Search results for: generating sets

Authors: Ladznar S. Laja, Rosalio G. Artes, Jr.

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This paper introduced a graph polynomial relating convexity concepts. A graph polynomial is a polynomial representing a graph given some parameters. On the other hand, a subgraph H of a graph G is said to be convex in G if for every pair of vertices in H, every shortest path with these end-vertices lies entirely in H. We define the convex subgraph polynomial of a graph G to be the generating function of the sequence of the numbers of convex subgraphs of G of cardinalities ranging from zero to the order of G. This graph polynomial is monic since G itself is convex. The convex index which counts the number of convex subgraphs of G of all orders is just the evaluation of this polynomial at 1. Relationships relating algebraic properties of convex subgraphs polynomial with graph theoretic concepts are established.

Keywords: convex subgraph, convex index, generating function, polynomial ring

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Authors: Shumaila Ehtisham

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In Statistical Distribution Theory, considering an additional parameter to classical distributions is a usual practice. In this study, a new distribution referred to as α-Power Pareto distribution is introduced by including an extra parameter. Several properties of the proposed distribution including explicit expressions for the moment generating function, mode, quantiles, entropies and order statistics are obtained. Unknown parameters have been estimated by using maximum likelihood estimation technique. Two real datasets have been considered to examine the usefulness of the proposed distribution. It has been observed that α-Power Pareto distribution outperforms while compared to different variants of Pareto distribution on the basis of model selection criteria.

Keywords: α-power transformation, maximum likelihood estimation, moment generating function, Pareto distribution

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Authors: Dae-Hee Son, Soon-Ryul Nam

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The power system frequency falls when disturbance such as rapid increase of system load or loss of a generating unit occurs in power systems. Especially, increase in the number of renewable generating units has a bad influence on the power system because of loss of generating unit depending on the circumstance. Conventional technologies use frequency droop control battery output for the frequency regulation and balance between supply and demand. If power is supplied using the fast output characteristic of the battery, power system stability can be further more improved. To improve the power system stability, we propose battery output control using ROCOF (Rate of Change of Frequency) in this paper. The bigger the power difference between the supply and the demand, the bigger the ROCOF drops. Battery output is controlled proportionally to the magnitude of the ROCOF, allowing for faster response to power imbalances. To simulate the control method of battery output system, we develop the user defined model using PSS/E and confirm that power system stability is improved by comparing with frequency droop control.

Keywords: PSS/E user defined model, power deviation, frequency droop control, ROCOF (rate of change of frequency)

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Authors: Shaleni Bajpai, V. Niveditha

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A fashion accessory is a product which used to give secondary way to the wearer’s outfit. The term came into use in the 19th century and was specifically chosen to complement the wearer’s look. The aim of project was to introduce the unconventional materials for statement jewellery. The materials used for statement jewellery were waste Cd’s, and scrap fabric. These materials were amalgamated with the traditional raw materials such as beads, sequins, charms and chains to form unique jewellery sets. The sets were divided into two categories based on the type of raw material used i.e. Category 1: Clef-Cd Jewellery, Category 2: Crumb-Fabric Jewellery. Each Jewellery set consisted of a necklace, a pair of earrings, a ring and a bracelet.

Keywords: statement jewellery, unconventional, crumb fabric, Cd’s

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Authors: Analen Malnegro, Gina Malacas

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Dominating sets and related topics have been studied extensively in the past few decades. A dominating set of a graph G is a subset D of V such that every vertex not in D is adjacent to at least one member of D. The domination number γ(G) is the number of vertices in a smallest dominating set for G. Some problems involving detection devices can be modeled with graphs. Finding the minimum number of devices needed according to the type of devices and the necessity of locating the object gives rise to locating-dominating sets. A subset S of vertices of a graph G is called locating-dominating set, LD-set for short, if it is a dominating set and if every vertex v not in S is uniquely determined by the set of neighbors of v belonging to S. The location-domination number λ(G) is the minimum cardinality of an LD-set for G. The complement of a graph G is a graph Ḡ on same vertices such that two distinct vertices of Ḡ are adjacent if and only if they are not adjacent in G. An LD-set of a graph G is global if it is an LD-set of both G and its complement Ḡ. The global location-domination number λg(G) is defined as the minimum cardinality of a global LD-set of G. In this paper, global LD-sets on the join of two graphs are characterized. Global location-domination numbers of these graphs are also determined.

Keywords: dominating set, global locating-dominating set, global location-domination number, locating-dominating set, location-domination number

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Authors: Shaharuddin Salleh, Sara Marouf, Hosein Mohammadi

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Directional sensor networks (DSNs) have recently attracted a great deal of attention due to their extensive applications in a wide range of situations. One of the most important problems associated with DSNs is covering a set of targets in a given area and, at the same time, maximizing the network lifetime. This is due to limitation in sensing angle and battery power of the directional sensors. This problem gets more complicated by the possibility that targets may have different coverage requirements. In the present study, this problem is referred to as priority-based target coverage (PTC). As sensors are often densely deployed, organizing the sensors into several cover sets and then activating these cover sets successively is a promising solution to this problem. In this paper, we propose a learning automata-based algorithm to organize the directional sensors into several cover sets in such a way that each cover set could satisfy coverage requirements of all the targets. Several experiments are conducted to evaluate the performance of the proposed algorithm. The results demonstrated that the algorithms were able to contribute to solving the problem.

Keywords: directional sensor networks, target coverage problem, cover set formation, learning automata

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Authors: Chalakorn Chitsaart, Suchada Rianmora, Mann Rattana-Areeyagon, Wutichai Namjaiprasert

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G-code is the main factor in computer numerical control (CNC) machine for controlling the tool-paths and generating the profile of the object’s features. For obtaining high surface accuracy of the surface finish, non-stop operation is required for CNC machine. Recently, to design a new product, the strategy that concerns about a change that has low impact on business and does not consume lot of resources has been introduced. Cost and time for designing minor changes can be reduced since the traditional geometric details of the existing models are applied. In order to support this strategy as the alternative channel for machining operation, this research proposes the automatic generating codes for CNC milling operation. Using this technique can assist the manufacturer to easily change the size and the geometric shape of the product during the operation where the time spent for setting up or processing the machine are reduced. The algorithm implemented on MATLAB platform is developed by analyzing and evaluating the geometric information of the part. Codes are created rapidly to control the operations of the machine. Comparing to the codes obtained from CAM, this developed algorithm can shortly generate and simulate the cutting profile of the part.

Keywords: geometric shapes, milling operation, minor changes, CNC Machine, G-code, cutting parameters

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Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

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Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

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Authors: Yaeji Lim, Hee-Seok Oh

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The coherence analysis measures the linear time-invariant relationship between two data sets and has been studied various fields such as signal processing, engineering, and medical science. However classical coherence analysis tends to be sensitive to outliers and focuses only on mean relationship. In this paper, we generalized cross periodogram to quantile cross periodogram and provide richer inter-relationship between two data sets. This is a general version of Laplace cross periodogram. We prove its asymptotic distribution under the long range process and compare them with ordinary coherence through numerical examples. We also present real data example to confirm the usefulness of quantile coherence analysis.

Keywords: coherence, cross periodogram, spectrum, quantile

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Authors: Ali M. Alakeel

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Assertion-based software testing has been shown to be a promising tool for generating test cases that reveal program faults. Because the number of assertions may be very large for industry-size programs, one of the main concerns to the applicability of assertion-based testing is the amount of search time required to explore a large number of assertions. This paper presents a new approach for assertions exploration during the process of Assertion-Based software testing. Our initial exterminations with the proposed approach show that the performance of Assertion-Based testing may be improved, therefore, making this approach more efficient when applied on programs with large number of assertions.

Keywords: software testing, assertion-based testing, program assertions, generating test

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Authors: P. K. Rahul Krishna, S. Sandeep Kumar, Jayanthi Sunder Raj

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The article explores one of the important relations between numbers-the Pythagorean triples (triplets) which finds its application in distance measurement, construction of roads, towers, buildings and wherever Pythagoras theorem finds its application. The Pythagorean triples are numbers, that satisfy the condition “In a given set of three natural numbers, the sum of squares of two natural numbers is equal to the square of the other natural number”. There are numerous methods and equations to obtain the triplets, which have their own merits and demerits. Here, quadratic approach for generating triples uses the hypotenuse leg difference method. The advantage is that variables are few and finally only three independent variables are present.

Keywords: arithmetic progression, hypotenuse leg difference method, natural numbers, Pythagorean triplets, quadratic equation

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Authors: M. Tiachachat, M. Mihoubi

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The Bell polynomials are special polynomials in combinatorial analysis that have a wide range of applications in mathematics. They have interested many authors. The exponential partial Bell polynomials have been well reduced to some special combinatorial sequences. Numerous researchers had already been interested in the above polynomials, as evidenced by many articles in the literature. Inspired by this work, in this work, we propose a family of special polynomials named after the 2-successive partial Bell polynomials. Using the combinatorial approach, we prove the properties of these numbers, derive several identities, and discuss some special cases. This family includes well-known numbers and polynomials such as Stirling numbers, Bell numbers and polynomials, and so on. We investigate their properties by employing generating functions

Keywords: 2-associated r-Stirling numbers, the exponential partial Bell polynomials, generating function, combinatorial interpretation

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Authors: Maryam Kamali Nezhad

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The Robert-Bourassa development (LG-2), the first to be built on the Grande Rivière, comprises two sets of eight turbines- generator units each, the East and West powerhouses. Each powerhouse has two tailrace tunnels with an average length of about 1178 m. The LG-2A powerhouse houses 6 turbine-generator units. The water is discharged through two tailrace tunnels with a length of about 1330 m. The objective of this work, at RB (LG-2), is; 1) to establish a new maximum transient level in the surge chamber, 2) to define the new maximum equipment flow rate for the future turbine-generator units, 3) to ensure safe access to various intervention locations in the surge chamber. The transient levels under normal operating conditions at the RB plant were determined in 2001 by the Hydraulics Unit of HQE using the "Chamber" software. It is a one-dimensional mass oscillation calculation software; it is used to determine the variation of the water level in the equilibrium chamber located downstream of a power plant during the load shedding of the power plant units; it can also be used in the case of an equilibrium stack upstream of a power plant. The RB (LG-2) plant study is based on the theoretical nominal geometry of the chamber and the tailrace tunnels and the flow-level relationship at the outlet of the galleries established during design. The software is used in such a way that the results have an acceptable margin of safety, especially with respect to the maximum transient level (e.g., resumption of flow at an inopportune time), to take into account the turbulent and three-dimensional aspects of the actual flow in the chamber. Note that the transient levels depend on the water levels in the river and in the steady-state equilibrium chambers. These data are established in the HQP CRP database and updated from time to time. The maximum transient levels in the RB-East and RB-West powerhouses surge chamber were revised based on the latest update (set 4) of in-river rating curves and steady-state surge chamber water levels. The results of the revision were also used to update the technical advice on the operating conditions for the aforementioned surge chamber access while considering revisions to the calculated water levels.

Keywords: generating station, surge chamber, maximum transient level, hydroelectric power station, turbine-generator, reservoir

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Authors: Xiuqin Ma, Hongwu Qin

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A new efficient normal parameter reduction algorithm of soft set in decision making was proposed. However, up to the present, few documents have focused on real-life applications of this algorithm. Accordingly, we apply a New Efficient Normal Parameter Reduction algorithm into real-life datasets of online shopping, such as Blackberry Mobile Phone Dataset. Experimental results show that this algorithm is not only suitable but feasible for dealing with the online shopping.

Keywords: soft sets, parameter reduction, normal parameter reduction, online shopping

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Authors: Mohammed F. Alhaddad

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Vortex induced Vibrations (VIV) is a phenomenon that occurs as a result of a flow passing by a bluff body. This phenomenon has been mainly studied to be suppressed to prevent fatigue and instability in offshore platforms. In 2006, some studies were conducted to maximize VIV instead of suppressing it, as these studies claimed that VIV is a potential method of generating energy. The aim of this paper is to identify factors for maximizing oscillation amplitude generated by VIV in order to enhance the energy harnessed through this method. The experimental study in this paper will examine the effect of oscillating cylinder diameter, surface roughness, the location of surface roughness with respect to the centerline of the oscillating cylinder and the velocity on the oscillation amplitude of the used module.

Keywords: energy, generation, generating, vibration, vortex.

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Authors: Mackenzie Leake, Liyu Xia, Kamil Rocki, Wayne Imaino

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In the Hierarchical Temporal Memory (HTM) paradigm the effect of overlap between inputs on the activation of columns in the spatial pooler is studied. Numerical results suggest that similar inputs are represented by similar sets of columns and dissimilar inputs are represented by dissimilar sets of columns. It is shown that the spatial pooler produces these results under certain conditions for the connectivity and proximal thresholds. Following the discussion of the initialization of parameters for the thresholds, corresponding qualitative arguments about the learning dynamics of the spatial pooler are discussed.

Keywords: hierarchical temporal memory, HTM, learning algorithms, machine learning, spatial pooler

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Authors: Ntungamili Kenosi, Moatlhodi W. Letshwenyo

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Negative environmental impacts due to construction of large projects such as dams have become an important aspect of land degradation. This paper will review the previous literature on the previous researches or study in the same area of study in the other parts of the world. After dam has been constructed, the actual environmental impacts are investigated and compared to the predicted results of the carried out Environmental Impact Assessment. GIS and Remote Sensing, play an important role in generating automated spatial data sets and in establishing spatial relationships. Results from other sources shows that the normalized vegetation index (NDVI) analysis was used to detect the spatial and temporal change of vegetation biomass in the study area. The result indicated that the natural vegetation biomass is declining. This is mainly due to the expansion of agricultural land and escalating human made structures in the area. Urgent environmental conservation is necessary when adjoining projects site. Less study on the evaluation of EIA on dam has been conducted in Botswana hence there is a need for the same study to be conducted and then it will be easy to be compared to other studies around the world.

Keywords: Botswana, dam, environmental impact assessment, GIS, normalized vegetation index (NDVI), remote sensing

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Authors: Wisu Suntoyo, Dedy Sushandoyo

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Innovation and digital transformation are essential for firms’ competitiveness in the digital age. The competition in Indonesia’s banking industry provides an intriguing case study for understanding how digital transformation can generate innovation in established companies. The empirical evidence of this study is mainly based on interviews and annual reports examining four established banks in their various states of digital transformation. The findings of this study reveal that banks’ digital transformations that lead to innovations differ in terms of the activities undertaken and the outcomes achieved depending on the state of advancement in which they are. Digital transformation is a complex and challenging process, and this study finds that with this strategy, established banks have shown capable of generating innovation. Banks can choose types of transformation activities that generate radical, architectural, modular, or even incremental innovations.

Keywords: digital transformation, innovations, banking industry, established banks

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Authors: Minh-Thuan Nguyen, Phuong-Thai Nguyen, Van-Vinh Nguyen, Quang-Minh Nguyen

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Research on automatically generating descriptions for e-commerce products is gaining increasing attention in recent years. However, the generated descriptions of their systems are often less informative and attractive because of lacking training datasets or the limitation of these approaches, which often use templates or statistical methods. In this paper, we explore a method to generate production descriptions by using the GPT-2 model. In addition, we apply text paraphrasing and task-adaptive pretraining techniques to improve the qualify of descriptions generated from the GPT-2 model. Experiment results show that our models outperform the baseline model through automatic evaluation and human evaluation. Especially, our methods achieve a promising result not only on the seen test set but also in the unseen test set.

Keywords: GPT-2, product description, transformer, task-adaptive, language model, pretraining

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Authors: Marilei Amadeu Sabino

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The aim of this study is to establish differences between the terms ‘false cognates’, ‘false friends’ and ‘deceptive cognates’, usually considered to be synonyms. It will be shown they are not synonyms, since they do not designate the same linguistic process or phenomenon. Despite their differences in meaning, many pairs of formally similar words in two (or more) different languages are true cognates, although they are usually known as ‘false’ cognates – such as, for instance, the English and Italian lexical items ‘assist x assistere’; ‘attend x attendere’; ‘argument x argomento’; ‘apology x apologia’; ‘camera x camera’; ‘cucumber x cocomero’; ‘fabric x fabbrica’; ‘factory x fattoria’; ‘firm x firma’; ‘journal x giornale’; ‘library x libreria’; ‘magazine x magazzino’; ‘parent x parente’; ‘preservative x preservativo’; ‘pretend x pretendere’; ‘vacancy x vacanza’, to name but a few examples. Thus, one of the theoretical objectives of this paper is firstly to elaborate definitions establishing a distinction between the words that are definitely ‘false cognates’ (derived from different etyma) and those that are just ‘deceptive cognates’ (derived from the same etymon). Secondly, based on Set Theory and on the concepts of equal sets, subsets, intersection of sets and disjoint sets, this study is intended to elaborate some theoretical and practical questions that will be useful in identifying more precisely similarities and differences between cognate words of different languages, and according to graphic interpretation of sets it will be possible to classify them and provide discernment about the processes of semantic changes. Therefore, these issues might be helpful not only to the Learning of Second and Foreign Languages, but they could also give insights into Foreign and Second Language Teaching Methodology. Acknowledgements: FAPESP – São Paulo State Research Support Foundation – the financial support offered (proc. n° 2017/02064-7).

Keywords: deceptive cognates, false cognates, foreign language learning, teaching methodology

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Authors: Jay L. Fu

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Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

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Authors: Ahmed Elaksher, Islam Omar

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For many years, Mars surface has been a mystery for scientists. Lately with the help of geospatial data and photogrammetric procedures researchers were able to capture some insights about this planet. Two of the most imperative data sources to explore Mars are the The High Resolution Imaging Science Experiment (HiRISE) and the Mars Orbiter Laser Altimeter (MOLA). HiRISE is one of six science instruments carried by the Mars Reconnaissance Orbiter, launched August 12, 2005, and managed by NASA. The MOLA sensor is a laser altimeter carried by the Mars Global Surveyor (MGS) and launched on November 7, 1996. In this project, we used MOLA-based DEMs to orthorectify HiRISE optical images for generating a more accurate and trustful surface of Mars. The MOLA data was interpolated using the kriging interpolation technique. Corresponding tie points were digitized from both datasets. These points were employed in co-registering both datasets using GIS analysis tools. In this project, we employed three different 3D to 2D transformation models. These are the parallel projection (3D affine) transformation model; the extended parallel projection transformation model; the Direct Linear Transformation (DLT) model. A set of tie-points was digitized from both datasets. These points were split into two sets: Ground Control Points (GCPs), used to evaluate the transformation parameters using least squares adjustment techniques, and check points (ChkPs) to evaluate the computed transformation parameters. Results were evaluated using the RMSEs between the precise horizontal coordinates of the digitized check points and those estimated through the transformation models using the computed transformation parameters. For each set of GCPs, three different configurations of GCPs and check points were tested, and average RMSEs are reported. It was found that for the 2D transformation models, average RMSEs were in the range of five meters. Increasing the number of GCPs from six to ten points improve the accuracy of the results with about two and half meters. Further increasing the number of GCPs didn’t improve the results significantly. Using the 3D to 2D transformation parameters provided three to two meters accuracy. Best results were reported using the DLT transformation model. However, increasing the number of GCPS didn’t have substantial effect. The results support the use of the DLT model as it provides the required accuracy for ASPRS large scale mapping standards. However, well distributed sets of GCPs is a key to provide such accuracy. The model is simple to apply and doesn’t need substantial computations.

Keywords: mars, photogrammetry, MOLA, HiRISE

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Authors: Dayane de Almeida

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This work aims at presenting a study that demonstrates the usability of categories of analysis from Discourse Semiotics – also known as Greimassian Semiotics in authorship cases in forensic contexts. It is necessary to know if the categories examined in semiotic analysis (the ‘grammar’ of the content plane) can distinguish authors. Thus, a study with 4 sets of texts from a corpus of ‘not on demand’ written samples (those texts differ in formality degree, purpose, addressees, themes, etc.) was performed. Each author contributed with 20 texts, separated into 2 groups of 10 (Author1A, Author1B, and so on). The hypothesis was that texts from a single author were semiotically more similar to each other than texts from different authors. The assumptions and issues that led to this idea are as follows: -The features analyzed in authorship studies mostly relate to the expression plane: they are manifested on the ‘surface’ of texts. If language is both expression and content, content would also have to be considered for more accurate results. Style is present in both planes. -Semiotics postulates the content plane is structured in a ‘grammar’ that underlies expression, and that presents different levels of abstraction. This ‘grammar’ would be a style marker. -Sociolinguistics demonstrates intra-speaker variation: an individual employs different linguistic uses in different situations. Then, how to determine if someone is the author of several texts, distinct in nature (as it is the case in most forensic sets), when it is known intra-speaker variation is dependent on so many factors?-The idea is that the more abstract the level in the content plane, the lower the intra-speaker variation, because there will be a greater chance for the author to choose the same thing. If two authors recurrently chose the same options, differently from one another, it means each one’s option has discriminatory power. -Size is another issue for various attribution methods. Since most texts in real forensic settings are short, methods relying only on the expression plane tend to fail. The analysis of the content plane as proposed by greimassian semiotics would be less size-dependable. -The semiotic analysis was performed using the software Corpus Tool, generating tags to allow the counting of data. Then, similarities and differences were quantitatively measured, through the application of the Jaccard coefficient (a statistical measure that compares the similarities and differences between samples). The results showed the hypothesis was confirmed and, hence, the grammatical categories of the content plane may successfully be used in questioned authorship scenarios.

Keywords: authorship attribution, content plane, forensic linguistics, greimassian semiotics, intraspeaker variation, style

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Authors: S. Ghammamy, M. Mirzaabdollahiha

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Quantum mechanical calculations of energies, geometries, and vibrational wavenumbers of fluorous 1,3-dion compounds are carried out using density functional theory (DFT/B3LYP) method with LANL2DZ basis sets. The calculated HOMO and LUMO energies show that charge transfer occurs in the molecules. The thermodynamic functions of fluorous 1,3-dion compounds have been performed at B3LYP/LANL2DZ basis sets. The theoretical spectrograms for F NMR spectra of fluorous 1,3-dion compounds have also been constructed. The F NMR nuclear shieldings of fluoride ligands in fluorous 1,3-dion compounds have been studied quantum chemical.

Keywords: density function theory, natural bond orbital, HOMO, LOMO, fluorous

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Authors: Prozorkevitch D., Mishurov A., Sokolov K., Karsakov L., Pestrikova L.

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The current body of knowledge about the marine environment and the dynamics of marine ecosystems includes a huge amount of heterogeneous data collected over decades. It generally includes a wide range of hydrological, biological and fishery data. Marine researchers collect these data and analyze how and why the ecosystem changes from past to present. Based on these historical records and linkages between the processes it is possible to predict future changes. Multivariate analysis of trends and their interconnection in the marine ecosystem may be used as an instrument for predicting further ecosystem evolution. A wide range of information about the components of the marine ecosystem for more than 50 years needs to be used to investigate how these arrays can help to predict the future.

Keywords: barents sea ecosystem, abiotic, biotic, data sets, trends, prediction

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Authors: Shamila Manie, Soraya Maart, Ayesha Osman

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Introduction: People diagnosed with multidrug resistant pulmonary tuberculosis (MDR-PTB) is subjected to prolonged hospitalization in South Africa. It has thus become essential for research to shift its focus from a purely medical approach, but to include social and environmental factors when looking at the impact of the disease on those affected. Aim: To explore the factors affecting individuals with multi-drug resistant pulmonary tuberculosis during long-term hospitalization using the comprehensive ICF core-sets for obstructive pulmonary disease (OPD) and cardiopulmonary (CPR) conditions at Brooklyn Chest Hospital (BCH). Methods: A quantitative descriptive, cross-sectional study design was utilized. A convenient sample of 19 adults at Brooklyn Chest Hospital were interviewed. Results: Most participants reported a decrease in exercise tolerance levels (b455: n=11). However it did not limit participation. Participants reported that a lack of privacy in the environment (e155) was a barrier to health. The presence of health professionals (e355) and the provision of skills development services (e585) are facilitators to health and well-being. No differences exist in the functional ability of HIV positive and negative participants in this sample. Conclusion: The ICF Core Sets appeared valid in identifying the barriers and facilitators experienced by individuals with MDR-PTB admitted to BCH. The hospital environment must be improved to add to the QoL of those admitted, especially improving privacy within the wards. Although the social grant is seen as a facilitator, greater emphasis must be placed on preparing individuals to be economically active in the labour for when they are discharged.

Keywords: multidrug resistant tuberculosis, MDR ICF core sets, health-related quality of life (HRQoL), hospitalization

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Authors: Ridwan Kiay Demak, Firmansyahrullah, Muchammad Sibro Mulis, Eko Tri Wasisto, Nixon Poltak Frederic, Agung Putu Andika, Lapo Ajis Kamamu, Muhammad Sobirin, Kornelius Eppang

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PC Prove LSM successfully improved the efficiency of Own Used Fuel Gas with the "Lotion" method in the PT Pertamina EP Cepu Donggi Matindok Generating System. The innovation of using the "LOTION" (LOAD PRIORITY SELECTION) method in the generating system is modeling that can provide a priority qualification of main and non-main equipment to keep gas processing running even though it leaves 1 GTG operating. GTG operating system has been integrated, controlled, and monitored properly through PC programs and web-based access to answer Industry 4.0 problems. The results of these improvements have succeeded in making Donggi Matindok Field Production reach 98.77 MMSCFD and become a proper EMAS candidate in 2022-2023. Additional revenue from increasing the efficiency of the use of own used gas amounting to USD USD 5.06 Million per year and reducing operational costs from maintenance efficiency (ABO) due to saving running hours GTG amounted to USD 3.26 Million per year. Continuity of fuel gas availability for the GTG generation system can maintain the operational reliability of the plant, which is 3.833333 MMSCFD. And reduced gas emissions wasted to the environment by 33,810 tons of C02 eq per year.

Keywords: LOTION method, load priority selection, fuel gas efficiency, gas turbine generator, reduce emissions

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Authors: Hashem Dehghanniri

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Crime scripting is a simple and effective crime modeling technique that aims to improve understanding of security analysts about security and crime incidents. Low-quality scripts provide a wrong, incomplete, or sophisticated understanding of the crime commission process, which oppose the purpose of their application, e.g., identifying effective and cost-efficient situational crime prevention (SCP) measures. One important and overlooked factor in generating quality scripts is the crime scripting method. This study investigates the problems within the existing crime scripting practices and proposes a crime scripting approach that contributes to generating quality crime scripts. It was validated by experienced crime scripters. This framework helps analysts develop better crime scripts and contributes to their effective application, e.g., SCP measures identification or policy-making.

Keywords: attack modelling, crime commission process, crime script, situational crime prevention

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Authors: Pavel H. Llamocca, Victoria Lopez

Abstract:

The main objective of our work is the comparative analysis of environmental data from Open Data bases, belonging to different governments. This means that you have to integrate data from various different sources. Nowadays, many governments have the intention of publishing thousands of data sets for people and organizations to use them. In this way, the quantity of applications based on Open Data is increasing. However each government has its own procedures to publish its data, and it causes a variety of formats of data sets because there are no international standards to specify the formats of the data sets from Open Data bases. Due to this variety of formats, we must build a data integration process that is able to put together all kind of formats. There are some software tools developed in order to give support to the integration process, e.g. Data Tamer, Data Wrangler. The problem with these tools is that they need data scientist interaction to take part in the integration process as a final step. In our case we don’t want to depend on a data scientist, because environmental data are usually similar and these processes can be automated by programming. The main idea of our tool is to build Hadoop procedures adapted to data sources per each government in order to achieve an automated integration. Our work focus in environment data like temperature, energy consumption, air quality, solar radiation, speeds of wind, etc. Since 2 years, the government of Madrid is publishing its Open Data bases relative to environment indicators in real time. In the same way, other governments have published Open Data sets relative to the environment (like Andalucia or Bilbao). But all of those data sets have different formats and our solution is able to integrate all of them, furthermore it allows the user to make and visualize some analysis over the real-time data. Once the integration task is done, all the data from any government has the same format and the analysis process can be initiated in a computational better way. So the tool presented in this work has two goals: 1. Integration process; and 2. Graphic and analytic interface. As a first approach, the integration process was developed using Java and Oracle and the graphic and analytic interface with Java (jsp). However, in order to open our software tool, as second approach, we also developed an implementation with R language as mature open source technology. R is a really powerful open source programming language that allows us to process and analyze a huge amount of data with high performance. There are also some R libraries for the building of a graphic interface like shiny. A performance comparison between both implementations was made and no significant differences were found. In addition, our work provides with an Official Real-Time Integrated Data Set about Environment Data in Spain to any developer in order that they can build their own applications.

Keywords: open data, R language, data integration, environmental data

Procedia PDF Downloads 301

Authors: Abbas Kamalibandpey, Alain Beland, Joseph Mukendi Kabuya

Abstract:

Since a rock mass is a discontinuum medium, its behaviour is governed by discontinuities such as faults, joint sets, lithologic contact, and bedding planes. Thus, rock slope stability analysis in jointed rock masses is largely dependent upon discontinuities constitutive equations. This paper studies the difference between the Mohr-Coulomb (MC) and the Barton-Bandis (BB) joint constitutive numerical models for lithological contacts and joint sets. For the rock in these models, generalized Hoek-Brown criteria have been considered. The joint roughness coefficient (JRC) and the joint wall compressive strength (JCS) are vital parameters in the BB model. The numerical models are applied to the rock slope stability analysis in the Mont-Wright (MW) mine. The Mont-Wright mine is owned and operated by ArcelorMittal Mining Canada (AMMC), one of the largest iron-ore open pit operations in Canada. In this regard, one of the high walls of the mine has been selected to undergo slope stability analysis with RS2D software, finite element method. Three piezometers have been installed in this zone to record pore water pressure and it is monitored by radar. In this zone, the AMP-IF and QRMS-IF contacts and very persistent and altered joint sets in IF control the rock slope behaviour. The height of the slope is more than 250 m and consists of different lithologies such as AMP, IF, GN, QRMS, and QR. To apply the B-B model, the joint sets and geological contacts have been scanned by Maptek, and their JRC has been calculated by different methods. The numerical studies reveal that the JRC of geological contacts, AMP-IF and QRMS-IF, and joint sets in IF had a significant influence on the safety factor. After evaluating the results of rock slope stability analysis and the radar data, the B-B constitutive equation for discontinuities has shown acceptable results to the real condition in the mine. It should be noted that the difference in safety factors in MC and BB joint constitutive models in some cases is more than 30%.

Keywords: barton-Bandis criterion, Hoek-brown and Mohr-Coulomb criteria, open pit, slope stability

Procedia PDF Downloads 87