Search results for: convolutional neural networks

Authors: Adi Gielgun-Katz, Alina S. Rusu

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In the last two decades, education systems worldwide have integrated new pedagogical methods and strategies in lesson plans, such as innovative technologies, social-emotional learning (SEL), gamification, mixed learning, multiple literacies, and many others. Visual language, such as photographs, is known to transcend cultures and languages, and it is commonly used by youth to express positions and affective states in social networks. Therefore, visual language needs more educational attention as a linguistic and communicative component that can create connectedness among the students and their teachers. Nowadays, when SEL is gaining more and more space and meaning in the area of academic improvement in relation to social well-being, and taking and sharing pictures is part of the everyday life of the majority of people, it becomes natural to add the visual language to SEL approach as a reinforcement strategy for connecting education to the contemporary culture and language of the youth. This article presents a program conducted in a high school class in Israel, which combines the five SEL with photography techniques, i.e., Social-Emotional Learning Visual Empowerments (SELVEs) program (experimental group). Another class of students from the same institution represents the control group, which is participating in the SEL program without the photography component. The SEL component of the programs addresses skills such as: troubleshooting, uncertainty, personal strengths and collaboration, accepting others, control of impulses, communication, self-perception, and conflict resolution. The aim of the study is to examine the effects of programs on the level of the five SEL aspects in the two groups of high school students: Self-Awareness, Social Awareness, Self-Management, Responsible Decision Making, and Relationship Skills. The study presents a quantitative assessment of the SEL programs’ impact on the students. The main hypothesis is that the students’ questionnaires' analysis will reveal a better understanding and improvement of the five aspects of the SEL in the group of students involved in the photography-enhanced SEL program.

Keywords: social-emotional learning, photography, education program, adolescents

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Authors: Gilberto Goracci, Fabio Curti

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This work presents a robust, light, and inexpensive algorithm to perform autonomous orbit determination using onboard magnetometer data in real-time. Magnetometers are low-cost and reliable sensors typically available on a spacecraft for attitude determination purposes, thus representing an interesting choice to perform real-time orbit determination without the need to add additional sensors to the spacecraft itself. Magnetic field measurements can be exploited by Extended/Unscented Kalman Filters (EKF/UKF) for orbit determination purposes to make up for GPS outages, yielding errors of a few kilometers and tens of meters per second in the position and velocity of a spacecraft, respectively. While this level of accuracy shows that Kalman filtering represents a solid baseline for autonomous orbit determination, it is not enough to provide a reliable state estimation in the absence of GPS signals. This work combines the solidity and reliability of the EKF with the versatility of a Recurrent Neural Network (RNN) architecture to further increase the precision of the state estimation. Deep learning models, in fact, can grasp nonlinear relations between the inputs, in this case, the magnetometer data and the EKF state estimations, and the targets, namely the true position, and velocity of the spacecraft. The model has been pre-trained on Sun-Synchronous orbits (SSO) up to 2126 kilometers of altitude with different initial conditions and levels of noise to cover a wide range of possible real-case scenarios. The orbits have been propagated considering J2-level dynamics, and the geomagnetic field has been modeled using the International Geomagnetic Reference Field (IGRF) coefficients up to the 13th order. The training of the module can be completed offline using the expected orbit of the spacecraft to heavily reduce the onboard computational burden. Once the spacecraft is launched, the model can use the GPS signal, if available, to fine-tune the parameters on the actual orbit onboard in real-time and work autonomously during GPS outages. In this way, the provided module shows versatility, as it can be applied to any mission operating in SSO, but at the same time, the training is completed and eventually fine-tuned, on the specific orbit, increasing performances and reliability. The results provided by this study show an increase of one order of magnitude in the precision of state estimate with respect to the use of the EKF alone. Tests on simulated and real data will be shown.

Keywords: artificial intelligence, extended Kalman filter, orbit determination, magnetic field

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Authors: Ana M. G. Sperandio, Adriana A. C. Rosa, Jussara C. Guarnieri

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This study consists of a research of the Post Occupancy Assessment (POA) of Medicinal Gardens' project of Urban Social Center’s square, in the city of 'Santa Barbara d'Oeste', located in the interior of Sao Paulo, Brazil. In view of the fact that community gardens, as well as medicinal gardens, are based on innumerable functions. The addition to the pedagogical function rescues people from their origins through (re)contact with the land, as a vehicle for social integration. Bearing in mind the project has the potential to fight hunger among the low-income population, to treat some diseases, also works as a strategy of environmental recovery especially of idle land. Such as very often only accumulate weeds and garbage, and therefore, must be considered in the Municipal Master Plan for the activity to be regulated. Objective: Identify on implantation the medicinal plants' value and principles for the promotion of a healthy city. Methodology: Application of the walkthrough, where it is possible to affirm that this instrument has three routes: one officer applied within the urban social center and two complementary ones, one being about 3 miles and the other being almost 5,5 miles. Results: Through a dialogical course, one can observe the benefits that the community medicinal gardens bring to the local population. In addition, it is consistent with the proposal for the community to be enabled to access collective care with home orientations that rescue the local and regional culture making the physical environment. This project aims at promoting more pleasant and inclusive through the actions of the caregiver, local leadership and the co-participation of local government. Although with the aim of increasing the supply value and improving the living conditions of social groups and interrelationship. Conclusion: This type of urban intervention, which articulates social participation, rescue of medicinal cultures and local knowledge, intersectoriality, social inclusion, among other premises connected with health promotion, and the city presents a potential for reverberation of practices in social networks with the objective of meeting the healthy city strategies.

Keywords: healthy city, healthy urban planning, medicinal gardens, social participation

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Authors: Nicholas C. Rose, Christopher D. Spicer

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The regeneration of damaged or diseased tissues would provide an invaluable therapeutic tool in biological research and medicine. Cells must be provided with a number of different biochemical signals in order to form mature tissue through complex signaling networks that are difficult to recreate in synthetic materials. The ability to attach and detach bioactive proteins from material in an iterative and dynamic manner would therefore present a powerful way to mimic natural biochemical signaling cascades for tissue growth. We propose to reversibly attach these bioactive proteins using ortho-boronoimine (oBI) linkages and related derivatives formed by the reaction of an ortho-boronobenzaldehyde with a nucleophilic amine derivative. To enable the use of oBIs for biomaterial modification, we have studied binding and cleavage processes with precise detail in the context of small molecule models. A panel of oBI complexes has been synthesized and screened using a novel Förster resonance energy transfer (FRET) assay, using a cyanine dye FRET pair (Cy3 and Cy5), to identify the most reactive boron-aldehyde/amine nucleophile pairs. Upon conjugation of the dyes, FRET occurs under Cy3 excitation and the resultant ratio of Cy3:Cy5 emission directly correlates to conversion. Reaction kinetics and equilibria can be accurately quantified for reactive pairs, with dissociation constants of oBI derivatives in water (KD) found to span 9-orders of magnitude (10⁻²-10⁻¹¹ M). These studies have provided us with a better understanding of oBI linkages that we hope to exploit to reversibly attach bioconjugates to materials. The long-term aim of the project is to develop a modular biomaterial platform that can be used to help combat chronic diseases such as osteoarthritis, heart disease, and chronic wounds by providing cells with potent biological stimuli for tissue engineering.

Keywords: dynamic, bioconjugation, bornoimine, rapid, physiological

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Authors: Desmond Okorie, Emmanuel Prince

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Availability of portable water has been a global challenge especially to the developing continents/nations such as Africa/Nigeria. The World Health Organization WHO has produced the guideline for drinking water quality GDWQ which aims at ensuring water safety from source to consumer. Portable water parameters test include physical (colour, odour, temperature, turbidity), chemical (PH, dissolved solids) biological (algae, plytoplankton). This paper discusses the use of wireless sensor networks to monitor water quality using efficient and effective sensors that have the ability to sense, process and transmit sensed data. The integration of wireless sensor network to a portable sensing device offers the feasibility of sensing distribution capability, on site data measurements and remote sensing abilities. The current water quality tests that are performed in government water quality institutions in Benue State Nigeria are carried out in problematic locations that require taking manual water samples to the institution laboratory for examination, to automate the entire process based on wireless sensor network, a system was designed. The system consists of sensor node containing one PH sensor, one temperature sensor, a microcontroller, a zigbee radio and a base station composed by a zigbee radio and a PC. Due to the advancement of wireless sensor network technology, unexpected contamination events in water environments can be observed continuously. local area network (LAN) wireless local area network (WLAN) and internet web-based also commonly used as a gateway unit for data communication via local base computer using standard global system for mobile communication (GSM). The improvement made on this development show a water quality monitoring system and prospect for more robust and reliable system in the future.

Keywords: local area network, Ph measurement, wireless sensor network, zigbee

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Authors: Robin Ferguson

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The context which this paper explores is the provision of Technical Vocational Education and Training (TVET) of southern African workers at sea on local and foreign vessels using a blended learning approach. The pedagogical challenge of providing quality education in this context is that multiple African and foreign languages and cultural norms are found amongst the all-male crew; and there are widely differing levels of education, low levels of digital literacy and limited connectivity. The methodology used is a nested case study. The study describes the mechanisms used to provide ongoing, real-time workplace TVET on two foreign vessels. Some training was done in person when the vessels came into port, however, the majority of the TVET was achieved from shore to ship using a combination of commonly available Google and Microsoft Apps and WhatsApp. Voice, video and text in multiple languages were used to accommodate different learning styles. The learning was supported by the development of learning networks using social media. This paper also reflects on the shore-based organisational change processes required to support sea learning. The conceptual framework used is the Theory of Practice Architectures (TPA) as is provides a site-ontological perspective of the sayings/thinkings, doings and relatings of this workplace training which is multiplanar as it plays out at sea and ashore, in-person and on-line. Using TPA, the overarching practice architectures and supporting structures which confound or enable these learning practices are revealed. The contribution which this paper makes is an insight into an innovative vocational pedagogy which promotes ICT-mediated learning amongst workers who suffer from low levels of literacies and limited ICT-access and who work and live in remote places. It is a pedagogy of possibility which crosses the digital divide.

Keywords: theory of practice architecture, microsoft, google, whatsapp, vocational pedagogy, mariners, distributed workplaces

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Authors: Michel T. Leger, Shawn Martin

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Leading an ecologically responsible lifestyle represents a difficult challenge. Though research in environmental education does point to an increase in the intention to act more responsibly towards the environment, this intent does not seem to translate to concrete ecological action. This mixed methods collective case study explores the adoption of ecological actions in the family, a context of socio-ecological transformation rarely examined in the scientific literature. More specifically, it takes into account the popular use of social media today to explore the potential role social media, namely Facebook, in promoting environmental action. In other words, for families who are intent on adopting an ecologically friendly lifestyle, could the use of Facebook positively affect the way family members relate to the environment and bring about real change in their daily household actions? To answer this question, twenty-one families living in an urban setting were recruited and then divided them into two distinct groups. The first group of families attempted to lower their household electrical bill as part of a private Facebook group, while the other aimed to do the same, but without the directed use of social media. For both groups, we recorded the amount of kilowatt-hours used during the project as well as the amount used for the same months the previous year, adjusting for temperature variations. Exit interviews were also conducted with each family in order to try to understand the processes of eco-citizenship development in the context of family. Results seem to suggest that both virtual social networks and one-on-one support can help to increase environmental awareness in participating family. Interestingly, families from the Facebook group seemed to demonstrate a higher degree of environmental engagement, and younger family members in this group were more active in the processes of collective behavioral change.

Keywords: environmental education, family-based eco-citizenship, social media, case study

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Authors: S. Jayasinghe, R. B. N. Dissanayake

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Optimization modelling together with the Network models and Linear Programming techniques is a powerful tool in problem solving and decision making in real world applications. This study developed a mathematical model to optimize the net profit by minimizing the transportation cost. This model focuses the transportation among decentralized production plants to a centralized distribution centre and then the distribution among island wide agencies considering the customer satisfaction as a requirement. This company produces basically 9 types of food items with 82 different varieties and 4 types of non-food items with 34 different varieties. Among 6 production plants, 4 were located near the city of Mawanella and the other 2 were located in Galewala and Anuradhapura cities which are 80 km and 150 km away from Mawanella respectively. The warehouse located in the Mawanella was the main production plant and also the only distribution plant. This plant distributes manufactured products to 39 agencies island-wide. The average values and average amount of the goods for 6 consecutive months from May 2013 to October 2013 were collected and then average demand values were calculated. The following constraints are used as the necessary requirement to satisfy the optimum condition of the model; there was one source, 39 destinations and supply and demand for all the agencies are equal. Using transport cost for a kilometer, total transport cost was calculated. Then the model was formulated using distance and flow of the distribution. Network optimization and linear programming techniques were used to originate the model while excel solver is used in solving. Results showed that company requires total transport cost of Rs. 146, 943, 034.50 to fulfil the customers’ requirement for a month. This is very much less when compared with data without using the model. Model also proved that company can reduce their transportation cost by 6% when distributing to island-wide customers. Company generally satisfies their customers’ requirements by 85%. This satisfaction can be increased up to 97% by using this model. Therefore this model can be used by other similar companies in order to reduce the transportation cost.

Keywords: mathematical model, network optimization, linear programming

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Authors: Havva Nur Tarakci, Bahar Urhan Torun

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The transformation that is seen in every area of life by technology, especially internet technology changes the structure of political communications too. Internet, which is at the top of new communication technologies, affects political communications with its structure in a way that no traditional communication tools ever have and enables interaction and the channel between receiver and sender, and it becomes one of the most effective tools preferred among the political communication applications. This state as a result of technological convergence makes Internet an unobtainable place for political communication campaigns. Political communications, which means every kind of communication strategies that political parties called 'actors of political communications' use with the aim of messaging their opinions and party programmes to their present and potential voters who are a target group for them, is a type of communication that is frequently used also among social media tools at the present day. The electorate consisting of different structures is informed, directed, and managed by social media tools. Political parties easily reach their electorate by these tools without any limitations of both time and place and also are able to take the opinions and reactions of their electorate by the element of interaction that is a feature of social media. In this context, Facebook, which is a place that political parties use in social media at most, is a communication network including in our daily life since 2004. As it is one of the most popular social networks today, it is among the most-visited websites in the global scale. In this way, the research is based on the question, “How do the political parties use Facebook at the campaigns, which they conduct during the election periods, for informing their voters?” and it aims at clarifying the Facebook using practices of the political parties. In direction of this objective the official Facebook accounts of the four political parties (JDP–AKParti, PDP–BDP, RPP-CHP, NMP-MHP), which reach their voters by social media besides other communication tools, are treated, and a frame for the politics of Turkey is formed. The time of examination is constricted with totally two weeks, one week before the mayoral elections and one week after the mayoral elections, when it is supposed that the political parties use their Facebook accounts in full swing. As a research method, the method of content analysis is preferred, and the texts and the visual elements that are gotten are interpreted based on this analysis.

Keywords: Facebook, political communications, social media, electrorate

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Authors: Yaolin Tian, Shanxiong Chen, Fujia Zhao, Xiaoyu Lin, Hailing Xiong

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Ancient books are significant culture inheritors and their background textures convey the potential history information. However, multi-style texture recovery of ancient books has received little attention. Restricted by insufficient ancient textures and complex handling process, the generation of ancient textures confronts with new challenges. For instance, training without sufficient data usually brings about overfitting or mode collapse, so some of the outputs are prone to be fake. Recently, image generation and style transfer based on deep learning are widely applied in computer vision. Breakthroughs within the field make it possible to conduct research upon multi-style texture recovery of ancient books. Under the circumstances, we proposed a network of layout analysis and image fusion system. Firstly, we trained models by using Deep Convolution Generative against Networks (DCGAN) to synthesize multi-style ancient textures; then, we analyzed layouts based on the Position Rearrangement (PR) algorithm that we proposed to adjust the layout structure of foreground content; at last, we realized our goal by fusing rearranged foreground texts and generated background. In experiments, diversified samples such as ancient Yi, Jurchen, Seal were selected as our training sets. Then, the performances of different fine-turning models were gradually improved by adjusting DCGAN model in parameters as well as structures. In order to evaluate the results scientifically, cross entropy loss function and Fréchet Inception Distance (FID) are selected to be our assessment criteria. Eventually, we got model M8 with lowest FID score. Compared with DCGAN model proposed by Radford at el., the FID score of M8 improved by 19.26%, enhancing the quality of the synthetic images profoundly.

Keywords: deep learning, image fusion, image generation, layout analysis

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Shengnan Chen, Shuhua Wang

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Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.

Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves

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Authors: Farheen Tabassum, Shoab Ahmed Khan

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The brutality of attacks on networks and decisive infrastructures are on the climb over recent years and appears to continue to do so. Distributed Denial of service attack is the most prevalent and easy attack on the availability of a service due to the easy availability of large botnet computers at cheap price and the general lack of protection against these attacks. Application layer DDoS attack is DDoS attack that is targeted on wed server, application server or database server. These types of attacks are much more sophisticated and challenging as they get around most conventional network security devices because attack traffic often impersonate normal traffic and cannot be recognized by network layer anomalies. Conventional techniques of single-hosted security systems are becoming gradually less effective in the face of such complicated and synchronized multi-front attacks. In order to protect from such attacks and intrusion, corporation among all network devices is essential. To overcome this issue, a collaborative intrusion detection system (CIDS) is proposed in which multiple network devices share valuable information to identify attacks, as a single device might not be capable to sense any malevolent action on its own. So it helps us to take decision after analyzing the information collected from different sources. This novel attack detection technique helps to detect seemingly benign packets that target the availability of the critical infrastructure, and the proposed solution methodology shall enable the incident response teams to detect and react to DDoS attacks at the earliest stage to ensure that the uptime of the service remain unaffected. Experimental evaluation shows that the proposed collaborative detection approach is much more effective and efficient than the previous approaches.

Keywords: Distributed Denial-of-Service (DDoS), Collaborative Intrusion Detection System (CIDS), Slowloris, OSSIM (Open Source Security Information Management tool), OSSEC HIDS

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Authors: Abdelhalim. N. Mohammed, Mohammed. Y. Esmail

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In the course of recent decades, medical imaging has been dominated by the use of costly film media for review and archival of medical investigation, however due to developments in networks technologies and common acceptance of a standard digital imaging and communication in medicine (DICOM) another approach in light of World Wide Web was produced. Web technologies successfully used in telemedicine applications, the combination of web technologies together with DICOM used to design a web-based and open source DICOM viewer. The Web server allowance to inquiry and recovery of images and the images viewed/manipulated inside a Web browser without need for any preinstalling software. The dynamic site page for medical images visualization and processing created by using JavaScript and HTML5 advancements. The XAMPP ‘apache server’ is used to create a local web server for testing and deployment of the dynamic site. The web-based viewer connected to multiples devices through local area network (LAN) to distribute the images inside healthcare facilities. The system offers a few focal points over ordinary picture archiving and communication systems (PACS): easy to introduce, maintain and independently platforms that allow images to display and manipulated efficiently, the system also user-friendly and easy to integrate with an existing system that have already been making use of web technologies. The wavelet-based image compression technique on which 2-D discrete wavelet transform used to decompose the image then wavelet coefficients are transmitted by entropy encoding after threshold to decrease transmission time, stockpiling cost and capacity. The performance of compression was estimated by using images quality metrics such as mean square error ‘MSE’, peak signal to noise ratio ‘PSNR’ and compression ratio ‘CR’ that achieved (83.86%) when ‘coif3’ wavelet filter is used.

Keywords: DICOM, discrete wavelet transform, PACS, HIS, LAN

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Authors: Sonam Chorol, Sharvan Kumar, Pritam Mukhopadhyay

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In biology, supramolecular systems require the use of chemical fuels to stay in sustained nonequilibrium steady states termed dissipative self-assembly in contrast to synthetic self-assembly. Biomimicking these natural dynamic systems, some studies have demonstrated artificial self-assembly under nonequilibrium utilizing various forms of energies (fuel) such as chemical, redox, and pH. Naphthalene diimides (NDIs) are well-known organic molecules in supramolecular architectures with high electron affinity and have applications in controlled electron transfer (ET) reactions, etc. Herein, we report the endergonic ET from tetraphenylborate to highly electron-deficient phosphonium NDI²+ dication to generate NDI•+ radical. The formation of radicals was confirmed by UV-Vis-NIR absorption spectroscopy. Electron-donor and electron-acceptor energy levels were calculated from experimental electrochemistry and theoretical DFT analysis. The HOMO of the electron donor locates below the LUMO of the electro-acceptor. This indicates that electron transfer is endergonic (ΔE°ET = negative). The endergonic ET from NaBPh₄ to NDI²+ dication was achieved thermodynamically by the formation of coupled biphenyl product confirmed by GC-MS analysis. NDI molecule bearing octyl phosphonium at the core and H-bond forming imide moieties at the axial position forms a gel. The rheological properties of purified radical ion NDI⦁+ gels were evaluated. The atomic force microscopy studies reveal the formation of large branching-type networks with a maximum height of 70-80 nm. The endergonic ET from NaBPh₄ to NDI²+ dication was used to design the assembly and disassembly redox reaction cycle using reducing (NaBPh₄) and oxidizing agents (Br₂) as chemical fuels. A part of NaBPh₄ is used to drive assembly, while a fraction of the NaBPh₄ is dissipated by forming a useful product. The system goes back to the disassembled NDI²+ dication state with the addition of Br₂. We think bioinspired dissipative self-assembly is the best approach to developing future lifelike materials with autonomous behavior.

Keywords: Ionic-gel, redox-cycle, self-assembly, useful product

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Authors: Ana Hol

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We live in a constantly changing environment where technology has become an integral component of our day to day life. We rely heavily on mobile devices, we search for data via web, we utilise smart home sensors to create the most suited ambiences and we utilise applications to shop, research, communicate and share data. Heavy reliance on technology therefore is creating new connections between STEM (Science, Technology, Engineering and Mathematics) fields which in turn rises a question of what the STEM education of the future should be like? This study was based on the reviews of the six Australian Information Systems students who undertook an international study tour to India where they were given an opportunity to network, communicate and meet local students, staff and business representatives and from them learn about the local business implementations, local customs and regulations. Research identifies that if we are to continue to implement and utilise electronic devices on the global scale, such as for example implement smart cars that can smoothly cross borders, we will need the workforce that will have the knowledge about the cars themselves, their parts, roads and transport networks, road rules, road sensors, road monitoring technologies, graphical user interfaces, movement detection systems as well as day to day operations, legal rules and regulations of each region and country, insurance policies, policing and processes so that the wide array of sensors can be controlled across country’s borders. In conclusion, it can be noted that allowing students to learn about the local conditions, roads, operations, business processes, customs and values in different countries is giving students a cutting edge advantage as such knowledge cannot be transferred via electronic sources alone. However once understanding of each problem or project is established, multidisciplinary innovative STEM projects can be smoothly conducted.

Keywords: STEM, curiosity, innovation, advancements

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Authors: Vedat Uyak

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Seasonal variations of trihalomethanes (THMs) and haloacetic acids (HAAs) concentrations were investigated within three distribution systems of a coastal city of Istanbul, Turkey. Moreover, total trihalomethanes and other organics concentration were also analyzed. The investigation was based on an intensive 16 month (2009-2010) sampling program, undertaken during the spring, summer, fall and winter seasons. Four THM (chloroform, dichlorobromomethane, chlorodibromomethane, bromoform), and nine HAA (the most commonly occurring one being dichloroacetic acid (DCAA) and trichloroacetic acid (TCAA); other compounds are monochloroacetic acid (MCAA), monobromoacetic acid (MBAA), dibromoacetic acid (DBAA), tribromoacetic acid (TBAA), bromochloroacetic acid (BCAA), bromodichloroacetic acid (BDCAA) and chlorodibromoacetic acid (CDBAA)) species and other water quality and operational parameters were monitored at points along the distribution system between the treatment plant and the system’s extremity. The effects of coastal water sources, seasonal variation and spatial variation were examined. The results showed that THMs and HAAs concentrations vary significantly between treated waters and water at the distribution networks. When water temperature exceeds 26°C in summer, the THMs and HAAs levels are 0.8 – 1.1, and 0.4 – 0.9 times higher than treated water, respectively. While when water temperature is below 12°C in the winter, the measured THMs and HAAs concentrations at the system’s extremity were very rarely higher than 100 μg/L, and 60 μg/L, respectively. The highest THM concentrations occurred in the Buyukcekmece distribution system, with an average total HAA concentration of 92 μg/L. Moreover, the lowest THM levels were observed in the Omerli distribution network, with a mean concentration of 7 μg/L. For HAA levels, the maximum concentrations again were observed in the Buyukcekmece distribution system, with an average total HAA concentration of 57 μg/l. High spatial and seasonal variation of disinfection by-products in the drinking water of Istanbul was attributed of illegal wastewater discharges to water supplies of Istanbul city.

Keywords: disinfection byproducts, drinking water, trihalomethanes, haloacetic acids, seasonal variation

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Authors: M. P. Tripathi, Priti Tiwari

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Soil and Water Assessment Tool (SWAT) is a distributed parameter continuous time model and was tested on daily and fortnightly basis for a small agricultural watershed (Dhangaon) of Chhattisgarh state in India. The SWAT model recently interfaced with ArcGIS and called as ArcSWAT. The watershed and sub-watershed boundaries, drainage networks, slope and texture maps were generated in the environment of ArcGIS of ArcSWAT. Supervised classification method was used for land use/cover classification from satellite imageries of the years 2009 and 2012. Manning's roughness coefficient 'n' for overland flow and channel flow and Fraction of Field Capacity (FFC) were calibrated for monsoon season of the years 2009 and 2010. The model was validated on a daily basis for the years 2011 and 2012 by using the observed daily rainfall and temperature data. Calibration and validation results revealed that the model was predicting the daily surface runoff and sediment yield satisfactorily. Sensitivity analysis showed that the annual sediment yield was inversely proportional to the overland and channel 'n' values whereas; annual runoff and sediment yields were directly proportional to the FFC. The model was also tested (calibrated and validated) for the fortnightly runoff and sediment yield for the year 2009-10 and 2011-12, respectively. Simulated values of fortnightly runoff and sediment yield for the calibration and validation years compared well with their observed counterparts. The calibration and validation results revealed that the ArcSWAT model could be used for identification of critical sub-watershed and for developing management scenarios for the Dhangaon watershed. Further, the model should be tested for simulating the surface runoff and sediment yield using generated rainfall and temperature before applying it for developing the management scenario for the critical or priority sub-watersheds.

Keywords: watershed, hydrologic and water quality, ArcSWAT model, remote sensing, GIS, runoff and sediment yield

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

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Authors: Mireya Mateo Gomez

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The purpose of this study was to examine the perceptions first-generation Mexican origin mothers living in San Diego have on postpartum depression (PPD), with a special focus on social influences and cultural beliefs towards those meanings. This study also aimed to examine possible PPD help-seeking behaviors that first-generation Mexican origin mothers can perform. The Health Belief Model (HBM) and Social Ecological Model (SEM) were the guiding theoretical frameworks for this study. Data for this study were collected from three focus groups, four in-depth interviews, and the distribution of an acculturation survey (ARSMA II). There were a total of 15 participants, in which participant’s mean age was 45, and the mean age migrated to the United States being 22. Most participants identified as being married, born in Southern or Western Mexico, and with a strong Mexican identity in relation to the ARSMA survey. Participants identified four salient PPD perceptions corresponding to the interpersonal level of SEM. These four main perceptions were: 1) PPD affecting the identity of motherhood; 2) PPD being a natural part of a mother’s experience but mitigated by networks; 3) PPD being a U.S. phenomenon due to family and community breakdown; and 4) natural remedies as a preferred PPD treatment. In regard to themes relating to help seeking behaviors, participants identified seven being: 1) seeking help from immediate family members; 2) practicing home remedies; 3) seeking help from a medical professional; 4) obtaining help from a clinic or organization; 5) seeking help from God; 6) participating in PPD support groups; and 7) talking to a friend. It was evident in this study that postpartum depression is not a well discussed topic within the Mexican immigrant population. In relation to the role culture and social influences have on PPD perceptions, most participants shared hearing or learning about PPD from their family members or friends. Participants also stated seeking help from family members if diagnosed with PPD and seeking out home remedies. This study as well provides suggestions to increase the awareness of PPD among the Mexican immigrant community.

Keywords: cultural beliefs, health belief model, Mexican origin mothers, perceptions, postpartum depression social ecological model

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Authors: Montree Bunruanses, Preecha Yupapin

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In this work, the quantum material called Amrita (elixir) is made from top-down gold into nanometer particles by fusing 99% gold with a laser and mixing it with drinking water using the atmospheric water (AWG) production system, which is made of water with air. The high energy laser power destroyed the four natural force bindings from gravity-weak-electromagnetic and strong coupling forces, where finally it was the purified Bose-Einstein condensate (BEC) states. With this method, gold atoms in the form of spherical single crystals with a diameter of 30-50 nanometers are obtained and used. They were modulated (activated) with a frequency generator into various matrix structures mixed with AWG water to be used in the upstream conversion (quantum reversible) process, which can be applied on humans both internally or externally by drinking or applying on the treated surfaces. Doing both space (body) and time (mind) will go back to the origin and start again from the coupling of space-time on both sides of time at fusion (strong coupling force) and push out (Big Bang) at the equilibrium point (singularity) occurs as strings and DNA with neutrinos as coupling energy. There is no distortion (purification), which is the point where time and space have not yet been determined, and there is infinite energy. Therefore, the upstream conversion is performed. It is reforming DNA to make it be purified. The use of Amrita is a method used for people who cannot meditate (quantum meditation). Various cases were applied, where the results show that the Amrita can make the body and the mind return to their pure origins and begin the downstream process with the Big Bang movement, quantum communication in all dimensions, DNA reformation, frequency filtering, crystal body forming, broadband quantum communication networks, black hole forming, quantum consciousness, body and mind healing, etc.

Keywords: quantum materials, quantum meditation, quantum reversible, Bose-Einstein condensate

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Authors: Jessica Achebe, Susan Tighe

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The recent Canadian infrastructure report card reveals the unhealthy state of municipal infrastructure intensified challenged faced by municipalities to maintain adequate infrastructure performance thresholds and meet user’s required service levels. For a road agency, huge funding gap issue is inflated by growing concerns of the environmental repercussion of road construction, operation and maintenance activities. As the reduction of material consumption and greenhouse gas emission when maintain and rehabilitating road networks can achieve added benefits including improved life cycle performance of pavements, reduced climate change impacts and human health effect due to less air pollution, improved productivity due to optimal allocation of resources and reduced road user cost. Incorporating environmental sustainability measure into pavement management is solution widely cited and studied. However measuring the environmental performance of road network is still a far-fetched practice in road network management, more so an ostensive agency-wide environmental sustainability or sustainable maintenance specifications is missing. To address this challenge, this present research focuses on the environmental sustainability performance of network-level pavement management. The ultimate goal is to develop a framework to incorporate environmental sustainability in pavement management systems for network-level maintenance programming. In order to achieve this goal, this study reviewed previous studies that employed environmental performance measures, as well as the suitability of environmental performance indicators for the evaluation of the sustainability of network-level pavement maintenance strategies. Through an industry practice survey, this paper provides a brief forward regarding the pavement manager motivations and barriers to making more sustainable decisions, and data needed to support the network-level environmental sustainability. The trends in network-level sustainable pavement management are also presented, existing gaps are highlighted, and ideas are proposed for sustainable network-level pavement management.

Keywords: pavement management, sustainability, network-level evaluation, environment measures

Procedia PDF Downloads 191

Authors: Elif D. Oguz Erkal, David Krackhardt, Erica Cochran-Hameen

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Even though social network analysis (SNA) is an abundantly studied concept for many organizations and industries, a clear SNA approach to the project teams has not yet been adopted by the construction industry. The main challenges for performing SNA in construction and the apparent reason for this gap is the unique and complex structure of each construction project, the comparatively high circulation of project team members/contributing parties and the variety of authentic problems for each project. Additionally, there are stakeholders from a variety of professional backgrounds collaborating in a high-stress environment fueled by time and cost constraints. Within this case study on Project RE, a design & build project performed at the Urban Design Build Studio of Carnegie Mellon University, social network analysis of the project design team will be performed with the main goal of applying social network theory to construction project environments. The research objective is to determine a correlation between the network of how individuals relate to each other on one’s perception of their own professional strengths and weaknesses and the communication patterns within the team and the group dynamics. Data is collected through a survey performed over four rounds conducted monthly, detailed follow-up interviews and constant observations to assess the natural alteration in the network with the effect of time. The data collected is processed by the means of network analytics and in the light of the qualitative data collected with observations and individual interviews. This paper presents the full ethnography of this construction design team of fourteen architecture students based on an elaborate social network data analysis over time. This study is expected to be used as an initial step to perform a refined, targeted and large-scale social network data collection in construction projects in order to deduce the impacts of social networks on project performance and suggest better collaboration structures for construction project teams henceforth.

Keywords: construction design teams, construction project management, social network analysis, team collaboration, network analytics

Procedia PDF Downloads 178

Authors: Monique Du Plessis, Anina Coetzee, Colleen L. Seymour, Claire N. Spottiswoode

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Artificial nectar feeders are used to attract nectarivorous birds to gardens and are increasing in popularity. The costs and benefits of these feeders remain controversial, however. Nectar feeders may have positive effects by attracting nectarivorous birds towards suburbia, facilitating their urban adaptation, and supplementing bird diets when floral resources are scarce. However, this may come at the cost of luring them away from the plants they pollinate in neighboring indigenous vegetation. This study investigated the effect of nectar feeders on an African pollinator-plant mutualism. Given that birds are important pollinators to many fynbos plant species, this study was conducted in gardens and natural vegetation along the urban edge of the Cape Peninsula. Feeding experiments were carried out to compare relative bird abundance and local distribution patterns for nectarivorous birds (i.e., sunbirds and sugarbirds) between feeder and control treatments. Resultant changes in their visitation rates to Erica flowers in the natural vegetation were tested by inspection of their anther ring status. Nectar feeders attracted higher densities of nectarivores to gardens relative to natural vegetation and decreased their densities in the neighboring fynbos, even when floral abundance in the neighboring vegetation was high. The consequent changes to their distribution patterns and foraging behavior decreased their visitation to at least Erica plukenetii flowers (but not to Erica abietina). This study provides evidence that nectar feeders may have positive effects for birds themselves by reducing their urban sensitivity but also highlights the unintended negative effects feeders may have on the surrounding fynbos ecosystem. Given that nectar feeders appear to compete with the flowers of Erica plukenetii, and perhaps those of other Erica species, artificial feeding may inadvertently threaten bird-plant pollination networks.

Keywords: avian nectarivores, bird feeders, bird pollination, indirect effects in human-wildlife interactions, sugar water feeders, supplementary feeding

Procedia PDF Downloads 123

Authors: Pascale Brasseur, Binu Gurung, Nicholas Halfpenny, James Eaton

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Development of minimally invasive treatments in recent years provides a potential alternative to invasive surgical interventions which are of limited value to patients with spinal metastases due to short life expectancy. A systematic review was conducted to explore the efficacy and safety of radiofrequency ablation (RFA), a minimally invasive treatment in patients with spinal metastases. EMBASE, Medline and CENTRAL were searched from database inception to March 2017 for randomised controlled trials (RCTs) and non-randomised studies. Conference proceedings for ASCO and ESMO published in 2015 and 2016 were also searched. Fourteen studies were included: three prospective interventional studies, four prospective case series and seven retrospective case series. No RCTs or studies comparing RFA with another treatment were identified. RFA was followed by cement augmentation in all patients in seven studies and some patients (40-96%) in the remaining seven studies. Efficacy was assessed as pain relief in 13/14 studies with the use of a numerical rating scale (NRS) or a visual analogue scale (VAS) at various time points. Ten of the 13 studies reported a significant decrease in pain outcome, post-RFA compared to baseline. NRS scores improved significantly at 1 week (5.9 to 3.5, p < 0.0001; 8 to 4.3, p < 0.02 and 8 to 3.9, p < 0.0001) and this improvement was maintained at 1 month post-RFA compared to baseline (5.9 to 2.6, p < 0.0001; 8 to 2.9, p < 0.0003; 8 to 2.9, p < 0.0001). Similarly, VAS scores decreased significantly at 1 week (7.5 to 2.7, p=0.00005; 7.51 to 1.73, p < 0.0001; 7.82 to 2.82, p < 0.001) and this pattern was maintained at 1 month post-RFA compared to baseline (7.51 to 2.25, p < 0.0001; 7.82 to 3.3; p < 0.001). A significant pain relief was achieved regardless of whether patients had cement augmentation in two studies assessing the impact of RFA with or without cement augmentation on VAS pain scores. In these two studies, a significant decrease in pain scores was reported for patients receiving RFA alone and RFA+cement at 1 week (4.3 to 1.7. p=0.0004 and 6.6 to 1.7, p=0.003 respectively) and 15-36 months (7.9 to 4, p=0.008 and 7.6 to 3.5, p=0.005 respectively) after therapy. Few minor complications were reported and these included neural damage, radicular pain, vertebroplasty leakage and lower limb pain/numbness. In conclusion, the efficacy and safety of RFA were consistently positive between prospective and retrospective studies with reductions in pain and few procedural complications. However, the lack of control groups in the identified studies indicates the possibility of selection bias inherent in single arm studies. Controlled trials exploring efficacy and safety of RFA in patients with spinal metastases are warranted to provide robust evidence. The identified studies provide an initial foundation for such future trials.

Keywords: pain relief, radiofrequency ablation, spinal metastases, systematic review

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Authors: A. Terfous, Y. Liu, A. Ghenaim, P. A. Garambois

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With increasing urbanization worldwide, it is crucial to sustainably manage sediment flows in urban networks and especially in stormwater detention basins. One key aspect is to propose optimized designs for detention tanks in order to best reduce flood peak flows and in the meantime settle particles. It is, therefore, necessary to understand complex flows patterns and sediment deposition conditions in stormwater detention basins. The aim of this paper is to study flow structure and particle deposition pattern for a given tank geometry in view to control and maximize sediment deposition. Both numerical simulation and experimental works were done to investigate the flow and sediment distribution in a storm tank with a cavity. As it can be indicated, the settle distribution of the particle in a rectangular tank is mainly determined by the flow patterns and the bed shear stress. The flow patterns in a rectangular tank differ with different geometry, entrance flow rate and the water depth. With the changing of flow patterns, the bed shear stress will change respectively, which also play an influence on the particle settling. The accumulation of the particle in the bed changes the conditions at the bottom, which is ignored in the investigations, however it worth much more attention, the influence of the accumulation of the particle on the sedimentation should be important. The approach presented here is based on the resolution of the Reynolds averaged Navier-Stokes equations to account for turbulent effects and also a passive particle transport model. An analysis of particle deposition conditions is presented in this paper in terms of flow velocities and turbulence patterns. Then sediment deposition zones are presented thanks to the modeling with particle tracking method. It is shown that two recirculation zones seem to significantly influence sediment deposition. Due to the possible overestimation of particle trap efficiency with standard wall functions and stick conditions, further investigations seem required for basal boundary conditions based on turbulent kinetic energy and shear stress. These observations are confirmed by experimental investigations processed in the laboratory.

Keywords: storm sewers, sediment deposition, numerical simulation, experimental investigation

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Authors: Van Trieu, Shouhuai Xu, Yusheng Feng

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Tracking attack trajectories can be difficult, with limited information about the nature of the attack. Even more difficult as attack information is collected by Intrusion Detection Systems (IDSs) due to the current IDSs having some limitations in identifying malicious and anomalous traffic. Moreover, IDSs only point out the suspicious events but do not show how the events relate to each other or which event possibly cause the other event to happen. Because of this, it is important to investigate new methods capable of performing the tracking of attack trajectories task quickly with less attack information and dependency on IDSs, in order to prioritize actions during incident responses. This paper proposes a two-level graph causality framework for tracking attack trajectories in internet networks by leveraging observable malicious behaviors to detect what is the most probable attack events that can cause another event to occur in the system. Technically, given the time series of malicious events, the framework extracts events with useful features, such as attack time and port number, to apply to the conditional independent tests to detect the relationship between attack events. Using the academic datasets collected by IDSs, experimental results show that the framework can quickly detect the causal pairs that offer meaningful insights into the nature of the internet network, given only reasonable restrictions on network size and structure. Without the framework’s guidance, these insights would not be able to discover by the existing tools, such as IDSs. It would cost expert human analysts a significant time if possible. The computational results from the proposed two-level graph network model reveal the obvious pattern and trends. In fact, more than 85% of causal pairs have the average time difference between the causal and effect events in both computed and observed data within 5 minutes. This result can be used as a preventive measure against future attacks. Although the forecast may be short, from 0.24 seconds to 5 minutes, it is long enough to be used to design a prevention protocol to block those attacks.

Keywords: causality, multilevel graph, cyber-attacks, prediction

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Authors: Stefan Papastefanou

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Artificial intelligence (AI) is an interdisciplinary field of computer science with the aim of creating intelligent machine behavior. Early approaches to AI have been configured to operate in very constrained environments where the behavior of the AI system was previously determined by formal rules. Knowledge was presented as a set of rules that allowed the AI system to determine the results for specific problems; as a structure of if-else rules that could be traversed to find a solution to a particular problem or question. However, such rule-based systems typically have not been able to generalize beyond the knowledge provided. All over the world and especially in IT-heavy industries such as the United States, the European Union, Singapore, and China, machine learning has developed to be an immense asset, and its applications are becoming more and more significant. It has to be examined how such products of machine learning models can and should be protected by IP law and for the purpose of this paper patent law specifically, since it is the IP law regime closest to technical inventions and computing methods in technical applications. Genetic breeding models are currently less popular than recursive neural network method and deep learning, but this approach can be more easily described by referring to the evolution of natural organisms, and with increasing computational power; the genetic breeding method as a subset of the evolutionary algorithms models is expected to be regaining popularity. The research method focuses on patentability (according to the world’s most significant patent law regimes such as China, Singapore, the European Union, and the United States) of AI inventions and machine learning. Questions of the technical nature of the problem to be solved, the inventive step as such, and the question of the state of the art and the associated obviousness of the solution arise in the current patenting processes. Most importantly, and the key focus of this paper is the problem of patenting inventions that themselves are developed through machine learning. The inventor of a patent application must be a natural person or a group of persons according to the current legal situation in most patent law regimes. In order to be considered an 'inventor', a person must actually have developed part of the inventive concept. The mere application of machine learning or an AI algorithm to a particular problem should not be construed as the algorithm that contributes to a part of the inventive concept. However, when machine learning or the AI algorithm has contributed to a part of the inventive concept, there is currently a lack of clarity regarding the ownership of artificially created inventions. Since not only all European patent law regimes but also the Chinese and Singaporean patent law approaches include identical terms, this paper ultimately offers a comparative analysis of the most relevant patent law regimes.

Keywords: algorithms, inventor, genetic breeding models, machine learning, patentability

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Authors: E. Nakamachi, K. Matsumoto, K. Yamamoto, Y. Morita, H. Sakamoto

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In recently, electromagnetic and mechanical stimulations have been recognized as the effective extracellular environment stimulation technique to enhance the defected peripheral nerve tissue regeneration. In this study, we developed a new hybrid bioreactor by adopting 50 Hz uniform alternative current (AC) magnetic stimulation and 4% strain mechanical stimulation. The guide tube for nerve regeneration is mesh structured tube made of biodegradable polymer, such as polylatic acid (PLA). However, when neural damage is large, there is a possibility that peripheral nerve undergoes necrosis. So it is quite important to accelerate the nerve tissue regeneration by achieving enhancement of nerve axonal extension rate. Therefore, we try to design and fabricate the system that can simultaneously load the uniform AC magnetic field stimulation and the stretch stimulation to cells for enhancement of nerve axonal extension. Next, we evaluated systems performance and the effectiveness of each stimulation for rat adrenal pheochromocytoma cells (PC12). First, we designed and fabricated the uniform AC magnetic field system and the stretch stimulation system. For the AC magnetic stimulation system, we focused on the use of pole piece structure to carry out in-situ microscopic observation. We designed an optimum pole piece structure using the magnetic field finite element analyses and the response surface methodology. We fabricated the uniform AC magnetic field stimulation system as a bio-reactor by adopting analytically determined design specifications. We measured magnetic flux density that is generated by the uniform AC magnetic field stimulation system. We confirmed that measurement values show good agreement with analytical results, where the uniform magnetic field was observed. Second, we fabricated the cyclic stretch stimulation device under the conditions of particular strains, where the chamber was made of polyoxymethylene (POM). We measured strains in the PC12 cell culture region to confirm the uniform strain. We found slightly different values from the target strain. Finally, we concluded that these differences were allowable in this mechanical stimulation system. We evaluated the effectiveness of each stimulation to enhance the nerve axonal extension using PC12. We confirmed that the average axonal extension length of PC12 under the uniform AC magnetic stimulation was increased by 16 % at 96 h in our bio-reactor. We could not confirm that the axonal extension enhancement under the stretch stimulation condition, where we found the exfoliating of cells. Further, the hybrid stimulation enhanced the axonal extension. Because the magnetic stimulation inhibits the exfoliating of cells. Finally, we concluded that the enhancement of PC12 axonal extension is due to the magnetic stimulation rather than the mechanical stimulation. Finally, we confirmed that the effectiveness of the uniform AC magnetic field stimulation for the nerve axonal extension using PC12 cells.

Keywords: nerve cell PC12, axonal extension, nerve regeneration, electromagnetic-mechanical stimulation, bioreactor

Procedia PDF Downloads 237

Authors: Assem Abdel Hamed Mousa

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The Internet of Things probably already influences your life. And if it doesn’t, it soon will, say computer scientists; Ubiquitous computing names the third wave in computing, just now beginning. First were mainframes, each shared by lots of people. Now we are in the personal computing era, person and machine staring uneasily at each other across the desktop. Next comes ubiquitous computing, or the age of calm technology, when technology recedes into the background of our lives. Alan Kay of Apple calls this "Third Paradigm" computing. Ubiquitous computing is essentially the term for human interaction with computers in virtually everything. Ubiquitous computing is roughly the opposite of virtual reality. Where virtual reality puts people inside a computer-generated world, ubiquitous computing forces the computer to live out here in the world with people. Virtual reality is primarily a horse power problem; ubiquitous computing is a very difficult integration of human factors, computer science, engineering, and social sciences. The approach: Activate the world. Provide hundreds of wireless computing devices per person per office, of all scales (from 1" displays to wall sized). This has required new work in operating systems, user interfaces, networks, wireless, displays, and many other areas. We call our work "ubiquitous computing". This is different from PDA's, dynabooks, or information at your fingertips. It is invisible; everywhere computing that does not live on a personal device of any sort, but is in the woodwork everywhere. The initial incarnation of ubiquitous computing was in the form of "tabs", "pads", and "boards" built at Xerox PARC, 1988-1994. Several papers describe this work, and there are web pages for the Tabs and for the Boards (which are a commercial product now): Ubiquitous computing will drastically reduce the cost of digital devices and tasks for the average consumer. With labor intensive components such as processors and hard drives stored in the remote data centers powering the cloud , and with pooled resources giving individual consumers the benefits of economies of scale, monthly fees similar to a cable bill for services that feed into a consumer’s phone.

Keywords: internet, cloud computing, ubiquitous computing, big data

Procedia PDF Downloads 362