Search results for: smart camera networks
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4545

Search results for: smart camera networks

2445 Track and Evaluate Cortical Responses Evoked by Electrical Stimulation

Authors: Kyosuke Kamada, Christoph Kapeller, Michael Jordan, Mostafa Mohammadpour, Christy Li, Christoph Guger

Abstract:

Cortico-cortical evoked potentials (CCEP) refer to responses generated by cortical electrical stimulation at distant brain sites. These responses provide insights into the functional networks associated with language or motor functions, and in the context of epilepsy, they can reveal pathological networks. Locating the origin and spread of seizures within the cortex is crucial for pre-surgical planning. This process can be enhanced by employing cortical stimulation at the seizure onset zone (SOZ), leading to the generation of CCEPs in remote brain regions that may be targeted for disconnection. In the case of a 24-year-old male patient suffering from intractable epilepsy, corpus callosotomy was performed as part of the treatment. DTI-MRI imaging, conducted using a 3T MRI scanner for fiber tracking, along with CCEP, is used as part of an assessment for surgical planning. Stimulation of the SOZ, with alternating monophasic pulses of 300µs duration and 15mA current intensity, resulted in CCEPs on the contralateral frontal cortex, reaching a peak amplitude of 206µV with a latency of 31ms, specifically in the left pars triangularis. The related fiber tracts were identified with a two-tensor unscented Kalman filter (UKF) technique, showing transversal fibers through the corpus callosum. The CCEPs were monitored through the progress of the surgery. Notably, the SOZ-associated CCEPs exhibited a reduction following the resection of the anterior portion of the corpus callosum, reaching the identified connecting fibers. This intervention demonstrated a potential strategy for mitigating the impact of intractable epilepsy through targeted disconnection of identified cortical regions.

Keywords: CCEP, SOZ, Corpus callosotomy, DTI

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2444 Research of Control System for Space Intelligent Robot Based on Vision Servo

Authors: Changchun Liang, Xiaodong Zhang, Xin Liu, Pengfei Sun

Abstract:

Space intelligent robotic systems are expected to play an increasingly important role in the future. The robotic on-orbital service, whose key is the tracking and capturing technology, becomes research hot in recent years. In this paper, the authors propose a vision servo control system for target capturing. Robotic manipulator will be an intelligent robotic system with large-scale movement, functional agility, and autonomous ability, and it can be operated by astronauts in the space station or be controlled by the ground operator in the remote operation mode. To realize the autonomous movement and capture mission of SRM, a kind of autonomous programming strategy based on multi-camera vision fusion is designed and the selection principle of object visual position and orientation measurement information is defined for the better precision. Distributed control system hierarchy is designed and reliability is considering to guarantee the abilities of control system. At last, a ground experiment system is set up based on the concept of robotic control system. With that, the autonomous target capturing experiments are conducted. The experiment results validate the proposed algorithm, and demonstrates that the control system can fulfill the needs of function, real-time and reliability.

Keywords: control system, on-orbital service, space robot, vision servo

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2443 Pilot Directional Protection Scheme Using Wireless Communication

Authors: Nitish Sharma, G. G. Karady

Abstract:

This paper presents a scheme for the protection of loop system from all type of faults using the direction of fault current. The presence of distributed generation in today’s system increases the complexity of fault detection as the power flow is bidirectional. Hence, protection scheme specific to this purpose needs to be developed. This paper shows a fast protection scheme using communication which can be fiber optic or wireless. In this paper, the possibility of wireless communication for protection is studied to exchange the information between the relays. The negative sequence and positive sequence directional elements are used to determine the direction of fault current. A PSCAD simulation is presented and validated using commercial SEL relays.

Keywords: smart grid protection, pilot protection, power system simulation, wireless communication

Procedia PDF Downloads 636
2442 A Survey of Novel Opportunistic Routing Protocols in Mobile Ad Hoc Networks

Authors: R. Poonkuzhali, M. Y. Sanavullah, M. R. Gurupriya

Abstract:

Opportunistic routing is used, where the network has the features like dynamic topology changes and intermittent network connectivity. In Delay Tolerant network or Disruption tolerant network opportunistic forwarding technique is widely used. The key idea of opportunistic routing is selecting forwarding nodes to forward data and coordination among these nodes to avoid duplicate transmissions. This paper gives the analysis of pros and cons of various opportunistic routing techniques used in MANET.

Keywords: ETX, opportunistic routing, PSR, throughput

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2441 Paddy/Rice Singulation for Determination of Husking Efficiency and Damage Using Machine Vision

Authors: M. Shaker, S. Minaei, M. H. Khoshtaghaza, A. Banakar, A. Jafari

Abstract:

In this study a system of machine vision and singulation was developed to separate paddy from rice and determine paddy husking and rice breakage percentages. The machine vision system consists of three main components including an imaging chamber, a digital camera, a computer equipped with image processing software. The singulation device consists of a kernel holding surface, a motor with vacuum fan, and a dimmer. For separation of paddy from rice (in the image), it was necessary to set a threshold. Therefore, some images of paddy and rice were sampled and the RGB values of the images were extracted using MATLAB software. Then mean and standard deviation of the data were determined. An Image processing algorithm was developed using MATLAB to determine paddy/rice separation and rice breakage and paddy husking percentages, using blue to red ratio. Tests showed that, a threshold of 0.75 is suitable for separating paddy from rice kernels. Results from the evaluation of the image processing algorithm showed that the accuracies obtained with the algorithm were 98.36% and 91.81% for paddy husking and rice breakage percentage, respectively. Analysis also showed that a suction of 45 mmHg to 50 mmHg yielding 81.3% separation efficiency is appropriate for operation of the kernel singulation system.

Keywords: breakage, computer vision, husking, rice kernel

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2440 Development of 3D Laser Scanner for Robot Navigation

Authors: Ali Emre Öztürk, Ergun Ercelebi

Abstract:

Autonomous robotic systems needs an equipment like a human eye for their movement. Robotic camera systems, distance sensors and 3D laser scanners have been used in the literature. In this study a 3D laser scanner has been produced for those autonomous robotic systems. In general 3D laser scanners are using 2 dimension laser range finders that are moving on one-axis (1D) to generate the model. In this study, the model has been obtained by a one-dimensional laser range finder that is moving in two –axis (2D) and because of this the laser scanner has been produced cheaper. Furthermore for the laser scanner a motor driver, an embedded system control board has been used and at the same time a user interface card has been used to make the communication between those cards and computer. Due to this laser scanner, the density of the objects, the distance between the objects and the necessary path ways for the robot can be calculated. The data collected by the laser scanner system is converted in to cartesian coordinates to be modeled in AutoCAD program. This study shows also the synchronization between the computer user interface, AutoCAD and the embedded systems. As a result it makes the solution cheaper for such systems. The scanning results are enough for an autonomous robot but the scan cycle time should be developed. This study makes also contribution for further studies between the hardware and software needs since it has a powerful performance and a low cost.

Keywords: 3D laser scanner, embedded system, 1D laser range finder, 3D model

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2439 Harmonizing Cities: Integrating Land Use Diversity and Multimodal Transit for Social Equity

Authors: Zi-Yan Chao

Abstract:

With the rapid development of urbanization and increasing demand for efficient transportation systems, the interaction between land use diversity and transportation resource allocation has become a critical issue in urban planning. Achieving a balance of land use types, such as residential, commercial, and industrial areas, is crucial role in ensuring social equity and sustainable urban development. Simultaneously, optimizing multimodal transportation networks, including bus, subway, and car routes, is essential for minimizing total travel time and costs, while ensuring fairness for all social groups, particularly in meeting the transportation needs of low-income populations. This study develops a bilevel programming model to address these challenges, with land use diversity as the foundation for measuring equity. The upper-level model maximizes land use diversity for balanced land distribution across regions. The lower-level model optimizes multimodal transportation networks to minimize travel time and costs while maintaining user equilibrium. The model also incorporates constraints to ensure fair resource allocation, such as balancing transportation accessibility and cost differences across various social groups. A solution approach is developed to solve the bilevel optimization problem, ensuring efficient exploration of the solution space for land use and transportation resource allocation. This study maximizes social equity by maximizing land use diversity and achieving user equilibrium with optimal transportation resource distribution. The proposed method provides a robust framework for addressing urban planning challenges, contributing to sustainable and equitable urban development.

Keywords: bilevel programming model, genetic algorithms, land use diversity, multimodal transportation optimization, social equity

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2438 Developing Confidence of Visual Literacy through Using MIRO during Online Learning

Authors: Rachel S. E. Lim, Winnie L. C. Tan

Abstract:

Visual literacy is about making meaning through the interaction of images, words, and sounds. Graphic communication students typically develop visual literacy through critique and production of studio-based projects for their portfolios. However, the abrupt switch to online learning during the COVID-19 pandemic has made it necessary to consider new strategies of visualization and planning to scaffold teaching and learning. This study, therefore, investigated how MIRO, a cloud-based visual collaboration platform, could be used to develop the visual literacy confidence of 30 diploma in graphic communication students attending a graphic design course at a Singapore arts institution. Due to COVID-19, the course was taught fully online throughout a 16-week semester. Guided by Kolb’s Experiential Learning Cycle, the two lecturers developed students’ engagement with visual literacy concepts through different activities that facilitated concrete experiences, reflective observation, abstract conceptualization, and active experimentation. Throughout the semester, students create, collaborate, and centralize communication in MIRO with infinite canvas, smart frameworks, a robust set of widgets (i.e., sticky notes, freeform pen, shapes, arrows, smart drawing, emoticons, etc.), and powerful platform capabilities that enable asynchronous and synchronous feedback and interaction. Students then drew upon these multimodal experiences to brainstorm, research, and develop their motion design project. A survey was used to examine students’ perceptions of engagement (E), confidence (C), learning strategies (LS). Using multiple regression, it¬ was found that the use of MIRO helped students develop confidence (C) with visual literacy, which predicted performance score (PS) that was measured against their application of visual literacy to the creation of their motion design project. While students’ learning strategies (LS) with MIRO did not directly predict confidence (C) or performance score (PS), it fostered positive perceptions of engagement (E) which in turn predicted confidence (C). Content analysis of students’ open-ended survey responses about their learning strategies (LS) showed that MIRO provides organization and structure in documenting learning progress, in tandem with establishing standards and expectations as a preparatory ground for generating feedback. With the clarity and sequence of the mentioned conditions set in place, these prerequisites then lead to the next level of personal action for self-reflection, self-directed learning, and time management. The study results show that the affordances of MIRO can develop visual literacy and make up for the potential pitfalls of student isolation, communication, and engagement during online learning. The context of how MIRO could be used by lecturers to orientate students for learning in visual literacy and studio-based projects for future development are discussed.

Keywords: design education, graphic communication, online learning, visual literacy

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2437 Immersive Learning in University Classrooms

Authors: Raminder Kaur

Abstract:

This paper considers the emerging area of integrating Virtual Reality (VR) technologies into the teaching of Visual Anthropology, Research Methods, and the Anthropology of Contemporary India in the University of Sussex. If deployed in a critical and self-reflexive manner, there are several advantages to VR-based immersive learning: (i) Based on data available for British schools, it has been noted that ‘Learning through experience can boost knowledge retention by up to 75%’. (ii) It can tutor students to learn with and from virtual worlds, devising new collaborative methods where suited. (iii) It can foster inclusive learning by aiding students with SEN and disabilities who may not be able to explore such areas in the physical world. (iv) It can inspire and instill confidence in students with anxieties about approaching new subjects, realms, or regions. (v) It augments our provision of ‘smart classrooms’ synchronised to the kinds of emerging immersive learning environments that students come from in schools.

Keywords: virtual reality, anthropology, immersive learning, university

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2436 Comparison of Two Neural Networks To Model Margarine Age And Predict Shelf-Life Using Matlab

Authors: Phakamani Xaba, Robert Huberts, Bilainu Oboirien

Abstract:

The present study was aimed at developing & comparing two neural-network-based predictive models to predict shelf-life/product age of South African margarine using free fatty acid (FFA), water droplet size (D3.3), water droplet distribution (e-sigma), moisture content, peroxide value (PV), anisidine valve (AnV) and total oxidation (totox) value as input variables to the model. Brick margarine products which had varying ages ranging from fresh i.e. week 0 to week 47 were sourced. The brick margarine products which had been stored at 10 & 25 °C and were characterized. JMP and MATLAB models to predict shelf-life/ margarine age were developed and their performances were compared. The key performance indicators to evaluate the model performances were correlation coefficient (CC), root mean square error (RMSE), and mean absolute percentage error (MAPE) relative to the actual data. The MATLAB-developed model showed a better performance in all three performance indicators. The correlation coefficient of the MATLAB model was 99.86% versus 99.74% for the JMP model, the RMSE was 0.720 compared to 1.005 and the MAPE was 7.4% compared to 8.571%. The MATLAB model was selected to be the most accurate, and then, the number of hidden neurons/ nodes was optimized to develop a single predictive model. The optimized MATLAB with 10 neurons showed a better performance compared to the models with 1 & 5 hidden neurons. The developed models can be used by margarine manufacturers, food research institutions, researchers etc, to predict shelf-life/ margarine product age, optimize addition of antioxidants, extend shelf-life of products and proactively troubleshoot for problems related to changes which have an impact on shelf-life of margarine without conducting expensive trials.

Keywords: margarine shelf-life, predictive modelling, neural networks, oil oxidation

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2435 Arbitrarily Shaped Blur Kernel Estimation for Single Image Blind Deblurring

Authors: Aftab Khan, Ashfaq Khan

Abstract:

The research paper focuses on an interesting challenge faced in Blind Image Deblurring (BID). It relates to the estimation of arbitrarily shaped or non-parametric Point Spread Functions (PSFs) of motion blur caused by camera handshake. These PSFs exhibit much more complex shapes than their parametric counterparts and deblurring in this case requires intricate ways to estimate the blur and effectively remove it. This research work introduces a novel blind deblurring scheme visualized for deblurring images corrupted by arbitrarily shaped PSFs. It is based on Genetic Algorithm (GA) and utilises the Blind/Reference-less Image Spatial QUality Evaluator (BRISQUE) measure as the fitness function for arbitrarily shaped PSF estimation. The proposed BID scheme has been compared with other single image motion deblurring schemes as benchmark. Validation has been carried out on various blurred images. Results of both benchmark and real images are presented. Non-reference image quality measures were used to quantify the deblurring results. For benchmark images, the proposed BID scheme using BRISQUE converges in close vicinity of the original blurring functions.

Keywords: blind deconvolution, blind image deblurring, genetic algorithm, image restoration, image quality measures

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2434 Water End-Use Classification with Contemporaneous Water-Energy Data and Deep Learning Network

Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

Abstract:

‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: deep learning network, smart metering, water end use, water-energy data

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2433 Development of Fluorescence Resonance Energy Transfer-Based Nanosensor for Measurement of Sialic Acid in vivo

Authors: Ruphi Naz, Altaf Ahmad, Mohammad Anis

Abstract:

Sialic acid (5-Acetylneuraminic acid, Neu5Ac) is a common sugar found as a terminal residue on glycoconjugates in many animals. Humans brain and the central nervous system contain the highest concentration of sialic acid (as N-acetylneuraminic acid) where these acids play an important role in neural transmission and ganglioside structure in synaptogenesis. Due to its important biological function, sialic acid is attracting increasing attention. To understand metabolic networks, fluxes and regulation, it is essential to be able to determine the cellular and subcellular levels of metabolites. Genetically-encoded fluorescence resonance energy transfer (FRET) sensors represent a promising technology for measuring metabolite levels and corresponding rate changes in live cells. Taking this, we developed a genetically encoded FRET (fluorescence resonance energy transfer) based nanosensor to analyse the sialic acid level in living cells. Sialic acid periplasmic binding protein (sia P) from Haemophilus influenzae was taken and ligated between the FRET pair, the cyan fluorescent protein (eCFP) and Venus. The chimeric sensor protein was expressed in E. coli BL21 (DE3) and purified by affinity chromatography. Conformational changes in the binding protein clearly confirmed the changes in FRET efficiency. So any change in the concentration of sialic acid is associated with the change in FRET ratio. This sensor is very specific to sialic acid and found stable with the different range of pH. This nanosensor successfully reported the intracellular level of sialic acid in bacterial cell. The data suggest that the nanosensors may be a versatile tool for studying the in vivo dynamics of sialic acid level non-invasively in living cells

Keywords: nanosensor, FRET, Haemophilus influenzae, metabolic networks

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2432 Collaboration between Grower and Research Organisations as a Mechanism to Improve Water Efficiency in Irrigated Agriculture

Authors: Sarah J. C. Slabbert

Abstract:

The uptake of research as part of the diffusion or adoption of innovation by practitioners, whether individuals or organisations, has been a popular topic in agricultural development studies for many decades. In the classical, linear model of innovation theory, the innovation originates from an expert source such as a state-supported research organisation or academic institution. The changing context of agriculture led to the development of the agricultural innovation systems model, which recognizes innovation as a complex interaction between individuals and organisations, which include private industry and collective action organisations. In terms of this model, an innovation can be developed and adopted without any input or intervention from a state or parastatal research organisation. This evolution in the diffusion of agricultural innovation has put forward new challenges for state or parastatal research organisations, which have to demonstrate the impact of their research to the legislature or a regulatory authority: Unless the organisation and the research it produces cross the knowledge paths of the intended audience, there will be no awareness, no uptake and certainly no impact. It is therefore critical for such a research organisation to base its communication strategy on a thorough understanding of the knowledge needs, information sources and knowledge networks of the intended target audience. In 2016, the South African Water Research Commission (WRC) commissioned a study to investigate the knowledge needs, information sources and knowledge networks of Water User Associations and commercial irrigators with the aim of improving uptake of its research on efficient water use in irrigation. The first phase of the study comprised face-to-face interviews with the CEOs and Board Chairs of four Water User Associations along the Orange River in South Africa, and 36 commercial irrigation farmers from the same four irrigation schemes. Intermediaries who act as knowledge conduits to the Water User Associations and the irrigators were identified and 20 of them were subsequently interviewed telephonically. The study found that irrigators interact regularly with grower organisations such as SATI (South African Table Grape Industry) and SAPPA (South African Pecan Nut Association) and that they perceive these organisations as credible, trustworthy and reliable, within their limitations. State and parastatal research institutions, on the other hand, are associated with a range of negative attributes. As a result, the awareness of, and interest in, the WRC and its research on water use efficiency in irrigated agriculture are low. The findings suggest that a communication strategy that involves collaboration with these grower organisations would empower the WRC to participate much more efficiently and with greater impact in agricultural innovation networks. The paper will elaborate on the findings and discuss partnering frameworks and opportunities to manage perceptions and uptake.

Keywords: agricultural innovation systems, communication strategy, diffusion of innovation, irrigated agriculture, knowledge paths, research organisations, target audiences, water use efficiency

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2431 Role of Power Electronics in Grid Integration of Renewable Energy Systems

Authors: M. N. Tandjaoui, C. Banoudjafar, C. Benachaiba, O. Abdelkhalek, A. Kechich

Abstract:

Advanced power electronic systems are deemed to be an integral part of renewable, green, and efficient energy systems. Wind energy is one of the renewable means of electricity generation that is now the world’s fastest growing energy source can bring new challenges when it is connected to the power grid due to the fluctuation nature of the wind and the comparatively new types of its generators. The wind energy is part of the worldwide discussion on the future of energy generation and use and consequent effects on the environment. However, this paper will introduce some of the requirements and aspects of the power electronic involved with modern wind generation systems, including modern power electronics and converters, and the issues of integrating wind turbines into power systems.

Keywords: power electronics, renewable energy, smart grid, green energy, power technology

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2430 The Challenges and Opportunities Faced by Women in Geomatics Engineering: The Case of the SADC Region

Authors: Moreblessings Shoko

Abstract:

Polymersomes are materials which are considered as artificial counterparts of natural vesicles. The nanotechnology of such smart nanovesicles is very useful to enhance the efficiency of many therapeutic and diagnostic drugs. Those compounds show a higher stability, flexibility, and mechanical strength to the membrane compared to natural liposomes. Also, they can be designed in detail, the permeability of the membrane can be controlled by different stimuli, and the surface can be functionalized with different biological molecules to facilitate monitoring and target. For this purpose, this study demonstrates the formation of multifunctional and pH sensitive polymersomes and their functionalization with different reactive groups or biomolecules inside and outside of polymersomes´ membrane providing by crossing the membrane and docking/undocking processes for biomedical applications. Overall, they are highly versatile and thus present new opportunities for the design of targeted and selective recognition systems, for example, in mimicking cell functions and in synthetic biology.

Keywords: women, geomatics, challenges, capacity building

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2429 Stability Analysis of a Low Power Wind Turbine for the Simultaneous Generation of Energy through Two Electric Generators

Authors: Daniel Icaza, Federico Córdova, Chiristian Castro, Fernando Icaza, Juan Portoviejo

Abstract:

In this article, the mathematical model is presented, and simulations were carried out using specialized software such as MATLAB before the construction of a 900-W wind turbine. The present study was conducted with the intention of taking advantage of the rotation of the blades of the wind generator after going through a process of amplification of speed by means of a system of gears to finally mechanically couple two electric generators of similar characteristics. This coupling allows generating a maximum voltage of 6 V in DC for each generator and putting in series the 12 V DC is achieved, which is later stored in batteries and used when the user requires it. Laboratory tests were made to verify the level of power generation produced based on the wind speed at the entrance of the blades.

Keywords: smart grids, wind turbine, modeling, renewable energy, robust control

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2428 Centralized Peak Consumption Smoothing Revisited for Habitat Energy Scheduling

Authors: M. Benbouzid, Q. Bresson, A. Duclos, K. Longo, Q. Morel

Abstract:

Currently, electricity suppliers must predict the consumption of their customers in order to deduce the power they need to produce. It is, then, important in a first step to optimize household consumption to obtain more constant curves by limiting peaks in energy consumption. Here centralized real time scheduling is proposed to manage the equipment's starting in parallel. The aim is not to exceed a certain limit while optimizing the power consumption across a habitat. The Raspberry Pi is used as a box; this scheduler interacts with the various sensors in 6LoWPAN. At the scale of a single dwelling, household consumption decreases, particularly at times corresponding to the peaks. However, it would be wiser to consider the use of a residential complex so that the result would be more significant. So, the ceiling would no longer be fixed. The scheduling would be done on two scales, firstly, per dwelling, and secondly, at the level of a residential complex.

Keywords: smart grid, energy box, scheduling, Gang Model, energy consumption, energy management system, wireless sensor network

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2427 Ethical Leadership and Employee Creative Behaviour: A Case Study of a State-Owned Enterprise in South Africa

Authors: Krishna Kistan Govender, Alex Masianoga

Abstract:

The aim of this explanatory study was to critically understand how ethical leadership impacts employee creative behaviour, as well as the creative behaviour dimensions, in a South African transport and logistics SOE. A quantitative study was conducted using a pre-developed questionnaire, and data for 160 middle and executive managers was analysed through structural equation modelling and multiple regression techniques conducted with the Smart PLS statistical software. All five hypothesized relationships were supported, and it was confirmed that ethical leadership has a significant positive influence on employee creative behaviour, as well as on each of the creative behaviour dimensions, namely: idea exploration, idea generation, idea championing, and idea implementation.

Keywords: ethical leaders, employee creative behaviour, state-owned enterprises, South Africa

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2426 A Study of Different Factors Influencing Youngsters’ Mobile Device Buying Behaviors in Malaysia

Authors: Z. S. Yip, T. K. Tan, C. C. Geh, T. T. Ting

Abstract:

The mobile phone is an indispensable device in today’s daily living. The arising new brands in the market with different specification are targeting at the different population. The most promising market would be the younger generation who are IT savvy. Therefore, it is beneficial to find out their factors of consideration in purchasing a mobile phone. A survey is carried out in Malaysia to discover the current youngster’s mobile phone buying behavior. This study has found that the most influencing factor of consideration is Price, followed by Feature, and Battery Lifespan. Gender and Income have no relationship with certain factors of consideration. It is important to discover the factors of consideration in order to provide industry insight into the current trend of smartphone in Malaysia.

Keywords: buying behavior, smart phone, mobile brand, mobile operating system, specification, battery lifespan

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2425 Analysis of Operating Speed on Four-Lane Divided Highways under Mixed Traffic Conditions

Authors: Chaitanya Varma, Arpan Mehar

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The present study demonstrates the procedure to analyse speed data collected on various four-lane divided sections in India. Field data for the study was collected at different straight and curved sections on rural highways with the help of radar speed gun and video camera. The data collected at the sections were analysed and parameters pertain to speed distributions were estimated. The different statistical distribution was analysed on vehicle type speed data and for mixed traffic speed data. It was found that vehicle type speed data was either follows the normal distribution or Log-normal distribution, whereas the mixed traffic speed data follows more than one type of statistical distribution. The most common fit observed on mixed traffic speed data were Beta distribution and Weibull distribution. The separate operating speed model based on traffic and roadway geometric parameters were proposed in the present study. The operating speed model with traffic parameters and curve geometry parameters were established. Two different operating speed models were proposed with variables 1/R and Ln(R) and were found to be realistic with a different range of curve radius. The models developed in the present study are simple and realistic and can be used for forecasting operating speed on four-lane highways.

Keywords: highway, mixed traffic flow, modeling, operating speed

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2424 Lung Cancer Detection and Multi Level Classification Using Discrete Wavelet Transform Approach

Authors: V. Veeraprathap, G. S. Harish, G. Narendra Kumar

Abstract:

Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.

Keywords: artificial neural networks, ANN, discrete wavelet transform, DWT, gray-level co-occurrence matrix, GLCM, k-nearest neighbor, KNN, region of interest, ROI

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2423 Passive Seismic Energy Dissipation Mechanisms for Smart Green Structural System (SGSS)

Authors: Daniel Y. Abebe, Jaehyouk Choi

Abstract:

The design philosophy of building structure has been changing over time. The reason behind this is an increase in human interest regarding the improvements in building materials and technology that will affect how we live, the aim to speed up construction period, and the environmental effect which includes earthquakes and other natural disasters. One technique which takes into account the above case is using a prefabricable structural system, in which each and every structural element is designed and prefabricated and assembled on a site so that the construction speed is increased and the environmental impact is also enhanced. This system has immense advantages such as reduced construction cost, reusability, recyclability, faster construction period and less enviromental effect. In this study, some of the developed and evaluated structural elements of building structures are presented.

Keywords: eccentrically braced frame, natural disaster, prefabricable structural system, removable link, SGSS

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2422 The Development of an Agent-Based Model to Support a Science-Based Evacuation and Shelter-in-Place Planning Process within the United States

Authors: Kyle Burke Pfeiffer, Carmella Burdi, Karen Marsh

Abstract:

The evacuation and shelter-in-place planning process employed by most jurisdictions within the United States is not informed by a scientifically-derived framework that is inclusive of the behavioral and policy-related indicators of public compliance with evacuation orders. While a significant body of work exists to define these indicators, the research findings have not been well-integrated nor translated into useable planning factors for public safety officials. Additionally, refinement of the planning factors alone is insufficient to support science-based evacuation planning as the behavioral elements of evacuees—even with consideration of policy-related indicators—must be examined in the context of specific regional transportation and shelter networks. To address this problem, the Federal Emergency Management Agency and Argonne National Laboratory developed an agent-based model to support regional analysis of zone-based evacuation in southeastern Georgia. In particular, this model allows public safety officials to analyze the consequences that a range of hazards may have upon a community, assess evacuation and shelter-in-place decisions in the context of specified evacuation and response plans, and predict outcomes based on community compliance with orders and the capacity of the regional (to include extra-jurisdictional) transportation and shelter networks. The intention is to use this model to aid evacuation planning and decision-making. Applications for the model include developing a science-driven risk communication strategy and, ultimately, in the case of evacuation, the shortest possible travel distance and clearance times for evacuees within the regional boundary conditions.

Keywords: agent-based modeling for evacuation, decision-support for evacuation planning, evacuation planning, human behavior in evacuation

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2421 The Effectiveness of Logotherapy in Alleviating Social Isolation for Visually Impaired Students

Authors: Mohamed M. Elsherbiny, Ahmed T. Helal Ibrahim

Abstract:

Social isolation is one of the common problems faced visual impaired students especially in new situations. It refers to lack of interactions with others (students, staff members, and others) and dissatisfaction of social networks with others. In addition, it means "a lack of quantity and quality of social contacts". The situation became more complicated if we know that visual impaired students at Sultan Qaboos University were in special schools for the blind completely away from any integration with regular student, which may lead to isolation for being with regular students for the first time. Because the researcher is an academic advisor for all blind students in the College of Arts and Social Sciences at Sultan Qaboos University, he has noted (from the regular meetings with them) some aspects of isolation and many complaints from staff which motivated the researcher to try to alleviate the problem. Logotherapy is an important therapy used in clinical social work with various problems to help children and young people who are facing problems related to the lack of meaning in their life. So, the aim of the therapy is to find meaning in life and to be satisfied with that life. The basic meaning for visual impaired students in this study is to provide opportunities to build relationships and friendships with others and help them to be satisfied about interactions with their networks. The study aimed to identify whether there is a relationship between the use of logotherapy and alleviating social isolation for visual impaired students. This study is considered one of the quasi-experimental studies, the researcher has used experimental method. The researcher used one design which is before and after experiment on two groups, one control (did not apply to the therapy) and experimental group which is applied to the therapy. About the study tools, social isolation scale (SIS) was used to assess the degree of isolation. The sample was (20) of the visually impaired students at the College of Arts and Social Sciences, Sultan Qaboos University. The results showed the effectiveness of logotherapy in alleviating isolation for students.

Keywords: social isolation, logotherapy, visually impaired, disability

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2420 Dynamic EEG Desynchronization in Response to Vicarious Pain

Authors: Justin Durham, Chanda Rooney, Robert Mather, Mickie Vanhoy

Abstract:

The psychological construct of empathy is to understand a person’s cognitive perspective and experience the other person’s emotional state. Deciphering emotional states is conducive for interpreting vicarious pain. Observing others' physical pain activates neural networks related to the actual experience of pain itself. The study addresses empathy as a nonlinear dynamic process of simulation for individuals to understand the mental states of others and experience vicarious pain, exhibiting self-organized criticality. Such criticality follows from a combination of neural networks with an excitatory feedback loop generating bistability to resonate permutated empathy. Cortical networks exhibit diverse patterns of activity, including oscillations, synchrony and waves, however, the temporal dynamics of neurophysiological activities underlying empathic processes remain poorly understood. Mu rhythms are EEG oscillations with dominant frequencies of 8-13 Hz becoming synchronized when the body is relaxed with eyes open and when the sensorimotor system is in idle, thus, mu rhythm synchrony is expected to be highest in baseline conditions. When the sensorimotor system is activated either by performing or simulating action, mu rhythms become suppressed or desynchronize, thus, should be suppressed while observing video clips of painful injuries if previous research on mirror system activation holds. Twelve undergraduates contributed EEG data and survey responses to empathy and psychopathy scales in addition to watching consecutive video clips of sports injuries. Participants watched a blank, black image on a computer monitor before and after observing a video of consecutive sports injuries incidents. Each video condition lasted five-minutes long. A BIOPAC MP150 recorded EEG signals from sensorimotor and thalamocortical regions related to a complex neural network called the ‘pain matrix’. Physical and social pain are activated in this network to resonate vicarious pain responses to processing empathy. Five EEG single electrode locations were applied to regions measuring sensorimotor electrical activity in microvolts (μV) to monitor mu rhythms. EEG signals were sampled at a rate of 200 Hz. Mu rhythm desynchronization was measured via 8-13 Hz at electrode sites (F3 & F4). Data for each participant’s mu rhythms were analyzed via Fast Fourier Transformation (FFT) and multifractal time series analysis.

Keywords: desynchronization, dynamical systems theory, electroencephalography (EEG), empathy, multifractal time series analysis, mu waveform, neurophysiology, pain simulation, social cognition

Procedia PDF Downloads 283
2419 Efficient Video Compression Technique Using Convolutional Neural Networks and Generative Adversarial Network

Authors: P. Karthick, K. Mahesh

Abstract:

Video has become an increasingly significant component of our digital everyday contact. With the advancement of greater contents and shows of the resolution, its significant volume poses serious obstacles to the objective of receiving, distributing, compressing, and revealing video content of high quality. In this paper, we propose the primary beginning to complete a deep video compression model that jointly upgrades all video compression components. The video compression method involves splitting the video into frames, comparing the images using convolutional neural networks (CNN) to remove duplicates, repeating the single image instead of the duplicate images by recognizing and detecting minute changes using generative adversarial network (GAN) and recorded with long short-term memory (LSTM). Instead of the complete image, the small changes generated using GAN are substituted, which helps in frame level compression. Pixel wise comparison is performed using K-nearest neighbours (KNN) over the frame, clustered with K-means, and singular value decomposition (SVD) is applied for each and every frame in the video for all three color channels [Red, Green, Blue] to decrease the dimension of the utility matrix [R, G, B] by extracting its latent factors. Video frames are packed with parameters with the aid of a codec and converted to video format, and the results are compared with the original video. Repeated experiments on several videos with different sizes, duration, frames per second (FPS), and quality results demonstrate a significant resampling rate. On average, the result produced had approximately a 10% deviation in quality and more than 50% in size when compared with the original video.

Keywords: video compression, K-means clustering, convolutional neural network, generative adversarial network, singular value decomposition, pixel visualization, stochastic gradient descent, frame per second extraction, RGB channel extraction, self-detection and deciding system

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2418 A Photovoltaic Micro-Storage System for Residential Applications

Authors: Alia Al Nuaimi, Ayesha Al Aberi, Faiza Al Marzouqi, Shaikha Salem Ali Al Yahyaee, Ala Hussein

Abstract:

In this paper, a PV micro-storage system for residential applications is proposed. The term micro refers to the size of the PV storage system, which is in the range of few kilo-watts, compared to the grid size (~GWs). Usually, in a typical load profile of a residential unit, two peak demand periods exist: one at morning and the other at evening time. The morning peak can be partly covered by the PV energy directly, while the evening peak cannot be covered by the PV alone. Therefore, an energy storage system that stores solar energy during daytime and use this stored energy when the sun is absent is a must. A complete design procedure including theoretical analysis followed by simulation verification and economic feasibility evaluation is addressed in this paper.

Keywords: battery, energy storage, photovoltaic, peak shaving, smart grid

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2417 Forecast Financial Bubbles: Multidimensional Phenomenon

Authors: Zouari Ezzeddine, Ghraieb Ikram

Abstract:

From the results of the academic literature which evokes the limitations of previous studies, this article shows the reasons for multidimensionality Prediction of financial bubbles. A new framework for modeling study predicting financial bubbles by linking a set of variable presented on several dimensions dictating its multidimensional character. It takes into account the preferences of financial actors. A multicriteria anticipation of the appearance of bubbles in international financial markets helps to fight against a possible crisis.

Keywords: classical measures, predictions, financial bubbles, multidimensional, artificial neural networks

Procedia PDF Downloads 577
2416 Perovskite Solar Cells Penetration on Electric Grids Based on the Power Hardware in the Loop Methodology

Authors: Alaa A. Zaky, Bandar Alfaifi, Saleh Alyahya, Alkistis Kontou, Panos Kotsampopoulos

Abstract:

In this work, we present for the first time the grid-integration of 3rd generation perovskite solar cells (PSCs) based on nanotechnology in fabrication. The effect of this penetration is analyzed in normal, fault and islanding cases of operation under different irradiation conditions using the power hardware in the loop (PHIL) methodology. The PHL method allows the PSCs connection to the electric grid which is simulated in the real-time digital simulator (RTDS), for laboratory validation of the PSCs behavior under conditions very close to real.

Keywords: perovskite solar cells, power hardware in the loop, real-time digital simulator, smart grid

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