Search results for: Big Data Movement

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

Procedia PDF Downloads 341

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: 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: 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: Ran Etgar, Yuval Cohen, Erel Avineri

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One of the major challenges of transportation in medium sized inner-cities (such as Tel-Aviv) is the last-mile solution. Personal rapid transit (PRT) seems like an applicable candidate for this, as it combines the benefits of personal (car) travel with the operational benefits of transit. However, the investment required for large area PRT grid is significant and there is a need to economically justify such investment by correctly evaluating the grid capacity. PRT main elements are small automated vehicles (sometimes referred to as podcars) operating on a network of specially built guideways. The research is looking at a specific concept of elevated PRT system. Literature review has revealed the drawbacks PRT modelling and simulation approaches, mainly due to the lack of consideration of technical and operational features of the system (such as headways, acceleration, safety issues); the detailed design of infrastructure (guideways, stations, and docks); the stochastic and sessional characteristics of demand; and safety regulations – all of them have a strong effect on the system performance. A highly detailed model of the system, developed in this research, is applying a discrete event simulation combined with an agent-based approach, to represent the system elements and the podecars movement logic. Applying a case study approach, the simulation model is used to study the capacity of the system, the expected throughput of the system, the utilization, and the level of service (journey time, waiting time, etc.).

Keywords: capacity, productivity measurement, PRT, simulation, transportation

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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: Shoohira Aftab, Hammad Afzal

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Information integration is a well known procedure to provide consolidated view on sets of heterogeneous information sources. It not only provides better statistical analysis of information but also facilitates users to query without any knowledge on the underlying heterogeneous information sources The problem of providing a consolidated view of information can be handled using Semantic data (information stored in such a way that is understandable by machines and integrate-able without manual human intervention). However, integrating information using semantic web technology without any access management enforced, will results in increase of privacy and confidentiality concerns. In this research we have designed and developed a framework that would allow information from heterogeneous formats to be consolidated, thus resolving the issue of interoperability. We have also devised an access control system for defining explicit privacy constraints. We designed and applied our framework on both semantic and non-semantic data from heterogeneous resources. Our approach is validated using scenario based testing.

Keywords: information integration, semantic data, interoperability, security, access control system

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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: 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: Jocelyn Lachance, Francis Jauréguiberry

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In a few years, the exceptionality of the situation of an individual who could be reached at any time and at any time was replaced by the normality of instantly hearing the voice or immediately seeing the face of the person. This participates in the transformation of our representations of time and space, which gives rise to new expectations. Expectations that parents formulate more or less clearly to their children. The obligation to remain reachable seems to be asserting itself as a general norm which, having imposed itself on adults, now extends to the youngest. In the case of parents and their children, the rationale for this ongoing connection is not always based on actual and imminent dangers. It is the potential for dangerous events that underpins the indisputable argument for the importance of remaining reachable. It is the contingent nature of the risks that imposes itself on these young people as an argument of authority. By entering this connected world, the younger generations also end up adhering in many cases to this reassuring standard of connection. Many teenagers in ours researches nonetheless firmly believe that their freedom of movement is subject to the obligation to carry their smartphone with them. In this way, a connection "pact" is generally established, concluded under pressure, which implies first and foremost that contact be possible at any time, hence the importance of keeping it within reach, and often of '' be attentive to calls and texts sent by parents, at the risk of losing a recently acquired freedom. In this context, if adolescents are growing up in a connected world today, it is also because of the connection the parents are expecting from them. In our conference, by evoking situations reported by teenagers and parents of teenagers during our surveys, we propose to think about the role of the parents in making their child connected and about the desire of the disconnection of the teens.

Keywords: connection, disconnection, smartphone, parents, ritual

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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

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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

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Authors: Abubakar Muhammad Umar, Nur Adeela Yasid, Hassan Mohd Daud, Mohd Yunus Abd Shukor

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Glyphosate [N-(phosphonomethyl) glycine] is among the most broadly and generally recognized broad-spectrum herbicides used in agriculture due to its low cost and effectiveness in weed management. The pollution of glyphosate in the aquatic environment can be via water run-off from agricultural lands, or by spray drift, aerial spraying or due to industrial discharge, which may be seen as a threat to aquatic biota. Fish is one of the best organisms to study the toxicological aspects of glyphosate. A 49 days experiment was conducted under laboratory condition to ascertain the effects of technical grade glyphosate on behaviour and histopathological conditions in the gills of red hybrid tilapia using light inverted microscope. Air gasping, erratic swimming, fin movement, mucus secretion, hemorrhages and loss of scales were observed as behavioural changes in the exposed fish. There was no any histopathological complication observed in the gill of the control fish, but various level of alterations were seen in the gills of the fish exposed to glyphosate herbicide. These include lifting of primary lamella, congestion of secondary lamella as well as hyperplasia in both primary and secondary gill lamella and hypertrophy of secondary gill lamella. Based on the findings of this study, glyphosate herbicide exerts behavioural and histopathological changes in the gill of red hybrid tilapia, and therefore the fish is considered as good bioindicator in aquatic environment monitoring. Excessive usage of glyphosate herbicide near aquatic habitats should be discouraged.

Keywords: glyphosate, behavioral, histopathological, tilapia

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

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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: Amira, A. Goma, U. E. Mahrous

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Welfare may be considered to be a subjective experience; it has a biological function that is related to the fitness and survival of the animal accordingly, researches have suggested that welfare is compromised when the animal's evolutionary fitness is reduced. This study was carried out to explain the effect of some managerial stressors as handling and restraint on behavioral patterns and biochemical parameters of rats. A total of 24 (12 males and 12 females) Sprague-Dawley rats (12 months and 150-180g) were allotted into 3 groups, handled group (4 male and 4 female), restrained group (4 male and 4 female) and control group (4 males and 4 females). The obtained results revealed that time spent feeding, drinking frequency, movement and cage exploration increased significantly in handled rats than other groups, while lying time and licking increased significantly in restrained rats than handled and controls. Moreover, social behavior decreased in both stressed groups than control. Triglycerides were significantly increased in handled rats than other groups, while total lipid, total protein and globulin significantly increased in both treated groups than control. Corticosterone increased in restrained and handled rats than control ones. Moreover, there was an increment in packed cell volume significantly in restrained rats than others. These deducted that if we want to study the effect of stress on animal welfare it is necessary to study the effect of such stressors on animal’s behavior and physiological responses.

Keywords: handling, restraint, welfare, rat, behavior, physiology

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Authors: Dinmukhamed T., Vassiliy S.

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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

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Authors: Genady Grabarnik, Serge Yaskolko

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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

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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

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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

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Authors: Tigabu Dagne Akal

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While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

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Authors: Adie, Julius Undiukeye

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This research investigated the practice of academic leadership succession planning in Nigerian higher education institutions, drawing on the lived experiences of the academic staff of the case study institutions. It is multi-case study research that adopts a qualitative research method. Ten participants (mainly academic staff) were used as the study sample. The study was guided by four research questions. Semi-structured interviews and archival information from official documents formed the sources of data. The data collected was analyzed using the Constant Comparative Technique (CCT) to generate empirical insights and facts on the subject of this paper. The following findings emerged from the data analysis: firstly, there was no formalized leadership succession plan in place in the institutions that were sampled for this study; secondly, despite the absence of a formal succession plan, the data indicates that academics believe that succession planning is very significant for institutional survival; thirdly, existing practices of succession planning in the sampled institutions, takes the forms of job seniority ranking, political process and executive fiat, ad-hoc arrangement, and external hiring; and finally, data revealed that there are some barriers to the practice of succession planning, such as traditional higher education institutions’ characteristics (e.g. external talent search, shared governance, diversity, and equality in leadership appointment) and the lack of interest in leadership positions. Based on the research findings, some far-reaching recommendations were made, including the urgent need for the ‘formalization’ of leadership succession planning by the higher education institutions concerned, through the design of an official policy framework.

Keywords: academic leadership, succession, planning, higher education

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Authors: Yasmeen Bassas, Sandra Kuebler, Allen Riddell

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Native language identification is one of the growing subfields in natural language processing (NLP). The task of native language identification (NLI) is mainly concerned with predicting the native language of an author’s writing in a second language. In this paper, we investigate the performance of two types of features; content-based features vs. content independent features, when they are evaluated on a different corpus (using social media data “Reddit”). In this NLI task, the predefined models are trained on one corpus (TOEFL), and then the trained models are evaluated on different data using an external corpus (Reddit). Three classifiers are used in this task; the baseline, linear SVM, and logistic regression. Results show that content-based features are more accurate and robust than content independent ones when tested within the corpus and across corpus.

Keywords: NLI, NLP, content-based features, content independent features, social media corpus, ML

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Authors: B. Madhevan, R. Sakkaravarthi, R. Diya

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The number and variety of mobile robot applications are increasing day by day, both in an industry and in our daily lives. First developed as a tool, nowadays mobile robots can be integrated as an entity in Internet-accessible resources. The present work is organized around four potential resources such as cloud computing, Internet of things, Big data analysis and Co-simulation. Further, the focus relies on integrating, analyzing and discussing the need for integrating Internet-accessible resources and the challenges deriving from such integration, and how these issues have been tackled. Hence, the research work investigates the concepts of the Internet-accessible resources from the aspect of the autonomous mobile robots with an overview of the performances of the currently available database systems. IaR is a world-wide network of interconnected objects, can be considered an evolutionary process in mobile robots. IaR constitutes an integral part of future Internet with data analysis, consisting of both physical and virtual things.

Keywords: internet-accessible resources, cloud computing, big data analysis, internet of things, mobile robot

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Authors: Mitsuhiro Hirai, Satoshi Ajito, Nobutaka Shimizu, Noriyuki Igarashi, Hiroki Iwase, Shinichi Takata

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Sugars and polyols are known to be bioprotectants preventing such as protein denaturation and enzyme deactivation and widely used as a nontoxic additive in various industrial and medical products. The mechanism of their protective actions has been explained by specific bindings between biological components and additives, changes in solvent viscosities, and surface tension and free energy changes upon transfer of those components into additive solutions. On the other hand, some organisms having tolerances against extreme environment produce stress proteins and/or accumulate sugars in cells, which is called cryptobiosis. In particular, trehalose has been drawing attention relevant to cryptobiosis under external stress such as high or low temperature, drying, osmotic pressure, and so on. The function of cryptobiosis by trehalose has been explained relevant to the restriction of the intra-and/or-inter-molecular movement by vitrification or from the replacement of water molecule by trehalose. Previous results suggest that the structure and interaction between sugar and water are a key determinant for understanding cryptobiosis. Recently, we have shown direct evidence that the protein hydration (solvation) and structural stability against chemical and thermal denaturation significantly depend on sugar species and glycerol. Sugar and glycerol molecules tend to be preferentially or weakly excluded from the protein surface and preserved the native protein hydration shell. Due to the protective action of the protein hydration shell by those molecules, the protein structure is stabilized against chemical (guanidinium chloride) and thermal denaturation. The protective action depends on sugar species. To understand the above trend and difference in detail, it is essentially important to clarify the characteristics of solutions containing those additives. In this study, by using wide-angle X-ray scattering technique covering a wide spatial region (~3-120 Å), we have clarified structures of sugar solutions with the concentration from 5% w/w to 65% w/w. The sugars measured in the present study were monosaccharides (glucose, fructose, mannose) and disaccharides (sucrose, trehalose, maltose). Due to observed scattering data with a wide spatial resolution, we have succeeded in obtaining information on the internal structure of individual sugar molecules and on the correlation between them. Every sugar gradually shortened the average inter-molecular distance as the concentration increased. The inter-molecular interaction between sugar molecules was essentially showed an exclusive tendency for every sugar, which appeared as the presence of a repulsive correlation hole. This trend was more weakly seen for trehalose compared to other sugars. The intermolecular distance and spread of individual molecule clearly showed the dependence of sugar species. We will discuss the relation between the characteristic of sugar solution and its protective action of biological materials.

Keywords: hydration, protein, sugar, X-ray scattering

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Authors: Nur Aishah Binti Awi, Zulfiqar Khan

Abstract:

Lean-kaizen has always been applied in manufacturing sector since many years ago. What about education sector? This paper discuss on how lean-kaizen can also be applied in education sector, specifically in academic area of Malaysian’s higher education sector. The purpose of this paper is to describe the application of lean kaizen in course plan and delivery. Lean-kaizen techniques have been used to identify waste in the course plan and delivery. A field study has been conducted to obtain the data. This study used both quantitative and qualitative data. The researcher had interviewed the chosen lecturers regarding to the problems of course plan and delivery that they encountered. Secondary data of students’ feedback at the end of semester also has been used to improve course plan and delivery. The result empirically shows that lean-kaizen helps to improve the course plan and delivery by reducing the wastes. Thus, this study demonstrates that lean-kaizen can also help education sector to improve their services as achieved by manufacturing sector.

Keywords: course delivery, education, Kaizen, lean

Procedia PDF Downloads 356

Authors: Shivani Verma, Amit Agrawal, Pankaj Kumar Meena, Ashish B. Deoghare

Abstract:

Over the decade robotics has been a major area of interest among the researchers and scientists in reducing human efforts. The need for robots to replace human work in different dangerous fields such as underground mining, nuclear power station and war against terrorist attack has gained huge attention. Most of the robot design is based on human structure popularly known as humanoid robots. However, the problems encountered in humanoid robots includes low speed of movement, misbalancing in structure, poor load carrying capacity, etc. The simplification and adaptation of the fundamental design principles seen in animals have led to the creation of bio-inspired robots. But the major challenges observed in naturally inspired robot include complexity in structure, several degrees of freedom and energy storage problem. The present work focuses on design and fabrication of a bionic quadruped walking robot which is based on different joint of quadruped mammals like a dog, cheetah, etc. The design focuses on the structure of the robot body which consists of four legs having three degrees of freedom per leg and the electronics system involved in it. The robot is built using readily available plastics and metals. The proposed robot is simple in construction and is able to move through uneven terrain, detect and locate obstacles and take images while carrying additional loads which may include hardware and sensors. The robot will find possible application in the artificial intelligence sector.

Keywords: artificial intelligence, bionic, quadruped robot, degree of freedom

Procedia PDF Downloads 201