Search results for: transdermal drug delivery system

Authors: M. N. A. Azman, M. S. S. Ahamad

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The Construction Industry Development Board of Malaysia has been actively promoting the use of precast manufacturing in the local construction industry over the last decade. In an era of rapid technological changes, precast manufacturing significantly contributes to improving construction activities and ensuring sustainable economic growth. Current studies on the location decision of precast manufacturing plants aimed to enhanced local economic development are scarce. To address this gap, the present research establishes a new set of spatial criteria, such as attribute maps and preference weights, derived from a survey of local industry decision makers. These data represent the input parameters for the MCE-GIS site selection model, for which the weighted linear combination method is used. Verification tests on the model were conducted to determine the potential precast manufacturing sites in the state of Penang, Malaysia. The tests yield a predicted area of 12.87 acres located within a designated industrial zone. Although, the model is developed specifically for precast manufacturing plant but nevertheless it can be employed to other types of industries by following the methodology and guidelines proposed in the present research.

Keywords: geographical information system, multi criteria evaluation, industrialised building system, civil engineering

Procedia PDF Downloads 270

Authors: Constanza A. Barriga, Rafael Bernardi, Amokrane Berdja, Christian D. Guzman

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Most image restoration methods in astronomy rely upon probabilistic tools that infer the best solution for a deconvolution problem. They achieve good performances when the point spread function (PSF) is spatially invariable in the image plane. However, this latter condition is not always satisfied with real optical systems. PSF angular variations cannot be evaluated directly from the observations, neither be corrected at a pixel resolution. We have developed a method for the restoration of images affected by static and anisotropic aberrations using deep neural networks that can be directly applied to sky images. The network is trained using simulated sky images corresponding to the T-80 telescope optical system, an 80 cm survey imager at Cerro Tololo (Chile), which are synthesized using a Zernike polynomial representation of the optical system. Once trained, the network can be used directly on sky images, outputting a corrected version of the image, which has a constant and known PSF across its field-of-view. The method was tested with the T-80 telescope, achieving better results than with PSF deconvolution techniques. We present the method and results on this telescope.

Keywords: aberrations, deep neural networks, image restoration, variable point spread function, wide field images

Procedia PDF Downloads 120

Authors: África Vicario, Fernando J. Álvarez, Felipe Parralejo, Fernando Aranda

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The irrigation systems of traditional agriculture, such as gravity-fed irrigation, produce a great waste of water because, generally, there is no control over the amount of water supplied in relation to the water needed. The AIRON Project tries to solve this problem by implementing an IoT-based system to sensor the irrigation plots so that the state of the crops and the amount of water used for irrigation can be known remotely. The IoT system consists of a sensor network that measures the humidity of the soil, the weather conditions (temperature, relative humidity, wind and solar radiation) and the irrigation water flow. The communication between this network and a central gateway is conducted by means of long-range wireless communication that depends on the characteristics of the irrigation plot. The main objective of the AIRON project is to deploy an IoT sensor network in two different plots of the irrigation community of Aranjuez in the Spanish region of Madrid. The first plot is 2 km away from the central gateway, so LoRa has been used as the base communication technology. The problem with this plot is the absence of mains electric power, so devices with energy-saving modes have had to be used to maximize the external batteries' use time. An ESP32 SOC board with a LoRa module is employed in this case to gather data from the sensor network and send them to a gateway consisting of a Raspberry Pi with a LoRa hat. The second plot is located 18 km away from the gateway, a range that hampers the use of LoRa technology. In order to establish reliable communication in this case, the long-term evolution (LTE) standard is used, which makes it possible to reach much greater distances by using the cellular network. As mains electric power is available in this plot, a Raspberry Pi has been used instead of the ESP32 board to collect sensor data. All data received from the two plots are stored on a proprietary server located at the irrigation management company's headquarters. The analysis of these data by means of machine learning algorithms that are currently under development should allow a short-term prediction of the irrigation water demand that would significantly reduce the waste of this increasingly valuable natural resource. The major finding of this work is the real possibility of deploying a remote sensing system for irrigated plots by using Commercial-Off-The-Shelf (COTS) devices, easily scalable and adaptable to design requirements such as the distance to the control center or the availability of mains electrical power at the site.

Keywords: internet of things, irrigation water control, LoRa, LTE, smart farming

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Authors: Chiyoung Kim, Jaegeol Yim

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Bus service is often either main or the only public transportation available in cities. In metropolitan areas, both subways and buses are available whereas in the medium sized cities buses are usually the only type of public transportation available. Bus Information Systems (BIS) provide current locations of running buses, efficient routes to travel from one place to another, points of interests around a given bus stop, a series of bus stops consisting of a given bus route, and so on to users. Thanks to BIS, people do not have to waste time at a bus stop waiting for a bus because BIS provides exact information on bus arrival times at a given bus stop. Therefore, BIS does a lot to promote the use of buses contributing to pollution reduction and saving natural resources. BIS implementation costs a huge amount of budget as it requires a lot of special equipment such as road side equipment, automatic vehicle identification and location systems, trunked radio systems, and so on. Consequently, medium and small sized cities with a low budget cannot afford to install BIS even though people in these cities need BIS service more desperately than people in metropolitan areas. It is possible to provide BIS service at virtually no cost under the assumption that everybody carries a smartphone and there is at least one person with a smartphone in a running bus who is willing to reveal his/her location details while he/she is sitting in a bus. This assumption is usually true in the real world. The smartphone penetration rate is greater than 100% in the developed countries and there is no reason for a bus driver to refuse to reveal his/her location details while driving. We have developed a mobile app that periodically reads values of sensors including GPS and sends GPS data to the server when the bus stops or when the elapsed time from the last send attempt is greater than a threshold. This app detects the bus stop state by investigating the sensor values. The server that receives GPS data from this app has also been developed. Under the assumption that the current locations of all running buses collected by the mobile app are recorded in a database, we have also developed a web site that provides all kinds of information that most BISs provide to users through the Internet. The development environment is: OS: Windows 7 64bit, IDE: Eclipse Luna 4.4.1, Spring IDE 3.7.0, Database: MySQL 5.1.7, Web Server: Apache Tomcat 7.0, Programming Language: Java 1.7.0_79. Given a start and a destination bus stop, it finds a shortest path from the start to the destination using the Dijkstra algorithm. Then, it finds a convenient route considering number of transits. For the user interface, we use the Google map. Template classes that are used by the Controller, DAO, Service and Utils classes include BUS, BusStop, BusListInfo, BusStopOrder, RouteResult, WalkingDist, Location, and so on. We are now integrating the mobile app system and the web app system.

Keywords: bus information system, GPS, mobile app, web site

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Authors: Mohammad H. Ruhipour, Mahdi Goharrokhi, Mahsa Ghasemi, Artadokht Ostadsarayi

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In this paper, we are aiming to study the consequences of chlorine gas leak in direct chlorine gas injection compared to using bleach (sodium hypochlorite), studying the negative effects both on the environment and individuals. This study was performed in the cooling towers of a natural fractioning unit of Bandar-e-IMAM petrochemical plant. Considering that chlorine gas is highly toxic and based on the health regulation, its release into the surrounding environment can be very dangerous for people and even fatal for individuals. We studied performing quantitative studies in the worst cases of event incidence. In addition, studying alternative methods with a lower risk was also on the agenda to select the least likely possible option causing an accident. In this paper chlorine gas release consequences have been evaluated by using PHAST software. Reaching to 10 ppm of chlorine gas concentration was basis of hazardous area determination. The results show that the full chlorine gas line rupture scenario in Pasquill category F, were worst case, and many people could be harmed around cooling towers area because of chlorine gas inhalation.

Keywords: chlorine gas, consequence modeling, cooling towers, direct chlorination, risk assessment, system failure

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Authors: Chia-Yu Chang, Yi-Feng Lin

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CO2 capture has attracted significant research attention due to global warming. Among the various CO2 capture methods, membrane technology has proven to be highly efficient in capturing CO2 due to the ease at which this technology can be scaled up, its low energy consumptions, small area requirements and overall environmental friendliness for use by industrial plants. Capturing CO2 is to use a membrane contactor with a combination of water-repellent porous membranes and chemical absorption processes. In a CO2 membrane contactor system, CO2 passes through a hydrophobic porous membrane in the gas phase to contact the amine absorbent in the liquid phase. Consequently, additional CO2 gas is absorbed by amine absorbents. This study examines highly porous Polydimethylsiloxane (PDMS)/Polystyrene (PS) Nanofibrous Membranes and successfully coated onto a macroporous Al2O3 membrane. The performance of these materials in a membrane contactor system for CO2 absorption is also investigated. Compared with pristine PS nanofibrous membranes, the PDMS/PS nanofibrous membranes exhibit greater solvent resistance and mechanical strength, making them more suitable for use in CO2 capture by the membrane contactor. The resulting hydrophobic membrane contactor also demonstrates the potential for large-scale CO2 absorption during post-combustion processes in power plants.

Keywords: CO2 capture, polystyrene, polydimethylsiloxane, superhydrophobic

Procedia PDF Downloads 368

Authors: P. S. Jagadeesh Kumar, Mingmin Pan, Yang Yung, Tracy Lin Huan

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Glaucoma is a group of visual maladies represented by the scheduled optic nerve neuropathy; means to the increasing dwindling in vision ground, resulting in loss of sight. In this paper, a novel support vector machine based retinal therapeutic for glaucoma using machine learning algorithm is conservative. The algorithm has fitting pragmatism; subsequently sustained on correlation clustering mode, it visualizes perfect computations in the multi-dimensional space. Support vector clustering turns out to be comparable to the scale-space advance that investigates the cluster organization by means of a kernel density estimation of the likelihood distribution, where cluster midpoints are idiosyncratic by the neighborhood maxima of the concreteness. The predicted planning has 91% attainment rate on data set deterrent on a consolidation of 500 realistic images of resolute and glaucoma retina; therefore, the computational benefit of depending on the cluster overlapping system pedestal on machine learning algorithm has complete performance in glaucoma therapeutic.

Keywords: machine learning algorithm, correlation clustering mode, cluster overlapping system, glaucoma, kernel density estimation, retinal therapeutic

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Authors: Katarzyna Kamińska

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The main purpose of the work is to present the results of the studies regarding joint physical custody in the Polish legal system. The issues addressed fit into the ongoing process of modernising family law regulations and their adaptation to changing social reality in Poland. The Polish legislator now faces a dilemma: whether to introduce into Polish law a developed substantive or procedural regulation of joint physical custody and then whether it should be considered a legal presumption. Joint physical custody after divorce or separation is theoretically possible in Poland. It can either follow from the court’s independent proposal based on the assessment of the circumstances or from the parenting plan submitted by parents wishing to jointly retain full parental authority. However, joint physical custody does not result directly from the Polish Family and Guardianship Code. Therefore, there is real legal uncertainty in this matter, which leads to different treatment of citizens by the public authorities and courts. Another problem is that joint physical custody is misunderstood by the Polish courts. The main thesis of the work is that joint physical custody does not only mean the system of symmetrical child care (50/50), and the possibility to award joint physical custody will require the courts to carefully weigh the pros and cons of such an arrangement in each individual case.

Keywords: joint physical custody, shared parenting, divorce, separation, parental authority

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Authors: Ammar Alali, Mahmoud Abughaban, William Contreras Otalvora

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Optimizing the drilling process for cost and efficiency requires the optimization of the rate of penetration (ROP). ROP is the measurement of the speed at which the wellbore is created, in units of feet per hour. It is the primary indicator of measuring drilling efficiency. Maximization of the ROP can indicate fast and cost-efficient drilling operations; however, high ROPs may induce unintended events, which may lead to nonproductive time (NPT) and higher net costs. The proposed ROP optimization solution is a hybrid, data-driven system that aims to improve the drilling process, maximize the ROP, and minimize NPT. The system consists of two phases: (1) utilizing existing geological and drilling data to train the model prior, and (2) real-time adjustments of the controllable dynamic drilling parameters [weight on bit (WOB), rotary speed (RPM), and pump flow rate (GPM)] that direct influence on the ROP. During the first phase of the system, geological and historical drilling data are aggregated. After, the top-rated wells, as a function of high instance ROP, are distinguished. Those wells are filtered based on NPT incidents, and a cross-plot is generated for the controllable dynamic drilling parameters per ROP value. Subsequently, the parameter values (WOB, GPM, RPM) are calculated as a conditioned mean based on physical distance, following Inverse Distance Weighting (IDW) interpolation methodology. The first phase is concluded by producing a model of drilling best practices from the offset wells, prioritizing the optimum ROP value. This phase is performed before the commencing of drilling. Starting with the model produced in phase one, the second phase runs an automated drill-off test, delivering live adjustments in real-time. Those adjustments are made by directing the driller to deviate two of the controllable parameters (WOB and RPM) by a small percentage (0-5%), following the Constrained Random Search (CRS) methodology. These minor incremental variations will reveal new drilling conditions, not explored before through offset wells. The data is then consolidated into a heat-map, as a function of ROP. A more optimum ROP performance is identified through the heat-map and amended in the model. The validation process involved the selection of a planned well in an onshore oil field with hundreds of offset wells. The first phase model was built by utilizing the data points from the top-performing historical wells (20 wells). The model allows drillers to enhance decision-making by leveraging existing data and blending it with live data in real-time. An empirical relationship between controllable dynamic parameters and ROP was derived using Artificial Neural Networks (ANN). The adjustments resulted in improved ROP efficiency by over 20%, translating to at least 10% saving in drilling costs. The novelty of the proposed system lays is its ability to integrate historical data, calibrate based geological formations, and run real-time global optimization through CRS. Those factors position the system to work for any newly drilled well in a developing field event.

Keywords: drilling optimization, geological formations, machine learning, rate of penetration

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Authors: Heng Chia Ying, Charmaine Tan Chai Nie, Burra Venkata Durga Kumar

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Process scheduling is the method of process management that determines which process the CPU will proceed with for the next task and how long it takes. Some issues were found in process management, particularly for Priority Scheduling (PS) and Round Robin Scheduling (RR). The proposed recommendations made for IPRRS are to combine the strengths of both into a combining algorithm while they draw on others to compensate for each weakness. A significant improvement on the combining technique of scheduler, Incorporating Priority Round-Robin Scheduler (IPRRS) address an algorithm for both high and low priority task to sustain the indefinite blocking issue faced in the priority scheduling algorithm and minimize the average turnaround time (ATT) and average waiting time (AWT) in RR scheduling algorithm. This paper will delve into the simple rules introduced by IPRRS and enhancements that both PS and RR bring to the execution of processes in the operating system. Furthermore, it incorporates the best aspects of each algorithm to build the optimum algorithm for a certain case in terms of prioritized processes, ATT, and AWT.

Keywords: round Robin scheduling, priority scheduling, indefinite blocking, process management, sustain, turnaround time

Procedia PDF Downloads 117

Authors: Farah Kanani

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Blue Tide Environmental is a company focused on developing a network of used motor oil recycling facilities across the U.S. They initiated the redesign of its recycling plant in Texas, and aimed to establish an updated carbon footprint of re-refined used motor oils compared to an equivalent product derived from virgin stock that is not re-refined. The aim was to quantify emissions savings of a circular alternative to conventional end-of-life combustion of used motor oil (UMO). To do so, they mandated an ISO-compliant carbon footprint, utilizing complex models requiring geographical and temporal accuracy to accommodate the U.S. refinery market. The quantification of linear and circular flows, proxies for fuel substitution and system expansion for multi-product outputs were all critical methodological choices and were tested through sensitivity analyses. The re-refined system consisted of continuous recycling of UMO and thus, end-of-life is considered non-existent. The unique perspective to this topic will be from a life cycle i.e. holistic one and essentially demonstrate using this example of how a cradle-to-cradle model can be used to quantify a comparative carbon footprint. The intended audience is lubricant manufacturers as the consumers, motor oil industry professionals and other industry members interested in performing a cradle-to-cradle modeling.

Keywords: circularity, used motor oil, re-refining, systems expansion

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Authors: Sirilak Areerachakul

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Water quality has initiated serious management efforts in many countries. Artificial Neural Network (ANN) models are developed as forecasting tools in predicting water quality trend based on historical data. This study endeavors to automatically classify water quality. The water quality classes are evaluated using 6 factor indices. These factors are pH value (pH), Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Nitrate Nitrogen (NO3N), Ammonia Nitrogen (NH3N) and Total Coliform (T-Coliform). The methodology involves applying data mining techniques using multilayer perceptron (MLP) neural network models. The data consisted of 11 sites of Saen Saep canal in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage Bangkok Metropolitan Administration during 2007-2011. The results of multilayer perceptron neural network exhibit a high accuracy multilayer perception rate at 94.23% in classifying the water quality of Saen Saep canal in Bangkok. Subsequently, this encouraging result could be combined with GIS data improves the classification accuracy significantly.

Keywords: artificial neural network, geographic information system, water quality, computer science

Procedia PDF Downloads 324

Authors: Mona Ghafouri-Azar, Sara Diamond, Jeremy Bowes, Grace Yuan, Aimee Burnett, Michelle Wyndham-West, Sara Wagner, Anand Pariyarath

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Transportation is the fastest growing source of greenhouse gas emissions worldwide. In Canada, it is responsible for 23% of total CO2emissions from fuel combustion, and emissions from the transportation sector are the second largest source of emissions after the oil and gas sector. Currently, most Canadian public transportation systems rely on buses that operateon fossil fuels.Canada is currently investing billions of dollars to replacediesel buses with electric busesas this isperceived to have a significant impact on climate mitigation. This paper focuses on the possible impacts of zero emission buses (ZEB) on sustainable development, considering three dimensions of sustainability; environmental quality, economic growth, and social development.A sustainable transportation system is one that is safe, affordable, accessible, efficient, and resilient and that contributes minimal emissions of carbon and other pollutants.To enable implementation of these goals, relevant indicators were selected and defined that measure progress towards a sustainable transportation system. These were drawn from Canadian and international examples. Studies compare different European cities in terms of development, sustainability, and infrastructures, by using transport performance indicators. A Normalized Transport Sustainability index measures and compares policies in different urban areas and allows fine-tuning of policies. Analysts use a number ofmethods for sustainable analysis, like cost-benefit analysis (CBA) toassess economic benefit, life-cycle assessment (LCA) to assess social, economic, and environment factors and goals, and multi-criteria decision making (MCDM) analysis which can comparediffering stakeholder preferences.A multi criteria decision making approach is an appropriate methodology to plan and evaluate sustainable transit development and to provide insights and meaningful information for decision makers and transit agencies. It is essential to develop a system thataggregates specific discrete indices to assess the sustainability of transportation systems.Theseprioritize indicators appropriate for the differentCanadian transit system agencies and theirpreferences and requirements. This studywill develop an integrating index that alliesexistingdiscrete indexes to supporta reliable comparison between the current transportation system (diesel buses) and the new ZEB system emerging in Canada. As a first step, theindexes for each category are selected, and the index matrix constructed. Second, the selected indicators arenormalized to remove anyinconsistency between them. Next, the normalized matrix isweighted based on the relative importance of each index to the main domains of sustainability using the analytical hierarchy process (AHP) method. This is accomplished through expert judgement around the relative importance of different attributes with respect to the goals through apairwise comparison matrix. The considerationof multiple environmental, economic, and social factors (including equity and health) is integrated intoa sustainable transit planning index (STPI) which supportsrealistic ZEB implementation in Canada and beyond and is useful to different stakeholders, agencies, and ministries.

Keywords: zero emission buses, sustainability, sustainable transit, transportation, analytical hierarchy process, environment, economy, social

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Authors: Saleh Alzahrani, Halim Boussabaine

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The majority of Public Private Partnership (PPP) are developed based on the rationale that the design, construction, operation, and financing of a public project is to be awarded to a private party within a single contractual framework. PPP project risks normally include the development and construction of a new asset as well as its operation for decades. Undoubtedly the most serious consequences of risks during the construction period are price and time overruns. These events are amongst the most broadly used scenarios in value for money analysis risks. The sources of risk change over the life cycle of a PPP project. In traditional procurement, the public sector normally has to cover all price distress from these risks. At least there is plenty evidence to suggest that price distress is a norm in some of the projects that are delivered under traditional procurement. This paper will find the impact of construction risk factors into actual construction price into PPP projects. The paper will present a brief literature review on PPP risk pricing strategies, and then using system dynamics (SD) to analyses of the risks associated with the estimated project price. Based on the finding from these analyses a risk pricing association model is presented and discussed. The paper concludes with thoughts for future research.

Keywords: Public Private Partnership (PPP), Risk, Risk Pricing, System Dynamics (SD), construction price

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Authors: Carlos Gonzalez

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This paper describes a system to optimize the use of the internet by clients requiring downloading of videos at peak hours. The system consists of a web server belonging to a provider of video contents, a provider of internet communications and a software application running on a client’s computer. The client using the application software will communicate to the video provider a list of the client’s future video demands. The video provider calculates which videos are going to be more in demand for download in the immediate future, and proceeds to request the internet provider the most optimal hours to do the downloading. The times of the downloading will be sent to the application software, which will use the information of pre-established hours negotiated between the video provider and the internet provider to download those videos. The videos will be saved in a special protected section of the user’s hard disk, which will only be accessed by the application software in the client’s computer. When the client is ready to see a video, the application will search the list of current existent videos in the area of the hard disk; if it does exist, it will use this video directly without the need for internet access. We found that the best way to optimize the download traffic of videos is by negotiation between the internet communication provider and the video content provider.

Keywords: internet optimization, video download, future demands, secure storage

Procedia PDF Downloads 123

Authors: Alaa El-Din Rezk

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In Egypt, management of crops still away from what is being used today by utilizing the advances of mechanical design capabilities, sensing and electronics technology. These technologies have been introduced in many places and recorm, for Straight Path, Curved Path, Sine Wave ded high accuracy in different field operations. So, an autonomous robotic platform based on machine vision has been developed and constructed to be implemented in Egyptian conditions as self-propelled mobile vehicle for carrying tools for inter/intra-row crop management based on different control modules. The experiments were carried out at plant protection research institute (PPRI) during 2014-2015 to optimize the accuracy of agricultural robotic platform control using machine vision in term of the autonomous navigation and performance of the robot’s guidance system. Results showed that the robotic platform' guidance system with machine vision was able to adequately distinguish the path and resisted image noise and did better than human operators for getting less lateral offset error. The average error of autonomous was 2.75, 19.33, 21.22, 34.18, and 16.69 mm. while the human operator was 32.70, 4.85, 7.85, 38.35 and 14.75 mm Path, Offset Discontinuity and Angle Discontinuity respectively.

Keywords: autonomous robotic, Hough transform, image processing, machine vision

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Authors: Kung-Jen Tu, Danny Vernatha

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To assist individual departments within universities in their energy management tasks, this study explores the application of Building Information Modeling in establishing the ‘BIM based Energy Management Support System’ (BIM-EMSS). The BIM-EMSS consists of six components: (1) sensors installed for each occupant and each equipment, (2) electricity sub-meters (constantly logging lighting, HVAC, and socket electricity consumptions of each room), (3) BIM models of all rooms within individual departments’ facilities, (4) data warehouse (for storing occupancy status and logged electricity consumption data), (5) building energy management system that provides energy managers with various energy management functions, and (6) energy simulation tool (such as eQuest) that generates real time 'standard energy consumptions' data against which 'actual energy consumptions' data are compared and energy efficiency evaluated. Through the building energy management system, the energy manager is able to (a) have 3D visualization (BIM model) of each room, in which the occupancy and equipment status detected by the sensors and the electricity consumptions data logged are displayed constantly; (b) perform real time energy consumption analysis to compare the actual and standard energy consumption profiles of a space; (c) obtain energy consumption anomaly detection warnings on certain rooms so that energy management corrective actions can be further taken (data mining technique is employed to analyze the relation between space occupancy pattern with current space equipment setting to indicate an anomaly, such as when appliances turn on without occupancy); and (d) perform historical energy consumption analysis to review monthly and annually energy consumption profiles and compare them against historical energy profiles. The BIM-EMSS was further implemented in a research lab in the Department of Architecture of NTUST in Taiwan and implementation results presented to illustrate how it can be used to assist individual departments within universities in their energy management tasks.

Keywords: database, electricity sub-meters, energy anomaly detection, sensor

Procedia PDF Downloads 289

Authors: Benlaifa Meriem, Berredjem Hajira, Bouasla Radia, Berredjem Malika, Djebar Med Reda

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Toxoplasmosis is a cosmopolitan infection due to Toxoplasma gondii (T.gondii). It is a significant cause of congenital disease and an important opportunistic pathogen which has become a worldwide increasing problem due to the AIDS epidemic. Current available drugs do not give satisfactory results and often have only a static and several adverse side effects as it is the case of pyrimethamine. So, the need to develop and evaluate new drugs is critical. The purpose of this study is to investigate the in vitro and in vivo effects of the new chiral N-acylsulfonamide bis-oxazolidin-2-ones on T.gondii. In this study, anti-T.gondii RH strain activities, of two new chiral N-acylsulfonamide bis-oxazolidin-2-ones were evaluated in vitro, using a MRC-5 fibroblast tissue cultures to determine the concentration that inhibit parasite multiplication by 50% (IC50) of each drug and in vivo, by PCR detection of the tachyzoites in mice ascites after new molecules treatment, using the 35-fold repetitive B1 gene of T.gondii. The in vitro results demonstrated that the treatment with the tested molecules decreased the amount of tachyzoites in cell culture in a dose-dependent manner. The inhibition was complete for concentrations over 4 mg/ml. The IC50 of Mol 1 and Mol 2 were 1.5 and 3 mg/ml, respectively, and were quite similar to the control one (2 mg/ml). The Mol 1 was highly active against T.gondii in cell cultures than Mol 2; these results were similar to those of sulfadiazine-treated group (p < 0.05). Toxoplasma-specific DNA was demonstrated in all ascites samples from infected mice of the different tested groups. Mol 1 showed better effect than Mol 2, but it did not completely inhibit the parasite proliferation. The intensity of amplification products increased when the treatment started late after infection. These findings suggest continuous parasite replication despite the treatment. In conclusion, our results showed a promising treatment effect of the tested molecules and suggest that in vitro, the Mol 1, and Mol 2 have a dose-dependent effect and a high cytotoxicity on the studied cells. The present study revealed that concentration and duration of tested molecules treatment are major factors that influence the course of Toxoplasma infection in infected mice.

Keywords: cytotoxicity, PCR, sulfonamide, Toxoplasma gondii

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Authors: Paolo Grasso, Sai Kalyan Yelike, Federico Benzi, Mathieu Le Cam

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The cabin air quality (CAQ) in commercial aircraft is of prime interest, especially in the context of the COVID-19 pandemic. Current Environmental Control Systems (ECS) rely on a prescribed fresh airflow per passenger to dilute contaminants. An adaptive ECS strategy is proposed, leveraging air sensing and filtration technologies to ensure a better CAQ. This paper investigates the CAQ level achieved in commercial aircraft’s cabin during various flight scenarios. The modeling and simulation analysis is performed in a Modelica-based environment describing the dynamic behavior of the system. The model includes the following three main systems: cabin, recirculation loop and air-conditioning pack. The cabin model evaluates the thermo-hygrometric conditions and the air quality in the cabin depending on the number of passengers and crew members, the outdoor conditions and the conditions of the air supplied to the cabin. The recirculation loop includes models of the recirculation fan, ordinary and novel filtration technology, mixing chamber and outflow valve. The air-conditioning pack includes models of heat exchangers and turbomachinery needed to condition the hot pressurized air bled from the engine, as well as selected contaminants originated from the outside or bled from the engine. Different ventilation control strategies are modeled and simulated. Currently, a limited understanding of contaminant concentrations in the cabin and the lack of standardized and systematic methods to collect and record data constitute a challenge in establishing a causal relationship between CAQ and passengers' comfort. As a result, contaminants are neither measured nor filtered during flight, and the current sub-optimal way to avoid their accumulation is their dilution with the fresh air flow. However, the use of a prescribed amount of fresh air comes with a cost, making the ECS the most energy-demanding non-propulsive system within an aircraft. In such a context, this study shows that an ECS based on a reduced and adaptive fresh air flow, and relying on air sensing and filtration technologies, provides promising results in terms of CAQ control. The comparative simulation results demonstrate that the proposed adaptive ECS brings substantial improvements to the CAQ in terms of both controlling the asymptotic values of the concentration of the contaminant and in mitigating hazardous scenarios, such as fume events. Original architectures allowing for adaptive control of the inlet air flow rate based on monitored CAQ will change the requirements for filtration systems and redefine the ECS operation.

Keywords: cabin air quality, commercial aircraft, environmental control system, ventilation

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Authors: Frederick N. F. Chou, Nguyen Thi Thuy Linh

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The impact of water shortages has been increasingly severe as a consequence of population growth, urbanization, economic development, and climate change. The need for improvements in reliable water supply systems is urgent with the increasing living standards of regions. In this study, a suitable shortage index capable of multi-aspect description - frequency, magnitude, and duration - is adopted to more accurately describe the characteristics of a shortage situation. The values of the index were determined to cope with the increasing need for reliability. There are four reservoirs in series located on the Be River of the Dong Nai River Basin in Southern Vietnam. The primary purpose of the three upstream reservoirs is hydropower generation while the primary purpose of the fourth is water supply. A compromise between hydropower generation and water supply can be negotiated for these four reservoirs to reduce the severity of water shortages. A generalized water allocation model was applied to simulate the water supply, and hydropower generation of various management alternatives and the system’s reliability was evaluated using the adopted multiple shortage indices. Modifying management policies of water resources using data-based indexes can improve the reliability of water supply.

Keywords: cascade reservoirs, hydropower, shortage index, water supply

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Authors: Natalie Frandsen

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Pursuing post-secondary education is a milestone for many Canadian youths. This transition involves many changes and opportunities for growth. However, this may also be a period where challenges arise. Perhaps not surprisingly, mental health challenges for post-secondary students are common. This poses difficulties for students and instructors. Common mental-health-related symptoms (e.g., low motivation, fatigue, inability to concentrate) can affect academic performance, and instructors may need to provide accommodations for these students without the necessary expertise. ‘Distance education’ has been growing and gaining momentum in Canada for three decades. As a consequence of the COVID-19 pandemic, post-secondary institutions have been required to deliver courses using ‘remote’ methods (i.e., various online delivery modalities). The learning challenges and subsequent academic performance issues experienced by students with mental-health-related disabilities studying online are not well understood. However, we can postulate potential factors drawing from learning theories, the relationship between mental-health-related symptoms and academic performance, and learning design. Identifying barriers and opportunities to academic performance is an essential step in ensuring that students with mental-health-related disabilities are able to achieve their academic goals. Completing post-secondary education provides graduates with more employment opportunities. It is imperative that our post-secondary institutions take a holistic view of learning by providing learning and mental health support while reducing structural barriers. Health-promoting universities and colleges infuse health into their daily operations and academic mandates. Acknowledged in this Charter is the notion that all sectors must take an active role in favour of health, social justice, and equity for all. Drawing from mental health promotion and Universal Design for Learning (UDL) frameworks, relevant adult learning concepts, and critical digital pedagogy, considerations for mental-health-promoting, online learning community development will be summarized. The education sector has the opportunity to create and foster equitable and mental health-promoting learning environments. This is of particular importance during a global pandemic when the mental health of students is being disproportionately impacted.

Keywords: academic performance, community, mental health promotion, online learning

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Authors: Krittiya Pornmai, Sumaeth Chavadej

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The increasing in global energy demand has affected the climate change caused by the generation of greenhouse gases. Therefore, the objective of this work was to investigate a direct production of synthesis gas from a CO₂-containing natural gas by using gliding arc discharge plasma technology. In this research, the effects of steam reforming, combined steam reforming and partial oxidation, and using multistage gliding arc discharge system on the process performance have been discussed. The simulated natural gas used in this study contains 70% methane, 5% ethane, 5% propane, and 20% carbon dioxide. In comparison with different plasma reforming processes (under their optimum conditions), the steam reforming provides the highest H₂ selectivity resulting from the cracking reaction of steam. In addition, the combined steam reforming and partial oxidation process gives a very high CO production implying that the addition of both oxygen and steam can offer the acceptably highest synthesis gas production. The stage number of plasma reactor plays an important role in the improvement of CO₂ conversion. Moreover, 3 stage number of plasma reactor is considered as an optimum stage number for the reforming of CO₂-containing natural gas with steam and partial oxidation in term of providing low energy consumption as compared with other plasma reforming processes.

Keywords: natural gas, reforming process, gliding arc discharge, plasma technology

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Authors: Aoxue Yang, Weili Tian, Yonghe Wu, Haikun Liu

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Brain tumor stem cells (BTSCs) are resistant to therapy and give rise to recurrent tumors. These rare and elusive cells are likely to disseminate during cancer progression, and some may enter dormancy, remaining viable but not increasing. The identification of dormant BTSCs is thus necessary to design effective therapies for glioblastoma (GBM) patients. Little progress has been made in therapeutic treatment of glioblastoma in the last decade despite rapid progress in molecular understanding of brain tumors1. Here we show that the stress hormone glucocorticoid is essential for the maintenance of brain tumor stem cells (BTSCs), which are resistant to conventional therapy. The glucocorticoid receptor (GR) regulates metabolic plasticity and chemoresistance of the dormant BTSC via controlling expression of GPD1 (glycerol-3-phosphate dehydrogenase 1), which is an essential regulator of lipid metabolism in BTSCs. Genomic, lipidomic and cellular analysis confirm that GR/GPD1 regulation is essential for BTSCs metabolic plasticity and survival. We further demonstrate that the GR agonist dexamethasone (DEXA), which is commonly used to control edema in glioblastoma, abolishes the effect of chemotherapy drug temozolomide (TMZ) by upregulating GPD1 and thus promoting tumor cell dormancy in vivo, this provides a mechanistic explanation and thus settle the long-standing debate of usage of steroid in brain tumor patient edema control. Pharmacological inhibition of GR/GPD1 pathway disrupts metabolic plasticity of BTSCs and prolong animal survival, which is superior to standard chemotherapy. Patient case study shows that GR antagonist mifepristone blocks tumor progression and leads to symptomatic improvement. This study identifies an important mechanism regulating cancer stem cell dormancy and provides a new opportunity for glioblastoma treatment.

Keywords: cancer stem cell, dormancy, glioblastoma, glycerol-3-phosphate dehydrogenase 1, glucocorticoid receptor, dexamethasone, RNA-sequencing, phosphoglycerides.

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Authors: Ziaullah, Shah Wahab Ali

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Micro-grid equipped with heterogeneous energy resources present the idea of small scale distributed energy management (DEM). DEM helps in minimizing the transmission and operation costs, power management and peak load demands. Micro-grids are collections of small, independent controllable power-generating units and renewable energy resources. Micro-grids also motivate to enable active customer participation by giving accessibility of real-time information and control to the customer. The capability of fast restoration against faulty situation, integration of renewable energy resources and Information and Communication Technologies (ICT) make micro-grid as an ideal system for distributed power systems. Micro-grids can have a bank of energy storage devices. The energy management system of micro-grid can perform real-time energy forecasting of renewable resources, energy storage elements and controllable loads in making proper short-term scheduling to minimize total operating costs. We present a review of existing micro-grids optimization objectives/goals, constraints, solution approaches and tools used in micro-grids for energy management. Cost-benefit analysis of micro-grid reveals that cooperation among different micro-grids can play a vital role in the reduction of import energy cost and system stability. Cooperative micro-grids energy trading is an approach to electrical distribution energy resources that allows local energy demands more control over the optimization of power resources and uses. Cooperation among different micro-grids brings the interconnectivity and power trading issues. According to the literature, it shows that open area of research is available for cooperative micro-grids energy trading. In this paper, we proposed and formulated the efficient energy management/trading module for interconnected micro-grids. It is believed that this research will open new directions in future for energy trading in cooperative micro-grids/interconnected micro-grids.

Keywords: distributed energy management, information and communication technologies, microgrid, energy management

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Authors: Mahnaz Motamedi, Mohammad Shahbazi, Shahrzad Rahimi-Naghani, Mehrdad Salehi

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Introduction: Identifying sexual health needs, developing appropriate plans, and delivering services to meet those needs is an essential component of health programs for women, men, and children all over the world, especially in poor countries. Main Subject: The aim of this study was to describe the needs of sexual health from the viewpoint of health policymakers in Iran. Methods: A qualitative study using thematic content analysis was designed and conducted. Data gathering was conducted through semi-structured, in-depth interviews with 25 key informants within the healthcare system. Key informants were selected through both purposive and snowball sampling. MAXQUDA software (version 10) was used to facilitate transcription, classification of codes, and conversion of data into meaningful units, by the process of reduction and compression. Results: The analysis of narratives and information categorized sexual health needs into five categories: culturalization of sexual health discourse, sexual health care services, sexual health educational needs, sexual health research needs, and organizational needs. Conclusion: Identifying and explaining sexual health needs is an important factor in determining the priority of sexual health programs and identification of barriers to meet these needs. This can help other policymakers and health planners to develop appropriate programs to promote sexual and reproductive health.

Keywords: sexual health, sexual health needs, policy makers, health system, qualitative study

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

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

Keywords: branding, marketing, technology, tourism product

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Authors: Olena Mayboroda, Angel Gonzalez Benito, Jonathan Sabate Del Rio, Marketa Svobodova, Sandra Julich, Herbert Tomaso, Ciara K. O'Sullivan, Ioanis Katakis

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DNA amplification is required for most molecular diagnostic applications but conventional PCR has disadvantages for field testing. Isothermal amplification techniques are being developed to respond to this problem. One of them is the Recombinase Polymerase Amplification (RPA) that operates at isothermal conditions without sacrificing specificity and sensitivity in easy-to-use formats. In this work RPA was used for the optical detection of solid-phase amplification of the potential biowarfare agent Yersinia pestis. Thiolated forward primers were immobilized on the surface of maleimide-activated microtitre plates for the quantitative detection of synthetic and genomic DNA, with elongation occurring only in the presence of the specific template DNA and solution phase reverse primers. Quantitative detection was achieved via the use of biotinylated reverse primers and post-amplification addition of streptavidin-HRP conjugate. The overall time of amplification and detection was less than 1 hour at a constant temperature of 37oC. Single-stranded and double-stranded DNA sequences were detected achieving detection limits of 4.04*10-13 M and 3.14*10-16 M, respectively. The system demonstrated high specificity with negligible responses to non-specific targets.

Keywords: recombinase polymerase amplification, Yersinia pestis, solid-phase detection, ELONA

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Authors: Lotfollah Rezagholizadeh

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Background and Aim: Diabetes mellitus is related to high mortality and morbidity caused by the early development of atherosclerosis correlated to diabetic macroangiopathy. The endothelium-derived vasodilator, nitric oxide (NO) has been implicated in the development of vascular complications via the regulation of blood flow, and various antiatherosclerotic actions. Patients with type 2 diabetes (T2D) have a decreased level of endothelial nitric oxide release. In this study we aimed to examine the effect of aquatic seed extract of Cichorium intybus L. (chicory) and metformin (a known prescription drug for diabetes) on NO levels in T2D rats. Methods: Five groups of adult male Wistar rats were used (n=6): Non-diabetic controls without extract treatment (Control), Non-diabetic controls with extract treatment (Chicory-control), T2D rats without extract treatment (NIA/STZ), T2D rats treated with the extract (Chicory-NIA/STZ), and T2D groups that received metformin (100 mg/kg) but no extract (Metformin-NIA/STZ). T2D was induced with intraperitoneal (i.p) injection of niacinamide (NIA, 200 mg/kg), 15 min after an i.p administration of streptozotocin (STZ, 55 mg/kg). Lyophilized chicory extract (125 mg/kg) was dissolved in 0.2 ml normal saline and administered one dose a day. The experiments lasted for 3 weeks after the diabetes induction. NO analysis was performed by assay based on the Griess reaction. Data were reported as the mean ± SD and statistical analysis was performed by ANOVA. Results: Serum nitric oxide levels decreased significantly in NIA/STZ group compared with Control and Chicory-control. Treatment with chicory extract caused a significant increase in serum levels of NO in Chicory-NIA/STZ group compare to NIA/STZ group (p<05). Metformin-NIA/STZ group did not show considerable difference when compared with NIA/STZ, with respect to NO levels. In a group of rats made diabetic by STZ alone (type 1 diabetic rats, T1D), chicory did not have a significant ameliorating effect. Conclusion: In this study, we clearly showed a relationship between low serum nitric oxide levels and diabetes mellitus in rats. The increase in serum nitric oxide by chicory extract is an indication of antiatherogenic effect of this plant. Chicory seed extract was more efficient than metformin in improving the NO levels in NO-deficient T2D diabetic rats.

Keywords: type 2 diabetes mellitus, nitric oxide, chicory, metformin

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Authors: Raed Hanandeh

Abstract:

This empirical study examines how knowledge sharing behaviors mediate the effect Technology-driven strategy on virtual organization success in Jordanian tourism sector firms. The results reveal that Social network ties are positively related to web knowledge seeking, web knowledge contributing and interactive system, but negatively related to accidental knowledge leakage. Furthermore, all types of knowledge sharing behavior are positively related to virtual organization success. Data collected from 23 firms. The total number of questionnaires mailed, 250 questionnaires were delivered. 214 were considered valid out of 241 Responses were received. The findings provide evidence that knowledge sharing behavior play a mediating role between Social network ties and virtual organization success and show that, web knowledge seeking, web knowledge contributing and interactive system playing an important impact on virtual organization success through knowledge sharing behaviors.

Keywords: social network ties, virtual organization success, knowledge sharing behaviors, web knowledge

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Authors: Jerome Joshi

Abstract:

The paper presents the modelling of financial markets using the Stochastic Pi Calculus model. The Stochastic Pi Calculus model is mainly used for biological applications; however, the feature of this model promotes its use in financial markets, more prominently in high frequency trading. The trading system can be broadly classified into exchange, market makers or intermediary traders and fundamental traders. The exchange is where the action of the trade is executed, and the two types of traders act as market participants in the exchange. High frequency trading, with its complex networks and numerous market participants (intermediary and fundamental traders) poses a difficulty while modelling. It involves the participants to seek the advantage of complex trading algorithms and high execution speeds to carry out large volumes of trades. To earn profits from each trade, the trader must be at the top of the order book quite frequently by executing or processing multiple trades simultaneously. This would require highly automated systems as well as the right sentiment to outperform other traders. However, always being at the top of the book is also not best for the trader, since it was the reason for the outbreak of the ‘Hot – Potato Effect,’ which in turn demands for a better and more efficient model. The characteristics of the model should be such that it should be flexible and have diverse applications. Therefore, a model which has its application in a similar field characterized by such difficulty should be chosen. It should also be flexible in its simulation so that it can be further extended and adapted for future research as well as be equipped with certain tools so that it can be perfectly used in the field of finance. In this case, the Stochastic Pi Calculus model seems to be an ideal fit for financial applications, owing to its expertise in the field of biology. It is an extension of the original Pi Calculus model and acts as a solution and an alternative to the previously flawed algorithm, provided the application of this model is further extended. This model would focus on solving the problem which led to the ‘Flash Crash’ which is the ‘Hot –Potato Effect.’ The model consists of small sub-systems, which can be integrated to form a large system. It is designed in way such that the behavior of ‘noise traders’ is considered as a random process or noise in the system. While modelling, to get a better understanding of the problem, a broader picture is taken into consideration with the trader, the system, and the market participants. The paper goes on to explain trading in exchanges, types of traders, high frequency trading, ‘Flash Crash,’ ‘Hot-Potato Effect,’ evaluation of orders and time delay in further detail. For the future, there is a need to focus on the calibration of the module so that they would interact perfectly with other modules. This model, with its application extended, would provide a basis for researchers for further research in the field of finance and computing.

Keywords: concurrent computing, high frequency trading, financial markets, stochastic pi calculus

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