Search results for: raw complex data

Authors: Noran Adel Emara, Elham Ghazi Mohammad

Abstract:

Qatar University is engaged in a systemic education reform that includes integrating the latest and most effective technologies for teaching and learning. ICube is high-immersive virtual reality technology is used to teach educational scenarios that are difficult to teach in real situations. The trends toward delivering science education via virtual reality applications have accelerated in recent years. However, research on students perceptions of integrating virtual reality especially ICube technology is somehow limited. Students often have difficulties focusing attention on learning science topics that require imagination and easily lose attention and interest during the lesson. The aim of this study was to examine students’ perception of integrating ICube technology in the solar system lesson. Moreover, to explore how ICube could engage students in learning scientific concept of the solar system. The research framework included the following quantitative research design with data collection and analysis from questionnaire results. The solar system lesson was conducted by teacher candidates (Diploma students) who taught in the ICube virtual lab in Qatar University. A group of 30 students from eighth grade were randomly selected to participate in the study. Results showed that the students were extremely engaged in learning the solar system and responded positively to integrating ICube in teaching. Moreover, the students showed interest in learning more lessons through ICube as it provided them with valuable learning experience about complex situations.

Keywords: ICube, integrating technology, science education, virtual reality

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Authors: Pablo Martinez, Emad Mohamed, Osama Mohsen, Yasser Mohamed

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Highway and bridge agencies, such as the Ministry of Transportation in Ontario, use the Bridge Condition Index (BCI) which is defined as the weighted condition of all bridge elements to determine the rehabilitation priorities for its bridges. Therefore, accurate forecasting of BCI is essential for bridge rehabilitation budgeting planning. The large amount of data available in regard to bridge conditions for several years dictate utilizing traditional mathematical models as infeasible analysis methods. This research study focuses on investigating different classification models that are developed to predict the bridge condition index in the province of Ontario, Canada based on the publicly available data for 2800 bridges over a period of more than 10 years. The data preparation is a key factor to develop acceptable classification models even with the simplest one, the k-NN model. All the models were tested, compared and statistically validated via cross validation and t-test. A simple k-NN model showed reasonable results (within 0.5% relative error) when predicting the bridge condition in an incoming year.

Keywords: asset management, bridge condition index, data mining, forecasting, infrastructure, knowledge discovery in databases, maintenance, predictive models

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Authors: Alexander Rych

Abstract:

Piql Preservation Services (“Piql”) is a turnkey solution designed for secure, migration-free long- term preservation of digital data. Piql sets an open standard for long- term preservation for the future. It consists of equipment and processes needed for writing and retrieving digital data. Exponentially growing amounts of data demand for logistically effective and cost effective processes. Digital storage media (hard disks, magnetic tape) exhibit limited lifetime. Repetitive data migration to overcome rapid obsolescence of hardware and software bears accelerated risk of data loss, data corruption or even manipulation and adds significant repetitive costs for hardware and software investments. Piql stores any kind of data in its digital as well as analog form securely for 500 years. The medium that provides this is a film reel. Using photosensitive film polyester base, a very stable material that is known for its immutability over hundreds of years, secure and cost-effective long- term preservation can be provided. The film reel itself is stored in a packaging capable of protecting the optical storage medium. These components have undergone extensive testing to ensure longevity of up to 500 years. In addition to its durability, film is a true WORM (write once- read many) medium. It therefore is resistant to editing or manipulation. Being able to store any form of data onto the film makes Piql a superior solution for long-term preservation. Paper documents, images, video or audio sequences – all of those file formats and documents can be preserved in its native file structure. In order to restore the encoded digital data, only a film scanner, a digital camera or any appropriate optical reading device will be needed in the future. Every film reel includes an index section describing the data saved on the film. It also contains a content section carrying meta-data, enabling users in the future to rebuild software in order to read and decode the digital information.

Keywords: digital data, long-term preservation, migration-free, photosensitive film

Procedia PDF Downloads 388

Authors: Rima T. Alfaraj, Murtadha J. Al Tammar, Khaqan Khan, Khalid M. Alruwaili

Abstract:

OBJECTIVE/SCOPE (25-75): Caliper logging data provides critical information about wellbore shape and deformations, such as stress-induced borehole breakouts or washouts. Multiarm mechanical caliper logs are often run using wireline, which can be time-consuming, costly, and/or challenging to run in certain formations. To minimize rig time and improve operational safety, it is valuable to develop analytical solutions that can estimate caliper logs using available Logging-While-Drilling (LWD) data without the need to run wireline caliper logs. As a first step, the objective of this paper is to perform statistical analysis using an extensive datasetto identify important physical parameters that should be considered in developing such analytical solutions. METHODS, PROCEDURES, PROCESS (75-100): Caliper logs and LWD data of eleven wells, with a total of more than 80,000 data points, were obtained and imported into a data analytics software for analysis. Several parameters were selected to test the relationship of the parameters with the measured maximum and minimum caliper logs. These parameters includegamma ray, porosity, shear, and compressional sonic velocities, bulk densities, and azimuthal density. The data of the eleven wells were first visualized and cleaned.Using the analytics software, several analyses were then preformed, including the computation of Pearson’s correlation coefficients to show the statistical relationship between the selected parameters and the caliper logs. RESULTS, OBSERVATIONS, CONCLUSIONS (100-200): The results of this statistical analysis showed that some parameters show good correlation to the caliper log data. For instance, the bulk density and azimuthal directional densities showedPearson’s correlation coefficients in the range of 0.39 and 0.57, which wererelatively high when comparedto the correlation coefficients of caliper data with other parameters. Other parameters such as porosity exhibited extremely low correlation coefficients to the caliper data. Various crossplots and visualizations of the data were also demonstrated to gain further insights from the field data. NOVEL/ADDITIVE INFORMATION (25-75): This study offers a unique and novel look into the relative importance and correlation between different LWD measurements and wireline caliper logs via an extensive dataset. The results pave the way for a more informed development of new analytical solutions for estimating the size and shape of the wellbore in real-time while drilling using LWD data.

Keywords: LWD measurements, caliper log, correlations, analysis

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Authors: Arka Roy, Chandra Prakash Dubey

Abstract:

Inverse problem generally used for recovering hidden information from outside available data. Vertical component of gravity field we will be going to use for underneath density structure calculation. Ill-posing nature is main obstacle for any inverse problem. Linear regularization using Tikhonov formulation are used for appropriate choice of SVD and GSVD components. For real time data handle, signal to noise ratios should have to be less for reliable solution. In our study, 2D and 3D synthetic model with rectangular grid are used for gravity field calculation and its corresponding inversion for density reconstruction. Fine grid also we have considered to hold any irregular structure. Keeping in mind of algebraic ambiguity factor number of observation point should be more than that of number of data point. Picard plot is represented here for choosing appropriate or main controlling Eigenvalues for a regularized solution. Another important study is depth resolution plot (DRP). DRP are generally used for studying how the inversion is influenced by regularizing or discretizing. Our further study involves real time gravity data inversion of Vredeforte Dome South Africa. We apply our method to this data. The results include density structure is in good agreement with known formation in that region, which puts an additional support of our method.

Keywords: depth resolution plot, gravity inversion, Picard plot, SVD, Tikhonov formulation

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Authors: Vishnu Pratap Singh Kirar, Madhuri Saxena

Abstract:

Advancement in sequence data generation technologies is churning out voluminous omics data and posing a massive challenge to annotate the biological functional features. With so much data available, the use of machine learning methods and tools to make novel inferences has become obvious. Machine learning methods have been successfully applied to a lot of disciplines, including computational biology and bioinformatics. Researchers in computational biology are interested to develop novel machine learning frameworks to classify the huge amounts of biological data. In this proposal, it plan to employ novel machine learning approaches to aid the understanding of how apparently innocuous mutations (in intergenic DNA and at synonymous sites) cause diseases. We are also interested in discovering novel functional sites in the genome and mutations in which can affect a phenotype of interest.

Keywords: genome wide association studies (GWAS), next generation sequencing (NGS), deep learning, omics

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Authors: Amanullah Lagharil, Majid Ali Laghari, M. Qasim, Jan. M., Asif Khan, M. Hassan Agheem

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The Nagar Parkar area in southeastern Sindh is a part of the Thar Desert adjacent to the Runn of Kutchh, and covers 480 km2. It contains exposures of a variety of igneous rocks referred to as the Nagar Parkar Igneous Complex. The complex comprises rocks belonging to at least six phases of magmatism, from oldest to youngest: 1) amphibolitic basement rocks, 2) riebeckite-aegirine grey granite, 3) biotite-hornblende pink granite, 4) acid dykes, 5) rhyolite “plugs”, and basic dykes (Jan et al., 1997). The last three of these are not significant in volume. Radiometric dates are lacking but the grey and pink granites are petrographically comparable to the Siwana and Jalore plutons, respectively, emplaced in the Malani volcanic series. Based on these similarities and proximity, the phase 2 to 6 bodies in the Nagar Parkar may belong to the Late Proterozoic (720–745 Ma) Malani magmatism that covers large areas in western Rajasthan. Khan et al. (2007) have reported a 745 ±30 – 755 ±22 Ma U-Th-Pb age on monazite from the pink granite. The grey granite is essentially composed of perthitic feldspar (microperthite, mesoperthite), quartz, small amount of plagioclase and, characteristically, sodic minerals such as riebeckite and aegirine. A few samples lack aegirine. Fe-Ti oxide and minute, well-developed crystals of zircon occur in almost all the studied samples. Tourmaline, fluorite, apatite and rutile occur in only some samples and astrophyllite is rare. Allanite, sphene and leucoxene occur as minor accessories along with local epidote. The pink granite is mostly leucocratic, but locally rich in biotite (up to 7 %). It is essentially made up of microperthite and quartz, with local microcline, and minor plagioclase (albite-oligoclase). Some rocks contain sufficient oligoclase and can be called adamellite or quartz mozonite. Biotite and hornblende are main accessory minerals along with iron oxide, but in a few samples are without hornblende. Fayalitic olivine, zircon, sphene, apatite, tourmaline, fluorite, allanite and cassiterite occur as sporadic accessory minerals. Epidote, carbonate, sericite and muscovite are produced due to the alteration of feldspar. This work concerns the major element geochemistry and comparison of the principal granitic rocks of Nagar Parkar. According to the scheme of De La Roche et al. (1980), majority of the grey and pink granites classify as alkali granite, 20 % as granite and 10 % as granodiorite. When evaluated on the basis of Shand's indices (after Maniar and Piccoli, 1989), the grey and pink granites span all three fields (peralkaline, metaluminous and peraluminous). Of the analysed grey granites, 67 % classify as peralkaline, 20 % as peraluminous and 10 % as metaluminous, while 50 % of pink granites classify as peralkaline, 30 % metaluminous and 20 % peraluminous.

Keywords: petrography, nagar parker, granites, geological sciences

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Authors: Mirjana Ruppel, Rajendra Persad, Amit Bahl, Sanja Dogramadzi, Chris Melhuish, Lyndon Smith

Abstract:

Multimodal image registration is a profoundly complex task which is why deep learning has been used widely to address it in recent years. However, two main challenges remain: Firstly, the lack of ground truth data calls for an unsupervised learning approach, which leads to the second challenge of defining a feasible loss function that can compare two images of different modalities to judge their level of alignment. To avoid this issue altogether we implement a generative adversarial network consisting of two registration networks GAB, GBA and two discrimination networks DA, DB connected by spatial transformation layers. GAB learns to generate a deformation field which registers an image of the modality B to an image of the modality A. To do that, it uses the feedback of the discriminator DB which is learning to judge the quality of alignment of the registered image B. GBA and DA learn a mapping from modality A to modality B. Additionally, a cycle-consistency loss is implemented. For this, both registration networks are employed twice, therefore resulting in images ˆA, ˆB which were registered to ˜B, ˜A which were registered to the initial image pair A, B. Thus the resulting and initial images of the same modality can be easily compared. A dataset of liver CT and MRI was used to evaluate the quality of our approach and to compare it against learning and non-learning based registration algorithms. Our approach leads to dice scores of up to 0.80 ± 0.01 and is therefore comparable to and slightly more successful than algorithms like SimpleElastix and VoxelMorph.

Keywords: cycle consistency, deformable multimodal image registration, deep learning, GAN

Procedia PDF Downloads 127

Authors: Marina Wagdy Nageeb Eskander

Abstract:

A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these "syndrome" forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or "non-syndrome" autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way for improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder, and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties ("sticky attention"), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.

Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills

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Authors: Hannan Al-Qanai, Haitham Mustafa, Rajeswaran Sivasankar

Abstract:

Kuwait Integrated Petroleum Industries Company (KIPIC, Company), established in 2016 as a subsidiary to Kuwait Petroleum Corporation (KPC), is responsible for operating and managing the largest grassroots integrated complex for refining, petrochemicals manufacture businesses, and liquefied natural gas import facilities at Al-Zour, Kuwait. KIPIC and its Contractors/sub-contractors employ over 69,000 staff in its current projects at Al-Zour during peak construction activity. KIPIC holds a unique responsibility to the society, which includes all stakeholders, and demonstrates its social commitment in developing an integrated environment & social management system (ESMS) and ensuring sustainability. This paper mainly demonstrates the knowledge on corporate branding from a corporate social responsibility (CSR) perspective and presents the achievements and best practices of KIPIC in the field of CSR and the challenges faced in handling social issues. Moreover, the study is based on qualitative data abstracted from KIPIC Health, Safety, Security & Environment Management System (HSSE MS) procedures, audit reports, the outcome of counseling sessions, national and international laws and regulations, and International Guidelines on Environment and Social Management System (ESMS). KIPIC has committed to caring for the environmental concerns and acting on social as they do on profits and economic growth. The main findings of this paper are that the successful implementation and operationalization of CSR within an organization depends on a simple but stringent process with both top-down and bottom-up commitment.

Keywords: welfare, corporate social responsibility, social management, sustainability

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Authors: Athanasios Raftopoulos

Abstract:

In this paper, an attempt is made to explain the evolution or development of human’s representational arsenal from its humble beginnings to its modern abstract symbols. Representations are physical entities that represent something else. To represent a thing (in a general sense of “thing”) means to use in the mind or in an external medium a sign that stands for it. The sign can be used as a proxy of the represented thing when the thing is absent. Representations come in many varieties, from signs that perceptually resemble their representative to abstract symbols that are related to their representata through conventions. Relying the distinction among indices, icons, and symbols, it is explained how symbolic representations gradually emerged from indices and icons. To understand the development or evolution of our representational arsenal, the development of the cognitive capacities that enabled the gradual emergence of representations of increasing complexity and expressive capability should be examined. The examination of these factors should rely on a careful assessment of the available empirical neuroscientific and paleo-anthropological evidence. These pieces of evidence should be synthesized to produce arguments whose conclusions provide clues concerning the developmental process of our representational capabilities. The analysis of the empirical findings in this paper shows that Homo Erectus was able to use both icons and symbols. Icons were used as external representations, while symbols were used in language. The first step in the emergence of representations is that a sensory-motor purely causal schema involved in indices is decoupled from its normal causal sensory-motor functions and serves as a representation of the object that initially called it into play. Sensory-motor schemes are tied to specific contexts of the organism-environment interactions and are activated only within these contexts. For a representation of an object to be possible, this scheme must be de-contextualized so that the same object can be represented in different contexts; a decoupled schema loses its direct ties to reality and becomes mental content. The analysis suggests that symbols emerged due to selection pressures of the social environment. The need to establish and maintain social relationships in ever-enlarging groups that would benefit the group was a sufficient environmental pressure to lead to the appearance of the symbolic capacity. Symbols could serve this need because they can express abstract relationships, such as marriage or monogamy. Icons, by being firmly attached to what can be observed, could not go beyond surface properties to express abstract relations. The cognitive capacities that are required for having iconic and then symbolic representations were present in Homo Erectus, which had a language that started without syntactic rules but was structured so as to mirror the structure of the world. This language became increasingly complex, and grammatical rules started to appear to allow for the construction of more complex expressions required to keep up with the increasing complexity of social niches. This created evolutionary pressures that eventually led to increasing cranial size and restructuring of the brain that allowed more complex representational systems to emerge.

Keywords: mental representations, iconic representations, symbols, human evolution

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Authors: Anubha Kaushik, Raman Preet

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Distillery wastewater in the form of spent wash is a complex and strong industrial effluent, with high load of organic pollutants that may deplete dissolved oxygen on being discharged into aquatic systems and contaminate groundwater by leaching of pollutants, while untreated spent wash disposed on land acidifies the soil. Stringent legislative measures have therefore been framed in different countries for discharge standards of distillery effluent. Utilising the organic pollutants present in various types of wastes as food by mixed microbial populations is emerging as an eco-friendly approach in the recent years, in which complex organic matter is converted into simpler forms, and simultaneously useful gases are produced as renewable and clean energy sources. In the present study, wastewater from a rice bran based distillery has been used as the substrate in a dark fermenter, and native microbial consortium from the digester sludge has been used as the inoculum to treat the wastewater and produce hydrogen. After optimising the operational conditions in batch reactors, sequential batch mode and continuous flow stirred tank reactors were used to study the best operational conditions for enhanced and sustained hydrogen production and removal of pollutants. Since the rate of hydrogen production by the microbial consortium during dark fermentation is influenced by concentration of organic matter, pH and temperature, these operational conditions were optimised in batch mode studies. Maximum hydrogen production rate (347.87ml/L/d) was attained in 32h dark fermentation while a good proportion of COD also got removed from the wastewater. Slightly acidic initial pH seemed to favor biohydrogen production. In continuous stirred tank reactor, high H₂ production from distillery wastewater was obtained from a relatively shorter substrate retention time (SRT) of 48h and a moderate organic loading rate (OLR) of 172 g/l/d COD.

Keywords: distillery wastewater, hydrogen, microbial consortium, organic pollution, sludge

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Authors: Mohammed Al-Shalabi, Alaa Obeidat

Abstract:

In any food stores, some items will be expired or destroyed because the demand on these items is infrequent, so we need a system that can help the decision maker to make an offer on such items to improve the demand on the items by putting them with some other frequent item and decrease the price to avoid losses. The system generates hundreds or thousands of patterns (offers) for each low demand item, then it uses the association rules (support, confidence) to find the interesting patterns (the best offer to achieve the lowest losses). In this paper, we propose a data mining method for determining the best offer by merging the data mining techniques with the e-commerce strategy. The task is to build a model to predict the best offer. The goal is to maximize the profits of a store and avoid the loss of products. The idea in this paper is the using of the association rules in marketing with a combination with e-commerce.

Keywords: data mining, association rules, confidence, online stores

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Authors: Yasmeen A. S. Essawy, Khaled Nassar

Abstract:

With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.

Keywords: building information modeling (BIM), elemental graph data model (EGDM), geometric and topological data models, graph theory

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Authors: W. Nootcharin, S. Sujittra, K. Mayuso, K. Kornphimol, M. Rawiwan

Abstract:

Silver has distinct antibacterial properties and has been used as a component of commercial products with many applications. An increasing number of commercial products cause risks of silver effects for human and environment such as the symptoms of Argyria and the release of silver to the environment. Therefore, the detection of silver in the aquatic environment is important. The colorimetric chemosensor is designed by the basic of ligand interactions with a metal ion, leading to the change of signals for the naked-eyes which are very useful method to this application. Dithizone ligand is considered as one of the effective chelating reagents for metal ions due to its high selectivity and sensitivity of a photochromic reaction for silver as well as the linear backbone of dithizone affords the rotation of various isomeric forms. The present study is focused on the conformation and interaction of silver ion and silver nanoparticles (AgNPs) with dithizone using density functional theory (DFT). The interaction parameters were determined in term of binding energy of complexes and the geometry optimization, frequency of the structures and calculation of binding energies using density functional approaches B3LYP and the 6-31G(d,p) basis set. Moreover, the interaction of silver–dithizone complexes was supported by UV–Vis spectroscopy, FT-IR spectrum that was simulated by using B3LYP/6-31G(d,p) and 1H NMR spectra calculation using B3LYP/6-311+G(2d,p) method compared with the experimental data. The results showed the ion exchange interaction between hydrogen of dithizone and silver atom, with minimized binding energies of silver–dithizone interaction. However, the result of AgNPs in the form of complexes with dithizone. Moreover, the AgNPs-dithizone complexes were confirmed by using transmission electron microscope (TEM). Therefore, the results can be the useful information for determination of complex interaction using the analysis of computer simulations.

Keywords: silver nanoparticles, dithizone, DFT, NMR

Procedia PDF Downloads 204

Authors: Eva Maged Hosni Sadek

Abstract:

A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these "syndrome" forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or "non-syndrome" autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way for improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder, and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties ("sticky attention"), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.

Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills

Procedia PDF Downloads 54

Authors: Aleksandra Kondraciuk

Abstract:

The reconstruction of post-war architecture in Warsaw is an important and complex project that requires physical restoration and cultural preservation. The incorporation of 18th-century art within the renovated structures of the urban area forms a crucial aspect of the reconstruction procedure. Information was gathered by interviewing current residents, examining additional data, and researching archival materials. This form of art was once a thriving cultural centre in Warsaw, playing a significant role in its history. Adding it to the rebuilt structures links them to the city’s vibrant past, making them more meaningful for locals and visitors. The reconstructed buildings showcase 18th-century art forms, including sketches, drawings, and paintings, accurately replicating the original buildings’ architectural details and decorative elements. These art forms elevate the buildings from mere functional spaces to works of art themselves, thus augmenting the beauty and distinctiveness of the city, setting it apart from other cities worldwide. Furthermore, this art form symbolises the city’s tenacity in adversity and destruction. Revitalising Warsaw requires rebuilding its physical structures, restoring its cultural identity, and preserving its rich history. Incorporating 18th-century art into the post-war architectural reconstruction process is a powerful way to achieve these goals and maintain the city. This approach acknowledges the city’s history and cultural significance, fostering a sense of continuity between the past and present, which is crucial for the city’s future growth and prosperity.

Keywords: 18th-century art, building reconstruction, cultural preservation, post-war architecture

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Authors: Tarek Dandashi

Abstract:

WSNs may provide a fast and reliable solution for the early detection of environment events like forest fires. This is crucial for alerting and calling for fire brigade intervention. Sensor nodes communicate sensor data to a host station, which enables a global analysis and the generation of a reliable decision on a potential fire and its location. A WSN with TinyOS and nesC for the capturing and transmission of a variety of sensor information with controlled source, data rates, duration, and the records/displaying activity traces is presented. We propose a similarity distance (SD) between the distribution of currently sensed data and that of a reference. At any given time, a fire causes diverging opinions in the reported data, which alters the usual data distribution. Basically, SD consists of a metric on the Cumulative Distribution Function (CDF). SD is designed to be invariant versus day-to-day changes of temperature, changes due to the surrounding environment, and normal changes in weather, which preserve the data locality. Evaluation shows that SD sensitivity is quadratic versus an increase in sensor node temperature for a group of sensors of different sizes and neighborhood. Simulation of fire spreading when ignition is placed at random locations with some wind speed shows that SD takes a few minutes to reliably detect fires and locate them. We also discuss the case of false negative and false positive and their impact on the decision reliability.

Keywords: forest fire, WSN, wireless sensor network, algortihm

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Authors: Mohamed Bin Alhaj, Hexu Liu, Mohammed Sulaiman, Osama Abudayyeh

Abstract:

An effective facility maintenance management (FMM) system plays a crucial role in improving the quality of services and maintaining the facility in good condition. Current FMM heavily relies on the quality of the data collection function of the FMM systems, at times resulting in inefficient FMM decision-making. The new technology-based crowdsourcing provides great potential to improve the current FMM practices, especially in terms of timeliness and quality of data. This research aims to investigate the feasibility of using new technology-driven crowdsourcing for FMM and highlight its opportunities and challenges. A survey was carried out to understand the human, data, system, geospatial, and automation characteristics of crowdsourcing for an educational campus FMM via social networks. The survey results were analyzed to reveal the challenges and recommendations for the implementation of crowdsourcing for FMM. This research contributes to the body of knowledge by synthesizing the challenges and opportunities of using crowdsourcing for facility maintenance and providing a road map for applying crowdsourcing technology in FMM. In future work, a conceptual framework will be proposed to support data-driven FMM using social networks.

Keywords: crowdsourcing, facility maintenance management, social networks

Procedia PDF Downloads 165

Authors: F. Saleh, F. Lyall, A. Abdulsid, L. Marks

Abstract:

Background: Labour in human is a complex biological process that involves interactions of neurological, hormonal and inflammatory pathways, with the placenta being a key regulator of these pathways. It is known that uterine contractions and labour pain cause physiological changes in gene expression in maternal and fetal blood, and in placenta during labour. Oxidative and inflammatory stress pathways are implicated in labour and they may cause alteration of placental gene expression. Additionally, in placental tissues, labour increases the expression of genes involved in placental oxidative stress, inflammatory cytokines, angiogenic regulators and apoptosis. Recently, Hydrogen Sulphide (H2S) has been considered as an endogenous gaseous mediator which promotes vasodilation and exhibits cytoprotective anti-inflammatory properties. The endogenous H2S is synthesised predominantly by two enzymes: cystathionine β-synthase (CBS) and cystathionine γ-lyase (CSE). As the H2S pathway has anti-oxidative and anti-inflammatory characteristics thus, we hypothesised that the expression of CBS and CSE in placental tissues would alter during labour. Methods: CBS and CSE expressions were examined in placentas using western blotting and RT-PCR in inner, middle and outer placental zones in placentas obtained from healthy non labouring women who delivered by caesarian section. These were compared with the equivalent zone of placentas obtained from women who had uncomplicated labour and delivered vaginally. Results: No differences in CBS and CSE mRNA or protein levels were found between the different sites within placentas in either the labour or non-labour group. There were no significant differences in either CBS or CSE expression between the two groups at the inner site and middle site. However, at the outer site there was a highly significant decrease in CBS protein expression in the labour group when compared to the non-labour group (p = 0.002). Conclusion: To the best of author’s knowledge, this is the first report to suggest that, CBS is expressed in a spatial manner within the human placenta. Further work is needed to clarify the precise function and mechanism of this spatial regulation although it is likely that inflammatory pathways regulation is a complex process in which this plays a role.

Keywords: anti-inflammatory, hydrogen sulphide, labour, oxidative stress

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Authors: Elyta Widyaningrum

Abstract:

The LiDAR data acquisition has been recognizable as one of the fastest solution to provide the basis data for topographic base mapping in Indonesia. The challenges to accelerate the provision of large-scale topographic base maps as a development plan basis gives the opportunity to implement the automated scheme in the map production process. The one stop processing will also contribute to accelerate the map provision especially to conform with the Indonesian fundamental spatial data catalog derived from ISO 19110 and geospatial database integration. Thus, the automated LiDAR classification, DTM generation and feature extraction will be conducted in one GIS-software environment to form all layers of topographic base maps. The quality of automated topographic base map will be assessed and analyzed based on its completeness, correctness, contiguity, consistency and possible customization.

Keywords: automation, GIS environment, LiDAR processing, map quality

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Authors: Taehan Bae

Abstract:

In this paper, a class of length-biased Weibull mixtures is presented to model loss severity data. The proposed model generalizes the Erlang mixtures with the common scale parameter, and it shares many important modelling features, such as flexibility to fit various data distribution shapes and weak-denseness in the class of positive continuous distributions, with the Erlang mixtures. We show that the asymptotic tail estimate of the length-biased Weibull mixture is Weibull-type, which makes the model effective to fit loss severity data with heavy-tailed observations. A method of statistical estimation is discussed with applications on real catastrophic loss data sets.

Keywords: Erlang mixture, length-biased distribution, transformed gamma distribution, asymptotic tail estimate, EM algorithm, expectation-maximization algorithm

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Authors: Harsh Vikram Singh, Ankur Rai, Anand Mohan

Abstract:

In this paper, we propose secure and robust data hiding algorithm based on DCT by Arnold transform and chaotic sequence. The watermark image is scrambled by Arnold cat map to increases its security and then the chaotic map is used for watermark signal spread in middle band of DCT coefficients of the cover image The chaotic map can be used as pseudo-random generator for digital data hiding, to increase security and robustness .Performance evaluation for robustness and imperceptibility of proposed algorithm has been made using bit error rate (BER), normalized correlation (NC), and peak signal to noise ratio (PSNR) value for different watermark and cover images such as Lena, Girl, Tank images and gain factor .We use a binary logo image and text image as watermark. The experimental results demonstrate that the proposed algorithm achieves higher security and robustness against JPEG compression as well as other attacks such as addition of noise, low pass filtering and cropping attacks compared to other existing algorithm using DCT coefficients. Moreover, to recover watermarks in proposed algorithm, there is no need to original cover image.

Keywords: data hiding, watermarking, DCT, chaotic sequence, arnold transforms

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Authors: Evisa Mitrou, Nicholas Tsitsianis, Supriya Shinde

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In the age of digitisation and globalisation, businesses have shifted online and are investing in big data analytics (BDA) to respond to changing market conditions and sustain their performance. Our study shifts the focus from the adoption of BDA to the impact of BDA on financial performance. We explore the financial performance of both BDA-vendors (business-to-business) and BDA-clients (business-to-customer). We distinguish between the five BDA-technologies (big-data-as-a-service (BDaaS), descriptive, diagnostic, predictive, and prescriptive analytics) and discuss them individually. Further, we use four perspectives (internal business process, learning and growth, customer, and finance) and discuss the significance of how each of the five BDA-technologies affects the performance measures of these four perspectives. We also present the analysis of employee engagement, average turnover, average net income, and average net assets for BDA-clients and BDA-vendors. Our study also explores the effect of the COVID-19 pandemic on business continuity for both BDA-vendors and BDA-clients.

Keywords: BDA-clients, BDA-vendors, big data analytics, financial performance

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Authors: Nathalie Piquemal, Faiçal Zellama, Bathélemy Bolivar, Leyla Sall

Abstract:

Canada defines itself as a country of immigration and a multicultural nation, ideologically, politically and programmatically (in terms of its integration practices). As such, principles of hospitality may seem, at first glance, incontestable, given the convergence of the views of the majority of Canadian politicians on the need to welcome, each year, a significant number of immigrants and to offer them the hospitality that facilitates their transition to Canadian citizenship. However, immigrants are welcomed in a Canadian societal context in which power and resources are unevenly distributed, resulting in complex social relationships between hosts and newcomers. Qualitative data obtained from newcomers in Winnipeg, Manitoba, Canada, focuses on experiences of hospitality, with special attention to host-guest social and power dynamics, contested policies on foreign credential and micro spaces of belongingin a multicultural context. The act of welcoming a newcomer is inherently shaped by both macropolitical structures and everyday relational practices that can lead to experiences of belonging, marginalisation, empowerment and/or disempowerment depending on economic agenda, humanitarian and humanistic orientations. We first explore the extent to which immigrants experience hospitality in relation to unequal distribution of power and resources as well as cultural discontinuities. We then examine ways in which immigrants have been able to find sanctuaries of hospitality within their own ethnocultural communities. Finally, we discuss the complexity of hospitality in a multicultural context and offer critical insights on host factors that may produce, develop and nurture hospitable environments.

Keywords: migration, hospitality, diversity, culture, race

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Authors: AmirHossein Mohajerzadeh, Mohammad Alishahi, Saeed Aslishahi, Mohsen Zabihi

Abstract:

In this paper, we consider sensor nodes with the capability of measuring the bearings (relative angle to the target). We use geometric methods to select a set of observer nodes which are responsible for collecting data from the target. Considering the characteristics of target tracking applications, it is clear that significant numbers of sensor nodes are usually inactive. Therefore, in order to minimize the total network energy consumption, a set of sensor nodes, called sentinel, is periodically selected for monitoring, controlling the environment and transmitting data through the network. The other nodes are inactive. Furthermore, the proposed algorithm provides a joint scheduling and routing algorithm to transmit data between network nodes and the fusion center (FC) in which not only provides an efficient way to estimate the target position but also provides an efficient target tracking. Performance evaluation confirms the superiority of the proposed algorithm.

Keywords: coverage, routing, scheduling, target tracking, wireless sensor networks

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Authors: Moustafa Osman Mohammed

Abstract:

This paper will explore formation of HCl aerosol at atmospheric boundary layers and encourages the uptake of environmental modeling systems (EMSs) as a practice evaluation of gaseous emissions (“framework measures”) from small and medium-sized enterprises (SMEs). The conceptual model predicts greenhouse gas emissions to ecological points beyond landfill site operations. It focuses on incorporation traditional knowledge into baseline information for both measurement data and the mathematical results, regarding parameters influence model variable inputs. The paper has simplified parameters of aerosol processes based on the more complex aerosol process computations. The simple model can be implemented to both Gaussian and Eulerian rural dispersion models. Aerosol processes considered in this study were (i) the coagulation of particles, (ii) the condensation and evaporation of organic vapors, and (iii) dry deposition. The chemical transformation of gas-phase compounds is taken into account photochemical formulation with exposure effects according to HCl concentrations as starting point of risk assessment. The discussion set out distinctly aspect of sustainability in reflection inputs, outputs, and modes of impact on the environment. Thereby, models incorporate abiotic and biotic species to broaden the scope of integration for both quantification impact and assessment risks. The later environmental obligations suggest either a recommendation or a decision of what is a legislative should be achieved for mitigation measures of landfill gas (LFG) ultimately.

Keywords: air pollution, landfill emission, environmental management, monitoring/methods and impact assessment

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Authors: Jhabakhar Aryal, Kesh Bahadur Rana, Durga Prasad Neupane

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This research analyzes the nature and impacts of the 2015 unofficial blockade in Nepal, a significant event that triggered an economic and humanitarian crisis. While official channels denied claims of involvement, Nepal perceived the blockade as orchestrated by India due to concerns about the newly adopted constitution and Madheshi infringements. The study adopts a qualitative approach, utilizing semi-structured interviews, document analysis, and content analysis to gather data from various perspectives. Employing a "colonial hangover lens," it investigates if colonial legacies continue to influence postcolonial nation dynamics, focusing on India's potential attempt to exert influence over Nepal. The findings suggest that the 2015 blockade had profound consequences for Nepal, potentially reflecting lingering colonial power dynamics in the region. Despite India's denials, a significant portion of Nepalis perceived the blockade as an act of external pressure. Examining these perceptions offers valuable insights into postcolonial relations and their impact on regional stability. The 2015 unofficial blockade serves as a critical case study in understanding the complex interplay of internal dynamics, external influences, and historical legacies in shaping the geopolitics of the region. This research contributes to a deeper understanding of these factors and their ongoing implications for Nepal and its relationship with India.

Keywords: blockade, unofficial, constitution, Madhesis, India, Nepal, postcolonial, regional stability, geopolitics

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Authors: Omid Amini

Abstract:

Nowadays, technology plays the most important role in the life of human beings because people use technology to share data and to communicate with each other, but the challenge is the security of this data. For instance, as more people turn to technology in the world, more data is generated, and more hackers try to steal or infiltrate data. In addition, the data is under the control of the central authority, which can trigger the challenge of losing information and changing information; this can create widespread anxiety for different people in different communities. In this paper, we sought to investigate Blockchain technology that can guarantee information security and eliminate the challenge of central authority access to information. Now a day, people are suffering from the current voting system. This means that the lack of transparency in the voting system is a big problem for society and the government in most countries, but blockchain technology can be the best alternative to the previous voting system methods because it removes the most important challenge for voting. According to the results, this research can be a good start to getting acquainted with this new technology, especially on the security part and familiarity with how to use a voting system based on blockchain in the world. At the end of this research, it is concluded that the use of blockchain technology can solve the major security problem and lead to a secure and transparent election.

Keywords: blockchain, technology, security, information, voting system, transparency

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Authors: Yaw Opoku-Damoah, Run Zhang, Hang Thu Ta, Zhi Ping Xu

Abstract:

Gas therapy is still at an early stage of research and development. Even though most gasotransmitters have proven their therapeutic potential, their handling, delivery, and controlled release have been extremely challenging. This research work employs a versatile nanosystem that is capable of delivering a gasotransmitter in the form of a photo-responsive carbon monoxide-releasing molecule (CORM) for targeted cancer therapy. The therapeutic action was mediated by upconversion nanoparticles (UCNPs) designed to transfer bio-friendly low energy near-infrared (NIR) light to ultraviolet (UV) light capable of triggering carbon monoxide (CO) from a water-soluble amphiphilic manganese carbonyl complex CORM incorporated into a carefully designed lipid drug delivery system. Herein, gaseous CO that plays a role as a gasotransmitter with cytotoxic and homeostatic properties was investigated to instigate cellular apoptosis. After successfully synthesizing the drug delivery system, the ability of the system to encapsulate and mediate the sustained release of CO after light excitation was demonstrated. CO fluorescence probe (COFP) was successfully employed to determine the in vitro drug release profile upon NIR light irradiation. The uptake of nanoparticles enhanced by folates and its receptor interaction was also studied for cellular uptake purposes. The anticancer potential of the final lipid nanoparticle Lipid/UCNPs/CORM/FA (LUCF) was also determined by cell viability assay. Intracellular CO release and a subsequent therapeutic action involving ROS production, mitochondrial damage, and CO production was also evaluated. In all, this current project aims to use in vitro studies to determine the potency and efficiency of a NIR-mediated CORM prodrug delivery system.

Keywords: carbon monoxide-releasing molecule, upconversion nanoparticles, site-specific delivery, amphiphilic manganese carbonyl complex, prodrug delivery system.

Procedia PDF Downloads 110