Search results for: binary logistic

Authors: Mengmeng Xiao

Abstract:

The study examines the proactive promotion of feminist agendas by states experiencing prolonged one-party dominance, with a specific focus on Japan. Through a case study approach, it explores why leaders of the dominant party, the Liberal Democratic Party (LDP), actively endorse women-friendly initiatives. The findings reveal three primary motivations: 1) the adoption of women-friendly policies for legitimation, 2) the establishment or funding of women’s organizations for co-optation, and 3) the enhancement of women’s economic and employment rights for state-building purposes. These findings bridge theories across the democracy/autocracy spectrum, emphasizing the need to restructure the research framework on state feminism beyond the binary categorization of regime types. Additionally, they underscore the significance of acknowledging the discretion exercised by state officials, providing insights into instances where state feminism may fail in certain democratic contexts.

Keywords: state feminism, feminist policies, national machinery, regime types, political parties, Japan

Procedia PDF Downloads 36

Authors: Evy Rombaut, Marie-Anne Guerry

Abstract:

Predicting voluntary turnover of employees is an important topic of study, both in academia and industry. Researchers try to uncover determinants for a broader understanding and possible prevention of turnover. In the current study, we use a data set based approach to reveal determinants for turnover, differing for blue and white collar workers. Our data set based approach made it possible to study actual turnover for more than 500000 employees in 15692 Belgian corporations. We use logistic regression to calculate individual turnover probabilities and test the goodness of our model with the AUC (area under the ROC-curve) method. The results of the study confirm the relationship of known determinants to employee turnover such as age, seniority, pay and work distance. In addition, the study unravels unknown and verifies known differences between blue and white collar workers. It shows opposite relationships to turnover for gender, marital status, the number of children, nationality, and pay.

Keywords: employee turnover, blue collar, white collar, dataset analysis

Procedia PDF Downloads 266

Authors: Salim Ouchtati, Aissa Belmeguenai, Mouldi Bedda

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In this study, we propose an offline system for the recognition of the fragmented handwritten numeric chains. Firstly, we realized a recognition system of the isolated handwritten digits, in this part; the study is based mainly on the evaluation of neural network performances, trained with the gradient backpropagation algorithm. The used parameters to form the input vector of the neural network are extracted from the binary images of the isolated handwritten digit by several methods: the distribution sequence, sondes application, the Barr features, and the centered moments of the different projections and profiles. Secondly, the study is extended for the reading of the fragmented handwritten numeric chains constituted of a variable number of digits. The vertical projection was used to segment the numeric chain at isolated digits and every digit (or segment) was presented separately to the entry of the system achieved in the first part (recognition system of the isolated handwritten digits).

Keywords: features extraction, handwritten numeric chains, image processing, neural networks

Procedia PDF Downloads 254

Authors: S. F. Bayona, J. Nunez, D. Paez

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The diagnostic processes have been consolidated as fundamental tools in the adequate knowledge of organizations and their processes. The diagnosis is related to the interpretation of the data, findings and the relevant information, to determine problems, causes, or the simple state and behavior of a process, without including a solution to the problems detected. The objective of this work is to identify the necessary stages to diagnose the logistic processes in a metalworking company, from the literary revision of different disciplines. A total of 62 articles were chosen to identify, through bibliometric analysis, the most cited articles, as well as the most frequent authors and journals. The results allowed to identify the two fundamental stages in the diagnostic process: a primary phase (general) based on the logical subjectivity of the knowledge of the person who evaluates, and the secondary phase (specific), related to the interpretation of the results, findings or data. Also, two phases were identified, one related to the definition of the scope of the actions to be developed and the other, as an initial description of what was observed in the process.

Keywords: business, diagnostic, management, process

Procedia PDF Downloads 146

Authors: Birome Holo Ba, Christian Prins, Caroline Prodhon

Abstract:

Optimization is an important aspect of logistics management. It can reduce significantly logistics costs and also be a good tool for decision support. In this paper, we address a planning problem specific to biomass supply chain. We propose a new mixed integer linear programming (MILP) model dealing with different feed stock production operations such as harvesting, packing, storage, pre-processing and transportation, with the objective of minimizing the total logistic cost of the system on a regional basis. It determines the optimal number of harvesting machine, the fleet size of trucks for transportation and the amount of each type of biomass harvested, stored and pre-processed in each period to satisfy demands of refineries in each period. We illustrate the effectiveness of the proposal model with a numerical example, a case study in Aube (France department), which gives preliminary and interesting, results on a small test case.

Keywords: biomass logistics, supply chain, modelling, optimization, bioenergy, biofuels

Procedia PDF Downloads 503

Authors: N. Šarlija, S. Pfeifer, M. Jeger, A. Bilandžić

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Enterprise growth is generally considered as a key driver of competitiveness, employment, economic development and social inclusion. As such, it is perceived to be a highly desirable outcome of entrepreneurship for scholars and decision makers. The huge academic debate resulted in the multitude of theoretical frameworks focused on explaining growth stages, determinants and future prospects. It has been widely accepted that enterprise growth is most likely nonlinear, temporal and related to the variety of factors which reflect the individual, firm, organizational, industry or environmental determinants of growth. However, factors that affect growth are not easily captured, instruments to measure those factors are often arbitrary, causality between variables and growth is elusive, indicating that growth is not easily modeled. Furthermore, in line with heterogeneous nature of the growth phenomenon, there is a vast number of measurement constructs assessing growth which are used interchangeably. Differences among various growth measures, at conceptual as well as at operationalization level, can hinder theory development which emphasizes the need for more empirically robust studies. In line with these highlights, the main purpose of this paper is twofold. Firstly, to compare structure and performance of three growth prediction models based on the main growth measures: Revenues, employment and assets growth. Secondly, to explore the prospects of financial indicators, set as exact, visible, standardized and accessible variables, to serve as determinants of enterprise growth. Finally, to contribute to the understanding of the implications on research results and recommendations for growth caused by different growth measures. The models include a range of financial indicators as lag determinants of the enterprises’ performances during the 2008-2013, extracted from the national register of the financial statements of SMEs in Croatia. The design and testing stage of the modeling used the logistic regression procedures. Findings confirm that growth prediction models based on different measures of growth have different set of predictors. Moreover, the relationship between particular predictors and growth measure is inconsistent, namely the same predictor positively related to one growth measure may exert negative effect on a different growth measure. Overall, financial indicators alone can serve as good proxy of growth and yield adequate predictive power of the models. The paper sheds light on both methodology and conceptual framework of enterprise growth by using a range of variables which serve as a proxy for the multitude of internal and external determinants, but are unlike them, accessible, available, exact and free of perceptual nuances in building up the model. Selection of the growth measure seems to have significant impact on the implications and recommendations related to growth. Furthermore, the paper points out to potential pitfalls of measuring and predicting growth. Overall, the results and the implications of the study are relevant for advancing academic debates on growth-related methodology, and can contribute to evidence-based decisions of policy makers.

Keywords: growth measurement constructs, logistic regression, prediction of growth potential, small and medium-sized enterprises

Procedia PDF Downloads 238

Authors: Paul Bigala, Samuel Oladipo, Steven Adebowale

Abstract:

This study examines factors influencing knowledge of HIV/AIDS Prevention Practices and Transmission (KHAPPT) among young undergraduate students (15-24 years). Knowledge composite index was computed for 820 randomly selected students. Chi-square, ANOVA, and multinomial logistic regression were used for the analyses (α=.05). The overall mean knowledge score was 16.5±3.4 out of a possible score of 28. About 83% of the students have undergone HIV test, 21.0% have high KHAPPT, 18% said there is cure for the disease, 23% believed that asking for condom is embarrassing and 11.7% said it is safe to share unsterilized sharp objects with friends or family members. The likelihood of high KHAPPT was higher among students who have had HIV test (OR=3.314; C.I=1.787-6.145, p<0.001) even when other variables were used as control. The identified predictors of high KHAPPT were; ever had HIV test, faculty, and ever used any HIV/AIDS prevention services. North-West University Mafikeng should intensify efforts on the HIV/AIDS awareness program on the campus.

Keywords: HIV/AIDS knowledge, undergraduate students, HIV testing, Mafikeng

Procedia PDF Downloads 425

Authors: Thinh Ngo, Paul Rad, Brian Kelley

Abstract:

Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.

Keywords: classification, CNN, deep learning, prediction, SNR

Procedia PDF Downloads 123

Authors: Adnan I. O. Zaid

Abstract:

As aluminum solidifies in columnar structure with large grain size which reduces its surface quality and mechanical strength; therefore it is normally grain refined either by titanium or titanium + boron (Ti or Ti + B). In this paper, the effect of addition of either Ti or Ti + B to commercially pure aluminum on its grain size, Vickers hardness, mechanical strength and fatigue strength and life is presented and discussed. Similarly, the effect of vanadium addition to Al grain refined by Ti or Ti+ B is presented and discussed. Two binary master alloys Al-Ti and Al-Vi were laboratory prepared from which five different micro-alloys in addition to the commercially pure aluminum namely Al-Ti, Al-Ti-B, Al-V, Al-Ti-V and Al-Ti-B-V were prepared for the investigation. Finally, the effect of their addition on the fatigue cracks initiation and propagation, using scanning electron microscope, SEM, is also presented and discussed. Photomirographs and photoscans are included in the paper.

Keywords: aluminum, fatigue, grain refinement, titanium, titanium+boron, vanadium

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Authors: Abraham Terán Salcedo, Didier Samayoa Ochoa

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This work presents a numerical implementation of a method for estimating the box-counting dimension of self-avoiding curves on a planar space, fractal objects captured on digital images; this method is named fractioning estimator. Classical methods of digital image processing, such as noise filtering, contrast manipulation, and thresholding, among others, are used in order to obtain binary images that are suitable for performing the necessary computations of the fractioning estimator. A user interface is developed for performing the image processing operations and testing the fractioning estimator on different captured images of real-life fractal objects. To analyze the results, the estimations obtained through the fractioning estimator are compared to the results obtained through other methods that are already implemented on different available software for computing and estimating the box-counting dimension.

Keywords: box-counting, digital image processing, fractal dimension, numerical method

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Authors: Wennan Long, Yuhao Nie, Yunan Li, Adam Brandt

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To fight against climate change, California government issued the Senate Bill No. 100 (SB-100) in 2018 September, which aims at achieving a target of 100% renewable electricity by the end of 2045. A capacity expansion problem is solved in this case study using a binary quadratic programming model. The optimal locations and capacities of the potential renewable power plants (i.e., solar, wind, biomass, geothermal and hydropower), the phase-out schedule of existing fossil-based (nature gas) power plants and the transmission of electricity across the entire network are determined with the minimal total annualized cost measured by net present value (NPV). The results show that the renewable electricity contribution could increase to 85.9% by 2030 and reach 100% by 2035. Fossil-based power plants will be totally phased out around 2035 and solar and wind will finally become the most dominant renewable energy resource in California electricity mix.

Keywords: 100% renewable electricity, California, capacity expansion, mixed integer non-linear programming

Procedia PDF Downloads 160

Authors: Mashood C., Abdul Vahid K., Ashique C. K.

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The technology is growing beyond human expectation. Internet is one of very sophisticated product of the information technology. It has various advantages like connecting the world, simplifying the difficult tasks done in past etc. Simultaneously it has demerits also; that is lack of authenticity and internet addiction. To find out the problems of internet addiction, a study conducted among the Postgraduate students of Pondicherry University and collected 454 samples. The study strictly focused to identify the internet addiction among students, influence and interdependence of personality on internet addiction among first years and second years. To evaluate this, we used two major analysis, these are Confirmatory Factor Analysis (CFA) to predict the internet addiction with the observed data and Logistic Regression to identify the difference between first years and second years in the case of internet addiction. Before applying to the core analysis, the data applied to some preliminary tests to check the model fit. The empirical findings shows that , the students of Pondicherry University are very much addicted to the internet, But there is no such huge difference between first years and second years in case of internet addiction.

Keywords: internet addiction, students, Pondicherry University, empirical study

Procedia PDF Downloads 451

Authors: A. K. O'Loughlin

Abstract:

In Simone de Beauvoir’s climatic 1959 meditation, The Second Sex, she avows that 'On ne naît pas femme; on le devient,' translated most recently in the unabridged text (2010) as 'One is not born, but rather becomes, woman.' The signifier ‘woman’ in this context, signifies Beauvoir’s contemplation of the institution, the concept of woman(ness) defined in relation to the binary and hegemonic man(ness.) She is 'the other.' This paper is a theoretical contemplation of (1) how we actively teach 'othering' in the institution of schooling and (2) new considerations of pluralism for self-reflection and subversion that teachers, in particular, are faced with. How, in schooling, do we learn one’s options for racialized, classed and sexualized gender identification and the hierarchical signification that define these signifiers? Just like the myth of apolitical schooling, we cannot escape teaching social organization in the classroom. Yet, we do have a choice. How do we as educators learn about our own embodied intersectionalities? How do we unlearn our own binaries? How do we teach about intersectional gender? How do we teach 'the other'? We posit the processes of these reflections by educators may move our classrooms beyond binaries, engage pluralism and queer alterity itself.

Keywords: othering, alterity, education, schooling, identity, racialization, gender, intersectionality, pluralism

Procedia PDF Downloads 235

Authors: S. O. Oyamakin, A. U. Chukwu

Abstract:

Richard's growth equation being a generalized logistic growth equation was improved upon by introducing an allometric parameter using the hyperbolic sine function. The integral solution to this was called hyperbolic Richard's growth model having transformed the solution from deterministic to a stochastic growth model. Its ability in model prediction was compared with the classical Richard's growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using the coefficient of determination (R2), Mean Absolute Error (MAE) and Mean Square Error (MSE) results. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the behavior of the error term for possible violations. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic Richard's nonlinear growth models better than the classical Richard's growth model.

Keywords: height, Dbh, forest, Pinus caribaea, hyperbolic, Richard's, stochastic

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Authors: Pavlo Selyshchev, Samuel Akintunde

Abstract:

A theoretical approach to consider formation of chemical compound layer at the interface between initial substances A and B due to the interfacial interaction and diffusion is developed. It is considered situation when speed of interfacial interaction is large enough and diffusion of A-atoms through AB-layer is much more then diffusion of B-atoms. Atoms from A-layer diffuse toward B-atoms and form AB-atoms on the surface of B-layer. B-atoms are assumed to be immobile. The growth kinetics of the AB-layer is described by two differential equations with non-linear coupling, producing a good fit to the experimental data. It is shown that growth of the thickness of the AB-layer determines by dependence of chemical reaction rate on reactants concentration. In special case the thickness of the AB-layer can grow linearly or parabolically depending on that which of processes (interaction or the diffusion) controls the growth. The thickness of AB-layer as function of time is obtained. The moment of time (transition point) at which the linear growth are changed by parabolic is found.

Keywords: phase formation, binary systems, interfacial reaction, diffusion, compound layers, growth kinetics

Procedia PDF Downloads 559

Authors: Sonia P. Marrero Duran, Lilian Noya Dominguez, Lisandra Quintana Alvarez, Evert Martinez Perez, Ana Julia Acevedo Urquiaga

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Cuban business and economic policy are in the constant update as well as facing a client ever more knowledgeable and demanding. For that reason become fundamental for companies competitiveness through the optimization of its processes and services. One of the Cuban’s pillars, which has been sustained since the triumph of the Cuban Revolution back in 1959, is the free health service to all those who need it. This service is offered without any charge under the concept of preserving human life, but it implied costly management processes and logistics services to be able to supply the necessary medicines to all the units who provide health services. One of the key actors on the medicine supply chain is the Havana Distribution Center (HDC), which is responsible for the delivery of medicines in the province; as well as the acquisition of medicines from national and international producers and its subsequent transport to health care units and pharmacies in time, and with the required quality. This HDC also carries for all distribution centers in the country. Given the eminent need to create an actor in the supply chain that specializes in the medicines supply, the possibility of centralizing this operation in a logistics service provider is analyzed. Based on this decision, pharmacies operate as clients of the logistic service center whose main function is to centralize all logistics operations associated with the medicine supply chain. The HDC is precisely the logistic service provider in Havana and it is the center of this research. In 2017 the pharmacies had affectations in the availability of medicine due to deficiencies in the distribution routes. This is caused by the fact that they are not based on routing studies, besides the long distribution cycle. The distribution routs are fixed, attend only one type of customer and there respond to a territorial location by the municipality. Taking into consideration the above-mentioned problem, the objective of this research is to optimize the routes system in the Havana Distribution Center. To accomplish this objective, the techniques applied were document analysis, random sampling, statistical inference and tools such as Ishikawa diagram and the computerized software’s: ArcGis, Osmand y MapIfnfo. As a result, were analyzed four distribution alternatives; the actual rout, by customer type, by the municipality and the combination of the two last. It was demonstrated that the territorial location alternative does not take full advantage of the transportation capacities or the distance of the trips, which leads to elevated costs breaking whit the current ways of distribution and the currents characteristics of the clients. The principal finding of the investigation was the optimum option distribution rout is the 4th one that is formed by hospitals and the join of pharmacies, stomatology clinics, polyclinics and maternal and elderly homes. This solution breaks the territorial location by the municipality and permits different distribution cycles in dependence of medicine consumption and transport availability.

Keywords: computerized geographic software, distribution, distribution routs, vehicle problem routing (VPR)

Procedia PDF Downloads 149

Authors: Preshanthan Moodley, E. B. Gueguim Kana

Abstract:

This study examines the kinetics of S. cerevisiae BY4743 growth and bioethanol production from sugarcane leaf waste (SLW), utilizing two different optimized pretreatment regimes; under two fermentation modes: steam salt-alkali filtered enzymatic hydrolysate (SSA-F), steam salt-alkali unfiltered (SSA-U), microwave salt-alkali filtered (MSA-F) and microwave salt-alkali unfiltered (MSA-U). The kinetic coefficients were determined by fitting the Monod, modified Gompertz, and logistic models to the experimental data with high coefficients of determination R² > 0.97. A maximum specific growth rate (µₘₐₓ) of 0.153 h⁻¹ was obtained under SSA-F and SSA-U whereas, 0.150 h⁻¹ was observed with MSA-F and MSA-U. SSA-U gave a potential maximum bioethanol concentration (Pₘ) of 31.06 g/L compared to 30.49, 23.26 and 21.79g/L for SSA-F, MSA-F and MSA-U respectively. An insignificant difference was observed in the μmax and Pm for the filtered and unfiltered enzymatic hydrolysate for both SSA and MSA pretreatments, thus potentially reducing a unit operation. These findings provide significant insights for process scale up.

Keywords: lignocellulosic bioethanol, microwave pretreatment, sugarcane leaves, kinetics

Procedia PDF Downloads 106

Authors: Samuel Oluwafemi Oyamakin, Angela Unna Chukwu

Abstract:

Richrads growth equation being a generalized logistic growth equation was improved upon by introducing an allometric parameter using the hyperbolic sine function. The integral solution to this was called hyperbolic Richards growth model having transformed the solution from deterministic to a stochastic growth model. Its ability in model prediction was compared with the classical Richards growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using the coefficient of determination (R2), Mean Absolute Error (MAE) and Mean Square Error (MSE) results. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the behavior of the error term for possible violations. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic Richards nonlinear growth models better than the classical Richards growth model.

Keywords: height, diameter at breast height, DBH, hyperbolic sine function, Pinus caribaea, Richards' growth model

Procedia PDF Downloads 378

Authors: Mohammad Tahir Yousafzai, Rubina Qasim

Abstract:

We assessed Hepatitis B vaccination and its determinants among health care workers (HCW) in Northwest Pakistan. HCWs from both public and private clinics were interviewed about hepatitis B vaccination, socio-demographic, hepatitis B virus transmission modes, disease threat and benefits of vaccination. Logistic regression was performed. Hepatitis B vaccination was 40% (Qualified Physicians: 86% and non-qualified Dispensers:16%). Being Qualified Physician (Adj. OR 26.6; 95%CI 9.3-73.2), Non-qualified Physician (Adj.OR 1.9; 95%CI 0.8-4.6), qualified Dispensers (Adj. OR 3.6; 95%CI 1.3-9.5) compared to non-qualified Dispensers, working in public clinics (Adj. OR 2.5; 95%CI 1.1-5.7) compared to private, perceived disease threat after exposure to blood and body fluids (Adj. OR 1.1; 95%CI 1.1-1.2) and perceived benefits of vaccination (Adj. OR 1.1; 95%CI 1.1-1.2) were significant predictors of hepatitis B vaccination. Improved perception of disease threat and benefits of vaccination and qualification of HCWs are associated with hepatitis B vaccination.

Keywords: Hepatitis B vaccine, immunization, healthcare workers, primary health

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Authors: Navab Karimi, Tohid Alizadeh

Abstract:

An intelligent vision-based system was designed to measure the quality and purity of raisins. A machine vision setup was utilized to capture the images of bulk raisins in ranges of 5-50% mixed pure-impure berries. The textural features of bulk raisins were extracted using Grey-level Histograms, Co-occurrence Matrix, and Local Binary Pattern (a total of 108 features). Genetic Algorithm and neural network regression were used for selecting and ranking the best features (21 features). As a result, the GLCM features set was found to have the highest accuracy (92.4%) among the other sets. Followingly, multiple feature combinations of the previous stage were fed into the second regression (linear regression) to increase accuracy, wherein a combination of 16 features was found to be the optimum. Finally, a Support Vector Machine (SVM) classifier was used to differentiate the mixtures, producing the best efficiency and accuracy of 96.2% and 97.35%, respectively.

Keywords: sun-dried organic raisin, genetic algorithm, feature extraction, ann regression, linear regression, support vector machine, south azerbaijan.

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Authors: Shady Gamal Aziz Shehata

Abstract:

Difficulty in defining construction quality arises due to perception based on the nature and requirements of the market, the different partners themselves and the results they want. Quantitative research was used in this constructivist research. A case-based study was conducted to assess the structures of positive attitudes and expectations in the context of quality improvement. A survey based on expert opinions was analyzed among construction organizations/companies operating in the construction industry in Pakistan. The financial strength, management structure and construction experience of the construction companies formed the basis of their selection. A good concept is visible at the project level and is seen as the most valuable part of the construction project. Each quality improvement technique was expected to increase the user's profits by improving the efficiency of the construction project. The Survey is useful for construction professionals to evaluate current construction concepts and expectations for the application of quality improvement techniques in construction projects.

Keywords: correlation analysis, lean construction tools, lean construction, logistic regression analysis, risk management, safety construction quality, expectation, improvement, perception

Procedia PDF Downloads 37

Authors: Ali Abdrhman M. Ukasha

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Data security needed in data transmission, storage, and communication to ensure the security. The single step parallel contour extraction (SSPCE) method is used to create the edge map as a key image from the different Gray level/Binary image. Performing the X-OR operation between the key image and each bit plane of the original image for image pixel values change purpose. The Arnold transform used to changes the locations of image pixels as image scrambling process. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Gary level image and completely reconstructed without any distortion. Also shown that the analyzed algorithm have extremely large security against some attacks like salt & pepper and JPEG compression. Its proof that the Gray level image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: SSPCE method, image compression-salt- peppers attacks, bitplanes decomposition, Arnold transform, lossless image encryption

Procedia PDF Downloads 420

Authors: M. D. D. Chathurangi, M. G. K. Nayanathara, K. M. H. M. M. Gunapala, G. M. R. G. Dayananda, Kavinga Yapa Abeywardena, Deemantha Siriwardana

Abstract:

Due to the growing popularity of social media platforms at present, there are various concerns, mostly cyberbullying, spam, bot accounts, and the spread of incorrect information. To develop a risk score calculation system as a thorough method for deciphering and exposing unethical social media profiles, this research explores the most suitable algorithms to our best knowledge in detecting the mentioned concerns. Various multiple models, such as Naïve Bayes, CNN, KNN, Stochastic Gradient Descent, Gradient Boosting Classifier, etc., were examined, and the best results were taken into the development of the risk score system. For cyberbullying, the Logistic Regression algorithm achieved an accuracy of 84.9%, while the spam-detecting MLP model gained 98.02% accuracy. The bot accounts identifying the Random Forest algorithm obtained 91.06% accuracy, and 84% accuracy was acquired for fake news detection using SVM.

Keywords: cyberbullying, spam behavior, bot accounts, fake news, machine learning

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Authors: Tak-Chung Fu, Ying-Kit Hung, Fu-Lai Chung

Abstract:

In the field of time series data mining, the concept of the Perceptually Important Point (PIP) identification process is first introduced in 2001. This process originally works for financial time series pattern matching and it is then found suitable for time series dimensionality reduction and representation. Its strength is on preserving the overall shape of the time series by identifying the salient points in it. With the rise of Big Data, time series data contributes a major proportion, especially on the data which generates by sensors in the Internet of Things (IoT) environment. According to the nature of PIP identification and the successful cases, it is worth to further explore the opportunity to apply PIP in time series ‘Big Data’. However, the performance of PIP identification is always considered as the limitation when dealing with ‘Big’ time series data. In this paper, two distributed versions of PIP identification based on the Specialized Binary (SB) Tree are proposed. The proposed approaches solve the bottleneck when running the PIP identification process in a standalone computer. Improvement in term of speed is obtained by the distributed versions.

Keywords: distributed computing, performance analysis, Perceptually Important Point identification, time series data mining

Procedia PDF Downloads 417

Authors: Mecheri Zeid Belmecheri, Maamar Ahfir, Izzet Kale

Abstract:

Automatic cardiac auscultation is still a subject of research in order to establish an objective diagnosis. Recorded heart sounds as Phonocardiogram signals (PCG) can be used for automatic segmentation into components that have clinical meanings. These are the first sound, S1, the second sound, S2, and the systolic and diastolic components, respectively. In this paper, an automatic method is proposed for the robust segmentation of heart sounds. This method is based on calculating an intermediate sawtooth-shaped signal from the length variation of the recorded Phonocardiogram (PCG) signal in the time domain and, using its positive derivative function that is a binary signal in training a Recurrent Neural Network (RNN). Results obtained in the context of a large database of recorded PCGs with their simultaneously recorded ElectroCardioGrams (ECGs) from different patients in clinical settings, including normal and abnormal subjects, show a segmentation testing performance average of 76 % sensitivity and 94 % specificity.

Keywords: heart sounds, PCG segmentation, event detection, recurrent neural networks, PCG curve length

Procedia PDF Downloads 167

Authors: Ali A. Ukasha

Abstract:

Data security needed in data transmission, storage, and communication to ensure the security. The single step parallel contour extraction (SSPCE) method is used to create the edge map as a key image from the different Gray level/Binary image. Performing the X-OR operation between the key image and each bit plane of the original image for image pixel values change purpose. The Arnold transform used to changes the locations of image pixels as image scrambling process. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Gary level image and completely reconstructed without any distortion. Also shown that the analyzed algorithm have extremely large security against some attacks like salt & pepper and JPEG compression. Its proof that the Gray level image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: SSPCE method, image compression, salt and peppers attacks, bitplanes decomposition, Arnold transform, lossless image encryption

Procedia PDF Downloads 481

Authors: Fasanmi Samuel Sunday

Abstract:

This study investigated the influence of gender and personality traits on emotional distress among awaiting trial inmates in Nigeria. Participants were three hundred and twenty (320) awaiting trial inmates, drawn from three main correctional centres in Northeast Nigeria, namely: Gashua Correctional Centre, Postiskum Correctional Centre, and Bauchi Correctional Centre. Expo facto research design was adopted. Questionnaires such as the Big Five Inventory and the Perceived Emotional Distress Inventory (PEDI) were used to measure the variables of the study. Three hypotheses were tested. Logistic regression was used for data analysis. Results of the analysis indicated that conscientiousness significantly predicted emotional distress among awaiting trial inmates. However, most of the identified personality traits did not significantly predict emotional distress among awaiting trial inmates. There was no significant gender difference in emotional distress among awaiting-trial inmates. The implications of the study were discussed.

Keywords: personality traits, emotional distress, awaiting-trial inmates, gender

Procedia PDF Downloads 81

Authors: Raghad A. Altowairgi

Abstract:

With the wide spread of social media platforms, young people tend to use them extensively as the first means of communication due to their ease and modernity. But these platforms often create a fertile ground for bullies to practice their aggressive behavior against their victims. Platform usage cannot be reduced, but intelligent mechanisms can be implemented to reduce the abuse. This is where machine learning comes in. Understanding and classifying text can be helpful in order to minimize the act of cyberbullying. Artificial intelligence techniques have expanded to formulate an applied tool to address the phenomenon of cyberbullying. In this research, machine learning models are built to classify text into two classes; cyberbullying and non-cyberbullying. After preprocessing the data in 4 stages; removing characters that do not provide meaningful information to the models, tokenization, removing stop words, and lowering text. BoW and TF-IDF are used as the main features for the five classifiers, which are; logistic regression, Naïve Bayes, Random Forest, XGboost, and Catboost classifiers. Each of them scores 92%, 90%, 92%, 91%, 86% respectively.

Keywords: cyberbullying, machine learning, Bag-of-Words, term frequency-inverse document frequency, natural language processing, Catboost

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Authors: Lisandy Arinta Suryana, Santi Novani, Utomo Sarjono

Abstract:

Paradox of business strategic is associated with the contradictory practice. It becomes one of the critical way to survive and win in the dynamic competitive landscape – high level of uncertainty and rapid change in the business environment. Those characteristics are similar with the environment of hijab fashion business, especially in Indonesia. This paper aims to describe the success of paradoxical strategic based on historical data of hijab fashion business which have been validated by qualitative approach. This paper discusses two main aspects of paradoxical strategic such as paradox in human resource management, and logistic center management. Then, the detail effects from each practice are described in term of causal loop diagram. Moreover, the practice of paradoxical strategic depends on leadership that can make a brave and dynamic decision by capturing the main problems and opportunities in their business, and also build commitment to achieve a specific goal.

Keywords: paradox of business strategic, paradoxical strategic, causal loop diagram, sustainable business, hijab fashion business, business strategic

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Authors: Sh. Gofurov, O. Ismailova, U. Makhmanov, A. Kokhkharov

Abstract:

The refractometric method has been used to determine optical properties of concentration features of aqueous solutions of ethanol, tetrahydrofuran and dimethylformamide at the room temperature. Changes in dielectric permittivity of aqueous solutions of ethanol, tetrahydrofuran and dimethylformamide in a wide range of concentrations (0÷1.0 molar fraction) have been studied using molecular dynamics method. The curves depending on the concentration of experimental data on excess refractive indices and excess dielectric permittivity were compared. It has been shown that stable heteromolecular complexes in binary solutions are formed in the concentration range of 0.3÷0.4 mole fractions. The real and complex part of dielectric permittivity was obtained from dipole-dipole autocorrelation functions of molecules. At the concentrations of C = 0.3 / 0.4 m.f. the heteromolecular structures with hydrogen bonds are formed. This is confirmed by the extremum values of excessive dielectric permittivity and excessive refractive index of aqueous solutions.

Keywords: refractometric method, aqueous solution, molecular dynamics, dielectric constant

Procedia PDF Downloads 255