Search results for: algorithm symbol recognition

Authors: Sukhleen Kaur

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In security groundwork, Intrusion Detection System (IDS) has become an important component. The IDS has received increasing attention in recent years. IDS is one of the effective way to detect different kinds of attacks and malicious codes in a network and help us to secure the network. Data mining techniques can be implemented to IDS, which analyses the large amount of data and gives better results. Data mining can contribute to improving intrusion detection by adding a level of focus to anomaly detection. So far the study has been carried out on finding the attacks but this paper detects the malicious files. Some intruders do not attack directly, but they hide some harmful code inside the files or may corrupt those file and attack the system. These files are detected according to some defined parameters which will form two lists of files as normal files and harmful files. After that data mining will be performed. In this paper a hybrid classifier has been used via Naive Bayes and Ripper classification methods. The results show how the uploaded file in the database will be tested against the parameters and then it is characterised as either normal or harmful file and after that the mining is performed. Moreover, when a user tries to mine on harmful file it will generate an exception that mining cannot be made on corrupted or harmful files.

Keywords: data mining, association, classification, clustering, decision tree, intrusion detection system, misuse detection, anomaly detection, naive Bayes, ripper

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Authors: Flora Paganelli

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The radiometric performance of remotely sensed images is important for volcanic monitoring. The Thermal Infrared Sensor (TIRS) on-board Landsat 8 was designed with specific requirements in regard to the noise-equivalent change in temperature (NEΔT) at ≤ 0.4 K at 300 K for the two thermal infrared bands B10 and B11. This study investigated the on-orbit NEΔT of the TIRS two bands from a scene-based method using clear-sky images over the volcanic activity of Kīlauea Volcano and the active East Rift Zone (Hawaii), in order to optimize the use of TIRS data. Results showed that the NEΔTs of the two bands exceeded the design specification by an order of magnitude at 300 K. Both separate bands and split window algorithm were examined to estimate the effect of NEΔT on the land surface temperature (LST) retrieval, and NEΔT contribution to the final LST error. These results were also useful in the current efforts to assess the requirements for volcanology research campaign using the Hyperspectral Infrared Imager (HyspIRI) whose airborne prototype MODIS/ASTER instruments is plan to be flown by NASA as a single campaign to the Hawaiian Islands in support of volcanology and coastal area monitoring in 2016.

Keywords: landsat 8, radiometric performance, thermal infrared sensor (TIRS), volcanology

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Authors: Bruk Gebregziabher

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The safe and efficient operation of Autonomous Mobile Robots (AMRs) in complex environments, such as manufacturing, logistics, and agriculture, necessitates accurate multiobject tracking and predictive collision avoidance. This paper presents algorithms and techniques for addressing these challenges using Lidar sensor data, emphasizing ensemble Kalman filter. The developed predictive collision avoidance algorithm employs the data provided by lidar sensors to track multiple objects and predict their velocities and future positions, enabling the AMR to navigate safely and effectively. A modification to the dynamic windowing approach is introduced to enhance the performance of the collision avoidance system. The overall system architecture encompasses object detection, multi-object tracking, and predictive collision avoidance control. The experimental results, obtained from both simulation and real-world data, demonstrate the effectiveness of the proposed methods in various scenarios, which lays the foundation for future research on global planners, other controllers, and the integration of additional sensors. This thesis contributes to the ongoing development of safe and efficient autonomous systems in complex and dynamic environments.

Keywords: autonomous mobile robots, multi-object tracking, predictive collision avoidance, ensemble Kalman filter, lidar sensors

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Authors: Aoqi Zhang, Changgil Lee Lee, Seunghee Park

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A non-contact nondestructive technique using laser-induced ultrasonic wave generation method was applied to visualize corrosion damage at aluminum alloy plate structures. The ultrasonic waves were generated by a Nd:YAG pulse laser, and a galvanometer-based laser scanner was used to scan specific area at a target structure. At the same time, wave responses were measured at a piezoelectric sensor which was attached on the target structure. The visualization of structural damage was achieved by calculating logarithmic values of root mean square (RMS). Damage-sensitive feature was defined as the scattering characteristics of the waves that encounter corrosion damage. The corroded damage was artificially formed by hydrochloric acid. To observe the effect of the location where the corrosion was formed, the both sides of the plate were scanned with same scanning area. Also, the effect on the depth of the corrosion was considered as well as the effect on the size of the corrosion. The results indicated that the damages were successfully visualized for almost cases, whether the damages were formed at the front or back side. However, the damage could not be clearly detected because the depth of the corrosion was shallow. In the future works, it needs to develop signal processing algorithm to more clearly visualize the damage by improving signal-to-noise ratio.

Keywords: non-destructive testing, corrosion, pulsed laser scanning, ultrasonic waves, plate structure

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Authors: Subhankar Kumar Sarkar

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Beetles of the subfamily Dynastinae under the family Scarabaeidae of the insect order Coleoptera are popularly known as ‘Rhinoceros beetles’ because of the characteristic horn borne by the males on their head. These horns are dedicated in mating battle against other males and have evolved as a result of phenotypic plasticity. Scarabaeidae is the largest of all families under Coleoptera and is composed of 11 subfamilies, of which the subfamily Dynastinae is represented by approximately 300 species. Some of these beetles have been reported to cause considerable damage to agriculture and forestry both in their larval and adult stages, while many of them are beneficial as they pollinate plants and recycle plant materials. Eastern Himalayas is regarded as one of the 35 biodiversity hotspot zones of the world and one of the four of India, which is exhibited by its rich and megadiverse tropical forests. However, our knowledge on the faunal diversity of these forests is very limited, particularly for the insect fauna. One such tropical forest of Eastern Himalayas is the ‘Buxa Tiger Reserve’ located between latitudes 26°30” to 26°55” North and Longitudes 89°20” to 89˚35” East of India and occupies an area of about 759.26 square kilometers. It is with this background an attempt has been made to explore the insect fauna of the forest. Insect sampling was carried out in each beat and range of Buxa Tiger Reserve in all the three seasons viz, Premonsoon, Monsoon, and Postmonsoon. Sample collections were done by sweep nets, hand picking technique and pit fall traps. UV light trap was used to collect the nocturnal insects. Morphological examinations of the collected samples were carried out with Stereozoom Binocular Microscopes (Zeiss SV6 and SV11) and were identified up to species level with the aid of relevant literature. Survey of the insect fauna of the forest resulted in the recognition of 76 scarab species, of which 8 belong to the subfamily dealt herein. Each of the 8 species represents a separate genus. The forest is dominated by the members of Xylotrupes gideon (Linnaeus) as is represented by highest number of individuals. The recorded taxa show about 12% endemism and are of mainly oriental in distribution. Premonsoon is the most favorable season for their occurrence and activity followed by Monsoon and Postmonsoon.

Keywords: Dynastinae, Scarabaeidae, diversity, Buxa Tiger Reserve

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Authors: Iqbal Pramukti, Mamat Lukman, Hasniatisari Harun, Kusman Ibrahim

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Introduction: People living with HIV had a higher risk of osteoporotic fracture than the general population. The purpose of this study was to predict the 10-year risk of fracture among people living with HIV (PLWH) using FRAX™ and to identify characteristics related to the fracture risk. Methodology: This study consisted of 75 subjects. The ten-year probability of major osteoporotic fractures (MOF) and hip fractures was assessed using the FRAX™ algorithm. A cross-tabulation was used to identify the participant’s characteristics related to fracture risk. Results: The overall mean 10-year probability of fracture was 2.4% (1.7) for MOF and 0.4% (0.3) for hip fractures. For MOF score, participants with parents’ hip fracture history, smoking behavior and glucocorticoid use showed a higher MOF score than those who were not (3.1 vs. 2.5; 4.6 vs 2.5; and 3.4 vs 2.5, respectively). For HF score, participants with parents’ hip fracture history, smoking behavior and glucocorticoid use also showed a higher HF score than those who were not (0.5 vs. 0.3; 0.8 vs. 0.3; and 0.5 vs. 0.3, respectively). Conclusions: The 10-year risk of fracture was higher among PLWH with several factors, including the parent’s hip. Fracture history, smoking behavior and glucocorticoid used. Further analysis on determining factors using multivariate regression analysis with a larger sample size is required to confirm the factors associated with the high fracture risk.

Keywords: HIV, PLWH, osteoporotic fractures, hip fractures, 10-year risk of fracture, FRAX

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Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

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This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: river stage-discharge process, LSSVM, discrete wavelet transform, Ensemble Empirical Decomposition Mode, multi-station modeling

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Authors: Prama Mukhopadhyay

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Starting from transport to food, today’s world platform economy and digital markets have taken over almost every sphere of consumers’ lives. Sellers and buyers are getting connected through platforms, which is acting as an intermediary. It has made consumer’s life easier in terms of time, price, choice and other factors. Having said that, there are several concerns regarding platforms. There are competition law concerns like unfair pricing, deep discounting by the platforms which affect the consumer welfare. Apart from that, the biggest problem is lack of transparency with respect to the business models, how it operates, price calculation, etc. In most of the cases, consumers are unaware of how their personal data are being used. In most of the cases, they are unaware of how algorithm uses their personal data to determine the price of the product or even to show the relevant products using their previous searches. Using personal or non-personal data without consumer’s consent is a huge legal concern. In addition to this, another major issue lies with the question of liability. If a dispute arises, who will be responsible? The seller or the platform? For example, if someone ordered food through a food delivery app and the food was bad, in this situation who will be liable: the restaurant or the food delivery platform? In this paper, the researcher tries to examine the legal concern related to platform economy from the consumer protection and consumer welfare perspectives. The paper analyses the cases from different jurisdictions and approach taken by the judiciaries. The author compares the existing legislation of EU, US and other Asian Countries and tries to highlight the best practices.

Keywords: competition, consumer, data, platform

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Authors: Handie Pramana Putra, Ani Dijah Rahajoe

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The proliferation of smart devices and advancements in mobile communication technologies have permeated various facets of life with the widespread influence of e-commerce. Detecting abnormal transactions holds paramount significance in this realm due to the potential for substantial financial losses. Moreover, the fusion of data flow and control flow assumes a critical role in the exploration of process modeling and data analysis, contributing significantly to the accuracy and security of business processes. This paper introduces an alternative approach to identify abnormal transactions through a model that integrates both data and control flows. Referred to as the Extended Data Petri net (DPNE), our model encapsulates the entire process, encompassing user login to the e-commerce platform and concluding with the payment stage, including the mobile transaction process. We scrutinize the model's structure, formulate an algorithm for detecting anomalies in pertinent data, and elucidate the rationale and efficacy of the comprehensive system model. A case study validates the responsive performance of each system component, demonstrating the system's adeptness in evaluating every activity within mobile transactions. Ultimately, the results of anomaly detection are derived through a thorough and comprehensive analysis.

Keywords: database, data analysis, DPNE, extended data flow, e-commerce

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Authors: Seungwoo Kim, Yeongcheol Cho

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In this paper, a holonomic mobile robot is designed in omnidirectional wheels and an adaptive fuzzy controller is presented for its precise trajectories. A kind of adaptive controller based on fuzzy multi-layered algorithm is used to solve the big parametric uncertainty of motor-controlled dynamic system of 3-wheels omnidirectional mobile robot. The system parameters such as a tracking force are so time-varying due to the kinematic structure of omnidirectional wheels. The fuzzy adaptive control method is able to solve the problems of classical adaptive controller and conventional fuzzy adaptive controllers. The basic idea of new adaptive control scheme is that an adaptive controller can be constructed with parallel combination of robust controllers. This new adaptive controller uses a fuzzy multi-layered architecture which has several independent fuzzy controllers in parallel, each with different robust stability area. Out of several independent fuzzy controllers, the most suited one is selected by a system identifier which observes variations in the controlled system parameter. This paper proposes a design procedure which can be carried out mathematically and systematically from the model of a controlled system. Finally, the good performance of a holonomic mobile robot is confirmed through live tests of the tracking control task.

Keywords: fuzzy adaptive control, fuzzy multi-layered controller, holonomic mobile robot, omnidirectional wheels, robustness and stability.

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Authors: Salman Hameed

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In this paper, a self-tuning fuzzy PI controller (STFPIC) is proposed for thyristor controlled series capacitor (TCSC) to improve power system dynamic performance. In a STFPIC controller, the output scaling factor is adjusted on-line by an updating factor (α). The value of α is determined from a fuzzy rule-base defined on error (e) and change of error (Δe) of the controlled variable. The proposed self-tuning controller is designed using a very simple control rule-base and the most natural and unbiased membership functions (MFs) (symmetric triangles with equal base and 50% overlap with neighboring MFs). The comparative performances of the proposed STFPIC and the standard fuzzy PI controller (FPIC) have been investigated on a multi-machine power system (namely, 4 machine two area system) through detailed non-linear simulation studies using MATLAB/SIMULINK. From the simulation studies it has been found out that for damping oscillations, the performance of the proposed STFPIC is better than that obtained by the standard FPIC. Moreover, the proposed STFPIC as well as the FPIC have been found to be quite effective in damping oscillations over a wide range of operating conditions and are quite effective in enhancing the power carrying capability of the power system significantly.

Keywords: genetic algorithm, power system stability, self-tuning fuzzy controller, thyristor controlled series capacitor

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Authors: Shan Jia, Jinbao Chen, Jinhua Zhou, Jiacheng Qian

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In response to the functional limitations of the fixed landers, those are to expand the detection range by the use of wheeled rovers with unavoidable path-repeatability in deep space exploration currently, a movable lander based on the leg-foot walking mechanism is presented. Firstly, a quadruped landing mechanism based on pushrod-damping is proposed. The configuration is of the bionic characteristics such as hip, knee and ankle joints, and the multi-function main/auxiliary buffers based on the crumple-energy absorption and screw-nut mechanism. Secondly, the workspace of the end of the leg-foot mechanism is solved by Monte Carlo method, and the key points on the desired trajectory of the end of the leg-foot mechanism are fitted by cubic spline curve. Finally, an optimal time-jerk trajectory based on weight coefficient is planned and analyzed by an adaptive genetic algorithm (AGA). The simulation results prove the rationality and stability of walking motion of the movable leg-foot lander in the star catalogue. In addition, this research can also provide a technical solution integrating of soft-landing, large-scale inspection and material transfer for future star catalogue exploration, and can even serve as the technical basis for developing the reusable landers.

Keywords: motion performance, trajectory planning, movable, leg-foot lander

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Authors: Yao-Hong Tsai

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Due to the sensor technology, video surveillance has become the main way for security control in every big city in the world. Surveillance is usually used by governments for intelligence gathering, the prevention of crime, the protection of a process, person, group or object, or the investigation of crime. Many surveillance systems based on computer vision technology have been developed in recent years. Moving target tracking is the most common task for Unmanned Aerial Vehicle (UAV) to find and track objects of interest in mobile aerial surveillance for civilian applications. The paper is focused on vision-based collision avoidance for UAVs by recurrent neural networks. First, images from cameras on UAV were fused based on deep convolutional neural network. Then, a recurrent neural network was constructed to obtain high-level image features for object tracking and extracting low-level image features for noise reducing. The system distributed the calculation of the whole system to local and cloud platform to efficiently perform object detection, tracking and collision avoidance based on multiple UAVs. The experiments on several challenging datasets showed that the proposed algorithm outperforms the state-of-the-art methods.

Keywords: unmanned aerial vehicle, object tracking, deep learning, collision avoidance

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Authors: Sandra Thompson, Paul Dervan

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Ireland’s first Technological University (TU Dublin) was established on 1st January 2019, and its creation is an exciting new milestone in Irish Higher Education. TU Dublin is now Ireland’s biggest University supporting 29,000 students across three campuses with 3,500 staff. The University aspires to create work-ready graduates who are socially responsible, open-minded global thinkers who are ambitious to change the world for the better. As graduates, they will be enterprising and daring in all their endeavors, ready to play their part in transforming the future. Feedback from Irish employers and students coupled with evidence from other authoritative sources such as the World Economic Forum points to a need for greater focus on the development of students’ employability skills as they prepare for today’s work environment. Moreover, with an increased focus on Universal Design for Learning (UDL) and inclusiveness, there is recognition that students are more than a numeric grade value. Robust grading systems have been developed to track a student’s performance around discipline knowledge but there is little or no global consensus on a definition of transversal skills nor on a unified framework to assess transversal skills. Education and industry sectors are often assessing one or two skills, and some are developing their own frameworks to capture the learner’s achievement in this area. Technological University Dublin (TU Dublin) have discovered and implemented a framework to allow students to develop, assess and record their transversal skills using transformative learning theory. The model implemented is an adaptation of Student Transformative Learning Record - STLR which originated in the University of Central Oklahoma (UCO). The purpose of this paper therefore, is to examine the views of students, staff and employers in the context of deploying a Transformative Learning model within the University to assess transversal skills. It will examine the initial impact the transformative learning model is having socially, personally and on the University as an organization. Crucially also, to identify lessons learned from the deployment in order to assist other Universities and Higher Education Institutes who may be considering a focused adoption of Transformative Learning to meet the challenge of preparing students for today’s work environment.

Keywords: assessing transversal skills, higher education, transformative learning, students

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Authors: Shreyansh Bharadwaj, Raghavendra Kollipara, Sijoy C. D., R. K. Mittal

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Utilizing the Lorentz force to propel an electrically conductive plunger through a solenoid represents a fundamental application in electromagnetism. The parameters of the solenoid significantly influence the force exerted on the plunger, impacting its response. A parametric study has been done to understand the effect of these parameters on the force acting on the plunger. This study is done to determine the most optimal combination of parameters to obtain the fast response. Analysis has been carried out using an algorithm capable of simulating the scenario of a plunger undergoing acceleration within a solenoid. Authors have conducted an analysis focusing on several key configuration parameters of the solenoid. These parameters include the inter-layer gap (in the case of a multi-turn solenoid), different conductor diameters, varying numbers of turns, and diverse numbers of layers. Primary objective of this paper is to discern how alterations in these parameters affect the force applied to the plunger. Through extensive numerical simulations, a dataset has been generated and utilized to construct informative plots. These plots provide visual representations of the relationships between the solenoid configuration parameters and the resulting force exerted on the plunger, which can further be used to deduce scaling laws. This research endeavors to offer valuable insights into optimizing solenoid configurations for enhanced electromagnetic acceleration, thereby contributing to advancements in electromagnetic propulsion technology.

Keywords: Lorentz force, solenoid configuration, electromagnetic acceleration, parametric analysis, simulation

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Authors: Alena Zemanová, Jan Zeman, Michal Šejnoha

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The polymer foil used for manufacturing of laminated glass members behaves in a viscoelastic manner with temperature dependence. This contribution aims at incorporating the time/temperature-dependent behavior of interlayer to our earlier elastic finite element model for laminated glass beams. The model is based on a refined beam theory: each layer behaves according to the finite-strain shear deformable formulation by Reissner and the adjacent layers are connected via the Lagrange multipliers ensuring the inter-layer compatibility of a laminated unit. The time/temperature-dependent behavior of the interlayer is accounted for by the generalized Maxwell model and by the time-temperature superposition principle due to the Williams, Landel, and Ferry. The resulting system is solved by the Newton method with consistent linearization and the viscoelastic response is determined incrementally by the exponential algorithm. By comparing the model predictions against available experimental data, we demonstrate that the proposed formulation is reliable and accurately reproduces the behavior of the laminated glass units.

Keywords: finite element method, finite-strain Reissner model, Lagrange multipliers, generalized Maxwell model, laminated glass, Newton method, Williams-Landel-Ferry equation

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Authors: Haniyeh Parhizkar

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When Sarris came up with the "auteur theory" in 1962, he emphasized that the utmost premise of auteur theory is the inner meanings and concepts of a film and that a film is purely an art form. Today's mainstream movies are conceptually closer to what the Frankfurt School scholars regarded as "reproduced" and "mass culture" years ago. Hollywood goes on to be a huge movie-making machine that leads the dominant paradigms of films throughout the world and cinema is far from art. Although there are still movies, directors, and audiences who favor art cinema over Hollywood and mainstream movies, it's an almost undeniable fact that, for the most part, people's perception of movies is widely influenced by their American depiction and Hollywood's legacy of mass culture. With the uprising of Hollywood studios as the forerunners of the movie industry and cinema being largely dependent on economics rather than artistic values, this distinctive role of cinema has diminished and is replaced with a global standard. The Blockbuster 2022 film, 'Everything, Everywhere, All at Once' is now the most-awarded movie of all time, winning seven Oscars at the 95th Academy Awards. Despite its main cast being Asian, the movie is produced by American incorporation and is heavily influenced by Hollywood's dominant themes of superheroes, fantasy, action, and adventure. The New Yorker film critic, Richard Brody, called the movie "a pitch for a Marvel" and critiqued the film for being "universalized" and "empty of history and culture". Other critics of Variety pinpointed the movie's similarities to Marvel, particularly in their storylines of multi-universe which manifest traces of American legacy. As argued by these critics, 'Everything, Everywhere, All at Once' might appear as a unique and authentic film at first glance, but it can be argued that it is yet another version of a Marvel movie. While the movie's universal acclaim was regarded as recognition and an acknowledgment of its Asian cast, the issue that arises here is when the Hollywood influences and American themes are so robust in the film, is the movie industry honoring another culture or is it yet another celebration of Hollywood's dominant paradigm. This essay will employ a critical approach to Hollywood's dominance and mass-produced culture, which has deprived authenticity of non-American movies and is constantly reproducing the same formula of success.

Keywords: hollywoodization, universalization, blockbuster, dominant paradigm, marvel, authenticity, diversity

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

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With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: activities of daily living, classification, internet of things, machine learning, prediction, smart home

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Authors: Tobias Strübing, Fatemeh Ziaeetabar

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Humans usually manipulate objects with their hands. To represent these actions in a simple and understandable way, we need to use a semantic framework. For this purpose, the Semantic Event Chain (SEC) method has already been presented which is done by consideration of touching and non-touching relations between manipulated objects in a scene. This method was improved by a computational model, the so-called enriched Semantic Event Chain (eSEC), which incorporates the information of static (e.g. top, bottom) and dynamic spatial relations (e.g. moving apart, getting closer) between objects in an action scene. This leads to a better action prediction as well as the ability to distinguish between more actions. Each eSEC manipulation descriptor is a huge matrix with thirty rows and a massive set of the spatial relations between each pair of manipulated objects. The current eSEC framework has so far only been used in the category of manipulation actions, which eventually involve two hands. Here, we would like to extend this approach to a whole body action descriptor and make a conjoint activity representation structure. For this purpose, we need to do a statistical analysis to modify the current eSEC by summarizing while preserving its features, and introduce a new version called Enhanced eSEC or (e2SEC). This summarization can be done from two points of the view: 1) reducing the number of rows in an eSEC matrix, 2) shrinking the set of possible semantic spatial relations. To achieve these, we computed the importance of each matrix row in an statistical way, to see if it is possible to remove a particular one while all manipulations are still distinguishable from each other. On the other hand, we examined which semantic spatial relations can be merged without compromising the unity of the predefined manipulation actions. Therefore by performing the above analyses, we made the new e2SEC framework which has 20% fewer rows, 16.7% less static spatial and 11.1% less dynamic spatial relations. This simplification, while preserving the salient features of a semantic structure in representing actions, has a tremendous impact on the recognition and prediction of complex actions, as well as the interactions between humans and robots. It also creates a comprehensive platform to integrate with the body limbs descriptors and dramatically increases system performance, especially in complex real time applications such as human-robot interaction prediction.

Keywords: enriched semantic event chain, semantic action representation, spatial relations, statistical analysis

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Authors: Showkat Ahmad Lone, Ahmadur Rahman, Ariful Islam

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The major assumption in accelerated life tests (ALT) is that the mathematical model relating the lifetime of a test unit and the stress are known or can be assumed. In some cases, such life–stress relationships are not known and cannot be assumed, i.e. ALT data cannot be extrapolated to use condition. So, in such cases, partially accelerated life test (PALT) is a more suitable test to be performed for which tested units are subjected to both normal and accelerated conditions. This study deals with estimating information about failure times of items under step-stress partially accelerated life tests using progressive failure-censored hybrid data with random removals. The life data of the units under test is considered to follow exponential life distribution. The removals from the test are assumed to have binomial distributions. The point and interval maximum likelihood estimations are obtained for unknown distribution parameters and tampering coefficient. An optimum test plan is developed using the D-optimality criterion. The performances of the resulting estimators of the developed model parameters are evaluated and investigated by using a simulation algorithm.

Keywords: binomial distribution, d-optimality, multiple censoring, optimal design, partially accelerated life testing, simulation study

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Authors: S. Behnia, S. Fathizadeh, A. Akhshani

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In the recent decades, DNA has increasingly interested in the potential technological applications that not directly related to the coding for functional proteins that is the expressed in form of genetic information. One of the most interesting applications of DNA is related to the construction of nanostructures of high complexity, design of functional nanostructures in nanoelectronical devices, nanosensors and nanocercuits. In this field, DNA is of fundamental interest to the development of DNA-based molecular technologies, as it possesses ideal structural and molecular recognition properties for use in self-assembling nanodevices with a definite molecular architecture. Also, the robust, one-dimensional flexible structure of DNA can be used to design electronic devices, serving as a wire, transistor switch, or rectifier depending on its electronic properties. In order to understand the mechanism of the charge transport along DNA sequences, numerous studies have been carried out. In this regard, conductivity properties of DNA molecule could be investigated in a simple, but chemically specific approach that is intimately related to the Su-Schrieffer-Heeger (SSH) model. In SSH model, the non-diagonal matrix element dependence on intersite displacements is considered. In this approach, the coupling between the charge and lattice deformation is along the helix. This model is a tight-binding linear nanoscale chain established to describe conductivity phenomena in doped polyethylene. It is based on the assumption of a classical harmonic interaction between sites, which is linearly coupled to a tight-binding Hamiltonian. In this work, the Hamiltonian and corresponding motion equations are nonlinear and have high sensitivity to initial conditions. Then, we have tried to move toward the nonlinear dynamics and phase space analysis. Nonlinear dynamics and chaos theory, regardless of any approximation, could open new horizons to understand the conductivity mechanism in DNA. For a detailed study, we have tried to study the current flowing in DNA and investigated the characteristic I-V diagram. As a result, It is shown that there are the (quasi-) ohmic areas in I-V diagram. On the other hand, the regions with a negative differential resistance (NDR) are detectable in diagram.

Keywords: DNA conductivity, Landauer resistance, negative dierential resistance, Chaos theory, mean Lyapunov exponent

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Authors: Amanda Rithieli Pereira Dos Santos, Rute Quelvia De Faria, Álvaro De Oliveira Cardoso, Anderson Rodrigo Da Silva, Érica Leão Fernandes Araújo

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The study of the kinetics of drying has great importance for the mathematical modeling, allowing to know about the processes of transference of heat and mass between the products and to adjust dryers managing new technologies for these processes. The present work had the objective of studying the kinetics of drying of soybean seeds and adjusting different statistical models to the experimental data varying cultivar and temperature. Soybean seeds were pre-dried in a natural environment in order to reduce and homogenize the water content to the level of 14% (b.s.). Then, drying was carried out in a forced air circulation oven at controlled temperatures of 38, 43, 48, 53 and 58 ± 1 ° C, using two soybean cultivars, BRS 8780 and Sambaíba, until reaching a hygroscopic equilibrium. The experimental design was completely randomized in factorial 5 x 2 (temperature x cultivar) with 3 replicates. To the experimental data were adjusted eleven statistical models used to explain the drying process of agricultural products. Regression analysis was performed using the least squares Gauss-Newton algorithm to estimate the parameters. The degree of adjustment was evaluated from the analysis of the coefficient of determination (R²), the adjusted coefficient of determination (R² Aj.) And the standard error (S.E). The models that best represent the drying kinetics of soybean seeds are those of Midilli and Logarítmico.

Keywords: curve of drying seeds, Glycine max L., moisture ratio, statistical models

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Authors: Lianne M. Q. Lee, Mohammed Sharaf Shaiban

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The importance of bank liquidity management took center stage as policy makers promoted a more resilient global banking system after the market turmoil of 2007. The growing recognition of Islamic banks’ function of intermediating funds in the economy warrants the need to investigate its balance sheet structure which is distinct from its conventional counterparts. Given that asymmetric risk, transformation is inevitable; Islamic banks need to identify the liquidity risk within their distinctive balance sheet structure. Thus, there is a strong need to quantify and assess the liquidity position to ensure proper functioning of a financial institution. It is vital to measure bank liquidity because liquid banks face less liquidity risk. We examine this issue by using two alternative quantitative measures of liquidity creation “cat fat” and “cat nonfat” constructed by Berger and Bouwman (2009). “Cat fat” measures all on balance sheet items including off balance sheet, whilst the latter measures only on balance sheet items. Liquidity creation is measured over the period 2007-2014 in 14 countries where Islamic and conventional commercial banks coexist. Also, separately by bank size class as empirical studies have shown that liquidity creation varies by bank size. An interesting and important finding shows that all size class of Islamic banks, on average have increased creation of aggregate liquidity in real dollar terms over the years for both liquidity creation measures especially for large banks indicating that Islamic banks actually generates more liquidity to the economy compared to its conventional counterparts, including from off-balance sheet items. The liquidity creation for off-balance sheets by conventional banks may have been affected by the global financial crisis when derivatives markets were severely hit. The results also suggest that Islamic banks have the higher volume of assets and deposits and that borrowing/issues of bonds are less in Islamic banks compared to conventional banks because most products are interest-based. As Islamic banks appear to create more liquidity than conventional banks under both measures, it translates that the development of Islamic banking is significant over the decades since its inception. This finding is encouraging as, despite Islamic banking’s overall size, it represents growth opportunities for these countries.

Keywords: financial institution, liquidity creation, liquidity risk, policy and regulation

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Authors: Ritula Thakur, Babankumar S. Bansod, Puneet Mehta, S. Chatterji

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Moisture plays an important role in storage, harvesting and processing of food grains and related agricultural products. It is an important characteristic of most agricultural products for maintenance of quality. Accurate knowledge of the moisture content can be of significant value in maintaining quality and preventing contamination of cereal grains. The present work reports the design and development of microcontroller based low cost non-destructive moisture meter, which uses complex impedance measurement method for moisture measurement of wheat using parallel plate capacitor arrangement. Moisture can conveniently be sensed by measuring the complex impedance using a small parallel-plate capacitor sensor filled with the kernels in-between the two plates of sensor, exciting the sensor at 30 KHz and 100 KHz frequencies. The effects of density and temperature variations were compensated by providing suitable compensations in the developed algorithm. The results were compared with standard dry oven technique and the developed method was found to be highly accurate with less than 1% error. The developed moisture meter is low cost, highly accurate, non-destructible method for determining the moisture of grains utilizing the fast computing capabilities of microcontroller.

Keywords: complex impedance, moisture content, electrical properties, safety of food

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Authors: Nasim Fallahi, Erasmo Carrera, Alfonso Pagani

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Variable angle tow describes the fibres which are curvilinearly steered in a composite lamina. Significantly, stiffness tailoring freedom of VAT composite laminate can be enlarged and enabled. Composite structures with curvilinear fibres have been shown to improve the buckling load carrying capability in contrast with the straight laminate composites. However, the optimal design and analysis of VAT are faced with high computational efforts due to the increasing number of variables. In this article, an efficient optimum solution has been used in combination with 1D Carrera’s Unified Formulation (CUF) to investigate the optimum fibre orientation angles for buckling analysis. The particular emphasis is on the LE-based CUF models, which provide a Lagrange Expansions to address a layerwise description of the problem unknowns. The first critical buckling load has been considered under simply supported boundary conditions. Special attention is lead to the sensitivity of buckling load corresponding to the fibre orientation angle in comparison with the results which obtain through the Genetic Algorithm (GA) optimization frame and then Artificial Neural Network (ANN) is applied to investigate the accuracy of the optimized model. As a result, numerical CUF approach with an optimal solution demonstrates the robustness and computational efficiency of proposed optimum methodology.

Keywords: beam structures, layerwise, optimization, variable stiffness

Procedia PDF Downloads 109

Authors: Munawar Malik, Muntaha Ahmad, Khalil Ullah Khan

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Linguistic abilities in students with hearing impairment yet remain a concern for educationists. The emerging technological support and provisions in recent era vows to have addressed the situation and claims significant contribution in terms of linguistic repertoire. Being a descriptive and quantitative paradigm of study, the purpose of this research set forth was to assess linguistic competencies of students with hearing impairment in English language. The goals were further broken down to identify level of reading abilities in the subject population. The population involved students with HI studying at higher secondary level in Lahore. Simple random sampling technique was used to choose a sample of fifty students. A purposive curriculum-based assessment was designed in line with accelerated learning program by Punjab Government, to assess Linguistic competence among the sample. Further to it, an Informal Reading Inventory (IRI) corresponding to reading levels was also developed by researchers duly validated and piloted before the final use. Descriptive and inferential statistics were utilized to reach to the findings. Spearman’s correlation was used to find out relationship between degree of hearing loss, grade level, gender and type of amplification device. Independent sample t-test was used to compare means among groups. Major findings of the study revealed that students with hearing impairment exhibit significant deviation from the mean scores when compared in terms of grades, severity and amplification device. The study divulged that respective students with HI have yet failed to qualify an independent level of reading according to their grades as majority falls at frustration level of word recognition and passage comprehension. The poorer performance can be attributed to lower linguistic competence as it shows in the frustration levels of reading, writing and comprehension. The correlation analysis did reflect an improved performance grade wise, however scores could only correspond to frustration level and independent levels was never achieved. Reported achievements at instructional level of subject population may further to linguistic skills if practiced purposively.

Keywords: linguistic competence, hearing impairment, reading levels, educationist

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Authors: Shankha Sanyal, Archi Banerjee, Sayan Biswas, Sourya Sengupta, Sayan Nag, Ranjan Sengupta, Dipak Ghosh

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The term ‘gestalt’ has been widely used in the field of psychology which defined the perception of human mind to group any object not in part but as a 'unified' whole. Music, in general, is polyphonic - i.e. a combination of a number of pure tones (frequencies) mixed together in a manner that sounds harmonious. The study of human brain response due to different frequency groups of the acoustic signal can give us an excellent insight regarding the neural and functional architecture of brain functions. Hence, the study of music cognition using neuro-biosensors is becoming a rapidly emerging field of research. In this work, we have tried to analyze the effect of different frequency bands of music on the various frequency rhythms of human brain obtained from EEG data. Four widely popular Rabindrasangeet clips were subjected to Wavelet Transform method for extracting five resonant frequency bands from the original music signal. These frequency bands were initially analyzed with Detrended/Adaptive Fractal analysis (DFA/AFA) methods. A listening test was conducted on a pool of 100 respondents to assess the frequency band in which the music becomes non-recognizable. Next, these resonant frequency bands were presented to 20 subjects as auditory stimulus and EEG signals recorded simultaneously in 19 different locations of the brain. The recorded EEG signals were noise cleaned and subjected again to DFA/AFA technique on the alpha, theta and gamma frequency range. Thus, we obtained the scaling exponents from the two methods in alpha, theta and gamma EEG rhythms corresponding to different frequency bands of music. From the analysis of music signal, it is seen that loss of recognition is proportional to the loss of long range correlation in the signal. From the EEG signal analysis, we obtain frequency specific arousal based response in different lobes of brain as well as in specific EEG bands corresponding to musical stimuli. In this way, we look to identify a specific frequency band beyond which the music becomes non-recognizable and below which in spite of the absence of other bands the music is perceivable to the audience. This revelation can be of immense importance when it comes to the field of cognitive music therapy and researchers of creativity.

Keywords: AFA, DFA, EEG, gestalt in music, Hurst exponent

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Authors: Y. Alrubyli

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Unmanned Arial Vehicles (UAVs), and more specifically, quadcopters need to be stable during their flights. Altitude stability is usually achieved by using a PID controller that is built into the flight controller software. Furthermore, the PID controller has gains that need to be tuned to reach optimal altitude stabilization during the quadcopter’s flight. For that, control system engineers need to tune those gains by using extensive modeling of the environment, which might change from one environment and condition to another. As quadcopters penetrate more sectors, from the military to the consumer sectors, they have been put into complex and challenging environments more than ever before. Hence, intelligent self-stabilizing quadcopters are needed to maneuver through those complex environments and situations. Here we show that by using online reinforcement learning with minimal background knowledge, the altitude stability of the quadcopter can be achieved using a model-free approach. We found that by using background knowledge instead of letting the online reinforcement learning algorithm wander for a while to tune the PID gains, altitude stabilization can be achieved faster. In addition, using this approach will accelerate development by avoiding extensive simulations before applying the PID gains to the real-world quadcopter. Our results demonstrate the possibility of using the trial and error approach of reinforcement learning combined with background knowledge to achieve faster quadcopter altitude stabilization in different environments and conditions.

Keywords: reinforcement learning, Q-leanring, online learning, PID tuning, unmanned aerial vehicle, quadcopter

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Authors: Hamed Alizadeh Dashagholi, Hossein Yousefi-Banaem, Mina Naeimi

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Current study established for EEG signal analysis in patients with language disorder. Language disorder can be defined as meaningful delay in the use or understanding of spoken or written language. The disorder can include the content or meaning of language, its form, or its use. Here we applied Z-score, power spectrum, and coherence methods to discriminate the language disorder data from healthy ones. Power spectrum of each channel in alpha, beta, gamma, delta, and theta frequency bands was measured. In addition, intra hemispheric Z-score obtained by scoring algorithm. Obtained results showed high Z-score and power spectrum in posterior regions. Therefore, we can conclude that peoples with language disorder have high brain activity in frontal region of brain in comparison with healthy peoples. Results showed that high coherence correlates with irregularities in the ERP and is often found during complex task, whereas low coherence is often found in pathological conditions. The results of the Z-score analysis of the brain dynamics showed higher Z-score peak frequency in delta, theta and beta sub bands of Language Disorder patients. In this analysis there were activity signs in both hemispheres and the left-dominant hemisphere was more active than the right.

Keywords: EEG, electroencephalography, coherence methods, language disorder, power spectrum, z-score

Procedia PDF Downloads 391

Authors: Sunghun Jung

Abstract:

The existing web map service providers contract with the satellite operators to update their maps by paying an astronomical amount of money, but the cost could be minimized by operating a cheap and small UAV. In contrast to the satellites, we only need to replace aged battery packs from time to time for the usage of UAVs. Utilizing both a regular camera and an infrared camera mounted on a small, solar-powered, long-endurance, and hoverable UAV, daytime ground surface photographs, and nighttime infrared photographs will be continuously and repeatedly uploaded to the web map server and overlapped with the existing ground surface photographs in real-time. The real-time web map service using a small, solar-powered, long-endurance, and hoverable UAV can also be applied to the surveillance missions, in particular, to detect border area intruders. The improved real-time image stitching algorithm is developed for the graphic map data overlapping. Also, a small home server will be developed to manage the huge size of incoming map data. The map photographs taken at tens or hundreds of kilometers by a UAV would improve the map graphic resolution compared to the map photographs taken at thousands of kilometers by satellites since the satellite photographs are limited by weather conditions.

Keywords: long-endurance, real-time web map service (RWMS), solar-powered, unmanned aerial vehicle (UAV)

Procedia PDF Downloads 250