Search results for: evolutionary cultural algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7739

Search results for: evolutionary cultural algorithm

3569 Cinema Reception in a Digital World: A Study of Cinema Audiences in India

Authors: Sanjay Ranade

Abstract:

Traditional film theory assumes the cinema audience in a darkened room where cinema is projected on to a white screen, and the audience suspends their sense of reality. Shifts in audiences due to changes in cultural tastes or trends have been studied for decades. In the past two decades, however, the audience, especially the youth, has shifted to digital media for the consumption of cinema. As a result, not only are audiences watching cinema on different devices, they are also consuming cinema in places and ways never imagined before. Public transport often crowded to the brim with a lot of ambient content, and a variety of workplaces have become sites for cinema viewing. Cinema is watched piecemeal and at different times of the day. Audiences use devices such as mobile phones and tablets to watch cinema. The cinema viewing experience is getting redesigned by the user. The emerging design allows the spectator to not only consume images and narratives but also produce, reproduce, and manipulate existing images and narratives, thereby participating in the process and influencing it. Spectatorship studies stress on the importance of subjectivity when dealing with the structure of the film text and the cultural and psychological implications in the engagement between the spectator and the film text. Indian cinema has been booming and contributing to global movie production significantly. In 2005 film production was 1000 films a year and doubled to 2000 by 2016. Digital technology helped push this growth in 2012. Film studies in India have had a decided Euro-American bias. The studies have chiefly analysed the content for ideological leanings or myth or as reflections of society, societal changes, or articulation of identity or presented retrospectives of directors, actors, music directors, etc. The one factor relegated to the background has been the spectator. If they have been addressed, they are treated as a collective of class or gender. India has a performative tradition going back several centuries. How Indians receive cinema is an important aspect to study with respect to film studies. This exploratory and descriptive study looked at 162 young media students studying cinema at the undergraduate and postgraduate levels. The students, speaking as many as 20 languages amongst them, were drawn from across the country’s media schools. The study looked at nine film societies registered with the Federation of Film Societies of India. A structured questionnaire was made and distributed online through media teachers for the students. The film societies were approached through the regional office of the FFSI in Mumbai. Lastly, group discussions were held in Mumbai with students and teachers of media. A group consisted of between five and twelve student participants, along with one or two teachers. All the respondents looked at themselves as spectators and shared their experiences of spectators of cinema, providing a very rich insight into Indian conditions of viewing cinema and challenges for cinema ahead.

Keywords: audience, digital, film studies, reception, reception spectatorship

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3568 A Neural Approach for the Offline Recognition of the Arabic Handwritten Words of the Algerian Departments

Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda

Abstract:

In this work we present an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods: the parameters of distribution, the moments centered of the different projections and the Barr features. It should be noted that these methods are applied on segments gotten after the division of the binary image of the word in six segments. The classification is achieved by a multi layers perceptron. Detailed experiments are carried and satisfactory recognition results are reported.

Keywords: handwritten word recognition, neural networks, image processing, pattern recognition, features extraction

Procedia PDF Downloads 513
3567 De-Commoditisation of Food: How Organic Farmers from the Madrid Region Reconnect Products and Places through Web Marketing

Authors: Salvatore Pinna

Abstract:

The growth of organic farming practices in the last few decades is continuing to stimulate the international debate about this alternative food market. As a part of a PhD project research about embeddedness in Alternative Food Networks (AFNs), this paper focuses on the promotional aspects of organic farms websites from the Madrid region. As a theoretical tool, some knowledge categories drawn on the geographic studies literature are used to classify the many ideas expressed in the web pages. By analysing texts and pictures of 30 websites, the study aims to question how and to what extent actors from organic world communicate to the potential customers their personal beliefs about farming practices, products qualities, and ecological and social benefits. Moreover, the paper raises the question of whether organic farming laws and regulations lack of completeness about the social and cultural aspects of food.

Keywords: alternative food networks, de-commoditisation, organic farming, madrid, reconnection of food

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3566 The Study of the Factors Affecting Entrepreneurship in Sport

Authors: Habib Honari

Abstract:

The purpose of this study is an investigation of the factors affecting entrepreneurship in sport from the point of view of experts in this field. This study is a descriptive analytic one and was conducted as a survey and statistical sample consisted of 64 subjects including top managers and sport management professors at physical education organization. Data is collected by research designed questionnaire. Its reliability (α=.95) is obtained after its validity confirmation (by professors). In this article the most important factors affecting sport entrepreneurship, both as an interdisciplinary field in the world, are studied. Initially, infrastructures are identified for entrepreneurial opportunities in sports and related problems become known so that identifying factors for social, cultural, and economical development to entrepreneurs will be a smooth path, because sport entrepreneurship, given its effective roles in business development, welfare, health development, and participation in various aspects of society, can also play a crucial role in the development of the country. Finally, some solutions for developing entrepreneurial sport are introduced.

Keywords: sport entrepreneurship, entrepreneurial opportunities, entrepreneurial barriers, interdisciplinary

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3565 Electric Load Forecasting Based on Artificial Neural Network for Iraqi Power System

Authors: Afaneen Anwer, Samara M. Kamil

Abstract:

Load Forecast required prediction accuracy based on optimal operation and maintenance. A good accuracy is the basis of economic dispatch, unit commitment, and system reliability. A good load forecasting system fulfilled fast speed, automatic bad data detection, and ability to access the system automatically to get the needed data. In this paper, the formulation of the load forecasting is discussed and the solution is obtained by using artificial neural network method. A MATLAB environment has been used to solve the load forecasting schedule of Iraqi super grid network considering the daily load for three years. The obtained results showed a good accuracy in predicting the forecasted load.

Keywords: load forecasting, neural network, back-propagation algorithm, Iraqi power system

Procedia PDF Downloads 583
3564 Constrained RGBD SLAM with a Prior Knowledge of the Environment

Authors: Kathia Melbouci, Sylvie Naudet Collette, Vincent Gay-Bellile, Omar Ait-Aider, Michel Dhome

Abstract:

In this paper, we handle the problem of real time localization and mapping in indoor environment assisted by a partial prior 3D model, using an RGBD sensor. The proposed solution relies on a feature-based RGBD SLAM algorithm to localize the camera and update the 3D map of the scene. To improve the accuracy and the robustness of the localization, we propose to combine in a local bundle adjustment process, geometric information provided by a prior coarse 3D model of the scene (e.g. generated from the 2D floor plan of the building) along with RGBD data from a Kinect camera. The proposed approach is evaluated on a public benchmark dataset as well as on real scene acquired by a Kinect sensor.

Keywords: SLAM, global localization, 3D sensor, bundle adjustment, 3D model

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3563 Dissimilarity-Based Coloring for Symbolic and Multivariate Data Visualization

Authors: K. Umbleja, M. Ichino, H. Yaguchi

Abstract:

In this paper, we propose a coloring method for multivariate data visualization by using parallel coordinates based on dissimilarity and tree structure information gathered during hierarchical clustering. The proposed method is an extension for proximity-based coloring that suffers from a few undesired side effects if hierarchical tree structure is not balanced tree. We describe the algorithm by assigning colors based on dissimilarity information, show the application of proposed method on three commonly used datasets, and compare the results with proximity-based coloring. We found our proposed method to be especially beneficial for symbolic data visualization where many individual objects have already been aggregated into a single symbolic object.

Keywords: data visualization, dissimilarity-based coloring, proximity-based coloring, symbolic data

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3562 Barriers to Social Entrepreneurship by Refugees: An Explorative Study How Prior Experience Influences Social Orientation

Authors: D. M. Koers, A. J. Groen, P. D. Englis, R. Harms

Abstract:

We are witnessing the largest level of displacement of people since World War II. Refugees want to become independent as quickly as possible and build a new, safe future; however, access to the labor market is difficult and they face many problems that are not easily solved. This makes self-employment including social entrepreneurship a valuable alternative. Our research studied refugee-based entrepreneurship and examined whether prior knowledge, unmet personal needs and contextual factors influence how refugees recognize opportunities and if this influences their social orientation. In addition, we examine the barriers refugees face when starting up a company in the Netherlands. We use a case study design with a mixed-method approach, combining in-depth interviews and survey data. Data was collected from two Dutch entrepreneurial training programs in the Netherlands. We have a sample size of 27 latent refugee entrepreneurs. Our results show that refugees score high on the social entrepreneurial measures. They perceive themselves as having a strong social vision and are determined to defend a social need. They also score high on sustainability and state that their business ideas improve the quality of life on the long run. Based on these findings, we did not expect that only 5 participants had business ideas with a social orientation. In this group, 37,5% started a company before and 77.8% used their personal experience to come up with this business idea. Another 70,3% had the higher professional education or academic education. In the interviews, we found that they often copy and paste their gained experience from a previous profession on their new context and expect that it would work well. The social aspect lies in their cultural values and personal beliefs but is not reflected in their business models. One of the reasons could be that the context in which the refugee operates as a moderator suppressing the social mission and social value creation opportunities. Refugees are first and foremost focused on their survival. They do not want to be on social welfare and feel a strong need to be independent. Since they cannot access the labor market easily and face labor market discrimination they want to start a company. Another factor that explains lack of the social orientation in their business ideas is that social entrepreneurship is not a known concept in their home countries. Their idea of entrepreneurship differs substantially. We found that a huge barrier for refugees is their expectations about setting up a business, which are often not realistic because they have little knowledge about the system, institutions and corresponding red tape. In those instances, can the institutional configuration of a country, cultural differences, and perspective on entrepreneurship hinders social entrepreneurship. In conclusion, there might be latent potential for social entrepreneurship in refugees but there are many barriers to overcome. Overcoming these barriers can enhance local communities and enhance integration. In addition it has a positive financial impact on the host country because it reduces the pressure on the social system and stimulate the economy.

Keywords: immigrant entrepreneurship, refugee entrepreneurship, social entrepreneurship, prior experience, opportunity recognition

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3561 A Digital Filter for Symmetrical Components Identification

Authors: Khaled M. El-Naggar

Abstract:

This paper presents a fast and efficient technique for monitoring and supervising power system disturbances generated due to dynamic performance of power systems or faults. Monitoring power system quantities involve monitoring fundamental voltage, current magnitudes, and their frequencies as well as their negative and zero sequence components under different operating conditions. The proposed technique is based on simulated annealing optimization technique (SA). The method uses digital set of measurements for the voltage or current waveforms at power system bus to perform the estimation process digitally. The algorithm is tested using different simulated data to monitor the symmetrical components of power system waveforms. Different study cases are considered in this work. Effects of number of samples, sampling frequency and the sample window size are studied. Results are reported and discussed.

Keywords: estimation, faults, measurement, symmetrical components

Procedia PDF Downloads 465
3560 Development and Psychometric Evaluation of the Malaysian Multi-Ethnic Discrimination Scale

Authors: Chua Bee Seok, Shamsul Amri Baharuddin, Ferlis Bahari, Jasmine Adela Mutang, Lailawati Madlan, Rosnah Ismail, Asong Joseph

Abstract:

Malaysia is a country famously known for its multiple unique cultural and ethnic diversities. Despite the diversity of culture, customs and beliefs, respectively, Malaysia still be able to stand as a harmonious country. However, if there is an attitude of stereotypes, prejudice and discrimination among ethnic, it may seriously affect the solidarity between people in Malaysia. Thus, this study focuses on constructing a scale measuring the Malaysian experience, strategy and effect of ethnic discrimination. To develop a quantitative measure on ethnic discrimination directed against Malaysian, a three-step process is proposed: Exploratory factor analysis, validity analysis, and internal consistency reliability analysis. Results, limitations, and implications of the study are discussed.

Keywords: test development, Malaysian multi-ethnic discrimination scale, exploratory factor analysis, validity, multi-ethnic, reliability, psychometrics

Procedia PDF Downloads 742
3559 'You’re Not Alone': Peer Feedback Practices for Cross-Cultural Writing Classrooms and Centers

Authors: Cassandra Branham, Danielle Farrar

Abstract:

As writing instructors and writing center administrators at a large research university with a significant population of English language learners (ELLs), we are interested in how peer feedback pedagogy can be effectively translated for writing center purposes, as well as how various modes of peer feedback can enrich the learning experiences of L1 and L2 writers in these spaces. Although peer feedback is widely used in classrooms and centers, instructor, student, and researcher opinions vary in respect to its effectiveness. We argue that peer feedback - traditional and digital, synchronous and asynchronous - is an indispensable element for both classrooms and centers and emphasize that it should occur with both L1 and L2 students to further develop an array of reading and writing skills. We also believe that further understanding of the best practices of peer feedback in such cross-cultural spaces, like the classroom and center, can optimize the benefits of peer feedback. After a critical review of the literature, we implemented an embedded tutoring program in our university’s writing center in collaboration with its First-Year Composition (FYC) program and Language Institute. The embedded tutoring program matches a graduate writing consultant with L1 and L2 writers enrolled in controlled-matriculation composition courses where ELLs make up at least 50% of each class. Furthermore, this program is informed by what we argue to be some best practices of peer feedback for both classroom and center purposes, including expectation-based training through rubrics, modeling effective feedback, hybridizing traditional and digital modes of feedback, recognizing the significance the body in composition (what we call writer embodiment), and maximizing digital technologies to exploit extended cognition. After conducting surveys and follow-up interviews with students, instructors, and writing consultants in the embedded tutoring program, we found that not only did students see an increased value in peer feedback, but also instructors saw an improvement in both writing style and critical thinking skills. Our L2 participants noted improvements in language acquisition while our L1 students recognized a broadening of their worldviews. We believe that both L1 and L2 students developed self-efficacy and agency in their identities as writers because they gained confidence in their abilities to offer feedback, as well as in the legitimacy of feedback they received from peers. We also argue that these best practices situate novice writers as experts, as writers become a valued and integral part of the revision process with their own and their peers’ papers. Finally, the use of iPads in embedded tutoring recovered the importance of the body and its senses in writing; the highly sensory feedback from these multi-modal sessions that offer audio and visual input underscores the significant role both the body and mind play in compositional practices. After beginning with a brief review of the literature that sparked this research, this paper will discuss the embedded tutoring program in detail, report on the results of the pilot program, and will conclude with a discussion of the pedagogical implications that arise from this research for both classroom and center.

Keywords: English language learners, peer feedback, writing center, writing classroom

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3558 Applications of Visual Ethnography in Public Anthropology

Authors: Subramaniam Panneerselvam, Gunanithi Perumal, KP Subin

Abstract:

The Visual Ethnography is used to document the culture of a community through a visual means. It could be either photography or audio-visual documentation. The visual ethnographic techniques are widely used in visual anthropology. The visual anthropologists use the camera to capture the cultural image of the studied community. There is a scope for subjectivity while the culture is documented by an external person. But the upcoming of the public anthropology provides an opportunity for the participants to document their own culture. There is a need to equip the participants with the skill of doing visual ethnography. The mobile phone technology provides visual documentation facility to everyone to capture the moments instantly. The visual ethnography facilitates the multiple-interpretation for the audiences. This study explores the effectiveness of visual ethnography among the tribal youth through public anthropology perspective. The case study was conducted to equip the tribal youth of Nilgiris in visual ethnography and the outcome of the experiment shared in this paper.

Keywords: visual ethnography, visual anthropology, public anthropology, multiple-interpretation, case study

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3557 Understanding Non-Utilization of AI Tools for Research and Academic Writing among Academic Staff in Nigerian Universities: A Paradigm Shift

Authors: Abubakar Abdulkareem, Nasir Haruna Soba

Abstract:

This study investigates the non-utilization of AI tools for research and academic writing among academic staff in Nigerian universities using the perceived attribute of innovation theory by Rogers as a theoretical framework to guide the investigation. This study was framed in an interpretative research paradigm. A qualitative methodology and case study research design was adopted. Interviews were conducted with 20 academic staff. The study used a thematic analysis process to identify 115 narratives. The narratives are organized into five major categories and further collapsed into five theoretical constructs explaining the non-use of AI tools for research and academic writing. Findings from this study revealed some of the reasons for the non-utilization of AI tools for research and academic writing as lack of Awareness, perceived Complexity, trust and Reliability Concerns, cost and accessibility, ethical and Privacy concerns and, cultural and institutional factors, etc.

Keywords: non-utilization, AI tools, research and academic writing, academic staff

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3556 Learning to Recommend with Negative Ratings Based on Factorization Machine

Authors: Caihong Sun, Xizi Zhang

Abstract:

Rating prediction is an important problem for recommender systems. The task is to predict the rating for an item that a user would give. Most of the existing algorithms for the task ignore the effect of negative ratings rated by users on items, but the negative ratings have a significant impact on users’ purchasing decisions in practice. In this paper, we present a rating prediction algorithm based on factorization machines that consider the effect of negative ratings inspired by Loss Aversion theory. The aim of this paper is to develop a concave and a convex negative disgust function to evaluate the negative ratings respectively. Experiments are conducted on MovieLens dataset. The experimental results demonstrate the effectiveness of the proposed methods by comparing with other four the state-of-the-art approaches. The negative ratings showed much importance in the accuracy of ratings predictions.

Keywords: factorization machines, feature engineering, negative ratings, recommendation systems

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3555 Global-Scale Evaluation of Two Satellite-Based Passive Microwave Soil Moisture Data Sets (SMOS and AMSR-E) with Respect to Modelled Estimates

Authors: A. Alyaaria, b, J. P. Wignerona, A. Ducharneb, Y. Kerrc, P. de Rosnayd, R. de Jeue, A. Govinda, A. Al Bitarc, C. Albergeld, J. Sabaterd, C. Moisya, P. Richaumec, A. Mialonc

Abstract:

Global Level-3 surface soil moisture (SSM) maps from the passive microwave soil moisture and Ocean Salinity satellite (SMOSL3) have been released. To further improve the Level-3 retrieval algorithm, evaluation of the accuracy of the spatio-temporal variability of the SMOS Level 3 products (referred to here as SMOSL3) is necessary. In this study, a comparative analysis of SMOSL3 with a SSM product derived from the observations of the Advanced Microwave Scanning Radiometer (AMSR-E) computed by implementing the Land Parameter Retrieval Model (LPRM) algorithm, referred to here as AMSRM, is presented. The comparison of both products (SMSL3 and AMSRM) were made against SSM products produced by a numerical weather prediction system (SM-DAS-2) at ECMWF (European Centre for Medium-Range Weather Forecasts) for the 03/2010-09/2011 period at global scale. The latter product was considered here a 'reference' product for the inter-comparison of the SMOSL3 and AMSRM products. Three statistical criteria were used for the evaluation, the correlation coefficient (R), the root-mean-squared difference (RMSD), and the bias. Global maps of these criteria were computed, taking into account vegetation information in terms of biome types and Leaf Area Index (LAI). We found that both the SMOSL3 and AMSRM products captured well the spatio-temporal variability of the SM-DAS-2 SSM products in most of the biomes. In general, the AMSRM products overestimated (i.e., wet bias) while the SMOSL3 products underestimated (i.e., dry bias) SSM in comparison to the SM-DAS-2 SSM products. In term of correlation values, the SMOSL3 products were found to better capture the SSM temporal dynamics in highly vegetated biomes ('Tropical humid', 'Temperate Humid', etc.) while best results for AMSRM were obtained over arid and semi-arid biomes ('Desert temperate', 'Desert tropical', etc.). When removing the seasonal cycles in the SSM time variations to compute anomaly values, better correlation with the SM-DAS-2 SSM anomalies were obtained with SMOSL3 than with AMSRM, in most of the biomes with the exception of desert regions. Eventually, we showed that the accuracy of the remotely sensed SSM products is strongly related to LAI. Both the SMOSL3 and AMSRM (slightly better) SSM products correlate well with the SM-DAS2 products over regions with sparse vegetation for values of LAI < 1 (these regions represent almost 50% of the pixels considered in this global study). In regions where LAI>1, SMOSL3 outperformed AMSRM with respect to SM-DAS-2: SMOSL3 had almost consistent performances up to LAI = 6, whereas AMSRM performance deteriorated rapidly with increasing values of LAI.

Keywords: remote sensing, microwave, soil moisture, AMSR-E, SMOS

Procedia PDF Downloads 357
3554 Parametric Template-Based 3D Reconstruction of the Human Body

Authors: Jiahe Liu, Hongyang Yu, Feng Qian, Miao Luo, Linhang Zhu

Abstract:

This study proposed a 3D human body reconstruction method, which integrates multi-view joint information into a set of joints and processes it with a parametric human body template. Firstly, we obtained human body image information captured from multiple perspectives. The multi-view information can avoid self-occlusion and occlusion problems during the reconstruction process. Then, we used the MvP algorithm to integrate multi-view joint information into a set of joints. Next, we used the parametric human body template SMPL-X to obtain more accurate three-dimensional human body reconstruction results. Compared with the traditional single-view parametric human body template reconstruction, this method significantly improved the accuracy and stability of the reconstruction.

Keywords: parametric human body templates, reconstruction of the human body, multi-view, joint

Procedia PDF Downloads 79
3553 Effect of Political and Social Context in Libya on Accounting Information System to Meet Development Needs

Authors: Bubaker F. Shareia, Almuetaz R. Boubakr

Abstract:

The aim of this paper is to show how Libya’s legal, economic, political, social, and cultural systems have shaped Libyan development. This will provide a background to develop an understanding of the current role of the accounting information system in Libya and the challenges facing the design of the aeronautical information system to meet the development needs of Libya. Our knowledge of the unified economic operating systems of the world paves the way for the economic development of every developing country. In order to achieve this understanding, every developing country should be provided with a high-efficiency communications system in order to be able to interact globally. From the point of view of the theory of globalization, Libya's understanding of its socio-economic and political systems is vital in order to be able to adopt and apply accounting techniques that will assist in the economic development of Libya.

Keywords: accounting, economic development, globalisation theory, information system

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3552 An Adaptive CFAR Algorithm Based on Automatic Censoring in Heterogeneous Environments

Authors: Naime Boudemagh

Abstract:

In this work, we aim to improve the detection performances of radar systems. To this end, we propose and analyze a novel censoring technique of undesirable samples, of priori unknown positions, that may be present in the environment under investigation. Therefore, we consider heterogeneous backgrounds characterized by the presence of some irregularities such that clutter edge transitions and/or interfering targets. The proposed detector, termed automatic censoring constant false alarm (AC-CFAR), operates exclusively in a Gaussian background. It is built to allow the segmentation of the environment to regions and switch automatically to the appropriate detector; namely, the cell averaging CFAR (CA-CFAR), the censored mean level CFAR (CMLD-CFAR) or the order statistic CFAR (OS-CFAR). Monte Carlo simulations show that the AC-CFAR detector performs like the CA-CFAR in a homogeneous background. Moreover, the proposed processor exhibits considerable robustness in a heterogeneous background.

Keywords: CFAR, automatic censoring, heterogeneous environments, radar systems

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3551 Balancing and Synchronization Control of a Two Wheel Inverted Pendulum Vehicle

Authors: Shiuh-Jer Huang, Shin-Ham Lee, Sheam-Chyun Lin

Abstract:

A two wheel inverted pendulum (TWIP) vehicle is built with two hub DC motors for motion control evaluation. Arduino Nano micro-processor is chosen as the control kernel for this electric test plant. Accelerometer and gyroscope sensors are built in to measure the tilt angle and angular velocity of the inverted pendulum vehicle. Since the TWIP has significantly hub motor dead zone and nonlinear system dynamics characteristics, the vehicle system is difficult to control by traditional model based controller. The intelligent model-free fuzzy sliding mode controller (FSMC) was employed as the main control algorithm. Then, intelligent controllers are designed for TWIP balance control, and two wheels synchronization control purposes.

Keywords: balance control, synchronization control, two-wheel inverted pendulum, TWIP

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3550 Learning Environments in the Early Years: A Case Study of an Early Childhood Centre in Australia

Authors: Mingxi Xiao

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Children’s experiences in the early years build and shape the brain. The early years learning environment plays a significantly important role in children’s development. A well-constructed environment will facilitate children’s physical and mental well-being. This case study used an early learning centre in Australia called SDN Hurstville as an example, describing the learning environment in the centre, as well as analyzing the functions of the affordances. In addition, this report talks about the sustainability of learning in the centre, and how the environment supports cultural diversity and indigenous learning. The early years for children are significant. Different elements in the early childhood centre should work together to help children develop better. This case study found that the natural environment and the artificial environment are both critical to children; only when they work together can children have better development in physical and mental well-being and have a sense of belonging when playing and learning in the centre.

Keywords: early childhood center, early childhood education, learning environment, Australia

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3549 A New Framework for ECG Signal Modeling and Compression Based on Compressed Sensing Theory

Authors: Siavash Eftekharifar, Tohid Yousefi Rezaii, Mahdi Shamsi

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The purpose of this paper is to exploit compressed sensing (CS) method in order to model and compress the electrocardiogram (ECG) signals at a high compression ratio. In order to obtain a sparse representation of the ECG signals, first a suitable basis matrix with Gaussian kernels, which are shown to nicely fit the ECG signals, is constructed. Then the sparse model is extracted by applying some optimization technique. Finally, the CS theory is utilized to obtain a compressed version of the sparse signal. Reconstruction of the ECG signal from the compressed version is also done to prove the reliability of the algorithm. At this stage, a greedy optimization technique is used to reconstruct the ECG signal and the Mean Square Error (MSE) is calculated to evaluate the precision of the proposed compression method.

Keywords: compressed sensing, ECG compression, Gaussian kernel, sparse representation

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3548 Associations Between Pornography Use Motivations and Sexual Satisfaction in Gender Diverse and Cisgender Individuals in the 43-Country International Sex Survey

Authors: Aurélie Michaud, Émilie Gaudet, Mónika Koós, Léna Nagy, Zsolt Demetrovics, Shane W. Kraus, Marc N. Potenza, Beáta Bőthe

Abstract:

Pornography use is prevalent among adults worldwide. Prior studies have assessed the associations between pornography use frequency and sexual satisfaction, in cisgender and heterosexual individuals, with mixed results. However, measuring pornography use solely by pornography use frequency is problematic, as it can lead to disregarding important contextual factors that may be related to pornography use’s potential effects. Pornography use motivations (PUMs) represent key predictors of sexual behaviors. Yet, their associations with different indicators of sexual wellbeing have yet to be extensively studied. This cross-cultural study examined the links between the eight PUMs most often reported in the general population (i.e. sexual pleasure, sexual curiosity, emotional distraction or suppression, fantasy, stress reduction, boredom avoidance, lack of sexual satisfaction, and self-exploration) and sexual satisfaction in gender diverse and cisgender individuals. Given the lack of scientific data on associations between individuals’ PUMs and sexual satisfaction, these links were examined in an exploratory manner. A total of 43 countries from five continents were included in the International Sex Survey (ISS). A secure online platform was used to collect self-report, anonymous data from 82,243 participants (39.6% men, 57% women, 3.4% gender diverse individuals; M = 32.4 years, SD = 12.5). Gender-based differences in levels of sexual pleasure, sexual curiosity, emotional distraction, fantasy, stress reduction, boredom avoidance, lack of sexual satisfaction, and self-exploration PUMs were examined using one-way ANOVAs. Then, for each gender group, the associations between each PUM and sexual satisfaction were examined using multiple linear regression, controlling for frequency of masturbation. One-way ANOVAs indicated significant differences between men, women, and gender diverse individuals on all PUMs. For sexual pleasure, sexual curiosity, fantasy, boredom avoidance, lack of sexual satisfaction, emotional distraction, and stress reduction PUMs, men showed the highest scores, followed by gender-diverse individuals, and women. However, for self-exploration, gender-diverse individuals had higher average scores than men. For all PUMs, women’s average scores were the lowest. After controlling for frequency of masturbation, for all genders, sexual pleasure, sexual curiosity and boredom avoidance were significant positive predictors of sexual satisfaction, while lack of sexual satisfaction PUM was a significant negative predictor. Fantasy, stress reduction and self-exploration PUMs were positive significant predictors of sexual satisfaction, and fantasy was a negative significant predictor, but only for women. Findings highlight important gender differences in regards to the main motivations underlying pornography use and their relations to sexual satisfaction. While men and gender diverse individuals show similar motivation profiles, woman report a particularly unique experience, with fantasy, stress reduction and self-exploration being associated to their sexual satisfaction. This work outlines the importance of considering the role of pornography use motivations when studying the links between pornography viewing and sexual well-being, and may provide basis for gender-based considerations when working with individuals seeking help for their pornography use or sexual satisfaction.

Keywords: pornography, sexual satifsaction, cross-cultural, gender diversity

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3547 Context-Aware Recommender System Using Collaborative Filtering, Content-Based Algorithm and Fuzzy Rules

Authors: Xochilt Ramirez-Garcia, Mario Garcia-Valdez

Abstract:

Contextual recommendations are implemented in Recommender Systems to improve user satisfaction, recommender system makes accurate and suitable recommendations for a particular situation reaching personalized recommendations. The context provides information relevant to the Recommender System and is used as a filter for selection of relevant items for the user. This paper presents a Context-aware Recommender System, which uses techniques based on Collaborative Filtering and Content-Based, as well as fuzzy rules, to recommend items inside the context. The dataset used to test the system is Trip Advisor. The accuracy in the recommendations was evaluated with the Mean Absolute Error.

Keywords: algorithms, collaborative filtering, intelligent systems, fuzzy logic, recommender systems

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3546 Using Historical Data for Stock Prediction

Authors: Sofia Stoica

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In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices in the past five years of ten major tech companies – Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We experimented with a variety of models– a linear regressor model, K nearest Neighbors (KNN), a sequential neural network – and algorithms - Multiplicative Weight Update, and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: finance, machine learning, opening price, stock market

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3545 Multiple Empowerments: How Work Team Shapes the Village Governance in China

Authors: Yang Liu

Abstract:

The work team has been being adopted by the CCP for special missions in a limited time. Since the 18th National Congress of CCP, the unprecedented practice of the work team has had impacts beyond the original goal of poverty alleviation, their functions in village governance have still not been well studied. As the state agents that come from the outside of the village community, this article argues that the work team is a group that represents the coexistence of political, economic, and cultural capital, which contributes to effectively empower the state, and the village cadres and the peasants. For the state, more accurate bottom-up information could be collected by the work team, and policies could be made scientifically and implemented without distortion. For the village cadres, they can learn leadership skills and share more resources owned or mobilized by the work team. For the peasants, they have more access to participate the public affairs of their village and express their claims. The multiple empowerments have greatly improved the relationship among the state, the peasants, and the village cadres since a series of reforms from 1980s to 2000s that alienated the relationship among them.

Keywords: state, village cadre, empowerment, work team, peasants

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3544 Prediction of the Tunnel Fire Flame Length by Hybrid Model of Neural Network and Genetic Algorithms

Authors: Behzad Niknam, Kourosh Shahriar, Hassan Madani

Abstract:

This paper demonstrates the applicability of Hybrid Neural Networks that combine with back propagation networks (BPN) and Genetic Algorithms (GAs) for predicting the flame length of tunnel fire A hybrid neural network model has been developed to predict the flame length of tunnel fire based parameters such as Fire Heat Release rate, air velocity, tunnel width, height and cross section area. The network has been trained with experimental data obtained from experimental work. The hybrid neural network model learned the relationship for predicting the flame length in just 3000 training epochs. After successful learning, the model predicted the flame length.

Keywords: tunnel fire, flame length, ANN, genetic algorithm

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3543 A Simple Recursive Framework to Generate Gray Codes for Weak Orders in Constant Amortized Time

Authors: Marsden Jacques, Dennis Wong

Abstract:

A weak order is a way to rank n objects where ties are allowed. In this talk, we present a recursive framework to generate Gray codes for weak orders. We then describe a simple algorithm based on the framework that generates 2-Gray codes for weak orders in constant amortized time per string. This framework can easily be modified to generate other Gray codes for weak orders. We provide an example on using the framework to generate the first Shift Gray code for weak orders, also in constant amortized time, where consecutive strings differ by a shift or a symbol change.

Keywords: weak order, Cayley permutation, Gray code, shift Gray code

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3542 Accounting for Downtime Effects in Resilience-Based Highway Network Restoration Scheduling

Authors: Zhenyu Zhang, Hsi-Hsien Wei

Abstract:

Highway networks play a vital role in post-disaster recovery for disaster-damaged areas. Damaged bridges in such networks can disrupt the recovery activities by impeding the transportation of people, cargo, and reconstruction resources. Therefore, rapid restoration of damaged bridges is of paramount importance to long-term disaster recovery. In the post-disaster recovery phase, the key to restoration scheduling for a highway network is prioritization of bridge-repair tasks. Resilience is widely used as a measure of the ability to recover with which a network can return to its pre-disaster level of functionality. In practice, highways will be temporarily blocked during the downtime of bridge restoration, leading to the decrease of highway-network functionality. The failure to take downtime effects into account can lead to overestimation of network resilience. Additionally, post-disaster recovery of highway networks is generally divided into emergency bridge repair (EBR) in the response phase and long-term bridge repair (LBR) in the recovery phase, and both of EBR and LBR are different in terms of restoration objectives, restoration duration, budget, etc. Distinguish these two phases are important to precisely quantify highway network resilience and generate suitable restoration schedules for highway networks in the recovery phase. To address the above issues, this study proposes a novel resilience quantification method for the optimization of long-term bridge repair schedules (LBRS) taking into account the impact of EBR activities and restoration downtime on a highway network’s functionality. A time-dependent integer program with recursive functions is formulated for optimally scheduling LBR activities. Moreover, since uncertainty always exists in the LBRS problem, this paper extends the optimization model from the deterministic case to the stochastic case. A hybrid genetic algorithm that integrates a heuristic approach into a traditional genetic algorithm to accelerate the evolution process is developed. The proposed methods are tested using data from the 2008 Wenchuan earthquake, based on a regional highway network in Sichuan, China, consisting of 168 highway bridges on 36 highways connecting 25 cities/towns. The results show that, in this case, neglecting the bridge restoration downtime can lead to approximately 15% overestimation of highway network resilience. Moreover, accounting for the impact of EBR on network functionality can help to generate a more specific and reasonable LBRS. The theoretical and practical values are as follows. First, the proposed network recovery curve contributes to comprehensive quantification of highway network resilience by accounting for the impact of both restoration downtime and EBR activities on the recovery curves. Moreover, this study can improve the highway network resilience from the organizational dimension by providing bridge managers with optimal LBR strategies.

Keywords: disaster management, highway network, long-term bridge repair schedule, resilience, restoration downtime

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3541 Using Cooperation Approaches at Different Levels of Artificial Bee Colony Method

Authors: Vahid Zeighami, Mohsen Ghsemi, Reza Akbari

Abstract:

In this work, a Multi-Level Artificial Bee Colony (called MLABC) is presented. In MLABC two species are used. The first species employs n colonies in which each of the them optimizes the complete solution vector. The cooperation between these colonies is carried out by exchanging information through a leader colony, which contains a set of elite bees. The second species uses a cooperative approach in which the complete solution vector is divided to k sub-vectors, and each of these sub-vectors is optimized by a a colony. The cooperation between these colonies is carried out by compiling sub-vectors into the complete solution vector. Finally, the cooperation between two species is obtained by exchanging information between them. The proposed algorithm is tested on a set of well known test functions. The results show that MLABC algorithms provide efficiency and robustness to solve numerical functions.

Keywords: artificial bee colony, cooperative, multilevel cooperation, vector

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3540 Discovering the Effects of Meteorological Variables on the Air Quality of Bogota, Colombia, by Data Mining Techniques

Authors: Fabiana Franceschi, Martha Cobo, Manuel Figueredo

Abstract:

Bogotá, the capital of Colombia, is its largest city and one of the most polluted in Latin America due to the fast economic growth over the last ten years. Bogotá has been affected by high pollution events which led to the high concentration of PM10 and NO2, exceeding the local 24-hour legal limits (100 and 150 g/m3 each). The most important pollutants in the city are PM10 and PM2.5 (which are associated with respiratory and cardiovascular problems) and it is known that their concentrations in the atmosphere depend on the local meteorological factors. Therefore, it is necessary to establish a relationship between the meteorological variables and the concentrations of the atmospheric pollutants such as PM10, PM2.5, CO, SO2, NO2 and O3. This study aims to determine the interrelations between meteorological variables and air pollutants in Bogotá, using data mining techniques. Data from 13 monitoring stations were collected from the Bogotá Air Quality Monitoring Network within the period 2010-2015. The Principal Component Analysis (PCA) algorithm was applied to obtain primary relations between all the parameters, and afterwards, the K-means clustering technique was implemented to corroborate those relations found previously and to find patterns in the data. PCA was also used on a per shift basis (morning, afternoon, night and early morning) to validate possible variation of the previous trends and a per year basis to verify that the identified trends have remained throughout the study time. Results demonstrated that wind speed, wind direction, temperature, and NO2 are the most influencing factors on PM10 concentrations. Furthermore, it was confirmed that high humidity episodes increased PM2,5 levels. It was also found that there are direct proportional relationships between O3 levels and wind speed and radiation, while there is an inverse relationship between O3 levels and humidity. Concentrations of SO2 increases with the presence of PM10 and decreases with the wind speed and wind direction. They proved as well that there is a decreasing trend of pollutant concentrations over the last five years. Also, in rainy periods (March-June and September-December) some trends regarding precipitations were stronger. Results obtained with K-means demonstrated that it was possible to find patterns on the data, and they also showed similar conditions and data distribution among Carvajal, Tunal and Puente Aranda stations, and also between Parque Simon Bolivar and las Ferias. It was verified that the aforementioned trends prevailed during the study period by applying the same technique per year. It was concluded that PCA algorithm is useful to establish preliminary relationships among variables, and K-means clustering to find patterns in the data and understanding its distribution. The discovery of patterns in the data allows using these clusters as an input to an Artificial Neural Network prediction model.

Keywords: air pollution, air quality modelling, data mining, particulate matter

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