Search results for: image and telemetric data

Authors: Sudipto Shanker Dasgupta

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One of the largest mining companies wanted to look at health analytics for their driverless trucks. These trucks were the key to their supply chain logistics. The automated trucks had multi-level sub-assemblies which would send out sensor information. The use case that was worked on was to capture the sensor signal from the truck subcomponents and analyze the health of the trucks from repair and replacement purview. Open source software was used to stream the data into a clustered Hadoop setup in Amazon Web Services cloud and Apache Spark SQL was used to analyze the data. All of this was achieved through a 10 node amazon 32 core, 64 GB RAM setup real-time analytics was achieved on ‘300 million records’. To check the scalability of the system, the cluster was increased to 100 node setup. This talk will highlight how Open Source software was used to achieve the above use case and the insights on the high data throughput on a cloud set up.

Keywords: streaming analytics, data science, big data, Hadoop, high throughput, sensor data

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Authors: Belgherbi Aicha, Bessaid Abdelhafid

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In the recent years a great deal of research work has been devoted to the development of semi-automatic and automatic techniques for the analysis of abdominal CT images. The first and fundamental step in all these studies is the semi-automatic liver and spleen segmentation that is still an open problem. In this paper, a semi-automatic liver and spleen segmentation method by the mathematical morphology based on watershed algorithm has been proposed. Our algorithm is currency in two parts. In the first, we seek to determine the region of interest by applying the morphological to extract the liver and spleen. The second step consists to improve the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce the over-segmentation problem by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. The aim of this work is to develop a method for semi-automatic segmentation liver and spleen based on watershed algorithm, improve the accuracy and the robustness of the liver and spleen segmentation and evaluate a new semi-automatic approach with the manual for liver segmentation. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work. The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts. Liver segmentation has achieved the sensitivity and specificity; sens Liver=96% and specif Liver=99% respectively. Spleen segmentation achieves similar, promising results sens Spleen=95% and specif Spleen=99%.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

Procedia PDF Downloads 327

Authors: Domenica L. DelPrete

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Viewed as a type of rapport-talk, troubles telling is a common conversational practice among female friends who wish to establish connection, show empathy, or share a disconcerting experience. This study shows how troubles talk between a mother and her adolescent daughter has a different interactional outcome. Specifically, it reveals how discursive interaction with an adolescent daughter becomes increasingly volatile when the mother steps out of the role of nurturer and into the role of troubles teller. Naturally occurring interactions between a mother and her 15-year-old daughter were videotaped in their family home over a two-week period. The data were primarily analyzed from an interactional sociolinguistic perspective, using conversation analytic techniques for transcriptions and discursive analysis. The following questions guided this research: (1) How are troubles telling discursively accomplished in the everyday talk of a mother and her adolescent daughter? and (2) What topic prompts the mother to engage in troubles talk? The data show that the mother engages her daughter in troubles to talk on issues related to body image and physical appearance and does so by (1) repeated questioning, (2) not accepting the daughter’s response as adequate, and (3) proffering self-deprecation. Findings reveal that engaging an adolescent daughter in a conversational practice reserved for female friendship groups creates a negative connection and relational disharmony. Since 'telling one’s troubles' assumes an egalitarian relationship between individuals, mother’s trouble telling creates a peer-like interaction that the adolescent daughter repeatedly resists. This study also proposes a discursive consciousness raising, which hopes to enhance communication between mothers and daughters by revealing the signals that show an adolescent daughter’s unwillingness to participate in troubles talk. Being in tune to these cues may prompt mothers to hesitate before pursuing a topic that will not garner the positive interactional outcome they seek.

Keywords: discursive interaction, maternal roles, mother-daughter interaction, troubles telling

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Authors: Elizabeta Krstić Vukelja

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Digitization of personal data is a consequence of the development of information and communication technologies that create a new work environment with many advantages and challenges, but also potential threats to privacy and personal data protection. Regulation (EU) 2016/679 of the European Parliament and of the Council is becoming a law and obligation that should address the issues of personal data protection and information security. The existence of the Regulation leads to the conclusion that national legislation in the field of virtual environment, protection of the rights of EU citizens and processing of their personal data is insufficiently effective. In the health system, special emphasis is placed on the processing of special categories of personal data, such as health data. The healthcare industry is recognized as a particularly sensitive area in which a large amount of medical data is processed, the digitization of which enables quick access and quick identification of the health insured. The protection of the individual requires quality IT solutions that guarantee the technical protection of personal categories. However, the real problems are the technical and human nature and the spatial limitations of the application of the Regulation. Some conclusions will be drawn by analyzing the implementation of the basic principles of the Regulation on the example of the Croatian health care system and comparing it with similar activities in other EU member states.

Keywords: regulation, healthcare system, personal dana protection, quality data assurance

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Authors: Nabeel Safdar, Qian Aimin

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Corporate philanthropy is important, as the donations have been considered as a source to improve the image of business entity in modern era of high competition. We used data on annual basis from 2000 to 2014 for 1,248 firms listed at Shanghai and Shenzhen stock exchanges. Results for giving firms reveal that there is curve linear relation of profitability and CP, as profitable firms utilize cash in an efficient way and have fewer amounts of slack resource and tradeoff among stakeholder and agency cost made it more justifiable. We found that more profitability does not mean that the cash flows are available, actually good performing firms or profitable firm also good at cash management. Cash is utilized in an effective way by profitable firms, and have fewer extents of slack resources which generate curvilinear relationship of profitability with Corporate Philanthropy. We found that the trend of Corporate Philanthropy also got affected due to natural disasters. Analysis made by innovation, slack resources and directors salary revealed the positive significant relationship. It is not compulsory that firm should be only profitable for engaging in philanthropy rather they should have abundant slack resources to donate.

Keywords: corporate philanthropy, free cash flows, natural disasters, profitability

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Authors: Nagi Mekhiel

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Many applications use vector operations by applying single instruction to multiple data that map to different locations in conventional memory. Transferring data from memory is limited by access latency and bandwidth affecting the performance gain of vector processing. We present a memory system that makes all of its content available to processors in time so that processors need not to access the memory, we force each location to be available to all processors at a specific time. The data move in different orbits to become available to other processors in higher orbits at different time. We use this memory to apply parallel vector operations to data streams at first orbit level. Data processed in the first level move to upper orbit one data element at a time, allowing a processor in that orbit to apply another vector operation to deal with serial code limitations inherited in all parallel applications and interleaved it with lower level vector operations.

Keywords: Memory Organization, Parallel Processors, Serial Code, Vector Processing

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Authors: David Percy

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Landslides are a geologic phenomenon that affects a large number of inhabited places and are constantly being monitored and studied for the prediction of future occurrences. Reconstructability analysis (RA) is a methodology for extracting informative models from large volumes of data that work exclusively with discrete data. While RA has been used in medical applications and social science extensively, we are introducing it to the spatial sciences through applications like landslide prediction. Since RA works exclusively with discrete data, such as soil classification or bedrock type, working with continuous data, such as porosity, requires that these data are binned for inclusion in the model. RA constructs models of the data which pick out the most informative elements, independent variables (IVs), from each layer that predict the dependent variable (DV), landslide occurrence. Each layer included in the model retains its classification data as a primary encoding of the data. Unlike other machine learning algorithms that force the data into one-hot encoding type of schemes, RA works directly with the data as it is encoded, with the exception of continuous data, which must be binned. The usual physical and derived layers are included in the model, and testing our results against other published methodologies, such as neural networks, yields accuracy that is similar but with the advantage of a completely transparent model. The results of an RA session with a data set are a report on every combination of variables and their probability of landslide events occurring. In this way, every combination of informative state combinations can be examined.

Keywords: reconstructability analysis, machine learning, landslides, raster analysis

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Authors: Monica Dantas

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At what socio-economic costs can the food industry offer products at low prices? This research seeks to understand and to explore how we attribute competence and meaning, what enables the outcomes of agriculture and what institutions provides validation regarding food production. This study objective is to explain and interpret conditions of the present state of agriculture in Brazil centring on two distinct segments, agribusiness and family farming, as the Brazilian, rapidly changing political environment unfolds. The approach is grounded in multidisciplinary literature drawing from the politics of development, the sociology of food, the sustainability framework and the conceptual differences between agribusiness and family farming regarding the innate purpose of the two segments. In addition, a quantitative portion of the research includes secondary data analysis from statistical measurements, economic indicators, federal budget information, and census data to compare the two segments, conveying a general snapshot of the conditions investigated. The results raised questions about the perceived image of the success of agribusiness, against some contradicting economic checks and balances. Analyzing how public funds are invested in agriculture shed light on what can enable or undermine the development of food systems in Brazil. It also revealed how politics, ideology, and corporations might influence the Brazilian Federal. In the 2000-2018 observed timeline of annual federal spending on agriculture in Brazil, there is variation in the amount invested in family farming that seems to 'coincide' with the ideological direction of the federal government in power. It was also observed that significant changes in the institutional framework and financial support either promoted or purposely undermined family farming importance using public institutions to validate support for agribusiness.

Keywords: food politics, sustainability, family farming, food system, public budget

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Authors: Tammy Wee, Detlev Remy, Arif Perdana

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In the recent years, data analytics has become the buzzword in the hospitality industry. The hospitality industry is another example of a data-rich industry that has yet fully benefited from the insights of data analytics. Effective use of data analytics can change how hotels operate, market and position themselves competitively in the hospitality industry. However, at the moment, the data obtained by individual hotels remain under-utilized. This research is a preliminary research on data analytics in the hospitality industry, using an in-depth face-to-face interview on one hotel as a start to a multi-level research. The main case study of this research, hotel A, is a chain brand of international hotel that has been systematically gathering and collecting data on its own customer for the past five years. The data collection points begin from the moment a guest book a room until the guest leave the hotel premises, which includes room reservation, spa booking, and catering. Although hotel A has been gathering data intelligence on its customer for some time, they have yet utilized the data to its fullest potential, and they are aware of their limitation as well as the potential of data analytics. Currently, the utilization of data analytics in hotel A is limited in the area of customer service improvement, namely to enhance the personalization of service for each individual customer. Hotel A is able to utilize the data to improve and enhance their service which in turn, encourage repeated customers. According to hotel A, 50% of their guests returned to their hotel, and 70% extended nights because of the personalized service. Apart from using the data analytics for enhancing customer service, hotel A also uses the data in marketing. Hotel A uses the data analytics to predict or forecast the change in consumer behavior and demand, by tracking their guest’s booking preference, payment preference and demand shift between properties. However, hotel A admitted that the data they have been collecting was not fully utilized due to two challenges. The first challenge of using data analytics in hotel A is the data is not clean. At the moment, the data collection of one guest profile is meaningful only for one department in the hotel but meaningless for another department. Cleaning up the data and getting standards correctly for usage by different departments are some of the main concerns of hotel A. The second challenge of using data analytics in hotel A is the non-integral internal system. At the moment, the internal system used by hotel A do not integrate with each other well, limiting the ability to collect data systematically. Hotel A is considering another system to replace the current one for more comprehensive data collection. Hotel proprietors recognized the potential of data analytics as reported in this research, however, the current challenges of implementing a system to collect data come with a cost. This research has identified the current utilization of data analytics and the challenges faced when it comes to implementing data analytics.

Keywords: data analytics, hospitality industry, customer relationship management, hotel marketing

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Authors: Yan Zou

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Approach to the theory of Musical Narrative, as well as the three criteria of the 'explicit narrative', 'potential narrative' and 'image narrative' which are used to analyze the music, the author put Beethoven’s Piano Sonata in E-flat major, Op.31/3, into the context of the music genre and Western music history, and interpreted the programmatic contents that were embodied and hid in the special music genres.

Keywords: analysis, genre, narrative, rhetoric

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Authors: Djelloul Benatiallah, Ali Benatiallah, Abdelkader Harouz

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Geographic Information Systems (GIS) include various methods and computer techniques to model, capture digitally, store, manage, view and analyze. Geographic information systems have the characteristic to appeal to many scientific and technical field, and many methods. In this article we will present a complete and operational geographic information system, following the theoretical principles of data management and adapting to spatial data, especially data concerning the monitoring of drinking water supply wells (DWS) Adrar region. The expected results of this system are firstly an offer consulting standard features, updating and editing beneficiaries and geographical data, on the other hand, provides specific functionality contractors entered data, calculations parameterized and statistics.

Keywords: GIS, DWS, drilling, Adrar

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Authors: S. Habte, K. Ouazzane, P. Patel, S. Patel

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The dynamic and highly competitive nature of the consumer electronics retail industry means that businesses in this industry are experiencing different decision making challenges in relation to pricing, inventory control, consumer satisfaction and product offerings. To overcome the challenges facing retailers and create opportunities, we propose a generic data warehousing solution which can be applied to a wide range of consumer electronics retailers with a minimum configuration. The solution includes a dimensional data model, a template SQL script, a high level architectural descriptions, ETL tool developed using C#, a set of APIs, and data access tools. It has been successfully applied by ASK Outlets Ltd UK resulting in improved productivity and enhanced sales growth.

Keywords: consumer electronics, data warehousing, dimensional data model, generic, retail industry

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Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

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Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: autonomous vehicles, deformable part model, dpm, pedestrian detection, real time

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Authors: Lei Ren, Michael Hartnett, Stephen Nash

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The abundant measured surface current from HF radar system in coastal area is assimilated into model to improve the modeling forecasting ability. A simple sequential data assimilation scheme, Direct Insertion (DI), is applied to update model forecast states. The influence of Direct Insertion data assimilation over time is analyzed at one reference point. Vector maps of surface current from models are compared with HF radar measurements. Root-Mean-Squared-Error (RMSE) between modeling results and HF radar measurements is calculated during the last four days with no data assimilation.

Keywords: data assimilation, CODAR, HF radar, surface current, direct insertion

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Authors: M. A. Hasan, M. R. Islam, R. A. Tarefder

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This study investigates how the site specific traffic data differs from the Mechanistic Empirical Pavement Design Software default values. Two Weigh-in-Motion (WIM) stations were installed in Interstate-40 (I-40) and Interstate-25 (I-25) to developed site specific data. A computer program named WIM Data Analysis Software (WIMDAS) was developed using Microsoft C-Sharp (.Net) for quality checking and processing of raw WIM data. A complete year data from November 2013 to October 2014 was analyzed using the developed WIM Data Analysis Program. After that, the vehicle class distribution, directional distribution, lane distribution, monthly adjustment factor, hourly distribution, axle load spectra, average number of axle per vehicle, axle spacing, lateral wander distribution, and wheelbase distribution were calculated. Then a comparative study was done between measured data and AASHTOWare default values. It was found that the measured general traffic inputs for I-40 and I-25 significantly differ from the default values.

Keywords: AASHTOWare, traffic, weigh-in-motion, axle load distribution

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Authors: Vichada Chokesikarin

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The study aims to determine which factors account for customer satisfaction and to investigate the relationship between entrepreneurial orientation and business success, in particular, context of the information understanding of hostel business in Pranakorn district, Bangkok and the significant element of entrepreneurship in tourism industry. This study covers 352 hostels customers and 61 hostel owners/managers nearby Khao San Road. Data collection methods were used by survey questionnaire and a series of hypotheses were developed from services marketing literature. The findings suggest the customer satisfaction most influenced by image, service quality, room quality and price accordingly. Furthermore the findings revealed that significant relationships exist between entrepreneurial orientation and business success; while competitive aggressiveness was found unrelated. The ECSI model’s generic measuring customer satisfaction was found partially mediate the business success. A reconsideration of other variables applicable should be supported with the model of hostel business. The study provides context and overall view of hostel business while discussing from the entrepreneurial orientation to customer satisfaction, thereby reducing decision risk on hostel investment.

Keywords: customer satisfaction, ECSI model, entrepreneurial orientation, small hotel, hostel, business performance

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Authors: Edoardo Lomi

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A problem of central interest in anthropology concerns the ethnographic displacement of modernity’s conceptual sovereignty over that of native collectives worldwide. Part of this critical project has been the association of Western modernity with a dualist, naturalist ontology. Despite its demonstrated value for comparative work, this association often comes at the cost of reproducing ideas that lack an empirical ethnographic basis. This paper proposes a way forward by bringing to bear some of the results produced by an ethnographic study of a village in Wiltshire, South England. Due to its picturesque qualities, this village has served for decades as a ready-made set for fantasy movies and a backdrop to fictional stories. These forms of mediation have in turn generated some apparent paradoxes, such as fictitious characters that affect actual material changes, films that become more real than history, and animated stories that, while requiring material grounds to unfold, inhabit a time and space in other respects distinct from that of material processes. Drawing on ongoing fieldwork and interviews with locals and tourists, this paper considers the ways villagers engage with fiction as part of their everyday lives. The resulting image is one of convergence, in the same landscape, of people and things having different ontological status. This study invites reflection on the implications of this image for diversifying our imagery of Western lifeworlds. To this end, the notion of ‘real fictions’ is put forth, connecting the ethnographic blurring of modernist distinctions–such as sign and signified, mind and matter, materiality and immateriality–with discussions on anthropology’s own reliance on fictions for critical comparative work.

Keywords: England, ethnography, landscape, modernity, mediation, ontology, post-structural theory

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Authors: Tauqir A. Moughal, Fusheng Yu, Abeer Mazher

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Land-cover and land-use change information are important because of their practical uses in various applications, including deforestation, damage assessment, disasters monitoring, urban expansion, planning, and land management. Therefore, developing change detection methods for remote sensing images is an important ongoing research agenda. However, detection of change through optical remote sensing images is not a trivial task due to many factors including the vagueness between the boundaries of changed and unchanged regions and spatial dependence of the pixels to its neighborhood. In this paper, we propose a binary change detection technique for bi-temporal optical remote sensing images. As in most of the optical remote sensing images, the transition between the two clusters (change and no change) is overlapping and the existing methods are incapable of providing the accurate cluster boundaries. In this regard, a methodology has been proposed which uses the fuzzy c-means clustering to tackle the problem of vagueness in the changed and unchanged class by formulating the soft boundaries between them. Furthermore, in order to exploit the neighborhood information of the pixels, the input patterns are generated corresponding to each pixel from bi-temporal images using 3×3, 5×5 and 7×7 window. The between images and within image spatial dependence of the pixels to its neighborhood is quantified by using Pearson product moment correlation and Moran’s I statistics, respectively. The proposed technique consists of two phases. At first, between images and within image spatial correlation is calculated to utilize the information that the pixels at different locations may not be independent. Second, fuzzy c-means technique is used to produce two clusters from input feature by not only taking care of vagueness between the changed and unchanged class but also by exploiting the spatial correlation of the pixels. To show the effectiveness of the proposed technique, experiments are conducted on multispectral and bi-temporal remote sensing images. A subset (2100×1212 pixels) of a pan-sharpened, bi-temporal Landsat 5 thematic mapper optical image of Los Angeles, California, is used in this study which shows a long period of the forest fire continued from July until October 2009. Early forest fire and later forest fire optical remote sensing images were acquired on July 5, 2009 and October 25, 2009, respectively. The proposed technique is used to detect the fire (which causes change on earth’s surface) and compared with the existing K-means clustering technique. Experimental results showed that proposed technique performs better than the already existing technique. The proposed technique can be easily extendable for optical hyperspectral images and is suitable for many practical applications.

Keywords: burned area, change detection, correlation, fuzzy clustering, optical remote sensing

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Authors: Angga Hidayah Ramadhan, Luciana Andrawina, M. Azani Hasibuan

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Data will be as a core of the decision if it has a good treatment or process, which is process that data into information, and information into knowledge to make a wisdom or decision. Today, many companies have not realize it include XYZ University Admission Directorate as executor of National Admission called Seleksi Masuk Bersama (SMB) that during the time, the workers only uses their feeling to make a decision. Whereas if it done, then that company can analyze the data to make a right decision to get a pin sales from student candidate or registrant that follow SMB as many as possible. Therefore, needs Knowledge Management System (KMS) with Geographic Information System (GIS) use 5C4C that can process that company data becomes more useful and can help make decisions. This information system can process data into information based on the pin sold data with 5C (Contextualized, Categorize, Calculation, Correction, Condensed) and convert information into knowledge with 4C (Comparing, Consequence, Connection, Conversation) that has been several steps until these data can be useful to make easier to take a decision or wisdom, resolve problems, communicate, and quicker to learn to the employees have not experience and also for ease of viewing/visualization based on spatial data that equipped with GIS functionality that can be used to indicate events in each province with indicator that facilitate in this system. The system also have a function to save the tacit on the system then to be proceed into explicit in expert system based on the problems that will be found from the consequences of information. With the system each team can make a decision with same ways, structured, and the important is based on the actual event/data.

Keywords: 5C4C, data, information, knowledge

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Authors: Zuhal Kurt, Meral Kurt, Bilge T. Bal, Kemal Ozkan

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Shade matching and reproduction is the most important element of success in prosthetic dentistry. Until recently, shade matching procedure was implemented by dentists visual perception with the help of shade guides. Since many factors influence visual perception; tooth shade matching using visual devices (shade guides) is highly subjective and inconsistent. Subjective nature of this process has lead to the development of instrumental devices. Nowadays, colorimeters, spectrophotometers, spectroradiometers and digital image analysing systems are used for instrumental shade selection. Instrumental devices have advantages that readings are quantifiable, can obtain more rapidly and simply, objectively and precisely. However, these devices have noticeable drawbacks. For example, translucent structure and irregular surfaces of teeth lead to defects on measurement with these devices. Also between the results acquired by devices with different measurement principles may make inconsistencies. So, its obligatory to search for new methods for dental shade matching process. A computer-aided system device; digital camera has developed rapidly upon today. Currently, advances in image processing and computing have resulted in the extensive use of digital cameras for color imaging. This procedure has a much cheaper process than the use of traditional contact-type color measurement devices. Digital cameras can be taken by the place of contact-type instruments for shade selection and overcome their disadvantages. Images taken from teeth show morphology and color texture of teeth. In last decades, a new method was recommended to compare the color of shade tabs taken by a digital camera using color features. This method showed that visual and computer-aided shade matching systems should be used as concatenated. Recently using methods of feature extraction techniques are based on shape description and not used color information. However, color is mostly experienced as an essential property in depicting and extracting features from objects in the world around us. When local feature descriptors with color information are extended by concatenating color descriptor with the shape descriptor, that descriptor will be effective on visual object recognition and classification task. Therefore, the color descriptor is to be used in combination with a shape descriptor it does not need to contain any spatial information, which leads us to use local histograms. This local color histogram method is remain reliable under variation of photometric changes, geometrical changes and variation of image quality. So, coloring local feature extraction methods are used to extract features, and also the Scale Invariant Feature Transform (SIFT) descriptor used to for shape description in the proposed method. After the combination of these descriptors, the state-of-art descriptor named by Color-SIFT will be used in this study. Finally, the image feature vectors obtained from quantization algorithm are fed to classifiers such as Nearest Neighbor (KNN), Naive Bayes or Support Vector Machines (SVM) to determine label(s) of the visual object category or matching. In this study, SVM are used as classifiers for color determination and shade matching. Finally, experimental results of this method will be compared with other recent studies. It is concluded from the study that the proposed method is remarkable development on computer aided tooth shade determination system.

Keywords: classifiers, color determination, computer-aided system, tooth shade matching, feature extraction

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Authors: Jasmal A. Syamsu, Muhammad Yusuf, Hikmah M. Ali, Mawardi A. Asja, Zulkharnaim

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This study was conducted and aimed in identifying and mapping the pasture as an ecological base of beef cattle. A survey was carried out during a period of April to June 2016, in Suppa, Mattirobulu, the district of Pinrang, South Sulawesi province. The mapping process of grazing area was conducted in several stages; inputting and tracking of data points into Google Earth Pro (version 7.1.4.1529), affirmation and confirmation of tracking line visualized by satellite with a variety of records at the point, a certain point and tracking input data into ArcMap Application (ArcGIS version 10.1), data processing DEM/SRTM (S04E119) with respect to the location of the grazing areas, creation of a contour map (a distance of 5 m) and mapping tilt (slope) of land and land cover map-making. Analysis of land cover, particularly the state of the vegetation was done through the identification procedure NDVI (Normalized Differences Vegetation Index). This procedure was performed by making use of the Landsat-8. The results showed that the topography of the grazing areas of hills and some sloping surfaces and flat with elevation vary from 74 to 145 above sea level (asl), while the requirements for growing superior grass and legume is an altitude of up to 143-159 asl. Slope varied between 0 - > 40% and was dominated by a slope of 0-15%, according to the slope/topography pasture maximum of 15%. The range of NDVI values for pasture image analysis results was between 0.1 and 0.27. Characteristics of vegetation cover of pasture land in the category of vegetation density were low, 70% of the land was the land for cattle grazing, while the remaining approximately 30% was a grove and forest included plant water where the place for shelter of the cattle during the heat and drinking water supply. There are seven types of graminae and 5 types of legume that was dominant in the region. Proportionally, graminae class dominated up 75.6% and legume crops up to 22.1% and the remaining 2.3% was another plant trees that grow in the region. The dominant weed species in the region were Cromolaenaodorata and Lantana camara, besides that there were 6 types of floor plant that did not include as forage fodder.

Keywords: pastoral, ecology, mapping, beef cattle

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Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi, Morvarid Lalenoor

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Background: Plantar pressure distribution measurement has been used for a long time to assess foot disorders. Plantar pressure is an important component affecting the foot and ankle function and Changes in plantar pressure distribution could indicate various foot and ankle disorders. Morphologic and mechanical properties of the foot may be important factors affecting the plantar pressure distribution. Accurate and early measurement may help to reduce the prevalence of pes planus. With recent developments in technology, new techniques such as machine learning have been used to assist clinicians in predicting patients with foot disorders. Significance of the study: This study proposes a neural network learning-based flat foot classification methodology using static foot pressure distribution. Methodologies: Data were collected from 895 patients who were referred to a foot clinic due to foot disorders. Patients with pes planus were labeled by an experienced physician based on clinical examination. Then all subjects (with and without pes planus) were evaluated for static plantar pressures distribution. Patients who were diagnosed with the flat foot in both feet were included in the study. In the next step, the leg length was normalized and the network was trained for plantar pressure mapping images. Findings: From a total of 895 image data, 581 were labeled as pes planus. A computational neural network (CNN) ran to evaluate the performance of the proposed model. The prediction accuracy of the basic CNN-based model was performed and the prediction model was derived through the proposed methodology. In the basic CNN model, the training accuracy was 79.14%, and the test accuracy was 72.09%. Conclusion: This model can be easily and simply used by patients with pes planus and doctors to predict the classification of pes planus and prescreen for possible musculoskeletal disorders related to this condition. However, more models need to be considered and compared for higher accuracy.

Keywords: foot disorder, machine learning, neural network, pes planus

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Authors: Shravani Itkelwar, Deepak Tewari, Bhaskar Natarajan

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The energy consumption data plays a vital role in energy efficiency policy design, implementation, and impact assessment. Any demand-side energy management intervention's success relies on the availability of accurate, comprehensive, granular, and up-to-date data on energy consumption. The Building sector, including residential and commercial, is one of the largest consumers of energy in India after the Industrial sector. With economic growth and increasing urbanization, the building sector is projected to grow at an unprecedented rate, resulting in a 5.6 times escalation in energy consumption till 2047 compared to 2017. Therefore, energy efficiency interventions will play a vital role in decoupling the floor area growth and associated energy demand, thereby increasing the need for robust data. In India, multiple institutions are involved in the collection and dissemination of data. This paper focuses on energy consumption data management in the building sector in India for both residential and commercial segments. It evaluates the robustness of data available through administrative and survey routes to estimate the key performance indicators and identify critical data gaps for making informed decisions. The paper explores several issues in the data, such as lack of comprehensiveness, non-availability of disaggregated data, the discrepancy in different data sources, inconsistent building categorization, and others. The identified data gaps are justified with appropriate examples. Moreover, the paper prioritizes required data in order of relevance to policymaking and groups it into "available," "easy to get," and "hard to get" categories. The paper concludes with recommendations to address the data gaps by leveraging digital initiatives, strengthening institutional capacity, institutionalizing exclusive building energy surveys, and standardization of building categorization, among others, to strengthen the management of building sector energy consumption data.

Keywords: energy data, energy policy, energy efficiency, buildings

Procedia PDF Downloads 187

Authors: Maria Ukolova

Abstract:

Social and cultural processes over the past decades have largely affected the understanding of conventional female beauty all over the world. Fine arts and design tendencies could not remain unchanged and show a dynamic interplay with female rights, gender equality, and other social processes. As of now, the area lacks comprehensive academic research on the tendencies of understanding female beauty in contemporary art. This article makes an attempt to outline and analyse the main tendencies of contemporary works of art that turn to the image of a woman, including photography, digital art, and various forms of design. The research bases itself on paintings, performing arts, photography, digital art, and various forms of design, mainly on the principle of the most broadly resonated in society, as an empirical basis, and on existing researches in the sphere. The results of the research show a general trend that the concept of female beauty in art is either challenged as such or its understanding has shifted to individuality, diversity, and the state of mental health. However, some categories of art, such as digital art in the gaming industry, remain resistant to change and retain the appearance-based understanding of beauty. Specific tendencies are, firstly, aestheticization of all types of appearances; secondly, a ubiquitous interest in mental health issues and understanding the state of mental health as a part of beauty; thirdly, a certain infantilization of the image of the woman is observed as compared to previous decades. The significance of the findings of the research is to contribute to a scientific understanding of the concept of beauty in contemporary art and to give ground for prospective further related research in sociology, phycology, etc. The findings might be perceived not only by academics but also by artists and practitioners in the spheres of art and society.

Keywords: fine arts, history of art, contemporary art, concept of beauty

Procedia PDF Downloads 90

Authors: Silvina Caíno-Lores, Jesús Carretero

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Large scale computing infrastructures have been widely developed with the core objective of providing a suitable platform for high-performance and high-throughput computing. These systems are designed to support resource-intensive and complex applications, which can be found in many scientific and industrial areas. Currently, large scale data-intensive applications are hindered by the high latencies that result from the access to vastly distributed data. Recent works have suggested that improving data locality is key to move towards exascale infrastructures efficiently, as solutions to this problem aim to reduce the bandwidth consumed in data transfers, and the overheads that arise from them. There are several techniques that attempt to move computations closer to the data. In this survey we analyse the different mechanisms that have been proposed to provide data locality for large scale high-performance and high-throughput systems. This survey intends to assist scientific computing community in understanding the various technical aspects and strategies that have been reported in recent literature regarding data locality. As a result, we present an overview of locality-oriented techniques, which are grouped in four main categories: application development, task scheduling, in-memory computing and storage platforms. Finally, the authors include a discussion on future research lines and synergies among the former techniques.

Keywords: data locality, data-centric computing, large scale infrastructures, cloud computing

Procedia PDF Downloads 261

Authors: Aanshika Puri, Sakshi Mehrotra

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Technology has always been a double edged sword. The constant rut of updating oneself to a better and newer version is the new norm. ‘Being Online’ is the latest addition to one’s everyday routine. Availability of various social online platforms being served on a platter topped with easy and cheap access to the internet makes it simple and doable for people of all social backgrounds. Interestingly, in India, a recent development is the line of demarcation between people from varied backgrounds, doing the vanishing act. One finds everybody on at least one, if not more, social platforms in a desire to stay connected. For instance, this ranges from sending a ‘WhatsApp’ message to a vegetable vendor for ordering your daily needs to vendors and small entrepreneurs. Even a rickshaw puller now has access to a mobile phone, an internet connection and apps/ platforms to stay connected. Recent observations show the extent to which everyone is hooked on to their mobile phones/ tabs/ laptops/ etc. Young mothers use them to distract their children and keep them busy while they finish the task at hand. Exposure to this part of the technology at such a tender age requires responsible and careful handling. Talking of adolescents, their self- image depends on their online social image to a large extent. There is a desire to be liked and accepted by the peer group at all times. Cyber-bullying is a by-product of the 24/7 availability of these resources. There is enough research-based evidence to prove the psychosocial and emotional impact on the development and well-being of the victim. The present paper attempts to understand the dynamics of cyber bullying vis-à-vis the developmental and mental health issues faced by the bully.

Keywords: Developmental Psychology, Empathy & Resilience Based Interventions, Mental Well-Being of Cyber Bully, Positive Psychology

Procedia PDF Downloads 255

Authors: Harold P. Villota, Alejandro Osorio B.

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The energy meteorology is an area for study energy complementarity and the use of renewable sources in interconnected systems. Due to diversify the energy matrix in Colombia with wind sources, is necessary to know the data bases about this one. However, the time series given by 260 automatic weather stations have empty, and no apply data, so the purpose is to fill the time series selecting two years to characterize, impute and use like base to complete the data between 2005 and 2020.

Keywords: complementarity, wind speed, renewable, colombia, characteri, characterization, imputation

Procedia PDF Downloads 168

Authors: Hyun-Woo Cho

Abstract:

Unexpected events may occur with serious impacts on industrial process. This work utilizes a data representation technique to model and to analyze process data pattern for the purpose of diagnosis. In this work, the use of triangular representation of process data is evaluated using simulation process. Furthermore, the effect of using different pre-treatment techniques based on such as linear or nonlinear reduced spaces was compared. This work extracted the fault pattern in the reduced space, not in the original data space. The results have shown that the non-linear technique based diagnosis method produced more reliable results and outperforms linear method.

Keywords: process monitoring, data analysis, pattern modeling, fault, nonlinear techniques

Procedia PDF Downloads 392

Authors: Prarabdh Tiwari, M. Vidya Sagar, K. Bhima Raju, Joy Choudhury, Subash Chandra, E. Nagaiah, Shakeel Ahmed

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Passive seismic, a wavefield interferometric imaging, low cost and rapid tool for subsurface investigation is used for various geotechnical purposes such as hydrocarbon exploration, seismic microzonation, etc. With the recent advancement, its application has also been extended to groundwater exploration by means of finding the bedrock depth. Council of Scientific & Industrial Research (CSIR)-National Geophysical Research Institute (NGRI) has experimented passive seismic studies along with electrical resistivity tomography for groundwater in hard rock (Choutuppal, Hyderabad). Passive Seismic with Electrical Resistivity (ERT) can give more clear 2-D subsurface image for Groundwater Exploration in Hard Rock area. Passive seismic data were collected using a Tromino, a three-component broadband seismometer, to measure background ambient noise and processed using GRILLA software. The passive seismic results are found corroborating with ERT (Electrical Resistivity Tomography) results. For data acquisition purpose, Tromino was kept over 30 locations consist recording of 20 minutes at each station. These location shows strong resonance frequency peak, suggesting good impedance contrast between different subsurface layers (ex. Mica rich Laminated layer, Weathered layer, granite, etc.) This paper presents signature of passive seismic for hard rock terrain. It has been found that passive seismic has potential application for formation characterization and can be used as an alternative tool for delineating litho-stratification in an urban condition where electrical and electromagnetic tools cannot be applied due to high cultural noise. In addition to its general application in combination with electrical and electromagnetic methods can improve the interpreted subsurface model.

Keywords: passive seismic, resonant frequency, Tromino, GRILLA

Procedia PDF Downloads 190

Authors: Mostafa Gamal, Hoda K. Mohamed, Islam El-Maddah, Ali Hamdi

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In recent years, many digital documents on the web have been created due to the rapid growth of ’social applications’ communities or ’Data-intensive applications’. The evolution of online-based multimedia data poses new challenges in storing and querying large amounts of data for online recommender systems. Graph data models have been shown to be more efficient than relational data models for processing complex data. This paper will explain the key differences between graph and relational databases, their strengths and weaknesses, and why using graph databases is the best technology for building a realtime recommendation system. Also, The paper will discuss several similarity metrics algorithms that can be used to compute a similarity score of pairs of nodes based on their neighbourhoods or their properties. Finally, the paper will discover how NLP strategies offer the premise to improve the accuracy and coverage of realtime recommendations by extracting the information from the stored unstructured knowledge, which makes up the bulk of the world’s data to enrich the graph database with this information. As the size and number of data items are increasing rapidly, the proposed system should meet current and future needs.

Keywords: graph databases, NLP, recommendation systems, similarity metrics

Procedia PDF Downloads 111