Search results for: automated driving

Authors: S. Grinnell

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A PhD Research Project exploring the Social Health and Well-Being Impacts associated with Hydraulic Fracturing, with an aim to produce a Best Practice Support Guidance for those anticipating dealing with planning applications or submitting Environmental Impact Assessments (EIAs). Amid a possible global energy crisis, founded upon a number of factors, including unstable political situations, increasing world population growth, people living longer, it is perhaps inevitable that Hydraulic Fracturing (commonly referred to as ‘fracking’) will become a major player within the global long-term energy and sustainability agenda. As there is currently no best practice guidance for governing bodies the Best Practice Support Document will be targeted at a number of audiences including, consultants undertaking EIAs, Planning Officers, those commissioning EIAs Industry and interested public stakeholders. It will offer a robust, evidence-based criteria and recommendations which provide a clear narrative and consistent and shared approach to the language used along with containing an understanding of the issues identified. It is proposed that the Best Practice Support Document will also support the mitigation of health impacts identified. The Best Practice Support Document will support the newly amended Environmental Impact Assessment Directive (2011/92/EU), to be transposed into UK law by 2017. A significant amendment introduced focuses on, ‘higher level of protection to the environment and health.’ Methodology: A qualitative research methods approach is being taken with this research. It will have a number of key stages. A literature review has been undertaken and been critically reviewed and analysed. This was followed by a descriptive content analysis of a selection of international and national policies, programmes and strategies along with published Environmental Impact Assessments and associated planning guidance. In terms of data collection, a number of stakeholders were interviewed as well as a number of focus groups of local community groups potentially affected by fracking. These were determined from across the UK. A theme analysis of all the data collected and the literature review will be undertaken, using NVivo. Best Practice Supporting Document will be developed based on the outcomes of the analysis and be tested and piloted in the professional fields, before a live launch. Concluding statement: Whilst fracking is not a new concept, the technology is now driving a new force behind the use of this engineering to supply fuels. A number of countries have pledged moratoria on fracking until further investigation from the impacts on health have been explored, whilst other countries including Poland and the UK are pushing to support the use of fracking. If this should be the case, it will be important that the public’s concerns, perceptions, fears and objections regarding the wider social health and well-being impacts are considered along with the more traditional biomedical health impacts.

Keywords: fracking, hydraulic fracturing, socio-economic health, well-being

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Authors: Simon Grossemy, Peggy P. Y. Chan, Pauline M. Doran

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Nerve tissue engineering is the main field of research aimed at finding an alternative to autografts as a treatment for nerve injuries. Scaffolds are used as a support to enhance nerve regeneration. In order to successfully design novel scaffolds and in vitro cell culture systems, a deep understanding of the factors affecting nerve regeneration processes is needed. Physical and biological parameters associated with the culture environment have been identified as potentially influential in nerve cell differentiation, including electrical stimulation, exposure to extracellular-matrix (ECM) proteins, dynamic medium conditions and co-culture with glial cells. The mechanisms involved in driving the cell to differentiation in the presence of these factors are poorly understood; the complexity of each of them raises the possibility that they may strongly influence each other. Some questions that arise in investigating nerve regeneration include: What are the best protein coatings to promote neural cell attachment? Is the scaffold design suitable for providing all the required factors combined? What is the influence of dynamic stimulation on cell viability and differentiation? In order to study these effects, scaffolds adaptable to bioreactor culture conditions were designed to allow electrical stimulation of cells exposed to ECM proteins, all within a dynamic medium environment. Gold coatings were used to make the surface of viscose rayon microfiber scaffolds (VRMS) conductive, and poly-L-lysine (PLL) and laminin (LN) surface coatings were used to mimic the ECM environment and allow the attachment of rat PC12 neural cells. The robustness of the coatings was analyzed by surface resistivity measurements, scanning electron microscope (SEM) observation and immunocytochemistry. Cell attachment to protein coatings of PLL, LN and PLL+LN was studied using DNA quantification with Hoechst. The double coating of PLL+LN was selected based on high levels of PC12 cell attachment and the reported advantages of laminin for neural differentiation. The underlying gold coatings were shown to be biocompatible using cell proliferation and live/dead staining assays. Coatings exhibiting stable properties over time under dynamic fluid conditions were developed; indeed, cell attachment and the conductive power of the scaffolds were maintained over 2 weeks of bioreactor operation. These scaffolds are promising research tools for understanding complex neural cell behavior. They have been used to investigate major factors in the physical culture environment that affect nerve cell viability and differentiation, including electrical stimulation, bioreactor hydrodynamic conditions, and combinations of these parameters. The cell and tissue differentiation response was evaluated using DNA quantification, immunocytochemistry, RT-qPCR and functional analyses.

Keywords: bioreactor, electrical stimulation, nerve differentiation, PC12 cells, scaffold

Procedia PDF Downloads 218

Authors: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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Authors: Yiea Funk Te, Daniel Mueller, Irena Pletikosa Cvijikj

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Small and medium enterprises (SMEs) play an important role in the economy of many countries. When the overall world economy is considered, SMEs represent 95% of all businesses in the world, accounting for 66% of the total employment. Existing studies show that the current business environment is characterized as highly turbulent and strongly influenced by modern information and communication technologies, thus forcing SMEs to experience more severe challenges in maintaining their existence and expanding their business. To support SMEs at improving their competitiveness, researchers recently turned their focus on applying data mining techniques to build risk and growth prediction models. However, data used to assess risk and growth indicators is primarily obtained via questionnaires, which is very laborious and time-consuming, or is provided by financial institutes, thus highly sensitive to privacy issues. Recently, web mining (WM) has emerged as a new approach towards obtaining valuable insights in the business world. WM enables automatic and large scale collection and analysis of potentially valuable data from various online platforms, including companies’ websites. While WM methods have been frequently studied to anticipate growth of sales volume for e-commerce platforms, their application for assessment of SME risk and growth indicators is still scarce. Considering that a vast proportion of SMEs own a website, WM bears a great potential in revealing valuable information hidden in SME websites, which can further be used to understand SME risk and growth indicators, as well as to enhance current SME risk and growth prediction models. This study aims at developing an automated system to collect business-relevant data from the Web and predict future growth trends of SMEs by means of WM and data mining techniques. The envisioned system should serve as an 'early recognition system' for future growth opportunities. In an initial step, we examine how structured and semi-structured Web data in governmental or SME websites can be used to explain the success of SMEs. WM methods are applied to extract Web data in a form of additional input features for the growth prediction model. The data on SMEs provided by a large Swiss insurance company is used as ground truth data (i.e. growth-labeled data) to train the growth prediction model. Different machine learning classification algorithms such as the Support Vector Machine, Random Forest and Artificial Neural Network are applied and compared, with the goal to optimize the prediction performance. The results are compared to those from previous studies, in order to assess the contribution of growth indicators retrieved from the Web for increasing the predictive power of the model.

Keywords: data mining, SME growth, success factors, web mining

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Authors: Samuel N. Forjuoh, Marcia G. Ory, Jaewoong Won, Samuel D. Towne, Suojin Wang, Chanam Lee

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The public health burden of obesity is well established as is the influence of physical activity (PA) on the health and wellness of individuals who are obese. This study examined the influence of selected demographic, health, and socioenvironmental factors on the walking behaviors of middle-aged and older overweight and obese adults. Online and paper surveys were administered to community-dwelling overweight and obese adults aged ≥ 50 years residing in four cities in central Texas and seen by a family physician in the primary care clinic from October 2013 to June 2014. Descriptive statistics were used to characterize participants’ anthropometric and demographic data as well as their health conditions and walking, socioenvironmental, and more broadly defined PA behaviors. Then Pearson chi-square tests were used to assess differences between participants who reported walking the recommended ≥ 150 minutes for any purpose in a typical week as a proxy to meeting the U.S. Centers for Disease Control and Prevention’s PA guidelines and those who did not. Finally, logistic regression was used to predict walking the recommended ≥ 150 minutes for any purpose, controlling for covariates. The analysis was conducted in 2016. Of the total sample (n=253, survey response rate of 6.8%), the majority were non-Hispanic white (81.7%), married (74.5%), male (53.5%), and reported an annual household income of ≥ $50,000 (65.7%). Approximately, half were employed (49.6%), or had at least a college degree (51.8%). Slightly more than 1 in 5 (n=57, 22.5%) reported walking the recommended ≥150 minutes for any purpose in a typical week. The strongest predictors of walking the recommended ≥ 150 minutes for any purpose in a typical week in adjusted analysis were related to education and a high favorable perception of the neighborhood environment. Compared to those with a high school diploma or some college, participants with at least a college degree were five times as likely to walk the recommended ≥ 150 minutes for any purpose (OR=5.55, 95% CI=1.79-17.25). Walking the recommended ≥ 150 minutes for any purpose was significantly associated with participants who disagreed that there were many distracted drivers (e.g., on the cell phone while driving) in their neighborhood (OR=4.08, 95% CI=1.47-11.36) and those who agreed that there are sidewalks or protected walkways (e.g., walking trails) in their neighborhood (OR=3.55, 95% CI=1.10-11.49). Those employed were less likely to walk the recommended ≥ 150 minutes for any purpose compared to those unemployed (OR=0.31, 95% CI=0.11-0.85) as were those who reported some difficulty walking for a quarter of a mile (OR=0.19, 95% CI=0.05-0.77). Other socio-environmental factors such as having care-giver responsibilities for elders, someone to walk with, or a dog in the household as well as Walk Score™ were not significantly associated with walking the recommended ≥ 150 minutes for any purpose in a typical week. Neighborhood perception appears to be an important factor associated with the walking behaviors of middle-aged and older overweight and obese individuals. Enhancing the neighborhood environment (e.g., providing walking trails) may promote walking among these individuals.

Keywords: determinants of walking, obesity, older adults, physical activity

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Authors: Moser Stephan, Lukasser Gerald, Weitlaner Robert

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Urban structures will be used more intensively in the future through redensification or new planned districts with high building densities. Especially, to achieve positive energy balances like requested for Positive Energy Districts (PED) the single use of roofs is not sufficient for dense urban areas. However, the increasing share of window significantly reduces the facade area available for use in PV generation. Through the use of PV technology at other building components, such as external venetian blinds, onsite generation can be maximized and standard functionalities of this product can be positively extended. While offering advantages in terms of infrastructure, sustainability in the use of resources and efficiency, these systems require an increased optimization in planning and control strategies of buildings. External venetian blinds with PV technology require an intelligent control concept to meet the required demands such as maximum power generation, glare prevention, high daylight autonomy, avoidance of summer overheating but also use of passive solar gains in wintertime. Today, geometric representation of outdoor spaces and at the building level, three-dimensional geometric information is available for planning with Building Information Modeling (BIM). In a research project, a web application which is called HELLA DECART was developed to provide this data structure to extract the data required for the simulation from the BIM models and to make it usable for the calculations and coupled simulations. The investigated object is uploaded as an IFC file to this web application and includes the object as well as the neighboring buildings and possible remote shading. This tool uses a ray tracing method to determine possible glare from solar reflections of a neighboring building as well as near and far shadows per window on the object. Subsequently, an annual estimate of the sunlight per window is calculated by taking weather data into account. This optimized daylight assessment per window provides the ability to calculate an estimation of the potential power generation at the integrated PV on the venetian blind but also for the daylight and solar entry. As a next step, these results of the calculations as well as all necessary parameters for the thermal simulation can be provided. The overall aim of this workflow is to advance the coordination between the BIM model and coupled building simulation with the resulting shading and daylighting system with the artificial lighting system and maximum power generation in a control system. In the research project Powershade, an AI based control concept for PV integrated façade elements with coupled simulation results is investigated. The developed automated workflow concept in this paper is tested by using an office living lab at the HELLA company.

Keywords: BIPV, building simulation, optimized control strategy, planning tool

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Authors: Davide Cocchi, Andrea Zucchelli, Luca Raimondi, Maria Brugo Tommaso

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The increasing attention is given to the issues of environmental pollution and climate change is exponentially stimulating the development of electrically propelled vehicles powered by renewable energy, in particular, the solar one. Given the small amount of solar energy that can be stored and subsequently transformed into propulsive energy, it is necessary to develop vehicles with high mechanical, electrical and aerodynamic efficiencies along with reduced masses. The reduction of the masses is of fundamental relevance especially for the unsprung masses, that is the assembly of those elements that do not undergo a variation of their distance from the ground (wheel, suspension system, hub, upright, braking system). Therefore, the reduction of unsprung masses is fundamental in decreasing the rolling inertia and improving the drivability, comfort, and performance of the vehicle. This principle applies even more in solar propelled vehicles, equipped with an electric motor that is connected directly to the wheel hub. In this solution, the electric motor is integrated inside the wheel. Since the electric motor is part of the unsprung masses, the development of compact and lightweight solutions is of fundamental importance. The purpose of this research is the design development and optimization of a CFRP 16 wheel hub motor for solar propulsion vehicles that can carry up to four people. In addition to trying to maximize aspects of primary importance such as mass, strength, and stiffness, other innovative constructive aspects were explored. One of the main objectives has been to achieve a high geometric packing in order to ensure a reduced lateral dimension, without reducing the power exerted by the electric motor. In the final solution, it was possible to realize a wheel hub motor assembly completely comprised inside the rim width, for a total lateral overall dimension of less than 100 mm. This result was achieved by developing an innovative connection system between the wheel and the rotor with a double purpose: centering and transmission of the driving torque. This solution with appropriate interlocking noses allows the transfer of high torques and at the same time guarantees both the centering and the necessary stiffness of the transmission system. Moreover, to avoid delamination in critical areas, evaluated by means of FEM analysis using 3D Hashin damage criteria, electrospun nanofibrous mats have been interleaved between CFRP critical layers. In order to reduce rolling resistance, the rim has been designed to withstand high inflation pressure. Laboratory tests have been performed on the rim using the Digital Image Correlation technique (DIC). The wheel has been tested for fatigue bending according to E/ECE/324 R124e.

Keywords: composite laminate, delamination, DIC, lightweight vehicle, motor hub wheel, nanofiber

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Authors: Vanessa Roulet, Marc Turini, Juliane Hey, Stéphanie Bord-Romeu, Emilie Bonzom, Mahmoud Badawi, Mohammed-Amine Chakir, Valérie Simon, Vanessa Viotti, Jérémie Gautier, Françoise Le Boulaire, Catherine Coignard, Claire Vincent, Sandrine Greaume, Isabelle Voisin

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Background: Beckman Coulter, Inc. has recently developed fully automated assays for the detection of HBsAg on a new immunoassay platform. The objective of this European multicenter study was to evaluate the performance of the ACCESS HBsAg and ACCESS HBsAg Confirmatory assays† on the recently CE-marked DxI 9000 ACCESS Immunoassay Analyzer. Methods: The clinical specificity of the ACCESS HBsAg and HBsAg Confirmatory assays was determined using HBsAg-negative samples from blood donors and hospitalized patients. The clinical sensitivity was determined using presumed HBsAg-positive samples. Sample HBsAg status was determined using a CE-marked HBsAg assay (Abbott ARCHITECT HBsAg Qualitative II, Roche Elecsys HBsAg II, or Abbott PRISM HBsAg assay) and a CE-marked HBsAg confirmatory assay (Abbott ARCHITECT HBsAg Qualitative II Confirmatory or Abbott PRISM HBsAg Confirmatory assay) according to manufacturer package inserts and pre-determined testing algorithms. False initial reactive rate was determined on fresh hospitalized patient samples. The sensitivity for the early detection of HBV infection was assessed internally on thirty (30) seroconversion panels. Results: Clinical specificity was 99.95% (95% CI, 99.86 – 99.99%) on 6047 blood donors and 99.71% (95%CI, 99.15 – 99.94%) on 1023 hospitalized patient samples. A total of six (6) samples were found false positive with the ACCESS HBsAg assay. None were confirmed for the presence of HBsAg with the ACCESS HBsAg Confirmatory assay. Clinical sensitivity on 455 HBsAg-positive samples was 100.00% (95% CI, 99.19 – 100.00%) for the ACCESS HBsAg assay alone and for the ACCESS HBsAg Confirmatory assay. The false initial reactive rate on 821 fresh hospitalized patient samples was 0.24% (95% CI, 0.03 – 0.87%). Results obtained on 30 seroconversion panels demonstrated that the ACCESS HBsAg assay had equivalent sensitivity performances compared to the Abbott ARCHITECT HBsAg Qualitative II assay with an average bleed difference since first reactive bleed of 0.13. All bleeds found reactive in ACCESS HBsAg assay were confirmed in ACCESS HBsAg Confirmatory assay. Conclusion: The newly developed ACCESS HBsAg and ACCESS HBsAg Confirmatory assays from Beckman Coulter have demonstrated high clinical sensitivity and specificity, equivalent to currently marketed HBsAg assays, as well as a low false initial reactive rate. †Pending achievement of CE compliance; not yet available for in vitro diagnostic use. 2023-11317 Beckman Coulter and the Beckman Coulter product and service marks mentioned herein are trademarks or registered trademarks of Beckman Coulter, Inc. in the United States and other countries. All other trademarks are the property of their respective owners.

Keywords: dxi 9000 access immunoassay analyzer, hbsag, hbv, hepatitis b surface antigen, hepatitis b virus, immunoassay

Procedia PDF Downloads 63

Authors: Chun-Liang Wu, Kai-Ping Shaw, Cheng-Ping Yu, Wu-Chien Chien, Hsiao-Ting Chen, Shao-Huang Wu

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Objective: This study analyzed three criminal judicial cases. We applied the patterned injuries of the rider to demonstrate the facts of each accident, reconstruct the scenes, and pursue the truth. Methods: Case analysis, a method that collects evidence and reasons the results in judicial procedures, then the importance of the pattern of injury as evidence will be compared and evaluated. The patterned injuries analysis method is to compare the collision situation between an object and human body injuries to determine whether the characteristics can reproduce the unique pattern of injury. Result: Case 1: Two motorcycles, A and B, head-on collided; rider A dead, and rider B was accused. During the prosecutor’s investigation, the defendant learned that rider A had an 80 mm open wound on his neck. During the court trial, the defendant requested copies of the case file and found out that rider A had a large contusion on his chest wall, and the cause of death was traumatic hemothorax and abdominal wall contusion. The defendant compared all the evidence at the scene and determined that the injury was obviously not caused by the collision of the body or the motorcycle of rider B but that rider was out of control and injured himself when he crossed the double yellow line. In this case, the defendant was innocent in the High Court judgment in April 2022. Case 2: Motorcycles C and D head-on crashed, and rider C died of massive abdominal bleeding. The prosecutor decided that rider C was driving under the influence (DUI), but rider D was negligent and sued rider D. The defendant requested the copies’ file and found the special phenomenon that the front wheel of motorcycle C was turned left. The defendant’s injuries were a left facial bone fracture, a left femur fracture, and other injuries on the left side. The injuries were of human-vehicle separation and human-vehicle collision, which proved that rider C suddenly turned left when the two motorcycles approached, knocked down motorcycle D, and the defendant flew forward. Case 3: Motorcycle E and F’s rear end collided, the front rider E was sentenced to 3 months, and the rear rider F sued rider E for more than 7 million N.T. The defendant found in the copies’ file that the injury of rider F was the left tibial platform fracture, etc., and then proved that rider F made the collision with his left knee, causing motorcycle E to fall out of control. This evidence was accepted by the court and is still on trial. Conclusion: The application of patterned injuries in the reconstruction of a motorcycle accident could discover the truth and provide the basis for judicial justice. The cases and methods could be the reference for the policy of preventing traffic accident casualties.

Keywords: judicial evidence, patterned injuries analysis, accident reconstruction, fatal motorcycle injuries

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Authors: Mairaj Salim, Asma Zaheer

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Oman has accomplished as much or more than its fellow Gulf monarchies, despite starting from scratch considerably later, having less oil income to utilize, dealing with a larger and more rugged geography, and resolving a bitter civil war along the way. Of course, Oman's progress in the past 30-plus years has not been without problems and missteps, but the balance is squarely on the positive side of the ledger. Oil has been the driving force of the Omani economy since Oman began commercial production in 1967. The oil industry supports the country’s high standard of living and is primarily responsible for its modern and expansive infrastructure, including electrical utilities, telephone services, roads, public education and medical services. In addition to extensive oil reserves, Oman also has substantial natural gas reserves, which are expected to play a leading role in the Omani economy in the Twenty-first Century. To reduce the country’s dependence on oil revenues, the government is restructuring the economy by directing investment to non-oil activities. Since the 21st century IT has changed the performing tasks. To manage the affairs for the benefits of organizations and economy, the Omani government has adopted E-Business technologies for the development. E-Business is important because it allows • Transformation of old economy relationships (vertical/linear relationships) to new economy relationships characterized by end-to-end relationship management solutions (integrated or extended relationships) • Facilitation and organization of networks, small firms depend on ‘partner’ firms for supplies and product distribution to meet customer demands • SMEs to outsource back-end process or cost centers enabling the SME to focus on their core competence • ICT to connect, manage and integrate processes internally and externally • SMEs to join networks and enter new markets, through shortened supply chains to increase market share, customers and suppliers • SMEs to take up the benefits of e-business to reduce costs, increase customer satisfaction, improve client referral and attract quality partners • New business models of collaboration for SMEs to increase their skill base • SMEs to enter virtual trading arena and increase their market reach A national strategy for the advancement of information and communication technology (ICT) has been worked out, mainly to introduce e-government, e-commerce, and a digital society. An information technology complex KOM (Knowledge Oasis Muscat) had been established, consisting of section for information technology, incubator services, a shopping center of technology software and hardware, ICT colleges, E-Government services and other relevant services. So, all these efforts play a vital role in the development of Oman economy.

Keywords: ICT, ITA, CRM, SCM, ERP, KOM, SMEs, e-commerce and e-business

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Authors: Tariq Ahamad, Mohammed S. Al-Kahtani, Taisir Eldos

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Optical communications technology has made enormous and steady progress for several decades, providing the key resource in our increasingly information-driven society and economy. Much of this progress has been in finding innovative ways to increase the data carrying capacity of a single optical fiber. In this research article we have explored basic issues in terms of security and reliability for secure and reliable information transfer through the fiber infrastructure. Conspicuously, one potentially enormous source of improvement has however been left untapped in these systems: fibers can easily support hundreds of spatial modes, but today’s commercial systems (single-mode or multi-mode) make no attempt to use these as parallel channels for independent signals. Bandwidth, performance, reliability, cost efficiency, resiliency, redundancy, and security are some of the demands placed on telecommunications today. Since its initial development, fiber optic systems have had the advantage of most of these requirements over copper-based and wireless telecommunications solutions. The largest obstacle preventing most businesses from implementing fiber optic systems was cost. With the recent advancements in fiber optic technology and the ever-growing demand for more bandwidth, the cost of installing and maintaining fiber optic systems has been reduced dramatically. With so many advantages, including cost efficiency, there will continue to be an increase of fiber optic systems replacing copper-based communications. This will also lead to an increase in the expertise and the technology needed to tap into fiber optic networks by intruders. As ever before, all technologies have been subject to hacking and criminal manipulation, fiber optics is no exception. Researching fiber optic security vulnerabilities suggests that not everyone who is responsible for their networks security is aware of the different methods that intruders use to hack virtually undetected into fiber optic cables. With millions of miles of fiber optic cables stretching across the globe and carrying information including but certainly not limited to government, military, and personal information, such as, medical records, banking information, driving records, and credit card information; being aware of fiber optic security vulnerabilities is essential and critical. Many articles and research still suggest that fiber optics is expensive, impractical and hard to tap. Others argue that it is not only easily done, but also inexpensive. This paper will briefly discuss the history of fiber optics, explain the basics of fiber optic technologies and then discuss the vulnerabilities in fiber optic systems and how they can be better protected. Knowing the security risks and knowing the options available may save a company a lot embarrassment, time, and most importantly money.

Keywords: in-house networks, fiber optics, security risk, money

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Authors: Christine F. Boos, Fernando M. Azevedo

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Electroencephalogram (EEG) is a record of the electrical activity of the brain that has many applications, such as monitoring alertness, coma and brain death; locating damaged areas of the brain after head injury, stroke and tumor; monitoring anesthesia depth; researching physiology and sleep disorders; researching epilepsy and localizing the seizure focus. Epilepsy is a chronic condition, or a group of diseases of high prevalence, still poorly explained by science and whose diagnosis is still predominantly clinical. The EEG recording is considered an important test for epilepsy investigation and its visual analysis is very often applied for clinical confirmation of epilepsy diagnosis. Moreover, this EEG analysis can also be used to help define the types of epileptic syndrome, determine epileptiform zone, assist in the planning of drug treatment and provide additional information about the feasibility of surgical intervention. In the context of diagnosis confirmation the analysis is made using long term EEG recordings with at least 24 hours long and acquired by a minimum of 24 electrodes in which the neurophysiologists perform a thorough visual evaluation of EEG screens in search of specific electrographic patterns called epileptiform discharges. Considering that the EEG screens usually display 10 seconds of the recording, the neurophysiologist has to evaluate 360 screens per hour of EEG or a minimum of 8,640 screens per long term EEG recording. Analyzing thousands of EEG screens in search patterns that have a maximum duration of 200 ms is a very time consuming, complex and exhaustive task. Because of this, over the years several studies have proposed automated methodologies that could facilitate the neurophysiologists’ task of identifying epileptiform discharges and a large number of methodologies used neural networks for the pattern classification. One of the differences between all of these methodologies is the type of input stimuli presented to the networks, i.e., how the EEG signal is introduced in the network. Five types of input stimuli have been commonly found in literature: raw EEG signal, morphological descriptors (i.e. parameters related to the signal’s morphology), Fast Fourier Transform (FFT) spectrum, Short-Time Fourier Transform (STFT) spectrograms and Wavelet Transform features. This study evaluates the application of these five types of input stimuli and compares the classification results of neural networks that were implemented using each of these inputs. The performance of using raw signal varied between 43 and 84% efficiency. The results of FFT spectrum and STFT spectrograms were quite similar with average efficiency being 73 and 77%, respectively. The efficiency of Wavelet Transform features varied between 57 and 81% while the descriptors presented efficiency values between 62 and 93%. After simulations we could observe that the best results were achieved when either morphological descriptors or Wavelet features were used as input stimuli.

Keywords: Artificial neural network, electroencephalogram signal, pattern recognition, signal processing

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Authors: Zheng Lulin, Xiong Guoping

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In recent years, agriculture, rural development, and peasants are among the top concerns and priorities of the Chinese Government. Several related issues have been paid many attentions by academic communities, including the impacts of corresponding policies on the rural villages, the mechanisms of these impacts, and the future development of rural society. However, most of the researchers focus on single rural policy instead of integral rural policy system. Hence, this dissertation focused on the mechanisms of policies’ influence on rural changes through a case study from Changfu Village in central Guangxi Province, China, to propose the optimized suggestions for rural development. Forty-three relevant pivotal policies of significant influence on rural development are summarized from literature and documents, covering five aspects of agricultural production, rural living security, open rural markets, rural household registration systems, and farmland transferring. Besides, having been live in this area for more than 20 years, researchers obtain the basic information about changing the social connection between citizens and villagers, the habitat of villagers by years of informal interviews. Furthermore, more than 200 questionnaires are given to villagers to analyze the changing of their personal and family information. The summary of rural policies revealed that the development trend of public rural policies followed the U-shape curve and these policies are characterized by economic intentions and operative economy. Report of questionnaires and interviews show that the development of rural economy was promoted greatly by public policies. Firstly, Social communication and rural culture were affected to a certain extent. Secondly, the educational level of rural individuals was significantly enhanced, whereas the quality of population had limited progress. Finally, the freedom of occupational choice for rural individuals into cities was greater than before, but still restricted by the class solidification of social background, resulting in more obstacles for rural individuals to settle down in cities. From what we discuss about, we may reach the conclusion on several perspectives: Firstly, the impact of the rural policies has a significant role in promoting the economy development of the rural area. However, separations between rural and urban area are still a major problem since rural policy contributed little to improve the rural population quality. Therefore, in the future, providing high quality educational facilities including teachers, libraries, and opportunities of broadening their knowledge base are key issues of future rural policy. Secondly, the development of rural economy would be a lack of driving force for further improvement owning to the fact that working hard couldn’t get more improvement. In the future, public policies should support the rural development of culture, technology, and personal qualities to create favorable social environment for the free increase of rural population.

Keywords: changing of rural area, rural development of China, rural policy, social environment

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Authors: Andi Setiawan, Annisa Ulfah Pristya

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Indonesian rubber plant area reached 2.9 million hectares with productivity reached 1.38 million. High rubber productivity is directly proportional to the amount of waste produced rubber processing industry. Rubber industry would produce a negative impact on the rubber industry in the form of environmental pollution caused by waste that has not been treated optimally. Rubber industrial wastewater containing high-nitrogen compounds (nitrate and ammonia) and phosphate compounds which cause water pollution and odor problems due to the high ammonia content. On the other hand, demand for NPK fertilizers in Indonesia continues to increase from year to year and in need of ammonia and phosphate as raw material. Based on domestic demand, it takes a year to 400,000 tons of ammonia and Indonesia imports 200,000 tons of ammonia per year valued at IDR 4.2 trillion. As well, the lack of phosphoric acid to be imported from Jordan, Morocco, South Africa, the Philippines, and India as many as 225 thousand tons per year. During this time, the process of wastewater treatment is generally done with a rubber on the tank to contain the waste and then precipitated, filtered and the rest released into the environment. However, this method is inefficient and thus require high energy costs because through many stages before producing clean water that can be discharged into the river. On the other hand, Indonesia has the potential of pineapple fruit can be harvested throughout the year in all of Indonesia. In 2010, production reached 1,406,445 tons of pineapple in Indonesia or about 9.36 percent of the total fruit production in Indonesia. Increased productivity is directly proportional to the amount of pineapple waste pineapple leaves are kept continuous and usually just dumped in the ground or disposed of with other waste at the final disposal. Through Eco-Nanofiltration Membrane-Based Fiber Pineapple leaves Waste so that environmental problems can be solved efficiently. Nanofiltration is a process that uses pressure as a driving force that can be either convection or diffusion of each molecule. Nanofiltration membranes that can split water to nano size so as to separate the waste processed residual economic value that N and P were higher as a raw material for the manufacture of NPK fertilizer to overcome the crisis in Indonesia. The raw materials were used to manufacture Eco-Nanofiltration Membrane is cellulose from pineapple fiber which processed into cellulose acetate which is biodegradable and only requires a change of the membrane every 6 months. Expected output target is Green eco-technology so with nanofiltration membranes not only treat waste rubber industry in an effective, efficient and environmentally friendly but also lowers the cost of waste treatment compared to conventional methods.

Keywords: biodegradable, cellulose diacetate, fertilizers, pineapple, rubber

Procedia PDF Downloads 423

Authors: Elham Koohi, Silvio Jose Gumiere, Hossein Bonakdari, Saeid Homayouni

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Water used in agricultural crops can be managed by irrigation scheduling based on soil moisture levels and plant water stress thresholds. Automated irrigation scheduling limits crop physiological damage and yield reduction. Knowledge of crop water stress monitoring approaches can be effective in optimizing the use of agricultural water. Understanding the physiological mechanisms of crop responding and adapting to water deficit ensures sustainable agricultural management and food supply. This aim could be achieved by analyzing and diagnosing crop characteristics and their interlinkage with the surrounding environment. Assessments of plant functional types (e.g., leaf area and structure, tree height, rate of evapotranspiration, rate of photosynthesis), controlling changes, and irrigated areas mapping. Calculating thresholds of soil water content parameters, crop water use efficiency, and Nitrogen status make irrigation scheduling decisions more accurate by preventing water limitations between irrigations. Combining Remote Sensing (RS), the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning Algorithms (MLAs) can improve measurement accuracies and automate irrigation scheduling. This paper is a review structured by surveying about 100 recent research studies to analyze varied approaches in terms of providing high spatial and temporal resolution mapping, sensor-based Variable Rate Application (VRA) mapping, the relation between spectral and thermal reflectance and different features of crop and soil. The other objective is to assess RS indices formed by choosing specific reflectance bands and identifying the correct spectral band to optimize classification techniques and analyze Proximal Optical Sensors (POSs) to control changes. The innovation of this paper can be defined as categorizing evaluation methodologies of precision irrigation (applying the right practice, at the right place, at the right time, with the right quantity) controlled by soil moisture levels and sensitiveness of crops to water stress, into pre-processing, processing (retrieval algorithms), and post-processing parts. Then, the main idea of this research is to analyze the error reasons and/or values in employing different approaches in three proposed parts reported by recent studies. Additionally, as an overview conclusion tried to decompose different approaches to optimizing indices, calibration methods for the sensors, thresholding and prediction models prone to errors, and improvements in classification accuracy for mapping changes.

Keywords: agricultural crops, crop water stress detection, irrigation scheduling, precision agriculture, remote sensing

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Authors: Taha Anjamrooz, Sareh Rajabi, Ayman Alzaatreh

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Smart cities are playing important roles in real life. Integration and automation between different features of modern cities and information technologies improve smart city efficiency, energy management, human and equipment resource management, life quality and better utilization of resources for the customers. One of difficulties in this path, is use, interface and link between software, hardware, and other IT technologies to develop and optimize processes in various business fields such as construction, supply chain management and transportation in parallel to cost-effective and resource reduction impacts. Also, Smart cities are certainly intended to demonstrate a vital role in offering a sustainable and efficient model for smart houses while mitigating environmental and ecological matters. Energy management is one of the most important matters within smart houses in the smart cities and communities, because of the sensitivity of energy systems, reduction in energy wastage and maximization in utilizing the required energy. Specially, the consumption of energy in the smart houses is important and considerable in the economic balance and energy management in smart city as it causes significant increment in energy-saving and energy-wastage reduction. This research paper develops features and concept of smart city in term of overall efficiency through various effective variables. The selected variables and observations are analyzed through data analysis processes to demonstrate the efficiency of smart city and compare the effectiveness of each variable. There are ten chosen variables in this study to improve overall efficiency of smart city through increasing effectiveness of smart houses using an automated solar photovoltaic system, RFID System, smart meter and other major elements by interfacing between software and hardware devices as well as IT technologies. Secondly to enhance aspect of energy management by energy-saving within smart house through efficient variables. The main objective of smart city and smart houses is to reproduce energy and increase its efficiency through selected variables with a comfortable and harmless atmosphere for the customers within a smart city in combination of control over the energy consumption in smart house using developed IT technologies. Initially the comparison between traditional housing and smart city samples is conducted to indicate more efficient system. Moreover, the main variables involved in measuring overall efficiency of system are analyzed through various processes to identify and prioritize the variables in accordance to their influence over the model. The result analysis of this model can be used as comparison and benchmarking with traditional life style to demonstrate the privileges of smart cities. Furthermore, due to expensive and expected shortage of natural resources in near future, insufficient and developed research study in the region, and available potential due to climate and governmental vision, the result and analysis of this study can be used as key indicator to select most effective variables or devices during construction phase and design

Keywords: smart city, traditional housing, RFID, photovoltaic system, energy efficiency, energy saving

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Authors: Susie Pryor, Palak Sadhwani

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The purpose of this research is to provide the foundations for a broad research agenda examining the role loneliness plays in entrepreneurship. While qualitative research in entrepreneurship incidentally captures the existence of loneliness as a part of the lived reality of entrepreneurs, to the authors’ knowledge, no academic work has to date explored this construct in this context. Moreover, many individuals reporting high levels of loneliness (women, ethnic minorities, immigrants, low income, low education) reflect those who are currently driving small business growth in the United States. Loneliness is a persistent state of emotional distress which results from feelings of estrangement and rejection or develops in the absence of social relationships and interactions. Empirical work finds links between loneliness and depression, suicide and suicide ideation, anxiety, hostility and passiveness, lack of communication and adaptability, shyness, poor social skills and unrealistic social perceptions, self-doubts, fear of rejection, and negative self-evaluation. Lonely individuals have been found to exhibit lower levels of self-esteem, higher levels of introversion, lower affiliative tendencies, less assertiveness, higher sensitivity to rejection, a heightened external locus of control, intensified feelings of regret and guilt over past events and rigid and overly idealistic goals concerning the future. These characteristics are likely to impact entrepreneurs and their work. Research identifies some key dangers of loneliness. Loneliness damages human love and intimacy, can disturb and distract individuals from channeling creative and effective energies in a meaningful way, may result in the formation of premature, poorly thought out and at times even irresponsible decisions, and produce hard and desensitized individuals, with compromised health and quality of life concerns. The current study utilizes meta-analysis and text analytics to distinguish loneliness from other related constructs (e.g., social isolation) and categorize antecedents and effects of loneliness across subpopulations. This work has the potential to materially contribute to the field of entrepreneurship by cleanly defining constructs and providing foundational background for future research. It offers a richer understanding of the evolution of loneliness and related constructs over the life cycle of entrepreneurial start-up and development. Further, it suggests preliminary avenues for exploration and methods of discovery that will result in knowledge useful to the field of entrepreneurship. It is useful to both entrepreneurs and those work with them as well as academics interested in the topics of loneliness and entrepreneurship. It adopts a grounded theory approach.

Keywords: entrepreneurship, grounded theory, loneliness, meta-analysis

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Authors: Antonio Martín-Pardo

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With regard to the context in which this paper is inserted, it is noteworthy that the current criminal policy model in which we find immersed, denominated by some doctrine sector as the citizen security model, is characterized by a marked tendency towards the discredit of expert knowledge. This type of technic knowledge has been displaced by the common sense and by the daily experience of the people at the time of legislative drafting, as well as by excessive attention to the short-term political effects of the law. Despite this criminal-political adverse scene, we still find valuable efforts in the side of experts to bring some rationality to the legislative development. This is the case of the proposal for a new cannabis regulation model in Spain carried out by the Cannabis Policy Studies Group (hereinafter referred as ‘GEPCA’). The GEPCA is a multidisciplinary group composed by authors with multiple/different orientations, trajectories and interests, but with a common minimum objective: the conviction that the current situation regarding cannabis is unsustainable and, that a rational legislative solution must be given to the growing social pressure for the regulation of their consumption and production. This paper details the main lines through which this technical proposal is developed with the purpose of its dissemination and discussion in the Congress. The basic methodology of the proposal is inductive-expository. In that way, firstly, we will offer a brief, but solid contextualization of the situation of cannabis in Spain. This contextualization will touch on issues such as the national regulatory situation and its relationship with the international context; the criminal, judicial and penitentiary impact of the offer and consumption of cannabis, or the therapeutic use of the substance, among others. In second place, we will get down to the business properly by detailing the minutia of the three main cannabis access channels that are proposed. Namely: the regulated market, the associations of cannabis users and personal self-cultivation. In each of these options, especially in the first two, special attention will be paid to both, the production and processing of the substance and the necessary administrative control of the activity. Finally, in a third block, some notes will be given on a series of subjects that surround the different access options just mentioned above and that give fullness and coherence to the proposal outlined. Among those related issues we find some such as consumption and tenure of the substance; the issue of advertising and promotion of cannabis; consumption in areas of special risk (work or driving v. g.); the tax regime; the need to articulate evaluation instruments for the entire process; etc. The main conclusion drawn from the analysis of the proposal is the unsustainability of the current repressive system, clearly unsuccessful, and the need to develop new access routes to cannabis that guarantee both public health and the rights of people who have freely chosen to consume it.

Keywords: cannabis regulation proposal, cannabis policies studies group, criminal policy, expertise participation

Procedia PDF Downloads 98

Authors: R. Tariq, R. Lee

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Background: Heywood, Middleton & Rochdale Urgent Community Care Team (UCCT)1 is a great example of using a multidisciplinary team to cope with demand. The service reduces unnecessary admissions to hospitals and ensures that patients can leave the hospital quicker by making care more readily available within the community and patient’s homes. The team comprises nurses, community practitioners, and allied health professions, including physiotherapy, occupational therapy, pharmacy, and GPs. The main challenge for a team with a range of experiences and skill sets is to maintain consistency of care, which technology can help address. Allied healthcare professionals (HCPs) are often used in expanded roles with duties mainly involving patient consultations and decision making to ease pressure on doctors. The Clinical Reasoning Platform (CRP) Dem Dx is used to support new as well as experienced professionals in the decision making process. By guiding HCPs through diagnosing patients from an expansive directory of differential diagnoses, patients can receive quality care in the community. Actions on the platform are determined using NICE guidelines along with local guidance influencing the assessment and management of a patient. Objective: To compare the clinical assessment, decisions, and actions taken by the UCCT multidisciplinary team in the community and Dem Dx, using retrospective clinical cases. Methodology: Dem Dx was used to analyse 192 anonymised cases provided by the HMR UCCT. The team’s performance was compared with Dem Dx regarding the quality of the documentation of the clinical assessment and the next steps on the patient’s journey, including the initial management, actions, and any onward referrals made. The cases were audited by two medical doctors. Results: The study found that the actions outlined by the Dem Dx platform were appropriate in almost 87% of cases. When in a direct comparison between DemDX and the actions taken by the clinical team, it was found that the platform was suitable 83% (p<0.001) of the time and could lead to a potential improvement of 66% in the assessment and management of cases. Dem Dx also served to highlight the importance of comprehensive and high quality clinical documentation. The quality of documentation of cases by UCCT can be improved to provide a detailed account of the assessment and management process. By providing step-by-step guidance and documentation at every stage, Dem Dx may ensure that legal accountability has been fulfilled. Conclusion: With the ever expanding workforce in the NHS, technology has become a key component in driving healthcare outcomes. To improve healthcare provision and clinical reasoning, a decision support platform can be integrated into HCPs’ clinical practice. Potential assistance with clinical assessments, the most appropriate next step and actions in a patient’s care, and improvements in the documentation was highlighted by this retrospective study. A further study has been planned to ascertain the effectiveness of improving outcomes using the clinical reasoning platform within the clinical setting by clinicians.

Keywords: allied health professional, assessment, clinical reasoning, clinical records, clinical decision-making, ocumentation

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Authors: Hafid Smaili, Wilfred Rouwhorst, Paul Frost

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The trend of recent accident and incident cases worldwide show that the state-of-the-art automation and operations, for current and future demanding operational environments, does not provide the desired level of operational safety under crew peak workload conditions, specifically in complex situations such as loss-of-control in-flight (LOC-I). Today, the short term focus is on preparing crews to recognise and handle LOC-I situations through upset recovery training. This paper describes the cockpit integration aspects and piloted assessment of both a manually assisted and automatic upset detection and recovery system that has been developed and demonstrated within the European Advanced Cockpit for Reduction Of StreSs and workload (ACROSS) programme. The proposed system is a function that continuously monitors and intervenes when the aircraft enters an upset and provides either manually pilot-assisted guidance or takes over full control of the aircraft to recover from an upset. In order to mitigate the highly physical and psychological impact during aircraft upset events, the system provides new cockpit functionalities to support the pilot in recovering from any upset both manually assisted and automatically. A piloted simulator assessment was made in Oct-Nov 2015 using ten pilots in a representative civil large transport fly-by-wire aircraft in terms of the preference of the tested upset detection and recovery system configurations to reduce pilot workload, increase situational awareness and safe interaction with the manually assisted or automated modes. The piloted simulator evaluation of the upset detection and recovery system showed that the functionalities of the system are able to support pilots during an upset. The experiment showed that pilots are willing to rely on the guidance provided by the system during an upset. Thereby, it is important for pilots to see and understand what the aircraft is doing and trying to do especially in automatic modes. Comparing the manually assisted and the automatic recovery modes, the pilot’s opinion was that an automatic recovery reduces the workload so that they could perform a proper screening of the primary flight display. The results further show that the manually assisted recoveries, with recovery guidance cues on the cockpit primary flight display, reduced workload for severe upsets compared to today’s situation. The level of situation awareness was improved for automatic upset recoveries where the pilot could monitor what the system was trying to accomplish compared to automatic recovery modes without any guidance. An improvement in situation awareness was also noticeable with the manually assisted upset recovery functionalities as compared to the current non-assisted recovery procedures. This study shows that automatic upset detection and recovery functionalities are likely to positively impact the operational safety by means of reduced workload, improved situation awareness and crew stress reduction. It is thus believed that future developments for upset recovery guidance and loss-of-control prevention should focus on automatic recovery solutions.

Keywords: aircraft accidents, automatic flight control, loss-of-control, upset recovery

Procedia PDF Downloads 189

Authors: Uraib Sharaha, Ahmad Salman, Eladio Rodriguez-Diaz, Elad Shufan, Klaris Riesenberg, Irving J. Bigio, Mahmoud Huleihel

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Antimicrobial drugs have played an indispensable role in controlling illness and death associated with infectious diseases in animals and humans. However, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global healthcare problem. Many antibiotics had lost their effectiveness since the beginning of the antibiotic era because many bacteria have adapted defenses against these antibiotics. Rapid determination of antimicrobial susceptibility of a clinical isolate is often crucial for the optimal antimicrobial therapy of infected patients and in many cases can save lives. The conventional methods for susceptibility testing require the isolation of the pathogen from a clinical specimen by culturing on the appropriate media (this culturing stage lasts 24 h-first culturing). Then, chosen colonies are grown on media containing antibiotic(s), using micro-diffusion discs (second culturing time is also 24 h) in order to determine its bacterial susceptibility. Other methods, genotyping methods, E-test and automated methods were also developed for testing antimicrobial susceptibility. Most of these methods are expensive and time-consuming. Fourier transform infrared (FTIR) microscopy is rapid, safe, effective and low cost method that was widely and successfully used in different studies for the identification of various biological samples including bacteria; nonetheless, its true potential in routine clinical diagnosis has not yet been established. The new modern infrared (IR) spectrometers with high spectral resolution enable measuring unprecedented biochemical information from cells at the molecular level. Moreover, the development of new bioinformatics analyses combined with IR spectroscopy becomes a powerful technique, which enables the detection of structural changes associated with resistivity. The main goal of this study is to evaluate the potential of the FTIR microscopy in tandem with machine learning algorithms for rapid and reliable identification of bacterial susceptibility to antibiotics in time span of few minutes. The UTI E.coli bacterial samples, which were identified at the species level by MALDI-TOF and examined for their susceptibility by the routine assay (micro-diffusion discs), are obtained from the bacteriology laboratories in Soroka University Medical Center (SUMC). These samples were examined by FTIR microscopy and analyzed by advanced statistical methods. Our results, based on 700 E.coli samples, were promising and showed that by using infrared spectroscopic technique together with multivariate analysis, it is possible to classify the tested bacteria into sensitive and resistant with success rate higher than 90% for eight different antibiotics. Based on these preliminary results, it is worthwhile to continue developing the FTIR microscopy technique as a rapid and reliable method for identification antibiotic susceptibility.

Keywords: antibiotics, E.coli, FTIR, multivariate analysis, susceptibility, UTI

Procedia PDF Downloads 153

Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

Procedia PDF Downloads 116

Authors: Hantian Wu, Bo Huang, Yuan Zeng

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Divisions between wealthy and poor, private and public landscapes are propagated by the increasing economic inequality of cities. While these are the spatial reflections of larger social issues and problems, urban design can at least employ spatial techniques that promote more inclusive rather than exclusive, overlapping rather than segregated, interlinked rather than disconnected landscapes. Indeed, the type of edge or border between urban landscapes plays a critical role in the way the environment is perceived. China experiences rapid urbanization, which poses unpredictable environmental challenges. The urban green cover and water body are under changes, which highly relevant to resident wealth and happiness. However, very limited knowledge and data on their rapid changes are available. In this regard, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understating the driving forces of urban landscape changes can be a significant contribution for urban planning and studying. High-resolution remote sensing data has been widely applied to urban management in China. The map of urban land use map for the entire China of 2018 with 10 meters resolution has been published. However, this research focuses on the large-scale and high-resolution remote sensing land use but does not precisely focus on the seasonal change of urban covers. High-resolution remote sensing data has a long-operation cycle (e.g., Landsat 8 required 16 days for the same location), which is unable to satisfy the requirement of monitoring urban-landscape changes. On the other hand, aerial-remote or unmanned aerial vehicle (UAV) sensing are limited by the aviation-regulation and cost was hardly widely applied in the mega-cities. Moreover, those data are limited by the climate and weather conditions (e.g., cloud, fog), and those problems make capturing spatial and temporal dynamics is always a challenge for the remote sensing community. Particularly, during the rainy season, no data are available even for Sentinel Satellite data with 5 days interval. Many natural events and/or human activities drive the changes of urban covers. In this case, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understanding the mechanism of urban landscape changes can be a significant contribution for urban planning and studying. This project aims to use the high spatiotemporal fusion of remote sensing data to create short-cycle, high-resolution remote sensing data sets for exploring the high-frequently urban cover changes. This research will enhance the long-term monitoring applicability of high spatiotemporal fusion of remote sensing data for the urban landscape for optimizing the urban management of landscape border to promoting the inclusive of the urban landscape to all communities.

Keywords: urban land cover changes, remote sensing, high spatiotemporal fusion, urban management

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Authors: Darko Prebežac, Josip Mikulić, Maja Šerić, Damir Krešić

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Camping tourism is recognized as a growing segment of the broader tourism industry, currently evolving from an inexpensive, temporary sojourn in a rural environment into a highly fragmented niche tourism sector. The trends among public-managed campgrounds seem to be moving away from rustic campgrounds that provide only a tent pad and a fire ring to more developed facilities that offer a range of different amenities, where campers still search for unique experiences that go above the opportunity to experience nature and social interaction. In addition, while camping styles and options changed significantly over the last years, coastal camping in particular became valorized as is it regarded with a heightened sense of nostalgia. Alongside this growing interest in the camping tourism, a demand for quality servicing infrastructure emerged in order to satisfy the wide variety of needs, wants, and expectations of an increasingly demanding traveling public. However, camping activity in general and quality of camping experience and campers’ satisfaction in particular remain an under-researched area of the tourism and consumption behavior literature. In this line, very few studies addressed the issue of quality product/service provision in satisfying nature based tourists and in driving their future behavior with respect to potential re-visitation and recommendation intention. The present study thus aims to investigate the drivers of positive and negative campsite experience using the case of Croatia. Due to the well-preserved nature and indented coastline, camping tourism has a long tradition in Croatia and represents one of the most important and most developed tourism products. During the last decade the number of tourist overnights in Croatian camps has increased by 26% amounting to 16.5 million in 2014. Moreover, according to Eurostat the market share of campsites in the EU is around 14%, indicating that the market share of Croatian campsites is almost double large compared to the EU average. Currently, there are a total of 250 camps in Croatia with approximately 75.8 thousands accommodation units. It is further noteworthy that Croatian camps have higher average occupancy rates and a higher average length of stay as compared to the national average of all types of accommodation. In order to explore the main drivers of positive and negative campsite experiences, this study uses principal components analysis (PCA) and an impact-asymmetry analysis (IAA). Using the PCA, first the main dimensions of the campsite experience are extracted in an exploratory manner. Using the IAA, the extracted factors are investigated for their potentials to create customer delight and/or frustration. The results provide valuable insight to both researchers and practitioners regarding the understanding of campsite satisfaction.

Keywords: Camping tourism, campsite, impact-asymmetry analysis, satisfaction

Procedia PDF Downloads 166

Authors: Alba Francesca Canta

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The present is one of those times when what normally seems to constitute a reason for living vanishes, particularly in times of crisis, during which certainties of all times crumble, and critical issues emerge, especially in already problematic areas such as the role of women and children. This paper aims to explore the issue of gender and highlight the importance of education for people’s development and well-being. The study is part of the broader framework of the capability approach, a multidimensional approach based on the need to consider a person’s wealth by virtue of their opportunity and freedom to live a ‘life of worth. The results of empirical research conducted in 2020 will be presented, the main objective of which was to measure, through qualitative (project techniques, focus groups, interviews with key informants) and quantitative (questionnaire) methods, the level of empowerment of women in two Italian territories and the consequent well-being of their children. By means of the relationship study, the present research results show that a higher level of women’s empowerment corresponds to a higher level of children’s well-being in a positive virtuous process. The opportunity structure and education are the main driving guide both to women’s empowerment and children’s well-being, emphasizing the importance of education to gender culture as a key factor for the development of the whole society. Among all the traumatic events that broke the harmony of the world and caused an abrupt turn in all areas of society, the crisis of democracy and education are some of the harshest. Nevertheless, education continues to be a fundamental pillar of Global Development Agendas, and above all, democratic education is the main factor in the development of a generative society, capable of forming people who know how to live in society. In this context, recovering democratic and inclusive education can be the key to a breakthrough. In the capability approach Sen, and other Scholars, point out education from two different perspectives: a. education as a fundamental right capable of influencing other real fields of people’s life (i.e., being educated to prevent illness, to vote, etc.) and b. spread communitarian education, tolerance, inclusive, democratic, and respectful, capable of forming human beings. This kind of educational system can directly lead to a general process of gender education that presupposes respect for essential principles: equality, uniqueness, and the participation of all in the processes of defining a democratic society. Many practices of women and children’s exclusions essentially derive from social factors (norms, values, quality of institutions, relations of power, educational and cultural practices) that can build strong barriers. Respect for these principles and education for gender culture could foster the renewal of society and the acquisition of fundamental skills for a generative and inclusive society, such as critical skills, cosmopolitan skills, and narrative imagination.

Keywords: capability approach, children’s well-being, education, women’s empowerment

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Authors: Moustafa Osman Mohammed

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This paper introduces topological order in descried social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. Topological order is important in describing the physical systems for exploiting optical systems and improving photonic devices. The stats of topological order have some interesting properties of topological degeneracy and fractional statistics that reveal the entanglement origin of topological order, etc. Topological ideas in photonics form exciting developments in solid-state materials, that being; insulating in the bulk, conducting electricity on their surface without dissipation or back-scattering, even in the presence of large impurities. A specific type of autopoiesis system is interrelated to the main categories amongst existing groups of the ecological phenomena interaction social and medical sciences. The hypothesis, nevertheless, has a nonlinear interaction with its natural environment 'interactional cycle' for exchange photon energy with molecules without changes in topology. The engineering topology of a biosensor is based on the excitation boundary of surface electromagnetic waves in photonic band gap multilayer films. The device operation is similar to surface Plasmonic biosensors in which a photonic band gap film replaces metal film as the medium when surface electromagnetic waves are excited. The use of photonic band gap film offers sharper surface wave resonance leading to the potential of greatly enhanced sensitivity. So, the properties of the photonic band gap material are engineered to operate a sensor at any wavelength and conduct a surface wave resonance that ranges up to 470 nm. The wavelength is not generally accessible with surface Plasmon sensing. Lastly, the photonic band gap films have robust mechanical functions that offer new substrates for surface chemistry to understand the molecular design structure and create sensing chips surface with different concentrations of DNA sequences in the solution to observe and track the surface mode resonance under the influences of processes that take place in the spectroscopic environment. These processes led to the development of several advanced analytical technologies: which are; automated, real-time, reliable, reproducible, and cost-effective. This results in faster and more accurate monitoring and detection of biomolecules on refractive index sensing, antibody-antigen reactions with a DNA or protein binding. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other in order to form unique spatial structure and dynamics of biological molecules for providing the environment mutual contribution in investigation of changes due to the pathogenic archival architecture of cell clusters.

Keywords: autopoiesis, photonics systems, quantum topology, molecular structure, biosensing

Procedia PDF Downloads 66

Authors: Einat Waizbard, Emilio Ferrer, Meghan Miller, Brianna Heath, Derek S. Andrews, Sally J. Rogers, Christine Wu Nordahl, Marjorie Solomon, David G. Amaral

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Background: Autism symptoms are comprised of social-communication deficits and restricted/repetitive behaviors (RRB). The severity of these symptoms can change during childhood, with differences between boys and girls. From the literature, it was found that young autistic girls show a stronger tendency to decrease and a weaker tendency to increase their overall autism symptom severity levels compared to young autistic boys. It is not clear, however, which symptoms are driving these sex differences across childhood. In the current study, we evaluated the trajectories of independent autism symptoms across childhood and compared the patterns of change in such symptoms between boys and girls. Method: The study included 183 children diagnosed with autism (55 girls) evaluated three times across childhood, at ages 3, 6 and 11. We analyzed 22 independent items from the Autism Diagnostic Observation Scheudule-2 (ADOS-2), the gold-standard assessment tool for autism symptoms, each item representing a specific autism symptom. First, we used latent growth curve models to estimate the trajectories for the 22 ADOS-2 items for each child in the study. Second, we extracted the factor scores representing the individual slopes for each ADOS-2 item (i.e., slope representing that child’s change in that specific item). Third, we used factor analysis to identify common patterns of change among the ADOS-2 items, separately for boys and girls, i.e., which autism symptoms tend to change together and which change independently across childhood. Results: The best-emerging patterns for both boys and girls identified four common factors: three factors representative of changes in social-communication symptoms and one factor describing changes in RRB. Boys and girls showed the same pattern of change in RRB, with four items (e.g., speech abnormalities) changing together across childhood and three items (e.g., mannerisms) changing independently of other items. For social-communication deficits in boys, three factors were identified: the first factor included six items representing initiating and engaging in social-communication (e.g., quality of social overtures, conversation), the second factor included five items describing responsive social-communication (e.g., response to name) and the third factor included three items related to different aspects of social-communication (e.g., level of language). Girls’ social-communications deficits also loaded onto three factors: the first factor included five items (e.g., unusual eye contact), the second factor included six items (e.g., quality of social response), and the third factor included four items (e.g., showing). Some items showed similar patterns of change for both sexes (e.g., responsive joint attention), while other items showed differences (e.g., shared enjoyment). Conclusions: Girls and boys had different patterns of change in autism symptom severity across childhood. For RRB, both sexes showed similar patterns. For social-communication symptoms, however, there were both similarities and differences between boys and girls in the way symptoms changed over time. The strongest patterns of change were identified for initiating and engaging in social communication for boys and responsive social communication for girls.

Keywords: autism spectrum disorder, autism symptom severity, symptom trajectories, sex differences

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Authors: Anastasia V. Kovaleva, Alena A. Ryabova, Vladimir N. Kasatkin

Abstract:

Background: The most simple form of entrainment to a sensory (typically auditory) rhythmic stimulus involves perceiving and synchronizing movements with an isochronous beat with one level of periodicity, such as that produced by a metronome. Children with pediatric cancer usually treated with chemo- and radiotherapy. Because of such treatment, psychologists and health professionals declare cognitive and motor abilities decline in cancer patients. The purpose of our study was to measure working memory characteristics with association with audio-motor synchronization tasks, also involved some memory resources, in children with different degrees of central nervous system lesions: posterior fossa tumors, acute lymphoblastic leukemia, and healthy controls. Methods: Our sample consisted of three groups of children: children treated for posterior fossa tumors (PFT-group, n=42, mean age 12.23), children treated for acute lymphoblastic leukemia (ALL-group, n=11, mean age 11.57) and neurologically healthy children (control group, n=36, mean age 11.67). Participants were tested for working memory characteristics with Cambridge Neuropsychological Test Automated Battery (CANTAB). Pattern recognition memory (PRM) and spatial working memory (SWM) tests were applied. Outcome measures of PRM test include the number and percentage of correct trials and latency (speed of participant’s response), and measures of SWM include errors, strategy, and latency. In the synchronization tests, the instruction was to tap out a regular beat (40, 60, 90 and 120 beats per minute) in synchrony with the rhythmic sequences that were played. This meant that for the sequences with an isochronous beat, participants were required to tap into every auditory event. Variations of inter-tap-intervals and deviations of children’s taps from the metronome were assessed. Results: Analysis of variance revealed the significant effect of group (ALL, PFT and control) on such parameters as short-term PRM, SWM strategy and errors. Healthy controls demonstrated more correctly retained elements, better working memory strategy, compared to cancer patients. Interestingly that ALL patients chose the bad strategy, but committed significantly less errors in SWM test then PFT and controls did. As to rhythmic ability, significant associations of working memory were found out only with 40 bpm rhythm: the less variable were inter-tap-intervals of the child, the more elements in memory he/she could retain. The ability to audio-motor synchronization may be related to working memory processes mediated by the prefrontal cortex whereby each sensory event is actively retrieved and monitored during rhythmic sequencing. Conclusion: Our results suggest that working memory, tested with appropriate cognitive methods, is associated with the ability to synchronize movements with rhythmic sounds, especially in sub-second intervals (40 per minute).

Keywords: acute lymphoblastic leukemia (ALL), audio-motor synchronization, posterior fossa tumor, working memory

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Authors: Alexandra Sargent, Sarah Ferris, Ioannis Theofanous

Abstract:

The Abbott RealTime High Risk HPV test (RealTime HPV) is one of five assays clinically validated and approved by the English NHS Cervical Screening Programme (CSP) for HPV triage of low grade dyskaryosis and test-of-cure of treated Cervical Intraepithelial Neoplasia. The assay is a highly automated multiplex real-time PCR test for detecting 14 high risk (hr) HPV types, with simultaneous differentiation of HPV 16 and HPV 18 versus non-HPV 16/18 hrHPV. An endogenous internal control ensures sample cellularity, controls extraction efficiency and PCR inhibition. The original cervical specimen collected in SurePath (SP) liquid-based cytology (LBC) medium (BD Diagnostics) and the SP post-gradient cell pellets (SPG) after cytological processing are both CE marked for testing with the RealTime HPV test. During the 2011 NHSCSP validation of new tests only the original aliquot of SP LBC medium was investigated. Residual sample volume left after cytology slide preparation is low and may not always have sufficient volume for repeat HPV testing or for testing of other biomarkers that may be implemented in testing algorithms in the future. The SPG samples, however, have sufficient volumes to carry out additional testing and necessary laboratory validation procedures. This study investigates the correlation of RealTime HPV results of cervical specimens collected in SP LBC medium from women with low grade cytological abnormalities observed with matched pairs of original SP LBC medium and SP post-gradient cell pellets (SPG) after cytology processing. Matched pairs of SP and SPG samples from 750 women with borderline (N = 392) and mild (N = 351) cytology were available for this study. Both specimen types were processed and parallel tested for the presence of hrHPV with RealTime HPV according to the manufacturer´s instructions. HrHPV detection rates and concordance between test results from matched SP and SPGCP pairs were calculated. A total of 743 matched pairs with valid test results on both sample types were available for analysis. An overall-agreement of hrHPV test results of 97.5% (k: 0.95) was found with matched SP/SPG pairs and slightly lower concordance (96.9%; k: 0.94) was observed on 392 pairs from women with borderline cytology compared to 351 pairs from women with mild cytology (98.0%; k: 0.95). Partial typing results were highly concordant in matched SP/SPG pairs for HPV 16 (99.1%), HPV 18 (99.7%) and non-HPV16/18 hrHPV (97.0%), respectively. 19 matched pairs were found with discrepant results: 9 from women with borderline cytology and 4 from women with mild cytology were negative on SPG and positive on SP; 3 from women with borderline cytology and 3 from women with mild cytology were negative on SP and positive on SPG. Excellent correlation of hrHPV DNA test results was found between matched pairs of SP original fluid and post-gradient cell pellets from women with low grade cytological abnormalities tested with the Abbott RealTime High-Risk HPV assay, demonstrating robust performance of the test with both specimen types and reassuring the utility of the assay for cytology triage with both specimen types.

Keywords: Abbott realtime test, HPV, SurePath liquid based cytology, surepath post-gradient cell pellet

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Authors: Anna Öqvist, Malin Malmström

Abstract:

Attaining a higher level of education has become an increasingly important prerequisite for people’s economic and social independence and mobility. Young people who do not pursue higher education are not as attractive as potential employees in the modern work environment. Although completing a higher education degree is not a guarantee for getting a job, it substantially increases the chances for employment and, consequently, the chances for a better life. Despite this, it’s a fact that in several regions in Sweden, fewer students are choosing to engage in higher education. Similar trends have been emphasized in, for instance, the US where high dropout patterns among young people have been noted. This is a threat to future employment and industry development in these regions because the future employment base for society is dependent upon students’ willingness to invest in higher education. Much of prior studies have focused on the role of parents’ involvement in their children’s’ school work and the positive influence parents involvement have on their children’s school performance. Parental influence on education in general has been a topic of interest among those concerned with optimal developmental and educational outcomes for children and youth in pre-, secondary- and high school. Across a range of studies, there has emerged a strong conclusion that parental influence on child and youths education generally benefits children's and youths learning and school success. Arguably then, we could expect that parents influence on whether or not to pursue a higher education would be of importance to understand young people’s choice to engage in higher education. Accordingly, understanding what drives students’ intentions to pursue higher education is an essential component of motivating students to aspire to make the most of their potential in their future work life. Drawing on the theory of planned behavior, this study examines the role of parents influence on students’ attitudes about whether higher education can be beneficial to their future work life. We used a qualitative approach by collecting interview data from 18 high school students in Sweden to capture students’ cognitive and motivational mechanisms (attitudes) to influence intentions to engage in higher education. We found that parents may positively or negatively influence students’ attitudes and subsequently a student's intention to pursue higher education. Accordingly, our results show that parents’ own attitudes and expectations on their children are keys for influencing students’ attitudes and intentions for higher education. Further, our finding illuminates the mechanisms that drive students in one direction or the other. As such, our findings show that the same categories of arguments are used for driving students’ attitudes and intentions in two opposite directions, namely; financial arguments and work life benefits arguments. Our results contribute to existing literature by showing that parents do affect young people’s intentions to engage in higher studies. The findings contribute to the theory of planned behavior and have implications for the literature on higher education and educational psychology and also provide guidance on how to inform students about facts of higher studies in school.

Keywords: higher studies, intentions, parents influence, theory of planned behavior

Procedia PDF Downloads 232