Search results for: field data

Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

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Authors: Harshit Mittal, Neeraj Garg

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Hand symbol recognition is a pivotal component in the domain of computer vision, with far-reaching applications spanning sign language interpretation, human-computer interaction, and accessibility. This research paper discusses the approach with the integration of the Canny Edge algorithm and convolutional neural network. The significance of this study lies in its potential to enhance communication and accessibility for individuals with hearing impairments or those engaged in gesture-based interactions with technology. In the experiment mentioned, the data is manually collected by the authors from the webcam using Python codes, to increase the dataset augmentation, is applied to original images, which makes the model more compatible and advanced. Further, the dataset of about 6000 coloured images distributed equally in 5 classes (i.e., 1, 2, 3, 4, 5) are pre-processed first to gray images and then by the Canny Edge algorithm with threshold 1 and 2 as 150 each. After successful data building, this data is trained on the Convolutional Neural Network model, giving accuracy: 0.97834, precision: 0.97841, recall: 0.9783, and F1 score: 0.97832. For user purposes, a block of codes is built in Python to enable a window for hand symbol recognition. This research, at its core, seeks to advance the field of computer vision by providing an advanced perspective on hand sign recognition. By leveraging the capabilities of the Canny Edge algorithm and convolutional neural network, this study contributes to the ongoing efforts to create more accurate, efficient, and accessible solutions for individuals with diverse communication needs.

Keywords: hand symbol recognition, computer vision, Canny edge algorithm, convolutional neural network

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Authors: Roaa Sait, Richard Cross

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The synthesis and characterization of one dimensional nanostructure such as nanowires has received considerable attention. Much effort has concentrated on TiN material especially in the biological field due to its useful and unique properties in this field. Therefore, for the purpose of this project, synthesis of Titanium Nitride (TiN) nanowires (NWs) will be presented. They will be synthesised by growing titanium dioxide (Ti) NWs in an aqueous solution at low temperatures under atmospheric pressure. Then the grown nanowires will undergo a 'Nitrodation process' in which results in the formation of TiN NWs. The structure, morphology and composition of the grown nanowires will be characterized using Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), X-ray Diffraction (XRD) and Cyclic Voltammetry (CV). Obtaining TiN NWs is a challenging task since it has not been formulated before, as far as we acknowledge. This might be due to the fact that nitriding Ti NWs can be difficult in terms of optimizing experimental parameters.

Keywords: nanowires, dissolution-growth, nucleation, PECVD, deposition, spin coating, scanning electron microscopic analysis, cyclic voltammetry analysis

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Authors: Sook Ching Yee, Angela Siew Hoong Lee

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Big data technologies have become a trend to exploit business opportunities and provide valuable business insights through the analysis of big data. However, there are still many organizations that have yet to adopt big data technologies especially small and medium organizations (SME). This study uses the technology acceptance model (TAM) to look into several constructs in the TAM and other additional constructs which are positive affect, negative affect, organizational factor and motivational factor. The conceptual model proposed in the study will be tested on the relationship and influence of positive affect, negative affect, organizational factor and motivational factor towards the intention to use big data technologies to produce an outcome. Empirical research is used in this study by conducting a survey to collect data.

Keywords: big data technologies, motivational factor, negative affect, organizational factor, positive affect, technology acceptance model (TAM)

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Authors: Farnoosh Faal

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The rapid growth of social media has brought significant changes to the field of urban e-planning. This study aims to review the existing literature on the impact of social media on urban e-planning processes. The study begins with a discussion of the evolution of social media and its role in urban e-planning. The review covers research on the use of social media for public engagement, citizen participation, stakeholder communication, decision-making, and monitoring and evaluation of urban e-planning initiatives. The findings suggest that social media has the potential to enhance public participation and improve decision-making in urban e-planning processes. Social media platforms such as Facebook, Twitter, and Instagram can provide a platform for citizens to engage with planners and policymakers, express their opinions, and provide feedback on planning proposals. Social media can also facilitate the collection and analysis of data, including real-time data, to inform urban e-planning decision-making. However, the literature also highlights some challenges associated with the use of social media in urban e-planning. These challenges include issues related to the representativeness of social media users, the quality of information obtained from social media, the potential for bias and manipulation of social media content, and the need for effective data management and analysis. The study concludes with recommendations for future research on the use of social media in urban e-planning. The recommendations include the need for further research on the impact of social media on equity and social justice in planning processes, the need for more research on effective strategies for engaging underrepresented groups, and the development of guidelines for the use of social media in urban e-planning processes. Overall, the study suggests that social media has the potential to transform urban e-planning processes but that careful consideration of the opportunities and challenges associated with its use is essential for effective and ethical planning practice.

Keywords: social media, Urban e-planning, public participation, citizen engagement

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Authors: Byung Ho Jung, Ji Eun Shin, Dong Hoon Lim

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Rhipe that integrates R and Hadoop environment made it possible to process and analyze massive amounts of data using a distributed processing environment. In this paper, we implemented multiple regression analysis using Rhipe with various data sizes of actual data. Experimental results for comparing the performance of our Rhipe with stats and biglm packages available on bigmemory, showed that our Rhipe was more fast than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases. We also compared the computing speeds of pseudo-distributed and fully-distributed modes for configuring Hadoop cluster. The results showed that fully-distributed mode was faster than pseudo-distributed mode, and computing speeds of fully-distributed mode were faster as the number of data nodes increases.

Keywords: big data, Hadoop, Parallel regression analysis, R, Rhipe

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Authors: M. Chojak

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Recently, more and more scientific disciplines refer to research in the field of neurobiology. Interdisciplinary research procedures are created using modern methods of brain imaging. Neither did the pedagogues start looking for neuronal conditions for various processes. The publications began to show concepts such as ‘neuropedagogy’, ‘neuroeducation’, ‘neurodidactics’, ‘brain-friendly education’. They were and are still used interchangeably. In the offer of training for teachers, the topics of multiple intelligences or educational kinesiology began to be more and more popular. These and other ideas have been actively introduced into the curricula. To our best knowledge, the literature on the subject lacks articles organizing the new nomenclature and indicating the methodological framework for research that would confirm the effectiveness of the above-mentioned innovations. The author of this article tries to find the place for neuropedagogy in the system of sciences, define its subject of research, methodological framework and basic concepts. This is necessary to plan studies that will verify the so-called neuromyths.

Keywords: brain, education, neuropedagogy, research

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Authors: Mona Almansoori, Ahmed Mustafa, Ahmad Elshamy

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Wireless sensor network was formed by a combination of nodes, systematically it transmitting the data to their base stations, this transmission data can be easily compromised if the limited processing power and the data consistency from these nodes are kept in mind; there is always a discussion to address the secure data transfer or transmission in actual time. This will present a mechanism to securely transmit the data over a chain of sensor nodes without compromising the throughput of the network by utilizing available battery resources available in the sensor node. Our methodology takes many different advantages of Z-MAC protocol for its efficiency, and it provides a unique key by sharing the mechanism using neighbor node MAC address. We present a light weighted data integrity layer which is embedded in the Z-MAC protocol to prove that our protocol performs well than Z-MAC when we introduce the different attack scenarios.

Keywords: hybrid MAC protocol, data integrity, lightweight encryption, neighbor based key sharing, sensor node dataprocessing, Z-MAC

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Authors: Suparwoko, M. Hardyan Prastyanto, Aisah Azhari Marwangi

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Today, we face with some paradoxical tendencies. In the field of culture, on the one hand, we are witnessing the emergence of ethnic and religious fervor that is becoming stronger, but on the other hand, we are also witnessing a new ideology that characterized the flow of transnationalism, globalism, and secularism. Through social media, the globalization movement is accommodated to spread all over the world. Globalization also requires the commercialization of many fields, including architecture. In the architecture of commercial buildings, the appeal of the building is an important aspect for the function of the building. That theory is the basis for research of this study. This study aimed to know the influence of social media on the changing trends in the design of restaurant in urban areas of Yogyakarta Province. This study is using observation (survey) method to restaurants in Yogyakarta and surrounding areas to collect data, then the assessment of data by using the theory of the social media Path and Instagram that provide trend information from interior and building facades of the restaurant. By using social media Path and Instagram based survey methods, it can be seen that the intensity of social media users who publish or promote restaurant that has been chosen. Generally, conventional character of the restaurant have changed into a material and visually conceptual restaurant.

Keywords: influence, social media, changes, architecture trend

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Authors: Ijaz Ahmed Khan, Zaheen Ullah, Rahamdad, Gul Hassan

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A field experiment was conducted at Agricultural Research Station Ahmad Wala, Karak, Khyber Pakhtunkhwa Province during rabi season of 2010-011 to study the effect of different weed management practices on weed control in chickpea under field conditions. The results revealed that treatments showed significant influence on weed density, seed yield kg ha-1 and other growth parameters. Significantly lower weed density (98 m-2) was recorded with the application of Isoproturon 500 EW as compared to control plots having 368.3 weeds m-2. Moreover, significantly highest seed yield (1583.3 kg ha-1) was produced in the plots assigned with Isoproturon 500 EW followed by Eucalyptus extract that produce seed yield of 1416.7 kg ha-1. It was concluded from the study that Isoproturon 500 EW is the best option for controlling weeds and increase the seed yield kg ha-1 of chickpea.

Keywords: chickpea, herbicides, weed control, weeds extracts

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Authors: G. Saxena, M. Kaushik

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In the present investigation, we have employed RMF+BCS (relativistic mean-field plus BCS) approach to carry out a systematic study for the ground state properties of the entire chains of even-even neutron magic nuclei represented by isotones of traditional neutron magic numbers N = 8, 20, 40, 50, 82, and 126. The main body of the results of our calculations includes the binding energy, deformation, two proton separation energies, rms radii of the proton and neutron distributions as well as the proton and neutron density profiles etc. Several of these results have been given in the form of a series of graphs for a ready reference. In addition, the possible locations of the proton and neutron drip-lines as well as the (Z,N) values for the shell closures as suggested by the detailed analyzes of the single particle spectra, and the two proton and two-neutron separation energies for the different isotonic chains are also discussed in detail.

Keywords: relativistic mean field theory, neutron magic nuclei, shell closure, separation energy, deformation

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Authors: Madaki Umar Yusuf, Mohd Rizam B. Abubakar

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The survival censored data with incomplete covariate data is a common occurrence in many studies in which the outcome is survival time. With model when the missing covariates are categorical, a useful technique for obtaining parameter estimates is the EM by the method of weights. The survival outcome for the class of generalized linear model is applied and this method requires the estimation of the parameters of the distribution of the covariates. In this paper, we propose some clinical trials with ve covariates, four of which have some missing values which clearly show that they were fully censored data.

Keywords: EM algorithm, incomplete categorical covariates, ignorable missing data, missing at random (MAR), Weibull Distribution

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Authors: Zeinab Gharibi, B. Stoevesandt, J. Peinke

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Long term surface erosion of wind turbine blades, especially at the leading edge, impairs aerodynamic performance; therefore, lowers efficiency of the blades mostly in the high-speed rotor tip regions. Blade protection provides significant improvements in annual energy production, reduces costly downtime, and protects the integrity of the blades. However, this protection still influences the aerodynamic behavior, and broadband noise caused by interaction between the impinging turbulence and blade’s leading edge. This paper presents an extensive numerical aeroacoustics approach by investigating the sound power spectra of the eroded and coated NACA 64-618 wind turbine airfoil and evaluates aeroacoustics improvements after the protection procedure. Using computational fluid dynamics (CFD), different quasi 2D numerical grids were implemented and special attention was paid to the refinement of the boundary layers. The noise sources were captured and decoupled with acoustic propagation via the derived formulation of Curle’s analogy implemented in OpenFOAM. Therefore, the noise spectra were compared for clean, coated and eroded profiles in the range of chord-based Reynolds number (1.6e6 ≤ Re ≤ 11.5e6). Angle of attack was zero in all cases. Verifications were conducted for the clean profile using available experimental data. Sensitivity studies for the far-field were done on different observational positions. Furthermore, beamforming studies were done simulating an Archimedean spiral microphone array for far-field noise directivity patterns. Comparing the noise spectra of the coated and eroded geometries, results show that, coating clearly improves aerodynamic and acoustic performance of the eroded airfoil.

Keywords: computational fluid dynamics, computational aeroacoustics, leading edge, OpenFOAM

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Authors: Dana Christensen

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Undergraduate students, particularly in the environmental sciences, have difficulty displaying quantitative skills in their laboratory courses. Students spend time sampling in the field, often using new methods, and are expected to make sense of the data they collect. Computational thinking may be used to navigate these new experiences. We developed a curriculum for the marine science department at a small liberal arts college in the Northeastern United States based on previous computational thinking frameworks. This curriculum incorporates marine science data sets with specific objectives and topics selected by the faculty at the College. The curriculum was distributed to all students enrolled in introductory marine science classes as a mandatory module. Two pre-tests and post-tests will be used to quantitatively assess student progress on both content-based and computational principles. Student artifacts are being collected with each lesson to be coded for content-specific and computational-specific items in qualitative assessment. There is an overall gap in marine science education research, especially curricula that focus on computational thinking and associated quantitative assessment. The curricula itself, the assessments, and our results may be modified and applied to other environmental science courses due to the nature of the inquiry-based laboratory components that use quantitative skills to understand nature.

Keywords: marine science, computational thinking, curriculum assessment, quantitative skills

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Authors: Hooman Fallah

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Seawater injection and produced water re-injection are presently the most commonly used approach to enhanced recovery. The dominant factors for total oil recovery are the reservoir temperature, reservoir pressure, crude oil and water composition. In this study, the production under water injection in Soroosh, one of the southern Iranian heavy oil field has been simulated (the fluid properties are focused). In order to reveal the dominant factors in this production process, the sensitivity analysis has been done for the following effective factors, fluid viscosity, initial water saturation, gravity force and injection well strategy. It is crystal clear that the study of the dominant factors in production processes will help the engineers to design the best production mechanisms in our numerous hydrocarbon reservoirs.

Keywords: water injection, initial water saturation, oil viscosity, gravity force, injection well strategy

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Authors: Abdeljalil Beniiche

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The limitation with smart contracts is that they cannot access external data that might be required to control the execution of business logic. Oracles can be used to provide external data to smart contracts. An oracle is an interface that delivers data from external data outside the blockchain to a smart contract to consume. Oracle can deliver different types of data depending on the industry and requirements. In this paper, we study and describe the widely used blockchain oracles. Then, we elaborate on his potential role, technical architecture, and design patterns. Finally, we discuss the human oracle and its key role in solving the truth problem by reaching a consensus about a certain inquiry and tasks.

Keywords: blockchain, oracles, oracles design, human oracles

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Authors: Majid Al-Busafi, Alexe Cristina Ioana, Alexe Dan Iulian

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The specific competition and pre-competition stress in professional track and field determined an increasing engagement, from a biological and psychological point of view, of the middle distance and long distance runners, to obtain the top performances that would get them to win in a competition. Under these conditions, if the psychological stress is not properly managed, the negative effects can lead to a total drop in self-confidence, and can affect the value, the talent, and the self-trust, which generates an even higher stress. One of the means at our disposal is the psychological training, specially adapted to the athlete's individual characteristics, to the characteristics of the athletic event, or of the competition. This paper aims to highlight certain original aspects regarding the effects of a specific psychological training program on the mood states characterized by psychological activation, vigor, vitality. The subjects were represented by 12 professional middle distance and long distance runners, subjected to an applicative intervention to which they have participated voluntarily, over the course of 6 months (a competition season). The results indicated that The application of a psychological training program, adapted to the track and field competition system, over a period of time characterized by high competition stress, can determine an increase in the states of vigor and psychological activation, at the same time diminishing those moods that have negative effects on the performance, in the middle distance and long distance running events. This conclusion confirms the hypothesis of this research.

Keywords: competition stress, psychological training, track and field, vigor-activity

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Authors: Tomas Vincze, Michal Micjan, Milan Pavuk, Martin Weis

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In recent years, alternative materials are gaining attention to replace polycrystalline and amorphous silicon, which are a standard for low requirement devices, where silicon is unnecessarily and high cost. For that reason, metal oxides are envisioned as the new materials for these low-requirement applications such as sensors, solar cells, energy storage devices, or field-effect transistors. Their most common way of layer growth is sputtering; however, this is a high-cost fabrication method, and a more industry-suitable alternative is the sol-gel method. In this group of materials, many oxides exhibit a semiconductor-like behavior with sufficiently high mobility to be applied as transistors. The sol-gel method is a cost-effective deposition technique for semiconductor-based devices. Copper oxides, as p-type semiconductors with free charge mobility up to 1 cm2/Vs., are suitable replacements for poly-Si or a-Si:H devices. However, to reach the potential of silicon devices, a fine-tuning of material properties is needed. Here we focus on the optimization of the electrical parameters of copper oxide-based field-effect transistors by modification of precursor solvent (usually 2-methoxy ethanol). However, to achieve solubility and high-quality films, a better solvent is required. Since almost no solvents have both high dielectric constant and high boiling point, an alternative approach was proposed with blend solvents. By mixing isopropyl alcohol (IPA) and 2-methoxy ethanol (2ME) the precursor reached better solubility. The quality of the layers fabricated using mixed solutions was evaluated in accordance with the surface morphology and electrical properties. The IPA:2ME solution mixture reached optimum results for the weight ratio of 1:3. The cupric oxide layers for optimal mixture had the highest crystallinity and highest effective charge mobility.

Keywords: copper oxide, field-effect transistor, semiconductor, sol-gel method

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Authors: Rehab Abdullah Shendi

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The use of customised soft-core processors in which instructions can be integrated into a system in application hardware is increasing in the Field Programmable Gate Array (FPGA) field. Specifically, the partial run-time reconfiguration of FPGAs in specialised processors for a particular domain can be very beneficial. In this report, the design and implementation for the customisation of a soft-core MIPS processor using an FPGA and partial reconfiguration (PR) of FPGA technology will be addressed to achieve efficient resource use. This can be achieved using a PR design flow that helps the design fit into a smaller device. Moreover, the impact of static power consumption could be reduced due to runtime reconfiguration. This will be done by configurable custom instructions implemented in the hardware as an extension on the MIPS CPU. The aim of this project is to investigate the PR of FPGAs for run-time adaptations of the instruction set of a soft-core CPU, including the integration of custom instructions and the exploration of the potential to use the MultiBoot feature available in Xilinx FPGAs to carry out the PR process. The system will be evaluated and tested on a Nexus 3 development board featuring a Xilinx Spartran-6 FPGA. The system will be able to load reconfigurable custom instructions dynamically into user programs with the help of the trap handler when the custom instruction is called by the MIPS CPU. The results of this experiment demonstrate that custom instructions in hardware can speed up a certain function and many instructions can be saved when compared to a software implementation of the same function. Implementing custom instructions in hardware is perfectly possible and worth exploring.

Keywords: customisation, FPGA, MIPS, partial reconfiguration, PR

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Authors: Pallab Bhattacharya, C. K. Das

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Development of microwave absorbing material is a growing field of research in both the commercial and defense sector, and also to enrich the field of stealth technology. The recent work is attentive to the preparation of nanocomposite based on acid modified MWCNT, hexagonal shaped magnetic M-type hexaferrite (CuFe10Al2O19) and polyaniline. CuFe10Al2O19 was prepared by a facile chemical co-precipitation method. An in-situ approach was employed for the coating of polyaniline on MWCNT/CuFe10Al2O19 nanocomposite. The final fabrication of this nanocomposite for microwave measurements was done suitably in the matrix of thermoplastic polyurethane with 10% filler content. The nanocomposites showed the maximum reflection loss of -60.2 dB (in X-band) at the thickness of 2.5 mm with a broad absorption range in contrast to the pristine MWCNT and CuFe10Al2O19. Addition of PANI improves the microwave absorption property of the nanocomposites. The thermal stability of the prepared nanocomposites is also very high.

Keywords: magnetic materials, microwave absorption, MWCNT, nanocomposites

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Authors: Hitham Yami

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This study will focus primarily on assessing the availability requirements of the electronic management of oil companies in Libya, and the mean objectives of the research applying electronic management and make recommendations and steps to approach electronic management. There are limited research and statistical analysis to support electronic management in Libyan companies. The groundwork for the proposed approach is to develop independent variables and the dependent variables to be restructured after it Alntra side of the field and the side to get the data to achieve the desired results and solving the problem faced by the Libyan Oil Corporation. All these strategies are proposed to achieve the goal, and solving Libyan oil installations.

Keywords: oil company’s revenue, independent variables, electronic management, Libyan oil corporation

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Authors: Mirza Mujtaba Baig

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Artificial Intelligence (AI) is evolving rapidly, and one of the areas in which this field has influenced is automation. The automobile, healthcare, education, and robotic industries deploy AI technologies constantly, and the automation of tasks is beneficial to allow time for knowledge-based tasks and also introduce convenience to everyday human endeavors. The paper reviews the challenges faced with the current implementations of autonomous self-driving cars by exploring the machine learning, robotics, and artificial intelligence techniques employed for the development of this innovation. The controversy surrounding the development and deployment of autonomous machines, e.g., vehicles, begs the need for the exploration of the configuration of the programming modules. This paper seeks to add to the body of knowledge of research assisting researchers in decreasing the inconsistencies in current programming modules. Blockchain is a technology of which applications are mostly found within the domains of financial, pharmaceutical, manufacturing, and artificial intelligence. The registering of events in a secured manner as well as applying external algorithms required for the data analytics are especially helpful for integrating, adapting, maintaining, and extending to new domains, especially predictive analytics applications.

Keywords: artificial intelligence, automation, big data, self-driving cars, machine learning, neural networking algorithm, blockchain, business intelligence

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Authors: Carlos Gonzales, Zaida Quiroz, Marcos Prates

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Several spatial variables collected at the same location that share a common spatial distribution can be modeled simultaneously through a multivariate geostatistical model that takes into account the correlation between these variables and the spatial autocorrelation. The main goal of this model is to perform spatial prediction of these variables in the region of study. Here we focus on a geostatistical multivariate formulation that relies on sharing common spatial random effect terms. In particular, the first response variable can be modeled by a mean that incorporates a shared random spatial effect, while the other response variables depend on this shared spatial term, in addition to specific random spatial effects. Each spatial random effect is defined through a Gaussian process with a valid covariance function, but in order to improve the computational efficiency when the data are large, each Gaussian process is approximated to a Gaussian random Markov field (GRMF), specifically to the block nearest neighbor Gaussian process (Block-NNGP). This approach involves dividing the spatial domain into several dependent blocks under certain constraints, where the cross blocks allow capturing the spatial dependence on a large scale, while each individual block captures the spatial dependence on a smaller scale. The multivariate geostatistical model belongs to the class of Latent Gaussian Models; thus, to achieve fast Bayesian inference, it is used the integrated nested Laplace approximation (INLA) method. The good performance of the proposed model is shown through simulations and applications for massive data.

Keywords: Block-NNGP, geostatistics, gaussian process, GRMF, INLA, multivariate models.

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Authors: Harish Bisht, Bahadur Singh Kotlia, Kireet Kumar

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In order to reconstruct past retreating rates, total area loss, volume change and shift in snout position were measured through multi-temporal satellite data from 1989 to 2016 and kinematic GPS survey from 2015 to 2016. The results obtained from satellite data indicate that in the last 27 years, Chaturangi glacier snout has retreated 1172.57 ± 38.3 m (average 45.07 ± 4.31 m/year) with a total area and volume loss of 0.626 ± 0.001 sq. Km and 0.139 Km³, respectively. The field measurements through differential global positioning system survey revealed that the annual retreating rate was 22.84 ± 0.05 m/year. The large variations in results derived from both the methods are probably because of higher difference in their accuracy. Snout monitoring of the Gangotri glacier during the ablation season (May to September) in the years 2005 and 2015 reveals that the retreating rate has been comparatively more declined than that shown by the earlier studies. The GPS dataset shows that the average recession rate is 10.26 ± 0.05 m/year. In order to determine the possible causes of decreased retreating rate, a relationship between debris thickness and melt rate was also established by using ablation stakes. The present study concludes that remote sensing method is suitable for large area and long term study, while kinematic GPS is more appropriate for the annual monitoring of retreating rate of glacier snout. The present study also emphasizes on mapping of all the tributary glaciers in order to assess the overall changes in the main glacier system and its health.

Keywords: Chaturangi glacier, Gangotri glacier, glacier snout, kinematic global positioning system, retreat rate

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Authors: Alhadi Bustaman, Soeganda Formalidin, Titin Siswantining

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DNA microarray technology is used to analyze thousand gene expression data simultaneously and a very important task for drug development and test, function annotation, and cancer diagnosis. Various clustering methods have been used for analyzing gene expression data. However, when analyzing very large and heterogeneous collections of gene expression data, conventional clustering methods often cannot produce a satisfactory solution. Biclustering algorithm has been used as an alternative approach to identifying structures from gene expression data. In this paper, we introduce a transform technique based on singular value decomposition to identify normalized matrix of gene expression data followed by Mixed-Clustering algorithm and the Lift algorithm, inspired in the node-deletion and node-addition phases proposed by Cheng and Church based on Agglomerative Hierarchical Clustering (AHC). Experimental study on standard datasets demonstrated the effectiveness of the algorithm in gene expression data.

Keywords: agglomerative hierarchical clustering (AHC), biclustering, gene expression data, lymphoma, singular value decomposition (SVD)

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Authors: Ramya P, Lino Abraham Varghese, S. Bose

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By cloud storage services, the data can be stored in the cloud, and can be shared across multiple users. Due to the unexpected hardware/software failures and human errors, which make the data stored in the cloud be lost or corrupted easily it affected the integrity of data in cloud. Some mechanisms have been designed to allow both data owners and public verifiers to efficiently audit cloud data integrity without retrieving the entire data from the cloud server. But public auditing on the integrity of shared data with the existing mechanisms will unavoidably reveal confidential information such as identity of the person, to public verifiers. Here a privacy-preserving mechanism is proposed to support public auditing on shared data stored in the cloud. It uses group signatures to compute verification metadata needed to audit the correctness of shared data. The identity of the signer on each block in shared data is kept confidential from public verifiers, who are easily verifying shared data integrity without retrieving the entire file. But on demand, the signer of the each block is reveal to the owner alone. Group private key is generated once by the owner in the static group, where as in the dynamic group, the group private key is change when the users revoke from the group. When the users leave from the group the already signed blocks are resigned by cloud service provider instead of owner is efficiently handled by efficient proxy re-signature scheme.

Keywords: data integrity, dynamic group, group signature, public auditing

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Authors: M. Moody, R. Mahmoodi, A. R. Zolfaghari, A. Aminottojari

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In this study, flow inside the shell side of a shell-and-tube heat exchanger is simulated numerically for laminar and turbulent flows in both steady state and transient mode. Governing equations of fluid flow are discrete using finite volume method and central difference scheme and solved with simple algorithm which is staggered grid by using MATLAB programming language. The heat transfer coefficient is obtained using velocity field from equation Dittus-Bolter. In comparison with, heat exchanger is simulated with ANSYS CFX software and experimental data measured in the THTL test loop. Numerical results obtained from the study show good agreement with experimental data and ANSYS CFX results. In addition, by deliberation the effect of the baffle spacing and the baffle cut on the heat transfer rate for turbulent flow, it is illustrated that the heat transfer rate depends on the baffle spacing and the baffle cut directly. In other word in spied of large turbulence, if these two parameters are not selected properly in the heat exchanger, the heat transfer rate can reduce.

Keywords: shell-and-tube heat exchanger, flow and heat transfer, laminar and turbulence flow, turbulence model, baffle spacing, baffle cut

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Authors: Pholosho M. Kgopa, Phatu W. Mashela

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Due to high incidents of marginal land in Limpopo Province, South Africa, and increasing demand for arable land, small-holder farmers tend to continuously cultivate the same fields and at the same time, applying fertilisers to improve yields for meeting local food security. These practices might have an impact on the distribution of trace and essential elements. Therefore, the objective of this investigation was to assess the distribution of essential elements and trace metals in a continuously cultivated and fertilised field, at the University of Limpopo Experimental Farm. Three fields, 3 ha each were identified as continuously cultivated (CC), moderately cultivated (MC) and virgin fields (VF). Each field was divided into 12 equal grids of 50 m × 50 m for sampling. A soil profile was opened in each grid, where soil samples were collected from 0-20; 20-40 and 40-60; 60-80 and 80-100 cm depths for analysis. Samples were analysed for soil texture, pH, electrical conductivity, organic matter content, selected essential elements (Ca, P and Mg), Na and trace elements (Cu, Fe, Ni, and Zn). Results suggested that most of the variables were vertically different, with high concentrations of the test elements except for magnesium. Soil pH in depth 0-20 cm was high (6.44) in CC when compared to that in VF (5.29), but lower than that of MC (7.84). There were no distinctive vertical trends of the variables, except for Mg, Na, and K which displayed a declining trend at 40-60 cm depth when compared to the 0-20 cm depth. Concentrations of Fe, Cu, Zn, and Ni were generally low which might be due to their indirect relationship with soil pH. Continuous cultivation and fertilisation altered soil chemical properties; which could explain the unproductivity of such fields.

Keywords: over-cultivation, soil chemical properties, vertical distribution, spatial distribution

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Authors: Nathainail Bashir, Neil Anderson

Abstract:

The objective of this study site was to investigate the current state of the practice with regards to karst detection methods and recommend the best method and pattern of arrays to acquire the desire results. Proper site investigation in karst prone regions is extremely valuable in determining the location of possible voids. Two geophysical techniques were employed: multichannel analysis of surface waves (MASW) and electric resistivity tomography (ERT).The MASW data was acquired at each test location using different array lengths and different array orientations (to increase the probability of getting interpretable data in karst terrain). The ERT data were acquired using a dipole-dipole array consisting of 168 electrodes. The MASW data was interpreted (re: estimated depth to physical top of rock) and used to constrain and verify the interpretation of the ERT data. The ERT data indicates poorer quality MASW data were acquired in areas where there was significant local variation in the depth to top of rock.

Keywords: dipole-dipole, ERT, Karst terrains, MASW

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Authors: H. W. Meerveld, R. H. A. Lindelauf

Abstract:

In contemporary warfare, data science is crucial for the military in achieving information superiority. Yet, to the authors’ knowledge, no extensive literature survey on data science in military decision-making has been conducted so far. In this study, 156 peer-reviewed articles were analysed through an integrative, semi-systematic literature review to gain an overview of the topic. The study examined to what extent literature is focussed on the opportunities or risks of data science in military decision-making, differentiated per level of war (i.e. strategic, operational, and tactical level). A relatively large focus on the risks of data science was observed in social science literature, implying that political and military policymakers are disproportionally influenced by a pessimistic view on the application of data science in the military domain. The perceived risks of data science are, however, hardly addressed in formal science literature. This means that the concerns on the military application of data science are not addressed to the audience that can actually develop and enhance data science models and algorithms. Cross-disciplinary research on both the opportunities and risks of military data science can address the observed research gaps. Considering the levels of war, relatively low attention for the operational level compared to the other two levels was observed, suggesting a research gap with reference to military operational data science. Opportunities for military data science mostly arise at the tactical level. On the contrary, studies examining strategic issues mostly emphasise the risks of military data science. Consequently, domain-specific requirements for military strategic data science applications are hardly expressed. Lacking such applications may ultimately lead to a suboptimal strategic decision in today’s warfare.

Keywords: data science, decision-making, information superiority, literature review, military

Procedia PDF Downloads 156