Search results for: driving distraction

Authors: Divine Agozie, Muesser Nat, Eric Afful-Dadzie

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This examination attempts an analysis of the effect of business intelligence and analytics (BI&A) capabilities on organizational role stressors and the implications of such an effect on performance. Two hundred twenty-eight responses gathered from seventy-six firms across Ghana were analyzed using the Partial Least Squares Structural Equation Modelling (PLS-SEM) approach to validate the hypothesized relationships identified in the research model. Findings suggest both endogenous and exogenous dependencies of the sensing capability on the multiple role requirements of personnel. Further, transforming capability increases role conflict, whereas driving capability of BI&A systems impacts role conflict and role ambiguity. This study poses many practical insights to firms seeking to acquire analytics capabilities to drive performance and data-driven decision-making. It is important for firms to consider balancing role changes and task requirements before implementing and post-implementation stages of BI&A innovations.

Keywords: business intelligence and analytics, dynamic capabilities view, organizational stressors, structural equation modelling

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Authors: Lamaa Sellami, Bechir Alaya

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Nowadays, video-on-demand (VoD) applications are becoming one of the tendencies driving vehicular network users. In this paper, considering the unpredictable vehicle density, the unexpected acceleration or deceleration of the different cars included in the vehicular traffic load, and the limited radio range of the employed communication scheme, we introduce the “Dynamic Vehicular Clustering” (DVC) algorithm as a new scheme for video streaming systems over VANET. The proposed algorithm takes advantage of the concept of small cells and the introduction of wireless backhauls, inspired by the different features and the performance of the Long Term Evolution (LTE)- Advanced network. The proposed clustering algorithm considers multiple characteristics such as the vehicle’s position and acceleration to reduce latency and packet loss. Therefore, each cluster is counted as a small cell containing vehicular nodes and an access point that is elected regarding some particular specifications.

Keywords: video-on-demand, vehicular ad-hoc network, mobility, vehicular traffic load, small cell, wireless backhaul, LTE-advanced, latency, packet loss

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Authors: Mona Lisa M. Oliveira, Nara A. Policarpo, Ana Luiza B. P. Barros, Carla A. Silva

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Selective catalytic reduction systems for nitrogen oxides reduction by ammonia has been the chosen technology by most of diesel vehicle (i.e. bus and truck) manufacturers in Brazil, as also in Europe. Furthermore, at some conditions, over-stoichiometric ammonia availability is also needed that increases the NH₃ slips even more. Ammonia (NH₃) by this vehicle exhaust aftertreatment system provides a maximum efficiency of NOx removal if a significant amount of NH₃ is stored on its catalyst surface. In the other words, the practice shows that slightly less than 100% of the NOx conversion is usually targeted, so that the aqueous urea solution hydrolyzes to NH₃ via other species formation, under relatively low temperatures. This paper presents a model based on neural networks integrated with a road vehicle simulator that allows to estimate NH₃-slip emission factors for different driving conditions and patterns. The proposed model generates high NH₃slips which are not also limited in Brazil, but more efforts needed to be made to elucidate the contribution of vehicle-emitted NH₃ to the urban atmosphere.

Keywords: ammonia slip, neural-network, vehicles emissions, SCR-NOx

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Authors: Dino Carpentras, Paul Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is dedicated to modeling the dynamic evolution of people's opinions. Models in this field are based on a micro-dynamic rule, which determines how people update their opinion when interacting. Despite the high number of new models (many of them based on new rules), little research has been dedicated to experimentally validate the rule. A few studies started bridging this literature gap by experimentally testing the rule. However, in these studies, participants are forced to express their opinion as a number instead of using natural language. Furthermore, some of these studies average data from experimental questions, without testing if differences existed between them. Indeed, it is possible that different topics could show different dynamics. For example, people may be more prone to accepting someone's else opinion regarding less polarized topics. In this work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions using natural language ('agree' or 'disagree') and the certainty of their answer, expressed as a number between 1 and 10. To keep the interaction based on natural language, certainty was not shown to other participants. We then showed to the participant someone else's opinion on the same topic and, after a distraction task, we repeated the measurement. To produce data compatible with standard opinion dynamics models, we multiplied the opinion (encoded as agree=1 and disagree=-1) with the certainty to obtain a single 'continuous opinion' ranging from -10 to 10. By analyzing the topics independently, we observed that each one shows a different initial distribution. However, the dynamics (i.e., the properties of the opinion change) appear to be similar between all topics. This suggested that the same micro-dynamic rule could be applied to unpolarized topics. Another important result is that participants that change opinion tend to maintain similar levels of certainty. This is in contrast with typical micro-dynamics rules, where agents move to an average point instead of directly jumping to the opposite continuous opinion. As expected, in the data, we also observed the effect of social influence. This means that exposing someone with 'agree' or 'disagree' influenced participants to respectively higher or lower values of the continuous opinion. However, we also observed random variations whose effect was stronger than the social influence’s one. We even observed cases of people that changed from 'agree' to 'disagree,' even if they were exposed to 'agree.' This phenomenon is surprising, as, in the standard literature, the strength of the noise is usually smaller than the strength of social influence. Finally, we also built an opinion dynamics model from the data. The model was able to explain more than 80% of the data variance. Furthermore, by iterating the model, we were able to produce polarized states even starting from an unpolarized population. This experimental approach offers a way to test the micro-dynamic rule. This also allows us to build models which are directly grounded on experimental results.

Keywords: experimental validation, micro-dynamic rule, opinion dynamics, update rule

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement

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Authors: Ghafor Ahmadi, Nader Bohloli Zynab

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Rapid scientific changes are the driving force of upheaval. As new technologies arrive, human’s life changes and information becomes one of the productive sources besides other factors. Optimum application of each technology depends on precise recognition of that technology. Options of mobile phones are constantly developing and evolving. Meanwhile, one of the influential variables for improving the performance and eternity of organizations is creativity. One of the new technologies tied with development and innovation is mobile phone. In this research, the contribution of different dimensions of mobile technologies such as perceived use, perceived enjoyment, continuance intention, confirmation and satisfaction to creativity of employees were investigated. Statistical population included 510 employees of Kermanshah Petrochemical Company. Sample size was defined 217 based on Morgan and Krejcie table. This study is descriptive and data gathering instrument was a questionnaire. Applying SPSS software, linear regression was analyzed. It was found out that all dimensions of mobile technologies except satisfaction affect on creativity of employees.

Keywords: mobile technologies, continuance intention, perceived enjoyment, perceived use, confirmation, satisfaction, creativity

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Authors: Shiuh-Jer Huang, Yun-Han Yeh

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A four-wheel drive electric vehicle was built with hub DC motors and FPGA embedded control structure. A 40 steps manual adjusting motorcycle shock absorber was refitted with DC motor driving mechanism to construct as a semi-active suspension system. Accelerometer and potentiometer sensors are installed to measure the sprung mass acceleration and suspension system compression or rebound states for control purpose. An intelligent fuzzy logic controller was proposed to real-time search appropriate damping ratio based on vehicle running condition. Then, a robust fuzzy sliding mode controller (FSMC) is employed to regulate the target damping ratio of each wheel axis semi-active suspension system. Finally, different road surface conditions are chosen to evaluate the control performance of this semi-active suspension and compare with that of passive system based on wheel axis acceleration signal.

Keywords: acceleration, FPGA, Fuzzy sliding mode control, semi-active suspension

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Authors: Upal Barua

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The risk of severe crashes at high-speed right-turns at intersections is a major safety concern these days. The application of a smart right-turn at an intersection is increasing day by day to address is an issue. The design, ‘Smart Right-turn’ consists of a narrow-angle of channelization at approximately 70°. This design increases the cone of vision of the right-tuning drivers towards the crossing pedestrians as well as traffic on the cross-road. As part of the Safety Improvement Program in Austin Transportation Department, several smart right-turns were constructed at high crash intersections where high-speed right-turns were found to be a contributing factor. This paper features the state of the art techniques applied in planning, engineering, designing and construction of this smart right-turn, key factors driving the success, and lessons learned in the process. This paper also presents the significant crash reductions achieved from the application of this smart right-turn design using Empirical Bayes method. The result showed that smart right-turns can reduce overall right-turn crashes by 43% and severe right-turn crashes by 70%.

Keywords: smart right-turn, intersection, cone of vision, empirical Bayes method

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Authors: Sudipta Ghorai, Ossama Salem

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Pavement maintenance, repair, and rehabilitation (MRR) processes may have considerable environmental impacts due to traffic disruptions associated with work zones. The simulation models in use to predict the emission of work zones were mostly static emission factor models (SEFD). SEFD calculates emissions based on average operation conditions e.g. average speed and type of vehicles. Although these models produce accurate results for large-scale planning studies, they are not suitable for analyzing driving conditions at the micro level such as acceleration, deceleration, idling, cruising, and queuing in a work zone. The purpose of this study is to prepare a comprehensive work zone environmental assessment (WEA) framework to calculate the emissions caused due to disrupted traffic; by integrating traffic microsimulation tools with emission models. This will help highway officials to assess the benefits of accelerated construction and opt for the most suitable TMP not only economically but also from an environmental point of view.

Keywords: accelerated construction, pavement MRR, traffic microsimulation, congestion, emissions

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Authors: Sandeep Kumar, Naveen Gupta

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Terahertz (THz) generation has been investigated by beating two cosh-Gaussian laser beams of the same amplitude but different wavenumbers and frequencies through rippled collisionless plasma. The ponderomotive force is operative which is induced due to the intensity gradient of the laser beam over the cross-section area of the wavefront. The electrons evacuate towards a low-intensity regime, which modifies the dielectric function of the medium and results in cross focusing of cosh-Gaussian laser beams. The evolution of spot size of laser beams has been studied by solving nonlinear Schrodinger wave equation (NLSE) with variational technique. The laser beams impart oscillations to electrons which are enhanced with ripple density. The nonlinear oscillatory motion of electrons gives rise to a nonlinear current density driving THz radiation. It has been observed that the periodicity of the ripple density helps to enhance the THz radiation.

Keywords: rippled collisionless plasma, cosh-gaussian laser beam, ponderomotive force, variational technique, nonlinear current density

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Authors: Sabita Mahapatra

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‘Going green’ has been an emerging issue worldwide driving companies to continuously enhance their green capabilities and implement innovative green practices to protect the environment and improve business performance. Green has become a contemporary business environmental issue. The resource advantage theory is adopted in the present study to observe the impact of marketing orientation and green innovation practices on environmental and firm’s performance. The small and medium firms compared to large firms have different approach towards market orientation as a strategic tool. The present study proposes a conceptual framework regarding the impact of market orientation on environmental and firm’s performance through green innovation practices in the context of small and medium scale industries (SMEs). The propositions developed in the present paper would provide scope for future research study to validate the conceptual framework in the emerging economy like India.

Keywords: market orientation, green innovation practices, environment performance, corporate performance, emerging market

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Authors: Galina Mihaleva, C. Koh

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Fashion, like many other design fields, undergoes numerous evolutions throughout the ages. This paper aims to recognize and evaluate the significance of advance technology in fashion design and examine how it changes the role of modern fashion designers by modifying the creation process. It also touches on how modern culture is involved in such developments and how it affects fashion design in terms of conceptualizing and fabrication. The methodology used is through surveying the various examples of technological applications to fashion design and drawing parallels between what was achievable then and what is achievable now. By comparing case studies, existing fashion design examples and crafting method experimentations; we then spot patterns in which to predict the direction of future developments in the field. A breakdown on the elements of technology in fashion design helps us understand the driving force behind such a trend. The results from explorations in the paper have shown that there is an observed pattern of a distinct increase in interest and progress in the field of fashion technology, which leads to the birth of hybrid crafting methods. In conclusion, it is shown that as fashion technology continues to evolve, their role in clothing crafting becomes more prominent and grows far beyond the humble sewing machine.

Keywords: fashion design, functional aesthetics, smart textiles, 3D printing

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Authors: Mbadiwe S. Benyeogor, Oladayo O. Olakanmi, Kosisochukwu P. Nnoli, Olusegun I. Lawal, Eric JJ. Gratton

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For a robot or any vehicular system to navigate in off-road terrain, its driving mechanisms and the electro-software system must be capable of generating, controlling, and moderating sufficient mechanical power with precision. This paper proposes an autonomous robot with a gyro-stabilized active suspension system in form of a hybrid quadrupedal wheel drive mechanism. This system is to serve as a miniature model for demonstrating how off-road vehicles can be robotized into efficient terramechanical mobile platforms that are capable of self-balanced autonomous navigation and maneuvering on rough and uneven topographies. Results from tests and analysis show that the developed system performs as expected. Therefore, our model and control devices can be adapted to computerizing, automating, and upgrading the operation of unmanned ground vehicles for off-road navigation.

Keywords: active suspension, autonomous robots, edge computing, navigational sensors, terramechanics

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Authors: Gurveer Kaur, T. K. Goswami

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Rasgulla (a sweet syrup cheese ball), a sweet, spongy dessert represents traditional sweet dish of an Indian subcontinent prepared by chhana. 100 g of Rasgulla contains 186 calories, and so it is a driving force behind obesity and diabetes. To reduce Rasgulla’s energy value sucrose mainly should be minimized, so instead of sucrose, stevia (zero calories natural sweetener) is used to prepare Rasgulla. In this study three samples were prepared with sucrose to stevia ratio taking 100:0 (as control sample), (i) 50:50 (T1); (ii) 25:75 (T2), and (iii) 0:100 (T3) from 4% fat milk. It was found that as the sucrose concentration decreases the percentage of fat increase in the Rasgulla slightly. Sample T2 showed < 0.1% (±0.06) sucrose content. But there was no significant difference on protein and ash content of the samples. Whitening index was highest (78.0 ± 0.13) for T2 and lowest (65.7 ± 0.21) for the control sample since less sucrose in syrup reduces the browning of the sample (T2). Energy value per 100 g was calculated to be 50, 72, 98, and 184 calories for T3, T2, T1 and control samples, respectively. According to optimization study, the preferred (high quality) order of samples was as follows: T1 > T1 > control > T3. Low sugar content Rasgulla with acceptable quality can be prepared with 25:75 ratio of sucrose to stevia.

Keywords: composition, rasgulla, sensory, stevia

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Authors: Muhammad Rizwan Tabassum, Ao Xia, Jerry D. Murphy

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The aim of this work is to provide an overview of macroalgae as an alternative feedstock for gaseous fuel production and key innovative technologies. Climate change and continuously depleting resources are the key driving forces to think for alternative sources of energy. Macroalgae can be favored over land based energy crops because they are not in direct competition with food crops. However, some drawbacks, such as high moisture content, seasonal variation in chemical composition and process inhibition limit the economic practicability. Macroalgae, like brown seaweed can be converted into gaseous and liquid fuel by different conversion technologies. Biomethane via anaerobic digestion is the appealing technology due to its dual advantage of a commercially applicable and environment friendly technology. Other technologies like biodiesel and bioethanol conversion technologies from seaweed are still under progress. Screening of high yielding macroalgae species, peak harvesting season and process optimization make the technology economically feasible for alternative source of feedstock for biofuel production in future.

Keywords: anaerobic digestion, biofuels, bio-methane, advanced conversion technologies, macroalgae

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Authors: Mamta M. Barapatre, V. N. Sahare

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Since from long time two wheeled vehicle self-balancing has always been a back-breaking task for both human and robots. Leaning a bicycle driving is long time process and goes through building knowledge base for parameter decision making while balancing robots. In order to create this machine learning phase with embedded system the proposed system is designed. The system proposed aims to construct a bicycle automaton, power-driven by an electric motor, which could balance by itself and move along a specific path. This path could be wavy with bumps and varying widths. The key aim was to construct a cycle which self-balances itself by controlling its handle. In order to take a turn, the mass was transferred to the center. In order to maintain the stability, the bicycle bot automatically turned the handle and a turn. Some problems were faced by the team which were Speed, Steering mechanism through mass- distribution (leaning), Center of mass location and gyroscopic effect of its wheel. The idea proposed have potential applications in automation of transportation system and is most efficient.

Keywords: gyroscope-flywheel, accelerometer, servomotor-controller, self stability concept

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Authors: Suren Chilingaryan

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We study two models describing a single two-level system coupled to two boson field modes in either a parallel or orthogonal setup. Both models may be feasible for experimental realization through Raman adiabatic driving in cavity QED. We study their ground state configurations; that is, we find the quantum precursors of the corresponding semi-classical phase transitions. We found that the ground state configurations of both models present the same critical coupling as the quantum Rabi model. Around this critical coupling, the ground state goes from the so-called normal configuration with no excitation, the qubit in the ground state and the fields in the quantum vacuum state, to a ground state with excitations, the qubit in a superposition of ground and excited state, while the fields are not in the vacuum anymore, for the first model. The second model shows a more complex ground state configuration landscape where we find the normal configuration mentioned above, two single-mode configurations, where just one of the fields and the qubit are excited, and a dual-mode configuration, where both fields and the qubit are excited.

Keywords: quantum optics, quantum phase transition, cavity QED, circuit QED

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Authors: Lystra Huggins

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The COVID-19 pandemic affected all facets of life, including pedagogical strategies and perceptual experiences for both instructors and students. While there have also been many challenges and advantages to the online teaching and learning environment, when students’ cameras are on, the daily experiences of students’ lives have been magnified during synchronous online instruction and have served to humanize them in the classroom. This means that students’ everyday experiences, now often on display on ZOOM, allow instructors to see the realities of students. They include children running, spouses walking by parents cooking or sitting on the sofa following the lecture, students at their place of employment or driving from work, or having their classroom engagement interrupted by a delivery. Students’ backgrounds and spaces create unique dynamics during synchronous instruction, which offers a holistic view of them outside academia. This research explores whether witnessing students’ daily experiences leads to empathy from their instructors and whether it results in a greater understanding of students’ challenges and circumstances. Ultimately, it will amplify instructors’ stance on the advantages of students having their cameras on during synchronous online classes to develop a connection with the instructor and a more cohesive classroom environment.

Keywords: instructor’s empathy, synchronous class, asynchronous class, online environment

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Authors: Mingbao Chen

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The blue economy is a new comprehensive marine economy integrated with resources, industries, and regions, and is an upgraded version of the marine economy. The blue economy attaches great importance to the coordinated development of the ecological environment and the economy, which is an emerging economic form advocated by all countries in the world. This paper constructs the model including four variables：natural capital, economic capital, intellectual capital, cultural capital. Theoretically, this paper deduces the function mechanism of variables on economic growth, and empirically calculates the driving force and influence of the blue economy on the national economy by using data of China's 2006-2015 year. The results show that natural capital and economic capital remain the main factors of blue growth in the blue economy. And with the development of economic society and technological progress, the role of intellectual capital and cultural capital is bigger and bigger. Therefore, promoting the development of marine science and technology and culture is the focus of the future blue economic development.

Keywords: blue growth, natural capital, intellectual capital, cultural capital

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Authors: Mingxin Li, Liya Ni

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Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

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Authors: Therese Scali

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Over the years, the European Union has continued to extend its action on lesbian, gay men, bisexual and transgender (LGBT) rights to a range of areas including access to justice, asylum, freedom of expression and assembly, parenting, and mutual recognition of civil status within the EU. The European Parliament has been a driving force behind such action adopting a range of resolutions calling for continued progress in this field. In particular, Belgium has been one of the first countries to legalize same-sex parenting and to create a general framework for action against negative attitudes towards gay and lesbian parents. The present paper aims at highlighting public healthcare workers’ attitudes towards different types of same-sex headed families in Belgium, and the content of their interventions in schools. Results revealed that attitudes can go from supportive to unsupportive, and participants do not show the same degree of support towards the different types of same-sex parenting. This contribution highlights work’s implication for public policy by understanding the resources and challenges that health-care professionals face in their work.

Keywords: attitudes, gay and lesbian parents, health-care workers, homophobia, prevention

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Authors: Shrikant V. Sangludkar, Dilip I. Sangotra, Sachin T. Bagde, Abhijeet A. Khandagale

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The paper discloses a controlled tracked humanoid robot moving platform. A driving and driven wheel are controlled by a control module to drive a robot body to move according to data signals of a monitoring module, in addition, remote transmission can be achieved, and a certain remote control function can be realized. A power management module circuit board looks after in used for providing electric drive for moving of the robot body and distribution of separate power source to be used in internal of robot system. An external port circuit board is arranged, the tracked robot moving platform can be used immediately for any data acquisition. The moving platform is simple and compact in structure, strong in adaptation performance, stable in operation and suitable for being operated in severe environments. Meanwhile, a layered modular installation structure is adopted, and therefore the moving platform is convenient to assemble and disassemble.

Keywords: moving platform, humanoid robot, embedded controlled drive, mobile robot, museum robots, self-localization, obstacle avoidance, communication

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Authors: Wei-Song Hung

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We utilized pressure, vacuum, and evaporation-assisted self-assembly techniques through which graphene oxide (GO) was deposited on modified polyacrylonitrile (mPAN). The fabricated composite GO/mPAN membranes were applied to dehydrate 1-butanol mixtures by pervaporation. Varying driving forces in the self-assembly techniques induced different GO assembly layer microstructures. XRD results indicated that the GO layer d-spacing varied from 8.3 Å to 11.5 Å. The self-assembly technique with evaporation resulted in a heterogeneous GO layer with loop structures; this layer was shown to be hydrophobic, in contrast to the hydrophilic layer formed from the other two techniques. From the pressure-assisted technique, the composite membrane exhibited exceptional pervaporation performance at 30 C: concentration of water at the permeate side = 99.6 wt% and permeation flux = 2.54 kg m-2 h-1. Moreover, the membrane sustained its operating stability at a high temperature of 70 C: a high water concentration of 99.5 wt% was maintained, and a permeation flux as high as 4.34 kg m-2 h-1 was attained. This excellent separation performance stemmed from the dense, highly ordered laminate structure of GO.

Keywords: graphene oxide, self-assembly, alcohol dehydration, polyacrylonitrile (mPAN)

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Authors: E. K. A. Ogunshile

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This paper is aimed at creating an Automatic Java X-Machine testing tool for software development. The nature of software development is changing; thus, the type of software testing tools required is also changing. Software is growing increasingly complex and, in part due to commercial impetus for faster software releases with new features and value, increasingly in danger of containing faults. These faults can incur huge cost for software development organisations and users; Cambridge Judge Business School’s research estimated the cost of software bugs to the global economy is $312 billion. Beyond the cost, faster software development methodologies and increasing expectations on developers to become testers is driving demand for faster, automated, and effective tools to prevent potential faults as early as possible in the software development lifecycle. Using X-Machine theory, this paper will explore a new tool to address software complexity, changing expectations on developers, faster development pressures and methodologies, with a view to reducing the huge cost of fixing software bugs.

Keywords: conformance testing, finite state machine, software testing, x-machine

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Authors: Gemala Dewi, Wirdyaningsih, Farida Prihatini

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The development of sharia business activities at present has solidified its societal mark and has crossed influence between several nations. In the practice, there may be disputes, breaches and other forms of conflict that occurred along the way. In the meantime, alternative settlements of disputes are utilized differently between nations in the context of their political, social, economic, legal and infrastructural (technology and transportation) scope. Besides the various conditions, there is a common driving factor, which is a consequence of the need for businesses to settle conflicts in an efficient and cost-efficient manner. This factor is paired symbiotically with the limitations of the court and legal processes. Knowing this, Indonesia and Egypt represent countries that have similar social, political, economic and legal conditions. This academic research establishes a normative analysis that looks and compares the rules that regulate the prospects and challenges in the regards of dispute settlements in reference to sharia economics in Indonesia and Egypt. This work recommends that sharia economics dispute settlement is significant to be incorporated in both Indonesian and Egyptian legal systems.

Keywords: sharia economics, dispute resolution, Indonesia, Egypt

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Authors: Peter Temitope Agboola

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Food insecurity continues to affect a large number of U.S households during this coronavirus COVID-19 pandemic. The pandemic has threatened the livelihoods of people, making them vulnerable to severe hardship and has had an unanticipated impact on the U.S economy. This study attempts to identify the food insecurity status of households and the determinant factors driving household food insecurity. Additionally, it attempts to discover the mitigation measures adopted by households during the pandemic in the city of Huntsville, Texas. A structured online sample survey was used to collect data, with a household expenditures survey used in evaluating the food security status of the household. Most survey respondents disclosed that the COVID-19 pandemic had affected their life and source of income. Furthermore, the main analytical tool used for the study is descriptive statistics and logistic regression modeling. A logistic regression model was used to determine the factors responsible for food insecurity in the study area. The result revealed that most households in the study area are food secure, with the remainder being food insecure.

Keywords: food insecurity, household expenditure survey, COVID-19, coping strategies, food pantry

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Authors: A. Bahar Ganiyeva, M. Sabuhi Tanriverdiyev

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The article analyzes state support and policy mechanisms aimed at driving tourism as one of the vibrant and rapidly developing economies. State programs and long-range strategic roadmaps and previous programs execution, results and their impact on the particular countries economy have been raised during the research. This theme provides a useful framework for discussions with a wider range of stakeholders as the implications arising are of importance both for academics and practitioners engaged in hospitality and tourism development and research. The impact that tourism has on sustainable regional development in emerging markets is highly substantial. For Azerbaijan, Turkey, Georgia, and Russia, with their rich natural resources and cultural heritage, tourism can be an important basis for economic expansion, and a way to form an acceptable image of the countries as safe, open, hospitable, and complex.

Keywords: Sustainable tourism, hospitality, destination, strategic roadmap, tourism, economy, growth, state support, mechanism, policy formation, state program

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Authors: Mohamed Haffar, Muhammad Abdul Aziz, Ahmad Ghoneim

Abstract:

The importance of having a good organizational culture that supports employee job satisfaction has fascinated both the business and academic world because of a tantalizing promise: culture can be fundamental to the enhancement of financial performance. This promise has led to growing interest for both researchers and practitioners in attempting to understand the influence of organizational culture on employees’ satisfaction and organizational performance. Even though the relationship between organizational culture and employee job satisfaction have gained attention in the literature, the majority of studies have been conducted within manufacturing organizations and tend to oversee the impact of culture on employee job satisfaction in a service-based environment. Thus, the main driving force of this study was to explore the role of organizational culture types in facilitating employee job satisfaction at Emerald Publishing Group. Interviews qualitative data analysis indicated that Emerald’s culture dominated by adhocracy and clan culture values. In addition, the findings provided evidence, which demonstrated that group and adhocracy organizational culture types play key roles in facilitating employee job satisfaction in a service-based environment.

Keywords: employee satisfaction, organizational culture, performance, service based environment

Procedia PDF Downloads 411

Authors: J. Y. Sun, H. Z. Shen

Abstract:

We study the photon blockade at exceptional points for a non-Hermitian optomechanical system coupled to the driven whispering-gallery-mode microresonator with two nanoparticles under the weak optomechanical coupling approximation, where exceptional points emerge periodically by controlling the relative angle of the nanoparticles. We find that conventional photon blockade occurs at exceptional points for the eigenenergy resonance of the single-excitation subspace driven by a laser field and discuss the physical origin of conventional photon blockade. Under the weak driving condition, we analyze the influences of the different parameters on conventional photon blockade. We investigate conventional photon blockade at nonexceptional points, which exists at two optimal detunings due to the eigenstates in the single-excitation subspace splitting from one (coalescence) at exceptional points to two at nonexceptional points. Unconventional photon blockade can occur at nonexceptional points, while it does not exist at exceptional points since the destructive quantum interference cannot occur due to the two different quantum pathways to the two-photon state not being formed. The realization of photon blockade in our proposal provides a viable and flexible way for the preparation of single-photon sources in the non-Hermitian optomechanical system.

Keywords: optomechanical systems, photon blockade, non-hermitian, exceptional points

Procedia PDF Downloads 105

Authors: Nurhak Altın, Ayhan Kucukmanisa, Oguzhan Urhan

Abstract:

It is important that highways are in good condition for traffic safety. Road crashes (road cracks, erosion of lane markings, etc.) can cause accidents by affecting driving. Image processing based methods for detecting road cracks are available in the literature. In this paper, a deep learning based road crack detection approach is proposed. YOLO (You Look Only Once) is adopted as core component of the road crack detection approach presented. The YOLO network structure, which is developed for object detection, is trained with road crack images as a new class that is not previously used in YOLO. The performance of the proposed method is compared using different training methods: using randomly generated weights and training their own pre-trained weights (transfer learning). A similar training approach is applied to the simplified version of the YOLO network model (tiny yolo) and the results of the performance are examined. The developed system is able to process 8 fps on NVIDIA Jetson TX1 development kit.

Keywords: deep learning, embedded platform, real-time processing, road crack detection

Procedia PDF Downloads 320