Search results for: manual data inquiry

Authors: Diego Saqui, José H. Saito, José R. Campos, Lúcio A. de C. Jorge

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Hyperspectral images and remote sensing are important for many applications. A problem in the use of these images is the high volume of data to be processed, stored and transferred. Dimensionality reduction techniques can be used to reduce the volume of data. In this paper, an approach to band selection based on clustering algorithms is presented. This approach allows to reduce the volume of data. The proposed structure is based on Fuzzy C-Means (or K-Means) and NWHFC algorithms. New attributes in relation to other studies in the literature, such as kurtosis and low correlation, are also considered. A comparison of the results of the approach using the Fuzzy C-Means and K-Means with different attributes is performed. The use of both algorithms show similar good results but, particularly when used attributes variance and kurtosis in the clustering process, however applicable in hyperspectral images.

Keywords: band selection, fuzzy c-means, k-means, hyperspectral image

Procedia PDF Downloads 396

Authors: Gyoutae Park, Woosuk Kim, Sangguk Ahn, Seungmo Kim, Minjun Kim, Jinhan Lee, Youngdo Jo, Jongsam Moon, Hiesik Kim

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In this research, we designed a remote system to test parameters of gas detectors such as gas concentration and initial response time. This testing system is available to measure two gas instruments simultaneously. First of all, we assembled an experimental jig with a square structure. Those parts are included with a glass flask, two high-quality cameras, and two Ethernet modems for transmitting data. This remote gas detector testing system extracts numerals from videos with continually various gas concentrations while LCDs show photographs from cameras. Extracted numeral data are received to a laptop computer through Ethernet modem. And then, the numerical data with gas concentrations and the measured initial response speeds are recorded and graphed. Our remote testing system will be diversely applied on gas detector’s test and will be certificated in domestic and international countries.

Keywords: gas leak detector, inspection instrument, extracting numerals, concentration

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Authors: Luis A. Anchordoqui, Jorge F. Soriano, Diego F. Torres

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Auger data show evidence for a correlation between ultrahigh-energy cosmic rays (UHECRs) and nearby starburst galaxies. This intriguing correlation is consistent with data collected by the Telescope Array, which have revealed a much more pronounced directional 'hot spot' in arrival directions not far from the starburst galaxy M82. In this work, we assume starbursts are sources of UHECRs, and we investigate the prospects to use the observed distribution of UHECR arrival directions to constrain galactic magnetic field models. We show that if the Telescope Array hot spot indeed originates on M82, UHECR data would place a strong constraint on the turbulent component of the galactic magnetic field.

Keywords: galactic magnetic field, Pierre Auger observatory, telescope array, ultra-high energy cosmic rays

Procedia PDF Downloads 141

Authors: Jaishree Ranganathan, Poonam Rajurkar, Angelina A. Tzacheva, Zbigniew W. Ras

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In today’s world, business often depends on the customer feedback and reviews. Sentiment analysis helps identify and extract information about the sentiment or emotion of the of the topic or document. Attribute selection is a challenging problem, especially with large datasets in actionable pattern mining algorithms. Action Rule Mining is one of the methods to discover actionable patterns from data. Action Rules are rules that help describe specific actions to be made in the form of conditions that help achieve the desired outcome. The rules help to change from any undesirable or negative state to a more desirable or positive state. In this paper, we present a Lexicon based weighted scheme approach to identify emotions from customer feedback data in the area of manufacturing business. Also, we use Rough sets and explore the attribute selection method for large scale datasets. Then we apply Actionable pattern mining to extract possible emotion change recommendations. This kind of recommendations help business analyst to improve their customer service which leads to customer satisfaction and increase sales revenue.

Keywords: actionable pattern discovery, attribute selection, business data, data mining, emotion

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Authors: Shriya Shukla, Lachin Fernando

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Pneumonia, a leading cause of mortality in young children globally, presents significant diagnostic challenges, particularly in resource-limited settings. This study presents an approach to diagnosing pediatric pneumonia using Chest X-Ray (CXR) images, employing a lightweight MobileNetV2 model enhanced with synthetic data augmentation. Addressing the challenge of dataset scarcity and imbalance, the study used a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to generate synthetic CXR images, improving the representation of normal cases in the pediatric dataset. This approach not only addresses the issues of data imbalance and scarcity prevalent in medical imaging but also provides a more accessible and reliable diagnostic tool for early pneumonia detection. The augmented data improved the model’s accuracy and generalization, achieving an overall accuracy of 95% in pneumonia detection. These findings highlight the efficacy of the MobileNetV2 model, offering a computationally efficient yet robust solution well-suited for resource-constrained environments such as mobile health applications. This study demonstrates the potential of synthetic data augmentation in enhancing medical image analysis for critical conditions like pediatric pneumonia.

Keywords: pneumonia, MobileNetV2, image classification, GAN, VAE, deep learning

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Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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Authors: Olaiya Folorunsho, Comfort Y. Daramola, Joel N. Ugwu, Lawrence B. Adewole, Olufisayo S. Ekundayo

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In today world, there is a tremendous rise in the usage of internet due to the fact that almost all the communication and information sharing is done over the web. Conversely, there is a continuous growth of unauthorized access to confidential data. This has posed a challenge to information security expertise whose major goal is to curtail the menace. One of the approaches to secure the safety delivery of data/information to the rightful destination without any modification is steganography. Steganography is the art of hiding information inside an embedded information. This research paper aimed at designing a secured algorithm with the use of image steganographic technique that makes use of Least Significant Bit (LSB) algorithm for embedding the data into the bit map image (bmp) in order to enhance security and reliability. In the LSB approach, the basic idea is to replace the LSB of the pixels of the cover image with the Bits of the messages to be hidden without destroying the property of the cover image significantly. The system was implemented using C# programming language of Microsoft.NET framework. The performance evaluation of the proposed system was experimented by conducting a benchmarking test for analyzing the parameters like Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR). The result showed that image steganography performed considerably in securing data hiding and information transmission over the networks.

Keywords: steganography, image steganography, least significant bits, bit map image

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Authors: Ali Razmi, Saeed Golian

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Climate change is known to have the potential to impact adversely hydrologic patterns for variables such as rainfall, maximum and minimum temperature and sea level rise. Long-term average of these climate variables could possibly change over time due to climate change impacts. In this study, trend analysis was performed on rainfall, maximum and minimum temperature and water level data of a coastal area in Manhattan, New York City, Central Park and Battery Park stations to investigate if there is a significant change in the data mean. Partial Man-Kendall test was used for trend analysis. Frequency analysis was then performed on data using common probability distribution functions such as Generalized Extreme Value (GEV), normal, log-normal and log-Pearson. Goodness of fit tests such as Kolmogorov-Smirnov are used to determine the most appropriate distributions. In flood frequency analysis, rainfall and water level data are often separately investigated. However, in determining flood zones, simultaneous consideration of rainfall and water level in frequency analysis could have considerable effect on floodplain delineation (flood extent and depth). The present study aims to perform flood frequency analysis considering joint probability distribution for rainfall and storm surge. First, correlation between the considered variables was investigated. Joint probability distribution of extreme water level and temperature was also investigated to examine how global warming could affect sea level flooding impacts. Copula functions were fitted to data and joint probability of water level with rainfall and temperature for different recurrence intervals of 2, 5, 25, 50, 100, 200, 500, 600 and 1000 was determined and compared with the severity of individual events. Results for trend analysis showed increase in long-term average of data that could be attributed to climate change impacts. GEV distribution was found as the most appropriate function to be fitted to the extreme climate variables. The results for joint probability distribution analysis confirmed the necessity for incorporation of both rainfall and water level data in flood frequency analysis.

Keywords: climate change, climate variables, copula, joint probability

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Authors: O. T. Oluriz, O. D. Akinyemi, J. A.Olowofela, O. A. Idowu, S. A. Ganiyu

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This study was carried out using aeromagnetic data which record variation in the magnitude of the earth magnetic field in order to detect local changes in the properties of the underlying geology. The aeromagnetic data (Sheet No. 261) was acquired from the archives of Nigeria Geological Survey Agency of Nigeria, obtained in 2009. The study present estimation of source parameters within an area of about 3,025 square kilometers on geographic latitude to and longitude to within Ibadan and it’s environs in Oyo State, southwestern Nigeria. The area under study belongs to part of basement complex in southwestern Nigeria. Estimation of source parameters of aeromagnetic data was achieve through the application of source imaging parameters (SPI) techniques that provide delineation, depth, dip contact, susceptibility contrast and mineral potentials of magnetic signatures within the region. The depth to the magnetic sources in the area ranges from 0.675 km to 4.48 km. The estimated depth limit to shallow sources is 0.695 km and depth to deep sources is 4.48 km. The apparent susceptibility values of the entire study area obtained ranges from 0.01 to 0.005 [SI]. This study has shown that the magnetic susceptibility within study area is controlled mainly by super paramagnetic minerals.

Keywords: aeromagnetic, basement complex, meta-sediment, precambrian

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Authors: Slawomir Pilip, Michal Wasilewski, Daniel Celinski, Leszek Szpakowski, Grzegorz Michalak

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The aim of the study was to evaluate the effectiveness of cardiopulmonary resuscitation taken by Medical Emergency Teams (MET) at the place of an accident including the usage of mechanical chest compression systems. In the period of January-May 2017, there were 137 cases of a sudden cardiac arrest in a chosen region of Eastern Poland with 360.000 inhabitants. Medical records and questionnaires filled by METs were analysed to prove the effectiveness of cardiopulmonary resuscitations that were considered to be effective when an early indication of spontaneous circulation was provided and the patient was taken to hospital. A chest compression system used by METs was applied in 60 cases (Lucas3 - 34 patients; Auto Pulse - 24 patients). The effectiveness of cardiopulmonary resuscitation among patients who were employed a chest compression system was much higher (43,3%) than the manual cardiac massage (36,4%). Thus, the usage of Lucas3 chest compression system resulted in 47% while Auto Pulse was 33,3%. The average ambulance arrival time could have had a significant impact on the subsequent effectiveness of cardiopulmonary resuscitation in these cases. Ambulances equipped with Lucas3 reached the destination within 8 minutes, and those with Auto Pulse needed 12,1 minutes. Moreover, taking effective basic life support (BLS) by bystanders before the ambulance arrival was much more frequent for ambulances with Lucas3 than Auto Pulse. Therefore, the percentage of BLS among the group of patients who were employed Lucas3 by METs was 26,5%, and 20,8% for Auto Pulse. The total percentage of taking BLS by bystanders before the ambulance arrival resulted in 25% of patients who were later applied a chest compression system by METs. Not only was shockable cardiac rhythm obtained in 47% of these cases, but an early indication of spontaneous circulation was also provided in all these patients. Both Lucas3 and Auto Pulse were evaluated to be significantly useful in improving the effectiveness of cardiopulmonary resuscitation by 97% of Medical Emergency Teams. Therefore, implementation of chest compression systems essentially makes the cardiopulmonary resuscitation even more effective. The ambulance arrival time, taking successful BLS by bystanders before the ambulance arrival and the presence of shockable cardiac rhythm determine an early indication of spontaneous circulation among patients after a sudden cardiac arrest.

Keywords: cardiac arrest, effectiveness, mechanical chest compression systems, resuscitation

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Authors: Hamidreza Namazi

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Fractal analysis is assessing fractal characteristics of data. It consists of several methods to assign fractal characteristics to a dataset which may be a theoretical dataset or a pattern or signal extracted from phenomena including natural geometric objects, sound, market fluctuations, heart rates, digital images, molecular motion, networks, etc. Fractal analysis is now widely used in all areas of science. An important limitation of fractal analysis is that arriving at an empirically determined fractal dimension does not necessarily prove that a pattern is fractal; rather, other essential characteristics have to be considered. For this purpose a Visual C++ based software called FRATSAN (FRActal Time Series ANalyser) was developed which extract information from signals through three measures. These measures are Fractal Dimensions, Jeffrey’s Measure and Hurst Exponent. After computing these measures, the software plots the graphs for each measure. Besides computing three measures the software can classify whether the signal is fractal or no. In fact, the software uses a dynamic method of analysis for all the measures. A sliding window is selected with a value equal to 10% of the total number of data entries. This sliding window is moved one data entry at a time to obtain all the measures. This makes the computation very sensitive to slight changes in data, thereby giving the user an acute analysis of the data. In order to test the performance of this software a set of EEG signals was given as input and the results were computed and plotted. This software is useful not only for fundamental fractal analysis of signals but can be used for other purposes. For instance by analyzing the Hurst exponent plot of a given EEG signal in patients with epilepsy the onset of seizure can be predicted by noticing the sudden changes in the plot.

Keywords: EEG signals, fractal analysis, fractal dimension, hurst exponent, Jeffrey’s measure

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Authors: Marco Sewald

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Due to the current enforcement of exterritorial U.S. legislation, up to 9 million U.S. (dual) citizens residing abroad are subject to U.S. double and surcharge taxation and at risk of losing access to otherwise basic financial services and investment opportunities abroad. The United States is the only OECD country that taxes non-resident citizens, lawful permanent residents and other non-resident aliens on their worldwide income, based on local U.S. tax laws. To enforce these policies the U.S. has implemented ‘saving clauses’ in all tax treaties and implemented several compliance provisions, including the Foreign Account Tax Compliance Act (FATCA), Qualified Intermediaries Agreements (QI) and Intergovernmental Agreements (IGA) addressing Foreign Financial Institutions (FFIs) to implement these provisions in foreign jurisdictions. This policy creates systematic cases of double and surcharge taxation. The increased enforcement of compliance rules is creating additional report burdens for U.S. persons abroad and FFIs accepting such U.S. persons as customers. FFIs in Europe react with a growing denial of specific financial services to this population. The numbers of U.S. citizens renouncing has dramatically increased in the last years. A case study is chosen as an appropriate methodology and research method, as being an empirical inquiry that investigates a contemporary phenomenon within its real-life context; when the boundaries between phenomenon and context are not clearly evident; and in which multiple sources of evidence are used. This evaluative approach is testing whether the combination of policies works in practice, or whether they are in accordance with desirable moral, political, economical aims, or may serve other causes. The research critically evaluates the financial and non-financial consequences and develops sufficient strategies. It further discusses these strategies to avoid the undesired consequences of exterritorial U.S. legislation. Three possible strategies are resulting from the use cases: (1) Duck and cover, (2) Pay U.S. double/surcharge taxes, tax preparing fees and accept imposed product limitations and (3) Renounce U.S. citizenship and pay possible exit taxes, tax preparing fees and the requested $2,350 fee to renounce. While the first strategy is unlawful and therefore unsuitable, the second strategy is only suitable if the U.S. citizen residing abroad is planning to move to the U.S. in the future. The last strategy is the only reasonable and lawful way provided by the U.S. to limit the exposure to U.S. double and surcharge taxation and the limitations on financial products. The results are believed to add a perspective to the current academic discourse regarding U.S. citizenship based taxation, currently dominated by U.S. scholars, while providing sufficient strategies for the affected population at the same time.

Keywords: citizenship based taxation, FATCA, FBAR, qualified intermediaries agreements, renounce U.S. citizenship

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Authors: Ruangdech Sirikit

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The purposes of this study were analyzed differential item functioning and differential test functioning of SWUSAT aptitude test classification by sex variable. The data used in this research is the secondary data from Srinakharinwirot University Scholastic Aptitude Test 2011 (SWUSAT 2011) SWUSAT test consists of four subjects. There are verbal ability test, number ability test, reasoning ability test and spatial ability test. The data analysis was carried out in 2 steps. The first step was analyzing descriptive statistics. In the second step were analyzed differential item functioning (DIF) and differential test functioning (DTF) by using the DIFAS program. The research results were as follows: The results of data analysis for all 10 tests in year 2011. Sex was the characteristic that found DIF all 10 tests. The percentage of item number that found DIF was between 10% - 46.67%. There are 4 tests that most of items favors female group. There are 3 tests that most of items favors male group and there are 3 tests that the number of items favors female group equal favors male group. For Differential test functioning (DTF), there are 8 tests that have small DIF effect variance.

Keywords: differential item functioning, differential test functioning, SWUSAT, aptitude test

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Authors: Aria Teimourzadeh, Marc Favier, Samaneh Kakavand

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The emergence of social networks has revolutionized the exchange of information. Every behavior on these platforms contributes to the generation of data known as social network data that are processed, stored and published by the social network service providers. Hence, it is vital to investigate the role of these platforms in user data by considering the privacy measures, especially when we observe the increased number of individuals and organizations engaging with the current virtual platforms without being aware that the data related to their positioning, connections and behavior is uncovered and used by third parties. Performing analytics on social network datasets may result in the disclosure of confidential information about the individuals or organizations which are the members of these virtual environments. Analyzing separate datasets can reveal private information about relationships, interests and more, especially when the datasets are analyzed jointly. Intentional breaches of privacy is the result of such analysis. Addressing these privacy concerns requires an understanding of the nature of data being accumulated and relevant data privacy regulations, as well as motivations for disclosure of personal information on social network platforms. Some significant points about how user's online information is controlled by the influence of social factors and to what extent the users are concerned about future use of their personal information by the organizations, are highlighted in this paper. Firstly, this research presents a short literature review about the structure of a network and concept of privacy in Online Social Networks. Secondly, the factors of user behavior related to privacy protection and self-disclosure on these virtual communities are presented. In other words, we seek to demonstrates the impact of identified variables on user information disclosure that could be taken into account to explain the privacy preservation of individuals on social networking platforms. Thirdly, a few research directions are discussed to address this topic for new researchers.

Keywords: information disclosure, privacy measures, privacy preservation, social network analysis, user experience

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Authors: Abigail Qian Zhou

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In today's China, the well-educated middle class, with stable jobs and above-average income, are the driving force behind its Internet society. Through the analysis of data from the 2015 Chinese General Social Survey and 50 interviewees, this study investigates the current situation of this group’s specific internet usage. The findings of this study demonstrate that daily life among the members of this socioeconomic group is closely tied to the Internet. For Chinese middle class, the Internet is used to socialize and entertain self and others. It is also used to search for and share information as well as to build their identities. The empirical results of this study will provide a reference, supported by factual data, for enterprises seeking to target the Chinese middle class through online marketing efforts.

Keywords: middle class, Internet use, network behaviour, online marketing, China

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Authors: Ferry Kurniawan

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In this paper, we nowcast quarterly output growth in Indonesia by exploiting higher frequency data (monthly indicators) using a mixed-frequency factor model and exploiting both quarterly and monthly data. Nowcasting quarterly GDP in Indonesia is particularly relevant for the central bank of Indonesia which set the policy rate in the monthly Board of Governors Meeting; whereby one of the important step is the assessment of the current state of the economy. Thus, having an accurate and up-to-date quarterly GDP nowcast every time new monthly information becomes available would clearly be of interest for central bank of Indonesia, for example, as the initial assessment of the current state of the economy -including nowcast- will be used as input for longer term forecast. We consider a small scale mixed-frequency factor model to produce nowcasts. In particular, we specify variables as year-on-year growth rates thus the relation between quarterly and monthly data is expressed in year-on-year growth rates. To assess the performance of the model, we compare the nowcasts with two other approaches: autoregressive model –which is often difficult when forecasting output growth- and Mixed Data Sampling (MIDAS) regression. In particular, both mixed frequency factor model and MIDAS nowcasts are produced by exploiting the same set of monthly indicators. Hence, we compare the nowcasts performance of the two approaches directly. To preview the results, we find that by exploiting monthly indicators using mixed-frequency factor model and MIDAS regression we improve the nowcast accuracy over a benchmark simple autoregressive model that uses only quarterly frequency data. However, it is not clear whether the MIDAS or mixed-frequency factor model is better. Neither set of nowcasts encompasses the other; suggesting that both nowcasts are valuable in nowcasting GDP but neither is sufficient. By combining the two individual nowcasts, we find that the nowcast combination not only increases the accuracy - relative to individual nowcasts- but also lowers the risk of the worst performance of the individual nowcasts.

Keywords: nowcasting, mixed-frequency data, factor model, nowcasts combination

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Authors: M. F. Haroun, T. A. Gulliver

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In this paper, an encryption algorithm is proposed for real-time image encryption. The scheme employs a dual chaotic generator based on a three dimensional (3D) discrete Lorenz attractor. Encryption is achieved using non-autonomous modulation where the data is injected into the dynamics of the master chaotic generator. The second generator is used to permute the dynamics of the master generator using the same approach. Since the data stream can be regarded as a random source, the resulting permutations of the generator dynamics greatly increase the security of the transmitted signal. In addition, a technique is proposed to mitigate the error propagation due to the finite precision arithmetic of digital hardware. In particular, truncation and rounding errors are eliminated by employing an integer representation of the data which can easily be implemented. The simple hardware architecture of the algorithm makes it suitable for secure real-time applications.

Keywords: chaotic systems, image encryption, non-autonomous modulation, FPGA

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Authors: Katerina Antoniou

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When examining conflicts around the world, it is evident that the majority of intractable conflicts are steeped in identity. Identity seems to be not only a causal variable for conflict, but also a catalytic parameter for the process of reconciliation that follows ceasefire. This paper focuses on the process of identity securitization that occurs between rival groups of heterogeneous collective identities – ethnic, national or religious – as well as on the relationship between identity securitization and the ability of the groups involved to reconcile. Are securitized identities obstacles to the process of reconciliation, able to hinder any prospects of peace? If the level to which an identity is securitized is catalytic to a conflict’s discourse and settlement, then which factors act as indicators of identity de-securitization? The level of an in-group’s identity securitization can be estimated through a number of indicators, one of which is narrative. The stories, views and stances each in-group adopts in relation to its history of conflict and relation with their rival out-group can clarify whether that specific in-group feels victimized and threatened or safe and ready to reconcile. Accordingly, this study discusses identity securitization through narrative in relation to intractable conflicts. Are there conflicts around the world that, despite having been identified as intractable, stagnated or insoluble, show signs of identity de-securitization through narrative? This inquiry uses the case of the Cyprus conflict and its partitioned societies to present official narratives from the two communities and assess whether these narratives have transformed, indicating a less securitized in-group identity for the Greek and Turkish Cypriots. Specifically, the study compares the official historical overviews presented by each community’s Ministry of Foreign Affairs website and discusses the extent to which the two official narratives present a securitized collective identity. In addition, the study will observe whether official stances by the two communities – as adopted by community leaders – have transformed to depict less securitization over time. Additionally, the leaders’ reflection of popular opinion is evaluated through recent opinion polls from each community. Cyprus is currently experiencing renewed optimism for reunification, with the leaders of its two communities engaging in rigorous negotiations, and with rumors calling for a potential referendum for reunification to be taking place even as early as within 2016. Although leaders’ have shown a shift in their rhetoric and have moved away from narratives of victimization, this is not the case for the official narratives used by their respective ministries of foreign affairs. The study’s findings explore whether this narrative inconsistency proves that Cyprus is transitioning towards reunification, or whether the leaders are risking sending a securitized population to the polls to reject a potential reunification. More broadly, this study suggests that in the event that intractable conflicts might be moving towards viable peace, in-group narratives--official narratives in particular--can act as indicators of the extent to which rival entities have managed to reconcile.

Keywords: conflict, identity, narrative, reconciliation

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Authors: B. K. Gill, Himani Sharma, V. K. Rattan

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Experimental data of refractive index, excess molar volume and viscosity of binary mixture of morpholine with cumene over the whole composition range at 298.15 K, 303.15 K, 308.15 K and normal atmospheric pressure have been measured. The experimental data were used to compute the density, deviation in molar refraction, deviation in viscosity and excess Gibbs free energy of activation as a function of composition. The experimental viscosity data have been correlated with empirical equations like Grunberg- Nissan, Herric correlation and three body McAllister’s equation. The excess thermodynamic properties were fitted to Redlich-Kister polynomial equation. The variation of these properties with composition and temperature of the binary mixtures are discussed in terms of intermolecular interactions.

Keywords: cumene, excess Gibbs free energy, excess molar volume, morpholine

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Authors: R. Mofeed, N. Elgendy

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Cinema constructs mind-spaces that reflect inherent human thoughts and emotions. As a representational art, Cinema would introduce comprehensive images of life phenomena in different ways. The term “represent” suggests verity of meanings; bring into presence, replace or typify. In that sense, Cinema may present a phenomenon through direct embodiment, or introduce a substitute image that replaces the original phenomena, or typify it by relating the produced image to a more general category through a process of abstraction. This research is interested in questioning the type of images that Egyptian Cinema introduces to informal urbanism and how these images were conditioned and reshaped in the last twenty years. The informalities/slums phenomenon first appeared in Egypt and, particularly, Cairo in the early sixties, however, this phenomenon was completely ignored by the state and society until the eighties, and furthermore, its evident representation in Cinema was by the mid-nineties. The Informal City represents the illegal housing developments, and it is a fast growing form of urbanization in Cairo. Yet, this expanding phenomenon is still depicted as the minority, exceptional and marginal through the Cinematic lenses. This paper aims at tracing the forms of representations of the urban informalities in the Egyptian Cinema between 1994 and 2014, and how did that affect the popular mind and its perception of these areas. The paper runs two main lines of inquiry; the first traces the phenomena through a chronological and geographical mapping of the informal urbanism has been portrayed in films. This analysis is based on an academic research work at Cairo University in Fall 2014. The visual tracing through maps and timelines allowed a reading of the phases of ignorance, presence, typifying and repetition in the representation of this huge sector of the city through more than 50 films that has been investigated. The analysis clearly revealed the “portrayed image” of informality by the Cinema through the examined period. However, the second part of the paper explores the “perceived image”. A designed questionnaire is applied to highlight the main features of that image that is perceived by both inhabitants of informalities and other Cairenes based on watching selected films. The questionnaire covers the different images of informalities proposed in the Cinema whether in a comic or a melodramatic background and highlight the descriptive terms used, to see which of them resonate with the mass perceptions and affected their mental images. The two images; “portrayed” and “perceived” are then to be encountered to reflect on issues of repetitions, stereotyping and reality. The formulated stereotype of informal urbanism is finally outlined and justified in relation to both production consumption mechanisms of films and the State official vision of informalities.

Keywords: cinema, informal urbanism, popular mind, representation

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Authors: T. M. Samuel, O. O. Aremu, I. O. Ismaila, L. I. Onu, B. O. Adetifa, S. E. Adegbite, O. O. Olokoshe

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The imperative of anthropometry in designing to fit cannot be overemphasized. Of essence is the variability of measurements among population for which data is collected. In this paper anthropometric data were collected for the design of gari-frying facility such that work system would be designed to fit the gari-frying population in the Southwestern states of Nigeria comprising Lagos, Ogun, Oyo, Osun, Ondo, and Ekiti. Twenty-seven body dimensions were measured among 120 gari-frying processors. Statistical analysis was performed using SPSS package to determine the mean, standard deviation, minimum value, maximum value and percentiles (2nd, 5th, 25th, 50th, 75th, 95th, and 98th) of the different anthropometric parameters. One sample t-test was conducted to determine the variation within the population. The 50th percentiles of some of the anthropometric parameters were compared with those from other populations in literature. The correlation between the worker’s age and the body anthropometry was also investigated.The mean weight, height, shoulder height (sitting), eye height (standing) and eye height (sitting) are 63.37 kg, 1.57 m, 0.55 m, 1.45 m, and 0.67 m respectively.Result also shows a high correlation with other populations and a statistically significant difference in variability of data within the population in all the body dimensions measured. With a mean age of 42.36 years, results shows that age will be a wrong indicator for estimating the anthropometry for the population.

Keywords: anthropometry, cassava processing, design to fit, gari-frying, workstation design

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Authors: Arunas Burinskas, Aurelija Burinskiene

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On average, ten percent of drugs - commercial products are not available in pharmacies due to shortage. The shortage event disbalance sales and requires a recovery period, which is too long. Therefore, one of the critical issues that pharmacies do not record potential sales transactions during shortage and recovery periods. The authors suggest estimating outliers during shortage and recovery periods. To shorten the recovery period, the authors suggest using average sales per sales day prediction, which helps to protect the data from being downwards or upwards. Authors use the outlier’s visualization method across different drugs and apply the Grubbs test for significance evaluation. The researched sample is 100 drugs in a one-month time frame. The authors detected that high demand variability products had outliers. Among analyzed drugs, which are commercial products i) High demand variability drugs have a one-week shortage period, and the probability of facing a shortage is equal to 69.23%. ii) Mid demand variability drugs have three days shortage period, and the likelihood to fall into deficit is equal to 34.62%. To avoid shortage events and minimize the recovery period, real data must be set up. Even though there are some outlier detection methods for drug data cleaning, they have not been used for the minimization of recovery period once a shortage has occurred. The authors use Grubbs’ test real-life data cleaning method for outliers’ adjustment. In the paper, the outliers’ adjustment method is applied with a confidence level of 99%. In practice, the Grubbs’ test was used to detect outliers for cancer drugs and reported positive results. The application of the Grubbs’ test is used to detect outliers which exceed boundaries of normal distribution. The result is a probability that indicates the core data of actual sales. The application of the outliers’ test method helps to represent the difference of the mean of the sample and the most extreme data considering the standard deviation. The test detects one outlier at a time with different probabilities from a data set with an assumed normal distribution. Based on approximation data, the authors constructed a framework for scaling potential sales and estimating outliers with Grubbs’ test method. The suggested framework is applicable during the shortage event and recovery periods. The proposed framework has practical value and could be used for the minimization of the recovery period required after the shortage of event occurrence.

Keywords: drugs, Grubbs' test, outlier, shortage event

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Authors: Nithipattara Balsiri

Abstract:

The purposes of this research was to develop instructional model by using research-based learning enhancing critical thinking, cognitive skills, and culture and local wisdom knowledge of undergraduate students. The sample consisted of 307 undergraduate students. Critical thinking and cognitive skills test were employed for data collection. Second-order confirmatory factor analysis, t-test, and one-way analysis of variance were employed for data analysis using SPSS and LISREL programs. The major research results were as follows; 1) the instructional model by using research-based learning enhancing critical thinking, cognitive skills, and culture and local wisdom knowledge should be consists of 6 sequential steps, namely (1) the setting research problem (2) the setting research hypothesis (3) the data collection (4) the data analysis (5) the research result conclusion (6) the application for problem solving, and 2) after the treatment undergraduate students possessed a higher scores in critical thinking and cognitive skills than before treatment at the 0.05 level of significance.

Keywords: critical thinking, cognitive skills, culture and local wisdom knowledge

Procedia PDF Downloads 357

Authors: H. Mahdavinezhad, M. Labbaf, H. R. Tavakoli

Abstract:

In recent decades, the study and control of the destructive effects of explosive vibration in construction projects has received more attention, and several experimental equations in the field of vibration prediction as well as allowable vibration limit for various structures are presented. Researchers have developed a number of experimental equations to estimate the peak particle velocity (PPV), in which the experimental constants must be obtained at the site of the explosion by fitting the data from experimental explosions. In this study, the most important of these equations was evaluated for strong massive conglomerates around Dez Dam by collecting data on explosions, including 30 particle velocities, 27 displacements, 27 vibration frequencies and 27 acceleration of earth vibration at different distances; they were recorded in the form of two types of detonation systems, NUNEL and electric. Analysis showed that the data from the explosion had the best correlation with the cube root of the explosive, R2=0.8636, but overall the correlation coefficients are not much different. To estimate the vibration in this project, data regression was performed in the other formats, which resulted in the presentation of new equation with R2=0.904 correlation coefficient. Finally according to the importance of the studied structures in order to ensure maximum non damage to adjacent structures for each diagram, a range of application was defined so that for distances 0 to 70 meters from blast site, exponent n=0.33 and for distances more than 70 m, n =0.66 was suggested.

Keywords: blasting, blast-induced vibration, empirical equations, PPV, tunnel

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Authors: Mwenya Mubanga, Sula Mazimba

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Background: In Zambia, much of the focus on nutrition and health has been on reducing micronutrient deficiencies, wasting and underweight malnutrition and not on the rising global projections of trends in obesity and type 2 diabetes. The aim of this review was to identify and collate studies on the prevalence of obesity, diabetes and diabetes-related cardiovascular disease conducted in Zambia, to summarize their findings and to identify areas that need further research. Methods: The Medical Literature Analysis and Retrieval System (MEDLINE) database was searched for peer-reviewed articles on the prevalence of, and factors associated with obesity, type 2 diabetes, and diabetes-related cardiovascular disease amongst Zambian residents using a combination of search terms. The period of search was from 1 January 2000 to 31 December 2016. We expanded the search terms to include all possible synonyms and spellings obtained in the search strategy. Additionally, we performed a manual search for other articles and references of peer-reviewed articles. Results: In Zambia, the current prevalence of Obesity and Type 2 diabetes is estimated at 13%-16% and 2.0 – 3.0% respectively. Risk factors such as the adoption of western dietary habits, the social stigmatization associated with rapid weight loss due to Tuberculosis and/ or the human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) and rapid urbanization have all been blamed for fueling the increased risk of obesity and type 2 diabetes. However, unlike traditional Western populations, those with no formal education were less likely to be obese than those who attained secondary or tertiary level education. Approximately 30% of those surveyed were unaware of their diabetes diagnosis and more than 60% were not on treatment despite a known diabetic status. Socio-demographic factors such as older age, female sex, urban dwelling, lack of tobacco use and marital status were associated with an increased risk of obesity, impaired glucose tolerance and type 2 diabetes. We were unable to identify studies that specifically looked at diabetes-related cardiovascular disease. Conclusion: Although the prevalence of Obesity and Type 2 diabetes in Zambia appears low, more representative studies focusing on parts of the country outside of the main industrial zone need to be conducted. There also needs to be research on diabetes-related cardiovascular disease. National surveillance, monitoring and evaluation on all non-communicable diseases need to be prioritized and policies that address underweight, obesity and type 2 diabetes developed.

Keywords: type 2 diabetes, Zambia, obesity, cardiovascular disease

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Authors: Dinmukhamed T., Vassiliy S.

Abstract:

This article suggests the idea of fitting clothes and accessories based on augmented reality. A logical data model has been developed, taking into account the decision-making module (colors, style, type, material, popularity, etc.) based on personal data (age, gender, weight, height, leg size, hoist length, geolocation, photogrammetry, number of purchases of certain types of clothing, etc.) and statistical data of the purchase history (number of items, price, size, color, style, etc.). Also, in order to provide information to the user, it is planned to develop an augmented reality system using a QR code. This system of selection and fitting of clothing and accessories based on augmented reality will be used in stores to reduce the time for the buyer to make a decision on the choice of clothes.

Keywords: augmented reality, online store, decision-making module, like QR code, clothing store, queue

Procedia PDF Downloads 151

Authors: Genady Grabarnik, Serge Yaskolko

Abstract:

Generative Artificial Intelligence (AI) has significantly expanded its applicability with the incorporation of Large Language Models (LLMs) and become a technology with promise to automate some areas that were very difficult to automate before. The paper describes the introduction of generative Artificial Intelligence into Introductory Computer and Data Science courses and analysis of effect of such introduction. The generative Artificial Intelligence is incorporated in the educational process two-fold: For the instructors, we create templates of prompts for generation of tasks, and grading of the students work, including feedback on the submitted assignments. For the students, we introduce them to basic prompt engineering, which in turn will be used for generation of test cases based on description of the problems, generating code snippets for the single block complexity programming, and partitioning into such blocks of an average size complexity programming. The above-mentioned classes are run using Large Language Models, and feedback from instructors and students and courses’ outcomes are collected. The analysis shows statistically significant positive effect and preference of both stakeholders.

Keywords: introductory computer and data science education, generative AI, large language models, application of LLMS to computer and data science education

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Authors: Yasuyuki Takahashi, Hirotaka Shimada, Takao Kanzaki

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A Dual-detector SPECT system is widely by use of myocardial SPECT studies. With 180-degree (180°) acquisition, reconstructed images are distorted in the posterior wall of myocardium due to the lack of sufficient data of posterior projection. We hypothesized that quality of myocardial SPECT images can be improved by the addition of data acquisition of only a few posterior projections to ordinary 180° acquisition. The proposed acquisition method (180° plus acquisition methods) uses the dual-detector SPECT system with a pair of detector arranged in 90° perpendicular. Sampling angle was 5°, and the acquisition range was 180° from 45° right anterior oblique to 45° left posterior oblique. After the acquisition of 180°, the detector moved to additional acquisition position of reverse side once for 2 projections, twice for 4 projections, or 3 times for 6 projections. Since these acquisition methods cannot be done in the present system, actual data acquisition was done by 360° with a sampling angle of 5°, and projection data corresponding to above acquisition position were extracted for reconstruction. We underwent the phantom studies and a clinical study. SPECT images were compared by profile curve analysis and also quantitatively by contrast ratio. The distortion was improved by 180° plus method. Profile curve analysis showed increased of cardiac cavity. Analysis with contrast ratio revealed that SPECT images of the phantoms and the clinical study were improved from 180° acquisition by the present methods. The difference in the contrast was not clearly recognized between 180° plus 2 projections, 180° plus 4 projections, and 180° plus 6 projections. 180° plus 2 projections method may be feasible for myocardial SPECT because distortion of the image and the contrast were improved.

Keywords: 180° plus acquisition method, a few posterior projections, dual-detector SPECT system, myocardial SPECT

Procedia PDF Downloads 285

Authors: Dermot O'Brien, Vasileios Christaras, Georgios Fontaras, Igor Nai Fovino, Ioannis Kounelis

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With the rise of the Internet of Things (IoT), 5G, and blockchain (BC) technologies, vehicles are becoming ever increasingly connected and are already transmitting substantial amounts of data to the original equipment manufacturers (OEMs) servers. This data could be used to help detect mileage fraud and enable more accurate vehicle emissions monitoring. This would not only help regulators but could enable applications such as permitting efficient drivers to pay less tax, geofencing for air quality improvement, as well as pollution tolling and trading platforms for transport-related businesses and EU citizens. Other applications could include traffic management and shared mobility systems. BC enables the transmission of data with additional security and removes single points of failure while maintaining data provenance, identity ownership, and the possibility to retain varying levels of privacy depending on the requirements of the applied use case. This research performs simulations of vehicles interacting with European member state authorities and European Commission BC nodes that are running hyperleger fabric and explores whether the technology is currently feasible for transport applications such as the emission monitoring use-case.

Keywords: future transportation systems, technological innovations, policy approaches for transportation future, economic and regulatory trends, blockchain

Procedia PDF Downloads 165

Authors: Santiago Macho, Miquel Montaner, Raivo Ruusalepp, Ferran Candela, Xavier Tarres, Rando Rostok

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During our lives, we generate a lot of personal information such as photos, music, text documents and videos that link us with our past. This data that used to be tangible is now digital information stored in our computers, which implies a software dependence to make them accessible in the future. Technology, however, constantly evolves and goes through regular shifts, quickly rendering various file formats obsolete. The need for accessing data in the future affects not only personal users but also organizations. In a digital environment, a reliable preservation plan and the ability to adapt to fast changing technology are essential for maintaining data collections in the long term. We present in this paper the European FP7 project called DURAFILE that provides the technology to preserve media files for personal users and organizations while maintaining their quality.

Keywords: artificial intelligence, digital preservation, social search, digital preservation plans

Procedia PDF Downloads 436