Search results for: transportation networks

Authors: A. Shebani, C. Pislaru

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Wear of materials is an everyday experience and has been observed and studied for long time. The prediction of wear is a fundamental problem in the industrial field, mainly correlated to the planning of maintenance interventions and economy. Pin-on-disc test is the most common test which is used to study the wear behaviour. In this paper, the pin-on-disc (AEROTECH UNIDEX 11) is used for the investigation of the effects of normal load and hardness of material on the wear under dry and sliding conditions. In the pin-on-disc rig, two specimens were used; one, a pin which is made of steel with a tip, is positioned perpendicular to the disc, where the disc is made of aluminium. The pin wear and disc wear were measured by using the following instruments: The Talysurf instrument, a digital microscope, and the alicona instrument; where the Talysurf profilometer was used to measure the pin/disc wear scar depth, and the alicona was used to measure the volume loss for pin and disc. After that, the Archard model, American Society for Testing and Materials model (ASTM), and neural network model were used for pin/disc wear modelling and the simulation results are implemented by using the Matlab program. This paper focuses on how the alicona can be considered as a powerful tool for wear measurements and how the neural network is an effective algorithm for wear estimation.

Keywords: wear modelling, Archard Model, ASTM Model, Neural Networks Model, Pin-on-disc Test, Talysurf, digital microscope, Alicona

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Authors: Abrar Al-Enzi

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This study investigates the role of the popular utilization of Wasta within Arab societies. Wasta, by definition, is a set of personal networks based on family or kinship ties in which power and influence are utilized to get things done. As Wasta evolved, it became intensely rooted in Arab cultures, which is considered as an intrinsic tool of the culture, a method of doing business transactions and as a family obligation. However, the consequences related to Wasta in business are substantial as it impacts organizational performance, employee’s perception of the organization and the atmosphere between employees. To date, there has been little in-depth organizational research on the impact of Wasta. Hence, the question that will be addressed is: Does Wasta influence human resource management, knowledge sharing and innovation in Kuwait, which in turn affects employees’ commitment within organizations? As a result, a mixed method sequential exploratory research design will be used to examine the mentioned subject, which consists of three phases: (1) Doing some initial exploratory interviews; (2) Developing a paper-based and online survey (Quantitative method) based on the findings; (3) Lastly, following up with semi-structured interviews (Qualitative method). The rationale behind this approach is that both qualitative and quantitative methods complement each other by providing a more complete picture of the subject matter.

Keywords: commitment, HRM practices, social capital, Wasta

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Authors: Ofoegbu Ositadinma Edward

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This research paper discusses a web based monitoring system that enables effective monitoring of fuel pump output and sales volume from distributed fuel stations under the domain of a single company/organization. The traditional method of operation by these organizations in Nigeria is non-automated and accounting for dispensed product is usually approximated and manual as there is little or no technology implemented to presently provide information relating to the state of affairs in the station both to on-ground staff and to supervisory staff that are not physically present in the station. This results in unaccountable losses in product and revenue as well as slow decision making. Remote monitoring technology as a vast research field with numerous application areas incorporating various data collation techniques and sensor networks can be applied to provide information relating to fuel pump status in distributed fuel stations reliably. Thus, the proposed system relies upon a microcontroller, keypad and pump to demonstrate the traditional fuel dispenser. A web-enabled PC with an accompanying graphic user interface (GUI) was designed using virtual basic which is connected to the microcontroller via the serial port which is to provide the web implementation.

Keywords: fuel pump, microcontroller, GUI, web

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Authors: Ting Gao, Mingyue He

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Reconfigurable intelligent surfaces (RISs) are expected to be an important part of next-generation wireless communication networks due to their potential to reduce the hardware cost and energy consumption of millimeter Wave (mmWave) massive multiple-input multiple-output (MIMO) technology. However, owing to the lack of signal processing abilities of the RIS, the perfect channel state information (CSI) in RIS-assisted communication systems is difficult to acquire. In this paper, the uplink channel estimation for mmWave systems with a hybrid active/passive RIS architecture is studied. Specifically, a deep learning-based estimation scheme is proposed to estimate the channel between the RIS and the user. In particular, the sparse structure of the mmWave channel is exploited to formulate the channel estimation as a sparse reconstruction problem. To this end, the proposed approach is derived to obtain the distribution of non-zero entries in a sparse channel. After that, the channel is reconstructed by utilizing the least-squares (LS) algorithm and compressed sensing (CS) theory. The simulation results demonstrate that the proposed channel estimation scheme is superior to existing solutions even in low signal-to-noise ratio (SNR) environments.

Keywords: channel estimation, reconfigurable intelligent surface, wireless communication, deep learning

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Authors: Safa’ Abdelkarim Hammad

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The electrical power system is one of the main parts of the nation's infrastructure, and the availability and cost of electricity are critical factors in industrial competitiveness and strategy. Restructuring of the electricity supply industries is a very complex exercise based on national energy strategies and policies, macroeconomic developments, and national conditions, and its application varies from country to country. Electricity regulation of natural monopolies is a challenging task. Regulators face the problem of providing appropriate incentives for improvement of efficiency. Incentive regulation is often considered as an efficient regulatory tool to handle the problem, and it is widely applied in several countries. However, the exact regulation methodologies differ from one country to another. Network quantitative reliability evaluation is an essential factor with regard to the quality of supply. The main factors used to judge the reliability of supply is measured by the number and duration of interruptions experienced by customers. Several indicators are used to evaluate reliability in distribution networks. This paper addresses the impact of incentive regulation and performance benchmarking in the field of electricity distribution in Jordan. The theory of efficiency measurement and the most common models; NCSQS and DEA models are presented.

Keywords: incentive regulations, reliability, restructuring, Tarrif

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Authors: Yating Yang, Xue Zhang, Chengli Zhao

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Technology capability refers to the comprehensive ability that influences all factors of technological development. Among them, researchers’ resources serve as the foundation and driving force for technology capability, representing a significant manifestation of a country/region's technological capability. Therefore, the cross-border transfer behavior of researchers to some extent reflects changes in technological capability between countries/regions, providing a unique research perspective for technological capability assessment. This paper proposes a technological capability assessment model based on personnel transfer networks, which consists of a researchers' transfer network model and a country/region role evolution model. It evaluates the changes in a country/region's technological capability roles from the perspective of researcher transfers and conducts an analysis using artificial intelligence as a case study based on literature data. The study reveals that the United States, China, and the European Union are core nodes, and identifies the role evolution characteristics of several major countries/regions.

Keywords: transfer network, technological capability assessment, central-peripheral structure, role evolution

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Authors: Bashir Abdu Muzakkari, Mohamad Afendee Mohamad, Mohd Fadzil Abdul Kadir

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Wireless Sensor Networks (WSNs) is an aggregation of several tiny, low-cost sensor nodes, spatially distributed to monitor physical or environmental status. WSN is constantly changing because of the rapid technological advancements in sensor elements such as radio, battery and operating systems. The Medium Access Control (MAC) protocols remain very vital in the WSN because of its role in coordinating communication amongst the sensors. Other than battery consumption, packet collision, network lifetime and latency are factors that largely depend on WSN MAC protocol and these factors have been widely treated in recent days. In this paper, we survey some latest proposed WSN Contention-based, Scheduling-based and Hybrid MAC protocols while presenting an examination, correlation of advantages and limitations of each protocol. Concentration is directed towards investigating the treatment of Quality of Service (QoS) performance metrics within these particular protocols. The result shows that majority of the protocols leaned towards energy conservation. We, therefore, believe that other performance metrics of guaranteed QoS such as latency, throughput, packet loss, network and bandwidth availability may play a critical role in the design of future MAC protocols for WSNs.

Keywords: WSN, QoS, energy consumption, MAC protocol

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Authors: Feng Wang, Shencheng Ni, Shuying Han, Shanhong You

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With the development of optical communication, optical performance monitoring (OPM) has received more and more attentions. Since optical signal-to-noise ratio (OSNR) is directly related to bit error rate (BER), it is one of the important parameters in optical networks. Recently, artificial neural network (ANN) has been greatly developed. ANN has strong learning and generalization ability. In this paper, a method of OSNR monitoring based on delay-tap sampling (DTS) and ANN has been proposed. DTS technique is used to extract the eigenvalues of the signal. Then, the eigenvalues are input into the ANN to realize the OSNR monitoring. The experiments of 10 Gb/s non-return-to-zero (NRZ) on–off keying (OOK), 20 Gb/s pulse amplitude modulation (PAM4) and 20 Gb/s return-to-zero (RZ) differential phase-shift keying (DPSK) systems are demonstrated for the OSNR monitoring based on the proposed method. The experimental results show that the range of OSNR monitoring is from 15 to 30 dB and the root-mean-square errors (RMSEs) for 10 Gb/s NRZ-OOK, 20 Gb/s PAM4 and 20 Gb/s RZ-DPSK systems are 0.36 dB, 0.45 dB and 0.48 dB respectively. The impact of chromatic dispersion (CD) on the accuracy of OSNR monitoring is also investigated in the three experimental systems mentioned above.

Keywords: artificial neural network (ANN), chromatic dispersion (CD), delay-tap sampling (DTS), optical signal-to-noise ratio (OSNR)

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Authors: Weiwei Cui, Dejian Lin, Leigang Zhang, Yao Wang, Zheng Sun, Lianfeng Li

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Built-in test (BIT) is an important technology in testability field, and it is widely used in state monitoring and fault diagnosis. With the improvement of modern equipment performance and complexity, the scope of BIT becomes larger, and it leads to the emergence of false alarm problem. The false alarm makes the health assessment unstable, and it reduces the effectiveness of BIT. The conventional false alarm suppression methods such as repeated test and majority voting cannot meet the requirement for a complicated system, and the intelligence algorithms such as artificial neural networks (ANN) are widely studied and used. However, false alarm has a very low frequency and small sample, yet a method based on ANN requires a large size of training sample. To recognize the false alarm, we propose a method based on multi-classification support vector machine (SVM) in this paper. Firstly, we divide the state of a system into three states: healthy, false-alarm, and faulty. Then we use multi-classification with '1 vs 1' policy to train and recognize the state of a system. Finally, an example of fault injection system is taken to verify the effectiveness of the proposed method by comparing ANN. The result shows that the method is reasonable and effective.

Keywords: false alarm, fault diagnosis, SVM, k-means, BIT

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Authors: F. Clara Fang, Hernan Castaneda

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The Connecticut Department of Transportation (ConnDOT) has constructed four roundabouts in the State of Connecticut within the past ten years. VISSIM traffic simulation software was utilized to analyze these roundabouts during their design phase. The queue length and level of service observed in the field appear to be better than predicted by the VISSIM model. The objectives of this project are to: identify VISSIM input variables most critical to accurate modeling; recommend VISSIM calibration factors; and, provide other recommendations for roundabout traffic operations modeling. Traffic data were collected at these roundabouts using Miovision Technologies. Cameras were set up to capture vehicle circulating activity and entry behavior for two weekdays. A large sample size of filed data was analyzed to achieve accurate and statistically significant results. The data extracted from the videos include: vehicle circulating speed; critical gap estimated by Maximum Likelihood Method; peak hour volume; follow-up headway; travel time; and, vehicle queue length. A VISSIM simulation of existing roundabouts was built to compare both queue length and travel time predicted from simulation with measured in the field. The research investigated a variety of simulation parameters as calibration factors for describing driver behaviors at roundabouts. Among them, critical gap is the most effective calibration variable in roundabout simulation. It has a significant impact to queue length, particularly when the volume is higher. The results will improve the design of future roundabouts in Connecticut and provide decision makers with insights on the relationship between various choices and future performance.

Keywords: driver critical gap, roundabout analysis, simulation, VISSIM modeling

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Authors: R. Verwiebe, L. Seewann, M. Wolf

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This presentation addresses marginalization and discrimination as experienced by young academics with a migrant background in the Austrian labor market. Focusing on second generation academics of Central Eastern European and Turkish descent we explore two major issues. First, we ask whether their career-entry and everyday professional life entails origin-specific barriers. As educational residents, they show competences which, when lacking, tend to be drawn upon to explain discrimination: excellent linguistic skills, accredited high-level training, and networks. Second, we concentrate on how this group reacts to discrimination and overcomes experiences of marginalization. To answer these questions, we utilize recent sociological and social psychological theories that focus on the diversity of individual experiences. This distinguishes us from a long tradition of research that has dealt with the motives that inform discrimination, but has less often considered the effects on those concerned. Similarly, applied coping strategies have less often been investigated, though they may provide unique insights into current problematic issues. Building upon present literature, we follow recent discrimination research incorporating the concepts of ‘multiple discrimination’, ‘subtle discrimination’, and ‘visual social markers’. 21 problem-centered interviews are the empirical foundation underlying this study. The interviewees completed their entire educational career in Austria, graduated in different universities and disciplines and are working in their first post-graduate jobs (career entry phase). In our analysis, we combined thematic charting with a coding method. The results emanating from our empirical material indicated a variety of discrimination experiences ranging from barely perceptible disadvantages to directly articulated and overt marginalization. The spectrum of experiences covered stereotypical suppositions at job interviews, the disavowal of competencies, symbolic or social exclusion by new colleges, restricted professional participation (e.g. customer contact) and non-recruitment due to religious or ethnical markers (e.g. headscarves). In these experiences the role of the academics education level, networks, or competences seemed to be minimal, as negative prejudice on the basis of visible ‘social markers’ operated ‘ex-ante’. The coping strategies identified in overcoming such barriers are: an increased emphasis on effort, avoidance of potentially marginalizing situations, direct resistance (mostly in the form of verbal opposition) and dismissal of negative experiences by ignoring or ironizing the situation. In some cases, the academics drew into their specific competences, such as an intellectual approach of studying specialist literature, focus on their intercultural competences or planning to migrate back to their parent’s country of origin. Our analysis further suggests a distinction between reactive (i.e. to act on and respond to experienced discrimination) and preventative strategies (applied to obviate discrimination) of coping. In light of our results, we would like to stress that the tension between educational and professional success experienced by academics with a migrant background – and the barriers and marginalization they continue to face – are essential issues to be introduced to socio-political discourse. It seems imperative to publicly accentuate the growing social, political and economic significance of this group, their educational aspirations, as well as their experiences of achievement and difficulties.

Keywords: coping strategies, discrimination, labor market, second generation university graduates

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Authors: Tiberiu Socaciu, Tudor Colomeischi, Eugenia Iancu

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Business failure affects in various proportions shareholders, managers, lenders (banks), suppliers, customers, the financial community, government and society as a whole. In the era in which we have telecommunications networks, exists an interdependence of markets, the effect of a failure of a company is relatively instant. To effectively manage risk exposure is thus require sophisticated support systems, supported by analytical tools to measure, monitor, manage and control operational risks that may arise. As we know, bankruptcy is a phenomenon that managers do not want no matter what stage of life is the company they direct / lead. In the analysis made by us, by the nature of economic models that are reviewed (Altman, Conan-Holder etc.), estimating the risk of bankruptcy of a company corresponds to some extent with its own business cycle tracing of the company. Various models for predicting bankruptcy take into account direct / indirect aspects such as market position, company growth trend, competition structure, characteristics and customer retention, organization and distribution, location etc. From the perspective of our research we will now review the economic models known in theory and practice for estimating the risk of bankruptcy; such models are based on indicators drawn from major accounting firms.

Keywords: Anglo-Saxon models, continental models, national models, statistical models

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Authors: M. S. Gadala, Khaled Ahmed, Elasadig Mahdi

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In this paper, we introduced a gradient-based inverse solver to obtain the missing boundary conditions based on the readings of internal thermocouples. The results show that the method is very sensitive to measurement errors, and becomes unstable when small time steps are used. The artificial neural networks are shown to be capable of capturing the whole thermal history on the run-out table, but are not very effective in restoring the detailed behavior of the boundary conditions. Also, they behave poorly in nonlinear cases and where the boundary condition profile is different. GA and PSO are more effective in finding a detailed representation of the time-varying boundary conditions, as well as in nonlinear cases. However, their convergence takes longer. A variation of the basic PSO, called CRPSO, showed the best performance among the three versions. Also, PSO proved to be effective in handling noisy data, especially when its performance parameters were tuned. An increase in the self-confidence parameter was also found to be effective, as it increased the global search capabilities of the algorithm. RPSO was the most effective variation in dealing with noise, closely followed by CRPSO. The latter variation is recommended for inverse heat conduction problems, as it combines the efficiency and effectiveness required by these problems.

Keywords: inverse analysis, function specification, neural net works, particle swarm, run-out table

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Authors: Juan de Ona, Esperanza Estevez, Rocío de Ona

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Urban traffic levels can be reduced by drawing travelers away from private vehicles over to using public transport. This modal change can be achieved by either introducing restrictions on private vehicles or by introducing measures which increase people’s satisfaction with public transport. For public transport users, quality of service affects customer satisfaction, which, in turn, influences the behavioral intentions towards the service. This paper intends to identify the main attributes which influence the perception private vehicle users have about the public transport services provided in five European cities: Berlin, Lisbon, London, Madrid and Rome. Ordinal logit models have been applied to an online panel survey with a sample size of 2,500 regular private vehicle users (approximately 500 inhabitants per city). To achieve a comprehensive analysis and to deal with heterogeneity in perceptions, 15 models have been developed for the entire sample and 14 user segments. The results show differences between the cities and among the segments. Madrid was taken as reference city and results indicate that the inhabitants are satisfied with public transport in Madrid and that the most important public transport service attributes for private vehicle users are frequency, speed and intermodality. Frequency is an important attribute for all the segments, while speed and intermodality are important for most of the segments. An analysis by segments has identified attributes which, although not important in most cases, are relevant for specific segments. This study also points out important differences between the five cities. Findings from this study can be used to develop policies and recommendations for persuading.

Keywords: service quality, satisfaction, public transportation, private vehicle users, car users, segmentation, ordered logit

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Authors: Xiaodong Li, Peng Gao, Chao-Jung Huang, Shiying Hao, Xuefeng B. Ling, Yongxia Han, Yaqi Zhang, Le Zheng, Chengyin Ye, Modi Liu, Minjie Xia, Changlin Fu, Bo Jin, Karl G. Sylvester, Eric Widen

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Predicting the risk of Pancreatic Adenocarcinoma (PA) in advance can benefit the quality of care and potentially reduce population mortality and morbidity. The aim of this study was to develop and prospectively validate a risk prediction model to identify patients at risk of new incident PA as early as 3 months before the onset of PA in a statewide, general population in Maine. The PA prediction model was developed using Deep Neural Networks, a deep learning algorithm, with a 2-year electronic-health-record (EHR) cohort. Prospective results showed that our model identified 54.35% of all inpatient episodes of PA, and 91.20% of all PA that required subsequent chemoradiotherapy, with a lead-time of up to 3 months and a true alert of 67.62%. The risk assessment tool has attained an improved discriminative ability. It can be immediately deployed to the health system to provide automatic early warnings to adults at risk of PA. It has potential to identify personalized risk factors to facilitate customized PA interventions.

Keywords: cancer prediction, deep learning, electronic health records, pancreatic adenocarcinoma

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Authors: Yujie Chen , Zhen Li

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In the context of planning transformation, how to promote public participation in the formulation and implementation of collaborative planning has been the focused issue of discussion. However, existing studies have often been case-specific or focused on a specific design field, leaving the role of participatory social media (PSM) in urban collaborative planning generally questioned. A systematic database search was conducted in December 2019. Articles and projects were eligible if they reported a quantitative empirical study applying participatory social media in the collaborative planning process (a prospective, retrospective, experimental, longitudinal research, or collective actions in planning practices). Twenty studies and seven projects were included in the review. Findings showed that social media are generally applied in public spatial behavior, transportation behavior, and community planning fields, with new technologies and new datasets. PSM has provided a new platform for participatory design, decision analysis, and collaborative negotiation most widely used in participatory design. Findings extracted several existing forms of PSM. PSM mainly act as three roles: the language of decision-making for communication, study mode for spatial evaluation, and decision agenda for interactive decision support. Three optimization content of PSM were recognized, including improving participatory scale, improvement of the grass-root organization, and promotion of politics. However, basically, participants only could provide information and comment through PSM in the future collaborative planning process, therefore the issues of low data response rate, poor spatial data quality, and participation sustainability issues worth more attention and solutions.

Keywords: participatory social media, collaborative planning, planning workshop, application mode

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Authors: Teja Koduru

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Untreated Lyme disease can lead to neurological, cardiac, and dermatological complications. Rapid diagnosis of the erythema migrans (EM) rash, a characteristic symptom of Lyme disease is therefore crucial to early diagnosis and treatment. In this study, we aim to utilize deep learning frameworks including Tensorflow and Keras to create deep convolutional neural networks (DCNN) to detect images of acute Lyme Disease from images of erythema migrans. This study uses a custom database of erythema migrans images of varying quality to train a DCNN capable of classifying images of EM rashes vs. non-EM rashes. Images from publicly available sources were mined to create an initial database. Machine-based removal of duplicate images was then performed, followed by a thorough examination of all images by a clinician. The resulting database was combined with images of confounding rashes and regular skin, resulting in a total of 683 images. This database was then used to create a DCNN with an accuracy of 93% when classifying images of rashes as EM vs. non EM. Finally, this model was converted into a web and mobile application to allow for rapid diagnosis of EM rashes by both patients and clinicians. This tool could be used for patient prescreening prior to treatment and lead to a lower mortality rate from Lyme disease.

Keywords: Lyme, untreated Lyme, erythema migrans rash, EM rash

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Authors: Marpaleni

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The intergovernmental Panel on Climate Change (IPCC) declared in 2007 that global warming and climate change are not just a series of events caused by nature, but rather caused by human behaviour. Thus, to reduce the impact of human activities on climate change it is required to have information about how people respond to the environmental issues and what constraints they face. However, information on these and other phenomena remains largely missing, or not fully integrated within the existing data systems. The proposed study is aimed at filling the gap in this knowledge by focusing on Environmentally Friendly Behaviour (EFB) of the people of Indonesia, by taking the province of South Sumatera as a case of study. EFB is defined as any activity in which people engage to improve the conditions of the natural resources and/or to diminish the impact of their behaviour on the environment. This activity is measured in terms of consumption in five areas at the household level, namely housing, energy, water usage, recycling and transportation. By adopting the Indonesia’s Environmentally Friendly Behaviour conducted by Statistics Indonesia in 2013, this study aims to precisely identify one’s orientation towards EFB based on socio demographic characteristics such as: age, income, occupation, location, education, gender and family size. The results of this research will be useful to precisely identify what support people require to strengthen their EFB, to help identify specific constraints that different actors and groups face and to uncover a more holistic understanding of EFB in relation to particular demographic and socio-economics contexts. As the empirical data are examined from the national data sample framework, which will continue to be collected, it can be used to forecast and monitor the future of EFB.

Keywords: environmentally friendly behavior, demographic, South Sumatera, Indonesia

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Authors: Tali Capua, Karin Hermon, Miguel Glatstein, Oren Tavor, Ayelet Rimon

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Background: Electric bicycles (E-bikes) are one of a wide range of light electric vehicles that provide convenient local transportation and attractive recreational opportunities. Along with their growing use worldwide, the E-bike related injury rate increases. To the best of our knowledge, this study is the first to specifically compare E-bike with classic bicycle related injuries in children. Methods: Data of all pediatric ( < 16 years of age) bicycle related injuries presenting to an urban level I trauma center between 2014 and 2015 were collected and analyzed. The recorded data included age, gender, details of the accident, as well severity of injury, medical diagnosis, and the outcome. Abbreviated Injury Score (AIS) and Injury Severity Score (ISS) were calculated for each patient. Data of E-bike related injuries and classic bicycle were then compared. Results: A total of 124 bicycle related injuries and 97 E-bike related injuries presented to the emergency department. Once pedestrians and bicycle passengers were removed, the groups of riders consisted of 111 bikers and 85 E-bikers. The mean age of bikers was 9.9 years (range 3-16 years) and of E-bikers was 13.7 years (range 7.5-16 years). Injuries to the head and the extremities were common in both groups. Compared to bikers, E-bikers had significantly more injuries to intra-abdominal organs (p = 0.04). Twenty patients (16%) with bicycle related injuries were admitted, and 13 (15%) patients with E-bike related injuries, of the latter group four underwent surgical intervention. ISS scores were low overall, but the injuries of higher severity (ISS > 9) were among the E-bikers. Conclusions: This study provides unique information which suggests that injuries in E-bikers tend to be more severe than in classic bikers. There is a need for regulation regarding the use of E-bikes to enhance the safety of both bikers and other road and pavement users.

Keywords: bicycle, electric bicycle, injury, pediatric, trauma

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Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

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Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

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Authors: Shigdaf Mekuriaw, Firew Tegegne, A. Tsunekawa, Dereje Tewabe

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The purpose of this paper is to make a comprehensive review on the use of water hyacinth (Eichhornia crassipes) as a potential livestock feed and argue its utilization as complementary strategy to other control methods. Water Hyacinth is one of the most noxious plant invaders of rivers and lakes. Such weeds cause environmental disaster and interfere with economic and recreational activities such as water transportation and fishing. Economic impacts of the weed in seven African countries have been estimated at between 20-50 million US$ every year. It would, therefore, be prudent to suggest utilization as a complementary control method. The majority of people in developing countries are dependent on traditional and inefficient crop-livestock production system that constrains their ability to enhance economic productivity and quality of life. Livestock in developing countries faces shortage of feed, especially during the long dry seasons. Existing literature shows the use of water hyacinth as livestock and fish feed. The chemical composition of water hyacinth varies considerably. Due to its relatively high crude protein (CP) content (5.8-20.0%), water hyacinth can be considered as a potential protein supplement for livestock which commonly feed cereal crop residues whose contribution as source of feed is increasing in Africa. Though the effects of anti-nutritional factors (ANFs) present in water hyacinth is not investigated, their concentrations are not above threshold hinder its utilization as livestock feed. In conclusion, water hyacinth could provide large quantities of nutritious feed for animals. Like other feeds, water hyacinth may not be offered as a sole feed and based on existing literature its optimum inclusion level reaches 50%.

Keywords: Africa, livestock feed, water bodies, water hyacinth and weed control method

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Authors: Arias M. L., D’Adamo J., Novosad M. N., Raffo P. A., Burbridge H. P., Artana G.

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Shale oils are highly paraffinic and, consequently, can create wax deposits that foul pipelines during transportation. Several factors must be considered when designing pipelines or treatment programs that prevents wax deposition: including chemical species in crude oils, flowrates, pipes diameters and temperature. This paper describes the wax deposition study carried out within the framework of Y-TEC's flow assurance projects, as part of the process to achieve a better understanding on wax deposition issues. Laboratory experiments were performed on a medium size, 1 inch diameter, wax deposition loop of 15 mts long equipped with a solid detector system, online microscope to visualize crystals, temperature and pressure sensors along the loop pipe. A baseline test was performed with diesel with no paraffin or additive content. Tests were undertaken with different temperatures of circulating and cooling fluid at different flow conditions. Then, a solution formed with a paraffin added to the diesel was considered. Tests varying flowrate and cooling rate were again run. Viscosity, density, WAT (Wax Appearance Temperature) with DSC (Differential Scanning Calorimetry), pour point and cold finger measurements were carried out to determine physical properties of the working fluids. The results obtained in the loop were analyzed through momentum balance and heat transfer models. To determine possible paraffin deposition scenarios temperature and pressure loop output signals were studied. They were compared with WAT static laboratory methods. Finally, we scrutinized the effect of adding a chemical inhibitor to the working fluid on the dynamics of the process of wax deposition in the loop.

Keywords: paraffin desposition, flow assurance, chemical inhibitors, flow loop

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Authors: KumarShashvat, ArshpreetKaur, RajeshKumar, Raman Chadha

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Wireless sensor networks have principal characteristic of having restricted energy and with limitation that energy of the nodes cannot be replenished. To increase the lifetime in this scenario WSN route for data transmission is opted such that utilization of energy along the selected route is negligible. For this energy efficient network, dandy infrastructure is needed because it impinges the network lifespan. Clustering is a technique in which nodes are grouped into disjoints and non–overlapping sets. In this technique data is collected at the cluster head. In this paper, Adaptive-PSO algorithm is proposed which forms energy aware clusters by minimizing the cost of locating the cluster head. The main concern is of the suitability of the swarms by adjusting the learning parameters of PSO. Particle Swarm Optimization converges quickly at the beginning stage of the search but during the course of time, it becomes stable and may be trapped in local optima. In suggested network model swarms are given the intelligence of the spiders which makes them capable enough to avoid earlier convergence and also help them to escape from the local optima. Comparison analysis with traditional PSO shows that new algorithm considerably enhances the performance where multi-dimensional functions are taken into consideration.

Keywords: Particle Swarm Optimization, adaptive – PSO, comparison between PSO and A-PSO, energy efficient clustering

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Authors: K. Gomathi

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Mobile Ad hoc Networks (MANET) is defined as collection of routable wireless mobile nodes with no centralized administration and communicate each other using radio signals. Especially MANETs deployed in hostile environments where hackers will try to disturb the secure data transfer and drain the valuable network resources. Since MANET is battery operated network, preserving the network resource is essential one. For resource constrained computation, efficient routing and to increase the network stability, the network is divided into smaller groups called clusters. The clustering architecture consists of Cluster Head(CH), ordinary node and gateway. The CH is responsible for inter and intra cluster routing. CH election is a prominent research area and many more algorithms are developed using many different metrics. The CH with longer life sustains network lifetime, for this purpose Secondary Cluster Head(SCH) also elected and it is more economical. To nominate efficient CH, a Enhanced Distributed Weighted Clustering Algorithm (EDWCA) has been proposed. This approach considers metrics like battery power, degree difference and speed of the node for CH election. The proficiency of proposed one is evaluated and compared with existing algorithm using Network Simulator(NS-2).

Keywords: MANET, EDWCA, clustering, cluster head

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Authors: Shreyansh Jain Jeetmal, Shobith P. Chadaga, Shreyas H. Srinivas

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Internet of Things (IoT) is seen as the next major step in the ongoing revolution in the Information Age. It is predicted that in the near future billions of embedded devices will be communicating with each other to perform a plethora of tasks with or without human intervention. One of the major ongoing hotbed of research activity in IoT is Human Computer Interaction (HCI). HCI is used to facilitate communication between an intelligent system and a user. An intelligent system typically comprises of a system consisting of various sensors, actuators and embedded controllers which communicate with each other to monitor data collected from the environment. Communication by the user to the system is typically done using voice. One of the major ongoing applications of HCI is in home automation as a personal assistant. The prime objective of our project is to implement a use case of HCI for home automation. Our system is designed to detect and recognize the users and personalize the appliances in the house according to their individual preferences. Our HCI system is also capable of speaking with the user when certain commands are spoken such as searching on the web for information and controlling appliances. Our system can also monitor the environment in the house such as air quality and gas leakages for added safety.

Keywords: human computer interaction, internet of things, computer vision, sensor networks, speech to text, text to speech, android

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Authors: Abdullahi Marshal Idris, Murtala Mohammed Alamai, Adama Jummai Idris, Bello Mohammed Gwagwada

Abstract:

The technological revolution of the 1990s have brought about many new opportunities and challenges for the tourism and hospitality industries mostly in Nigeria and with tourism having global industry information as its life-blood and technology becoming fundamental to the ability of the industry to operate effectively and competitively. The whole system of information technologies is being rapidly diffused throughout the tourism industry and no player will escape information technologies impacts. The paper gives an insight into the importance of destination branding and the application of information technologies and the use of Internet in tourism and hospitality industries in Nigeria giving strategic frameworks, providing analysis of the Internet and its impact on these sectors. It also aims to show how technological innovations and information system can be beneficial for destinations companies like game reserves national parks, and other resorts by using the literature of existing efforts in global industry players as well as documented evidences where recommendations for destinations and companies is made to seek to foster the development of this connection by investing considerable resources in marketing activities on social networks and by reinforcing the trust of users, because credibility and reliability are still critical in this area.

Keywords: branding, marketing, technology, tourism product

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Authors: Binoun Chaki Hagar

Abstract:

Studies have investigated grandparents' perceptions relating to their grandchildren with disabilities. Literature on grandparenthood focuses on the Western grandparents. Autism within the Arab populations has also being investigated. Moreover, the Bedouin population can also be seen in various studies related to different experiences and different perceptions about disabilities in general and among children in particular. However, as far as we know, no studies were found on grand parenting a child with autism in Bedouin society. This study combines three areas of knowledge, to create another knowledge domain. The aim of this study was to learn about the experience of grand parenting an autistic child in the Bedouin Arab society, to examine how it affects the grandparents' relationships, feelings, and functioning within the family, and as individuals, as well as to examine their coping mechanisms and their social support networks. This study is significant and as it examines autism and grandparents among the Bedouin Arab population in Israel, a population that has unique socio-demographic, cultural and traditional characteristics. The study revealed three themes concerning the meaning of grandparenthood to be associated with family continuity, how autism is perceived, and the importance of religion. It also suggests another category – the status of the elderly in the Arab-Bedouin family. It is recognized that the role of the elderly is held in high esteem, and can be affected by the grandchild’s’ autism.

Keywords: Arab–Bedouin family, autism, grandparents, family relationships

Procedia PDF Downloads 276

Authors: Kuang-Hsiung Tan, Chih-Chan Hu, Chien-Wu Lan, Shih-Sung Lin, Te-Jen Chang

Abstract:

An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.

Keywords: distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone

Procedia PDF Downloads 378

Authors: N. M. G. Al-Saidi, K. A. Kadhim, N. A. Rajab

Abstract:

Over the past decades, computer networks and data communication system has been developing fast, so, the necessity to protect a transmitted data is a challenging issue, and data security becomes a serious problem nowadays. A secret sharing scheme is a method which allows a master key to be distributed among a finite set of participants, in such a way that only certain authorized subsets of participants to reconstruct the original master key. To create a secret sharing scheme, many mathematical structures have been used; the most widely used structure is the one that is based on graph theory (graph access structure). Subsequently, many researchers tried to find efficient schemes based on graph access structures. In this paper, we propose a novel efficient construction of a perfect secret sharing scheme for uniform access structure. The dominating set of vertices in a regular graph is used for this construction in the following way; each vertex represents a participant and each minimum independent dominating subset represents a minimal qualified subset. Some relations between dominating set, graph order and regularity are achieved, and can be used to demonstrate the possibility of using dominating set to construct a secret sharing scheme. The information rate that is used as a measure for the efficiency of such systems is calculated to show that the proposed method has some improved values.

Keywords: secret sharing scheme, dominating set, information rate, access structure, rank

Procedia PDF Downloads 383

Authors: W. Swiderski

Abstract:

Composite materials are one answer to the growing demand for materials with better parameters of construction and exploitation. Composite materials also permit conscious shaping of desirable properties to increase the extent of reach in the case of metals, ceramics or polymers. In recent years, composite materials have been used widely in aerospace, energy, transportation, medicine, etc. Fiber-reinforced composites including carbon fiber, glass fiber and aramid fiber have become a major structural material. The typical defect during manufacture and operation is delamination damage of layered composites. When delamination damage of the composites spreads, it may lead to a composite fracture. One of the many methods used in non-destructive testing of composites is active infrared thermography. In active thermography, it is necessary to deliver energy to the examined sample in order to obtain significant temperature differences indicating the presence of subsurface anomalies. To detect possible defects in composite materials, different methods of thermal stimulation can be applied to the tested material, these include heating lamps, lasers, eddy currents, microwaves or ultrasounds. The use of a suitable source of thermal stimulation on the test material can have a decisive influence on the detection or failure to detect defects. Samples of multilayer structure carbon composites were prepared with deliberately introduced defects for comparative purposes. Very thin defects of different sizes and shapes made of Teflon or copper having a thickness of 0.1 mm were screened. Non-destructive testing was carried out using the following sources of thermal stimulation, heating lamp, flash lamp, ultrasound and eddy currents. The results are reported in the paper.

Keywords: Non-destructive testing, IR thermography, composite material, thermal stimulation

Procedia PDF Downloads 251