capture Extreme Rainfall Events

Authors: Willy Mbenza, Sho Kenjiro

Abstract:

Increasing efforts are directed towards a better understanding and foreknowledge of extreme precipitation likelihood, given the adverse effects associated with their occurrence. This knowledge plays a crucial role in long-term planning and the formulation of effective emergency response. However, predicting extreme events reliably presents a challenge to conventional empirical/statistics due to the involvement of numerous variables spanning different time and space scales. In the recent time, Machine Learning has emerged as a promising tool for predicting the dynamics of extreme precipitation. ML techniques enables the consideration of both local and regional physical variables that have a strong influence on the likelihood of extreme precipitation. These variables encompasses factors such as air temperature, soil moisture, specific humidity, aerosol concentration, among others. In this study, we develop an ML model that incorporates both local and regional variables while establishing a robust relationship between physical variables and precipitation during the downscaling process. Furthermore, the model provides valuable information on the frequency and duration of a given intensity of precipitation.

Keywords: machine learning (ML), predictions, rainfall events, regional variables

Procedia PDF Downloads 85
5634 Corporate Profitability through Effective Supply Chain Performance

Authors: Tareq N. Issa

Abstract:

The main pressuring challenges of global competition and high returns have forced businesses to shift their strategic competitive advantage from physical distribution management to integrated logistics management, finally moving into supply chain management. Conventionally, corporate profitability is a function of cost, capital employed, revenue and customer service. This article gives an insight into the effect of supply chain management on each of the above variables. It investigates the impact of the changing levels/ effects of these variables on corporate profitability and the means of measuring supply chain financial effectiveness. Information technology tools form the basis for supply chain optimal performance through alignment of supply chain systems in this ever increasing complexity in business decisions.

Keywords: corporate profitability, sypply chain systems, business decisions, competitive advanage

Procedia PDF Downloads 331
5633 Lubricant-Impregnated Nanoporous Surfaces for Biofilm Prevention

Authors: Yuen Yee Li Sip, Lei Zhai

Abstract:

Biofilms are formed by the attachment of microorganisms onto substrates via self-synthesized extracellular polymeric substances. They have been observed in the International Space Stations (ISS), in which biofilms can jeopardize the performance of key equipment and can pose health threats to the astronauts. This project aims at building conformal nanoporous surfaces that are infused with lubricant and decorated with antimicrobial nanoparticles while simultaneously evaluating their efficacy in preventing biofilm formation. Lubricant-impregnated surfaces (LIS) are fabricated by using a layer-by-layer assembly of silica nanoparticles to generate conformal nanoporous coatings on substrates and fill the films with fluorinated fluids. LIS has demonstrated excellent repellency to a broad range of liquids, preventing microbe adhesion (anti-biofouling). Silver or copper nanoparticles were deposited on the coatings prior to lubricant infusion in order to provide antimicrobial characteristics to the coating. Surface morphology and biofilm growth were characterized to understand how the coating morphology affects the LIS stability and anti-biofouling behaviors (stationary and in a flow).

Keywords: biofilm, coatings, nanoporous, antifouling

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5632 Demographics Are Not Enough! Targeting and Segmentation of Anti-Obesity Campaigns in Mexico

Authors: Dagmara Wrzecionkowska

Abstract:

Mass media campaigns against obesity are often designed to impact large audiences. This usually means that their audience is defined based on general demographic characteristics like age, gender, occupation etc., not taking into account psychographics like behavior, motivations, wants, etc. Using psychographics, as the base for the audience segmentation, is a common practice in case of successful campaigns, as it allows developing more relevant messages. It also serves a purpose of identifying key segments, those that generate the best return on investment. For a health campaign, that would be segments that have the best chance of being converted into healthy lifestyle at the lowest cost. This paper presents the limitations of the demographic targeting, based on the findings from the reception study of IMSS anti-obesity TV commercials and proposes mothers as the first level of segmentation, in the process of identifying the key segment for these campaigns.

Keywords: anti-obesity campaigns, mothers, segmentation, targeting

Procedia PDF Downloads 400
5631 Towards Integrating Statistical Color Features for Human Skin Detection

Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani

Abstract:

Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.

Keywords: color space, neural network, random forest, skin detection, statistical feature

Procedia PDF Downloads 460
5630 Enhancement in the Absorption Efficiency of GaAs/InAs Nanowire Solar Cells through a Decrease in Light Reflection

Authors: Latef M. Ali, Farah A. Abed, Zheen L. Mohammed

Abstract:

In this paper, the effect of the Barium fluoride (BaF2) layer on the absorption efficiency of GaAs/InAs nanowire solar cells was investigated using the finite difference time domain (FDTD) method. By inserting the BaF2 as antireflection with the dominant size of 10 nm to fill the space between the shells of wires on the Si (111) substrate. The absorption is significantly improved due to the strong reabsorption of light reflected at the shells and compared with the reference cells. The present simulation leads to a higher absorption efficiency (Qabs) and reaches a value of 97%, and the external quantum efficiencies (EQEs) above 92% are observed. The current density (Jsc) increases by 0.22 mA/cm2 and the open-circuit voltage (Voc) is enhanced by 0.11 mV. it explore the design and optimization of high-efficiency solar cells on low-reflective absorption efficiency of GaAs/InAs using simulation software tool. The changes in the core and shell diameters profoundly affects the generation and recombination process, thus affecting the conversion efficiency of solar cells.

Keywords: nanowire solar cells, absorption efficiency, photovoltaic, band structures, FDTD simulation

Procedia PDF Downloads 47
5629 A Qualitative Investigation into Street Art in an Indonesian City

Authors: Michelle Mansfield

Abstract:

Introduction: This paper uses the work of Deleuze and Guattari to consider the street art practice of youth in the Indonesian city of Yogyakarta, a hub of arts and culture in Central Java. Around the world young people have taken to city streets to populate the new informal exhibition spaces outside the galleries of official art institutions. However, rarely is the focus outside the urban metropolis of the ‘Global North.' This paper looks at these practices in a ‘Global South’ Asian context. Space and place are concepts central to understanding youth cultural expression as it emerges on the streets. Deleuze and Guattari’s notion of assemblage enriches understanding of this complex spatial and creative relationship. Yogyakarta street art combines global patterns and motifs with local meanings, symbolism, and language to express local youth voices that convey a unique sense of place on the world stage. Street art has developed as a global urban youth art movement and is theorised as a way in which marginalised young people reclaim urban space for themselves. Methodologies: This study utilised a variety of qualitative methodologies to collect and analyse data. This project took a multi-method approach to data collection, incorporating the qualitative social research methods of ethnography, nongkrong (deep hanging out), participatory action research, online research, in-depth interviews and focus group discussions. Both interviews and focus groups employed photo-elicitation methodology to stimulate rich data gathering. To analyse collected data, rhizoanalytic approaches incorporating discourse analysis and visual analysis were utilised. Street art practice is a fluid and shifting phenomenon, adding to the complexity of inquiry sites. A qualitative approach to data collection and analysis was the most appropriate way to map the components of the street art assemblage and to draw out complexities of this youth cultural practice in Yogyakarta. Major Findings: The rhizoanalytic approach devised for this study proved a useful way of examining in the street art assemblage. It illustrated the ways in which the street art assemblage is constructed. Especially the interaction of inspiration, materials, creative techniques, audiences, and spaces operate in the creations of artworks. The study also exposed the generational tensions between the senior arts practitioners, the established art world, and the young artists. Conclusion: In summary, within the spatial processes of the city, street art is inextricably linked with its audience, its striving artistic community and everyday life in the smooth rather than the striated worlds of the state and the official art world. In this way, the anarchic rhizomatic art practice of nomadic urban street crews can be described not only as ‘becoming-artist’ but as constituting ‘nomos’, a way of arranging elements which are not dependent on a structured, hierarchical organisation practice. The site, streets, crews, neighbourhood and the passers by can all be examined with the concept of assemblage. The assemblage effectively brings into focus the complexity, dynamism, and flows of desire that is a feature of street art practice by young people in Yogyakarta.

Keywords: assemblage, Indonesia, street art, youth

Procedia PDF Downloads 181
5628 Recognizing Human Actions by Multi-Layer Growing Grid Architecture

Authors: Z. Gharaee

Abstract:

Recognizing actions performed by others is important in our daily lives since it is necessary for communicating with others in a proper way. We perceive an action by observing the kinematics of motions involved in the performance. We use our experience and concepts to make a correct recognition of the actions. Although building the action concepts is a life-long process, which is repeated throughout life, we are very efficient in applying our learned concepts in analyzing motions and recognizing actions. Experiments on the subjects observing the actions performed by an actor show that an action is recognized after only about two hundred milliseconds of observation. In this study, hierarchical action recognition architecture is proposed by using growing grid layers. The first-layer growing grid receives the pre-processed data of consecutive 3D postures of joint positions and applies some heuristics during the growth phase to allocate areas of the map by inserting new neurons. As a result of training the first-layer growing grid, action pattern vectors are generated by connecting the elicited activations of the learned map. The ordered vector representation layer receives action pattern vectors to create time-invariant vectors of key elicited activations. Time-invariant vectors are sent to second-layer growing grid for categorization. This grid creates the clusters representing the actions. Finally, one-layer neural network developed by a delta rule labels the action categories in the last layer. System performance has been evaluated in an experiment with the publicly available MSR-Action3D dataset. There are actions performed by using different parts of human body: Hand Clap, Two Hands Wave, Side Boxing, Bend, Forward Kick, Side Kick, Jogging, Tennis Serve, Golf Swing, Pick Up and Throw. The growing grid architecture was trained by applying several random selections of generalization test data fed to the system during on average 100 epochs for each training of the first-layer growing grid and around 75 epochs for each training of the second-layer growing grid. The average generalization test accuracy is 92.6%. A comparison analysis between the performance of growing grid architecture and self-organizing map (SOM) architecture in terms of accuracy and learning speed show that the growing grid architecture is superior to the SOM architecture in action recognition task. The SOM architecture completes learning the same dataset of actions in around 150 epochs for each training of the first-layer SOM while it takes 1200 epochs for each training of the second-layer SOM and it achieves the average recognition accuracy of 90% for generalization test data. In summary, using the growing grid network preserves the fundamental features of SOMs, such as topographic organization of neurons, lateral interactions, the abilities of unsupervised learning and representing high dimensional input space in the lower dimensional maps. The architecture also benefits from an automatic size setting mechanism resulting in higher flexibility and robustness. Moreover, by utilizing growing grids the system automatically obtains a prior knowledge of input space during the growth phase and applies this information to expand the map by inserting new neurons wherever there is high representational demand.

Keywords: action recognition, growing grid, hierarchical architecture, neural networks, system performance

Procedia PDF Downloads 157
5627 Using Artificial Vision Techniques for Dust Detection on Photovoltaic Panels

Authors: Gustavo Funes, Eduardo Peters, Jose Delpiano

Abstract:

It is widely known that photovoltaic technology has been massively distributed over the last decade despite its low-efficiency ratio. Dust deposition reduces this efficiency even more, lowering the energy production and module lifespan. In this work, we developed an artificial vision algorithm based on CIELAB color space to identify dust over panels in an autonomous way. We performed several experiments photographing three different types of panels, 30W, 340W and 410W. Those panels were soiled artificially with uniform and non-uniform distributed dust. The algorithm proposed uses statistical tools to provide a simulation with a 100% soiled panel and then performs a comparison to get the percentage of dirt in the experimental data set. The simulation uses a seed that is obtained by taking a dust sample from the maximum amount of dust from the dataset. The final result is the dirt percentage and the possible distribution of dust over the panel. Dust deposition is a key factor for plant owners to determine cleaning cycles or identify nonuniform depositions that could lead to module failure and hot spots.

Keywords: dust detection, photovoltaic, artificial vision, soiling

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5626 Investigating the Effect of Artificial Intelligence on the Improvement of Green Supply Chain in Industry

Authors: Sepinoud Hamedi

Abstract:

Over the past few decades, companies have appeared developing concerns in connection to the natural affect of their fabricating exercises. Green supply chain administration has been considered by the producers as a attainable choice to decrease the natural affect of operations whereas at the same time moving forward their operational execution. Contemporaneously the coming of digitalization and globalization within the supply chain space has driven to a developing acknowledgment of the importance of data preparing methodologies, such as enormous information analytics and fake insights innovations, in improving and optimizing supply chain execution. Also, supply chain collaboration in part intervenes the relationship between manufactured innovation and supply chain execution Ponders appear that the use of BDA-AI advances includes a significant impact on natural handle integration and green supply chain collaboration conjointly underlines that both natural handle integration and green supply chain collaboration have a critical affect on natural execution. Correspondingly savvy supply chain contributes to green execution through overseeing green connections and setting up green operations.

Keywords: green supply chain, artificial intelligence, manufacturers, technology, environmental

Procedia PDF Downloads 71
5625 Spatial Analysis of Park and Ride Users’ Dynamic Accessibility to Train Station: A Case Study in Perth

Authors: Ting (Grace) Lin, Jianhong (Cecilia) Xia, Todd Robinson

Abstract:

Accessibility analysis, examining people’s ability to access facilities and destinations, is a fundamental assessment for transport planning, policy making, and social exclusion research. Dynamic accessibility which measures accessibility in real-time traffic environment has been an advanced accessibility indicator in transport research. It is also a useful indicator to help travelers to understand travel time daily variability, assists traffic engineers to monitor traffic congestions, and finally develop effective strategies in order to mitigate traffic congestions. This research involved real-time traffic information by collecting travel time data with 15-minute interval via the TomTom® API. A framework for measuring dynamic accessibility was then developed based on the gravity theory and accessibility dichotomy theory through space and time interpolation. Finally, the dynamic accessibility can be derived at any given time and location under dynamic accessibility spatial analysis framework.

Keywords: dynamic accessibility, hot spot, transport research, TomTom® API

Procedia PDF Downloads 387
5624 Genetic Analysis of Iron, Phosphorus, Potassium and Zinc Concentration in Peanut

Authors: Ajay B. C., Meena H. N., Dagla M. C., Narendra Kumar, Makwana A. D., Bera S. K., Kalariya K. A., Singh A. L.

Abstract:

The high-energy value, protein content and minerals makes peanut a rich source of nutrition at comparatively low cost. Basic information on genetics and inheritance of these mineral elements is very scarce. Hence, in the present study inheritance (using additive-dominance model) and association of mineral elements was studied in two peanut crosses. Dominance variance (H) played an important role in the inheritance of P, K, Fe and Zn in peanut pods. Average degree of dominance for most of the traits was greater than unity indicating over dominance for these traits. Significant associations were also observed among mineral elements both in F2 and F3 generations but pod yield had no associations with mineral elements (with few exceptions). Di-allele/bi-parental mating could be followed to identify high yielding and mineral dense segregates.

Keywords: correlation, dominance variance, mineral elements, peanut

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5623 Mutual Authentication for Sensor-to-Sensor Communications in IoT Infrastructure

Authors: Shadi Janbabaei, Hossein Gharaee Garakani, Naser Mohammadzadeh

Abstract:

Internet of things is a new concept that its emergence has caused ubiquity of sensors in human life, so that at any time, all data are collected, processed and transmitted by these sensors. In order to establish a secure connection, the first challenge is authentication between sensors. However, this challenge also requires some features so that the authentication is done properly. Anonymity, untraceability, and being lightweight are among the issues that need to be considered. In this paper, we have evaluated the authentication protocols and have analyzed the security vulnerabilities found in them. Then an improved light weight authentication protocol for sensor-to-sensor communications is presented which uses the hash function and logical operators. The analysis of protocol shows that security requirements have been met and the protocol is resistant against various attacks. In the end, by decreasing the number of computational cost functions, it is argued that the protocol is lighter than before.

Keywords: anonymity, authentication, Internet of Things, lightweight, un-traceability

Procedia PDF Downloads 289
5622 Machine Learning Driven Analysis of Kepler Objects of Interest to Identify Exoplanets

Authors: Akshat Kumar, Vidushi

Abstract:

This paper identifies 27 KOIs, 26 of which are currently classified as candidates and one as false positives that have a high probability of being confirmed. For this purpose, 11 machine learning algorithms were implemented on the cumulative kepler dataset sourced from the NASA exoplanet archive; it was observed that the best-performing model was HistGradientBoosting and XGBoost with a test accuracy of 93.5%, and the lowest-performing model was Gaussian NB with a test accuracy of 54%, to test model performance F1, cross-validation score and RUC curve was calculated. Based on the learned models, the significant characteristics for confirm exoplanets were identified, putting emphasis on the object’s transit and stellar properties; these characteristics were namely koi_count, koi_prad, koi_period, koi_dor, koi_ror, and koi_smass, which were later considered to filter out the potential KOIs. The paper also calculates the Earth similarity index based on the planetary radius and equilibrium temperature for each KOI identified to aid in their classification.

Keywords: Kepler objects of interest, exoplanets, space exploration, machine learning, earth similarity index, transit photometry

Procedia PDF Downloads 73
5621 Feature Extraction Based on Contourlet Transform and Log Gabor Filter for Detection of Ulcers in Wireless Capsule Endoscopy

Authors: Nimisha Elsa Koshy, Varun P. Gopi, V. I. Thajudin Ahamed

Abstract:

The entire visualization of GastroIntestinal (GI) tract is not possible with conventional endoscopic exams. Wireless Capsule Endoscopy (WCE) is a low risk, painless, noninvasive procedure for diagnosing diseases such as bleeding, polyps, ulcers, and Crohns disease within the human digestive tract, especially the small intestine that was unreachable using the traditional endoscopic methods. However, analysis of massive images of WCE detection is tedious and time consuming to physicians. Hence, researchers have developed software methods to detect these diseases automatically. Thus, the effectiveness of WCE can be improved. In this paper, a novel textural feature extraction method is proposed based on Contourlet transform and Log Gabor filter to distinguish ulcer regions from normal regions. The results show that the proposed method performs well with a high accuracy rate of 94.16% using Support Vector Machine (SVM) classifier in HSV colour space.

Keywords: contourlet transform, log gabor filter, ulcer, wireless capsule endoscopy

Procedia PDF Downloads 540
5620 Night Patrolling Robot for Suspicious Activity Detection

Authors: Amruta Amune, Rohit Agrawal, Yashashree Shastri, Syeda Zarah Aiman, Rutuja Rathi, Vaishnav Suryawanshi, Sameer Sumbhe

Abstract:

Every human being needs a sense of security. The requirement for security has risen in proportion with the population growth. However, because of a scarcity of resources, effective protection is not possible. It costs a lot of money to get appropriate security that not many can handle or afford. The goal of the study was to find a solution to the issue by developing a system capable of providing strong protection at a very low cost when long-term benefits are taken into account. The objective was to design and develop a robot that could travel around and survey the region and inform the command center if anything unusual was found. The system will be controlled manually on the server to find out its workplace's paths. The system is outfitted with a camera so that it can be used to capture built-in live video of the attacker and display it on the server.

Keywords: night patrolling, node MCU, server, security

Procedia PDF Downloads 157
5619 Colada Sweet Like Mercy: Gender Stereotyping in Twitter Conversations by Big Brother Naija 2019 Viewers

Authors: Mary-Magdalene N. Chumbow

Abstract:

This study explores how a reality TV show which aired in Nigeria in 2019 (Big Brother Naija - BBN), played a role in enhancing gender-biased conversations among its viewers and social media followers. Thematic analysis is employed here to study Twitter conversations among BBN 2019 followers, which ensued after the show had stopped airing. The study reveals that the show influenced the way viewers and fans engaged with each other, as well as with the show’s participants, on Twitter, and argues that, despite having aired for a short period of time, BBN 2019 was able to draw people together and provide a community where viewers could engage with each other online. Though the show aired on TV, the viewers found a digital space where they could air their views, react to what was happening on the show, as well as simply catch up on action that they probably missed. Within these digital communities, viewers expressed their attractions, disgust and identities, most of these having a form of reference to sexuality and gender identities and roles, as were also portrayed by the show’s producers both on TV and on social media.

Keywords: commodification of bodies, gender stereotypes, Big Brother Naija, social media

Procedia PDF Downloads 130
5618 Intelligent Process Data Mining for Monitoring for Fault-Free Operation of Industrial Processes

Authors: Hyun-Woo Cho

Abstract:

The real-time fault monitoring and diagnosis of large scale production processes is helpful and necessary in order to operate industrial process safely and efficiently producing good final product quality. Unusual and abnormal events of the process may have a serious impact on the process such as malfunctions or breakdowns. This work try to utilize process measurement data obtained in an on-line basis for the safe and some fault-free operation of industrial processes. To this end, this work evaluated the proposed intelligent process data monitoring framework based on a simulation process. The monitoring scheme extracts the fault pattern in the reduced space for the reliable data representation. Moreover, this work shows the results of using linear and nonlinear techniques for the monitoring purpose. It has shown that the nonlinear technique produced more reliable monitoring results and outperforms linear methods. The adoption of the qualitative monitoring model helps to reduce the sensitivity of the fault pattern to noise.

Keywords: process data, data mining, process operation, real-time monitoring

Procedia PDF Downloads 638