Search results for: large eddy simulation

Authors: Zhou Mo, Dennis Chow

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In the dynamic positioning system (DPS) for vessels, the reliable information transmission between each note basically relies on the wireless protocols. From the perspective of cluster-based routing pro-tocols for wireless sensor networks, the data fusion technology based on the sleep scheduling mechanism and remaining energy in network layer is proposed, which applies the sleep scheduling mechanism to the routing protocols, considering the remaining energy of node and location information when selecting cluster-head. The problem of uneven distribution of nodes in each cluster is solved by the Equilibrium. At the same time, Classified Forwarding Mechanism as well as Redelivery Policy strategy is adopted to avoid congestion in the transmission of huge amount of data, reduce the delay in data delivery and enhance the real-time response. In this paper, a simulation test is conducted to improve the routing protocols, which turns out to reduce the energy consumption of nodes and increase the efficiency of data delivery.

Keywords: DPS for vessel, wireless sensor network, data fusion, routing protocols

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Authors: Jing Zhang

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Sustainable development in the new energy vehicles field is the requirement of the net zero aim. Green bonds are accepted as a practical financial tool to boost the transformation of relevant enterprises. The paper analyzes the interactions among governments, enterprises of new energy vehicles, and financial institutions by an evolutionary game theory model and offers advice to stakeholders in China. The decision-making subjects of green behavior are affected by experiences, interests, perception ability, and risk preference, so it is difficult for them to be completely rational. Based on the bounded rationality hypothesis, this paper applies prospect theory in the evolutionary game analysis framework and analyses the costs of government regulation of enterprises adopting green bonds. The influence of the perceived value of revenue prospect and the probability and risk transfer coefficient of the government's active regulation on the decision-making agent's strategy is verified by numerical simulation. Finally, according to the research conclusions, policy suggestions are given to promote green bonds.

Keywords: green bonds, new energy vehicles, sustainable development, evolutionary Game Theory model

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Authors: Mahmoud Lot

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In this article, we will discuss the solution of elliptic optimal control problem. First, by using the nite element method, we obtain the discrete form of the problem. The obtained discrete problem is actually a large scale constrained optimization problem. Solving this optimization problem with traditional methods is difficult and requires a lot of CPU time and memory. But split Bergman method converts the constrained problem to an unconstrained, and hence it saves time and memory requirement. Then we use the split Bregman method for solving this problem, and examples show the speed and accuracy of split Bregman methods for solving these types of problems. We also use the SQP method for solving the examples and compare with the split Bregman method.

Keywords: Split Bregman Method, optimal control with elliptic partial differential equation constraint, finite element method

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Authors: Omran Alharbi, Victor Lally

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The advantages of the adoption of new technology such as learning management systems (LMSs) in education and teaching methods have been widely recognised. This has led a large number of universities to integrate this type of technology into their daily learning and teaching activities in order to facilitate the education process for both learners and teachers. On the other hand, in some developing countries such as Saudi Arabia, educators have seldom used this technology. As a result, this study was conducted in order to investigate the factors that impede teachers’ use of technology (LMSs) in their teaching in Saudi Arabian institutions. This study used a qualitative approach. Eight participants were invited to take part in this study, and they were asked to give their opinions about the most significant factors that prevented them from integrating technology into their daily activities. The results revealed that a lack of LMS skills, interest in and knowledge about the LMS among teachers were the most significant factors impeding them from using technology in their lessons. The participants suggested that incentive training should be provided to reduce these challenges.

Keywords: LMS, factors, KSA, teachers

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Authors: Ioannis Binas, Marios Moschakis

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Electrical faults in transmission and distribution networks can have great impact on the electrical equipment used. Fault effects depend on the characteristics of the fault as well as the network itself. It is important to anticipate the network’s behavior during faults when planning a new equipment installation, as well as troubleshooting. Moreover, working backwards, we could be able to estimate the characteristics of the fault when checking the perceived effects. Different transformer winding connections dominantly used in the Greek power transfer and distribution networks and the effects of 1-phase to neutral, phase-to-phase, 2-phases to neutral and 3-phase faults on different locations of the network were simulated in order to present voltage sag characteristics. The study was performed on a generic network with three steps down transformers on two voltage level buses (one 150 kV/20 kV transformer and two 20 kV/0.4 kV). We found that during faults, there are significant changes both on voltage magnitudes and on phase angles. The simulations and short-circuit analysis were performed using the PSCAD simulation package. This paper presents voltage characteristics calculated for the simulated network, with different approaches on the transformer winding connections during symmetrical and asymmetrical faults on various locations.

Keywords: Phase angle shift, power quality, transformer winding connections, voltage sag propagation

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Authors: Nga Yui Tong

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Mandarin, the official language of China, is based on the Beijing dialect and is spoken by more than one billion people from all over the world. To investigate the trends of Mandarin acquisition, 192 preschoolers are recruited by stratified random sampling. They are from 4 different districts in Beijing, 2 schools in each district, with 4 age groups, both genders, and 3 children in each stratum. The children are paired up to conduct semi-structured free play for 30 minutes. Their language output is videotaped, transcribed, and coded for the calculation of Mean Length of Utterance (MLU). Two-way ANOVA showed that the variation of MLU is significantly contributed by age, which is coherent to previous findings of other languages. This first large-scale study to investigate the developmental trend of Mandarin in young children in Beijing provides empirical evidence to the development of standards and curriculum planning for early Mandarin education. Interestingly, the gender effect in the study is insignificant, with boys showing a slightly higher MLU than girls across all age groups and settings, except the 4.5 years same-gender dyads. The societal factors in the Chinese context on parenting and gender bias are worth looking into.

Keywords: Beijing, language development, Mandarin, preschoolers

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Authors: Syeda Afsana Azad

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Climate change, due to the release of greenhouse gases into the atmosphere has been recognized as one of the biggest threats to the present world. The condition of the earth is getting worse day by day due to climate change. Bangladesh is considered to be one of the most vulnerable countries to climate change due to large population, sharp urbanization, etc. Construction of green building is a very good solution to reduce the greenhouse effect. Green building technology refers to that kind of structures which are environmentally friendly and resource-efficient throughout a building’s service life. This technology can provide at least 50% energy saving opportunity to the nation. The necessity of the construction of structures in an environment-friendly way is increasing now. This study shows the scenario of rapid population growth, urbanization, necessity of green building in Bangladesh and also discusses the construction process of green building. As the present climate condition of Bangladesh is not friendly, construction of green building is very much needed. To battle climate change, it is mandatory to construct green building.

Keywords: Bangladesh, climate change, green building, green house effect

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Authors: Mohammed Berka, Khaled Merit

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Recent works on microwave filters show that the constituent materials such filters are very important in the design and realization. Several solutions have been proposed to improve the qualities of filtering. In this paper, we propose a new dual band-pass filter based on the coupling of a composite (CRLH) coplanar waveguide with complementary split ring resonators (CSRRs). The (CRLH) CPW is composed of two resonators, each one has an interdigital capacitor (CID) and two short-circuited stubs parallel to top ground plane. On the lower ground plane, we use defected ground structure technology (DGS) to engrave two (CSRRs) offered with different shapes and dimensions. Between the top ground plane and the substrate, we place a ferrite layer to control the electromagnetic coupling between (CRLH) CPW and (CSRRs). The global filter that has coplanar access will have a dual band-pass behavior around the magnetic resonances of (CSRRs). Since there’s no scientific or experimental result in the literature for this kind of complicated structure, it was necessary to perform simulation using HFSS Ansoft designer.

Keywords: complementary split ring resonators, coplanar waveguide, ferrite, filter, stub.

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Authors: Xiangrong Liu, Chuanhui Xiong

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With the concern of large pollution emissions from coal-fired power plants and new commitment to green energy, global solar power industry was emerging recently. Due to the advanced technology, the price of solar photovoltaic(PV) module was reduced at a fast rate, which arose an interesting but challenge question to solar supply chain. This research is modeling the inventory strategies for a PV supply chain with a PV manufacturer, an assembler and an end customer. Through characterizing the manufacturer's and PV assembler's optimal decision in decentralized and centralized situation, this study shed light on how to improve supply chain performance through parameters setting in the contract design. The results suggest the assembler to lower the optimal stock level gradually each period before price reduction and set up a newsvendor base-stock policy in all periods after price reduction. As to the PV module manufacturer, a non-stationary produce-up-to policy is optimal.

Keywords: photovoltaic, supply chain, inventory policy, base-stock policy

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Authors: Alexandre M. Brighenti

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One of the most damaging species in sunflower crops in Brazil is the hairy beggarticks (Bidens pilosa L.). The large number of seeds, the various vegetative cycles during the year, the staggered germination and the scarcity of selective and effective herbicides to control this weed in sunflower are some of attributes that hinder the effectiveness in controlling hairy beggarticks populations. The experiment was carried out with the objectives of evaluating the control of hairy beggarticks plants in sunflower crops, and to assess sunflower tolerance to residual herbicides. The treatments were as follows: S-metolachlor (1,200 and 2,400 g ai ha^-1), flumioxazin (60 and 120 g ai ha^-1), sulfentrazone (150 and 300 g ai ha^-1) and two controls (weedy and weed-free check). Phytotoxicity on sunflower plants, percentage of control and density of hairy beggarticks plants, sunflower stand and plant height, head diameter, oil content and sunflower yield were evaluated. The herbicides flumioxazin and sulfentrazone were the most efficient in hairy beggarticks control. S-metolachlor provided acceptable control levels. S-metolachlor (1,200 g ha^-1), flumioxazin (60 g ha^-1) and sulfentrazone (150 g ha^-1) were the most selective doses for sunflower crop.

Keywords: flumioxazin, Helianthus annuus, S-metolachlor, sulfentrazone, weeds

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Authors: Nisrine Benzbiria, Abderrahmane Thoume, Mustapha Zertoubi

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The goal of this research is to investigate the corrosion inhibition potential of functionalized graphene oxide (GO) with oxime derivative on AA2024-T3 surface in synthetic seawater. The utilization of functionalized graphene oxide is creating a category of corrosion inhibitors known as organically modified nanomaterials. In our work, the functionalization of GO by chalcone oxime enables graphene oxide to have enhanced water solubility and a good corrosion mitigation capacity. Fourier-transform infrared (FT-IR) spectroscopy was utilized to evaluate the main functional groups of the inhibitor. Electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization curves (PDP) showed that the inhibitor acts as a mixed-type inhibitor. The inhibitory efficiency (IE) improved as the concentration increased to a value of 96% after one hour of exposure to a medium containing 60 mg/L ppm of the inhibitor. According to thermodynamic calculations, the adsorption of the inhibitor on the AA2024-T3 surface in 3% NaCl followed the Langmuir isotherm. The formation of a barrier layer was further confirmed by surface analysis. The protective film prevented the alloy dissolution and limited the accessibility of attacking ions, as evinced by solution analysis techniques.

Keywords: AA2024-T3, NaCl, electrochemical methods, FT-IR, SEM/AFM, DFT, MC simulation

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Authors: Ebasa Girma, Nathnael Minyelshowa, Lebsework Negash

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The use of unmanned aerial vehicles (UAVs) in precision agriculture has seen a huge increase recently. As such, systems that aim to apply various algorithms on the field need a structured framework of abstractions. This paper defines the various tasks of the UAVs in precision agriculture and models them into an architectural framework. The presented architecture is built on the context that there will be minimal physical intervention to do the tasks defined with multiple coordinated and cooperative UAVs. Various tasks such as image processing, path planning, communication, data acquisition, and field mapping are employed in the architecture to provide an efficient system. Besides, different limitation for applying Multi-UAVs in precision agriculture has been considered in designing the architecture. The architecture provides an autonomous end-to-end solution, starting from mission planning, data acquisition, and image processing framework that is highly efficient and can enable farmers to comprehensively deploy UAVs onto their lands. Simulation and field tests show that the architecture offers a number of advantages that include fault-tolerance, robustness, developer, and user-friendliness.

Keywords: deep learning, multi-UAVs, precision agriculture, UAVs architecture

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Authors: Qiuhua Miao, Peng Huang, Yifei Ding

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Particles with different properties tend to be unevenly distributed along an axial direction of the rotating drum, which is usually ignored. Therefore, it is important to study the relationship between axial segregation characteristics and particle crushing efficiency in longer drums. In this paper, a relative area total energy (RRTE) index is proposed, which aims to evaluate the overall crushing energy distribution characteristics. Based on numerical simulation verification, the proposed RRTE index can reflect the overall grinding effect more comprehensively, clearly representing crushing energy distribution in different drum areas. Furthermore, the proposed method is applied to the relation between axial segregation and crushing energy in drums. Compared with the radial section, the collision loss energy of the axial section can better reflect the overall crushing effect in long drums. The axial segregation characteristics directly affect the total energy distribution between medium and abrasive, reducing overall crushing efficiency. Therefore, the axial segregation characteristics should be avoided as much as possible in the crushing of the long rotary drum.

Keywords: relative regional total energy, crushing energy, axial segregation characteristics, rotary drum

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Authors: Anatoly V. Stepanov, Maria Y. Ilyushkina, Alexander S. Burnasov

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Expansion of tourism, especially after WWII, has led to significant improvements in the regional infrastructure. The present study has revealed a lot of progress in the advancement of industrial heritage narrative in the Central Urals. The evidence comes from the general public’s increased fascination with some of Europe’s oldest mining and industrial sites, and the agreement of many stakeholders that the Urals industrial heritage should be preserved. The development of tourist sites in Nizhny Tagil and Nevyansk, gold-digging in Beryosovsky, gemstone search in Murzinka, and the progress with the Urals Gemstone Ring project are the examples showing the immense opportunities of industrial heritage tourism development in the region that are still to be realized. Regardless of the economic future of the Central Urals, whether it will remain an industrial region or experience a deeper deindustrialization, the sprouts of the industrial heritage tourism should be advanced and amplified for the benefit of local communities and the tourist community at large as it is hard to imagine a more suitable site for the discovery of industrial and mining heritage than the Central Urals Region of Russia.

Keywords: industrial heritage, mining heritage, Central Urals, Russia

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Authors: Yingjie Zhang, Ming Li, Ying Zhang, Jing Zhang, Zuolei Hu

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In the actual start-up process of DC motors, the DC drive system often faces a conflict between energy consumption and acceleration performance. To resolve the conflict, this paper proposes a comprehensive performance index that energy consumption index is added on the basis of classical control performance index in the DC motor starting process. Taking the comprehensive performance index as the cost function, particle swarm optimization algorithm is designed to optimize the comprehensive performance. Then it conducts simulations on the optimization of the comprehensive performance of the DC motor on condition that the weight coefficient of the energy consumption index should be properly designed. The simulation results show that as the weight of energy consumption increased, the energy efficiency was significantly improved at the expense of a slight sacrifice of fastness indicators with the comprehensive performance index method. The energy efficiency was increased from 63.18% to 68.48% and the response time reduced from 0.2875s to 0.1736s simultaneously compared with traditional proportion integrals differential controller in energy saving.

Keywords: comprehensive performance index, energy consumption, acceleration performance, particle swarm optimal control

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Authors: Adnan I. O. Zaid, Safwan M. A. Alqawabah

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Review of the available literature on grain refinement of aluminum and its alloys reveals that little work is published on the effect of refiners on mechanical characteristics and wear resistance. In this paper, the effect of addition of Zr to Al grain refined by Ti+B on its metallurgical, mechanical characteristics and wear resistance both in the as cast and after extrusion condition are presented and discussed. It was found that Addition of Zr to Al resulted in deterioration of its mechanical strength and hardness, whereas it resulted in improvement of both of them when added to Al grain refined by Ti+B. Furthermore it was found that the direct extrusion process resulted in further increase of the mechanical strength and hardness of Al and its micro-alloys. Also it resulted in increase of their work hardening index, n, i.e. improved their formability, hence it reduces the number of stages required for forming at large strains in excess of the plastic instability before Zr addition.

Keywords: aluminum, grain refinement, titanium + boron, zirconium, mechanical characteristics, wear resistance, direct extrusion

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Authors: Lucile Rapin, Cynthia El Hage, Rihab Gamaoun, Maria-Fernanda Arboleda, Erin Prosk

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Introduction: Sante Cannabis (SC), a Canadian group of clinics dedicated to medical cannabis, based in Montreal and in the province of Quebec, has served more than 8000 patients seeking cannabis-based treatment over the past five years. As randomized clinical trials with natural medical cannabis are scarce, real-world evidence offers the opportunity to fill research gaps between scientific evidence and clinical practice. Data on the use of medical cannabis products from SC patients were prospectively collected, leading to a large real-world database on the use of medical cannabis. The aim of this study was to report information on the profiles of both patients and prescribed medical cannabis products at SC clinics, and to assess the safety of medical cannabis among Canadian patients. Methods: This is an observational retrospective study of 1342 adult patients who were authorized with medical cannabis products between October 2017 and September 2019. Information regarding demographic characteristics, therapeutic indications for medical cannabis use, patterns in dosing and dosage form of medical cannabis and adverse effects over one-year follow-up (initial and 4 follow-up (FUP) visits) were collected. Results: 59% of SC patients were female, with a mean age of 56.7 (SD= 15.6, range= (19-97)). Cannabis products were authorized mainly for patients with a diagnosis of chronic pain (68.8% of patients), cancer (6.7%), neurological disorders (5.6%), and mood disorders (5.4 %). At initial visit, a large majority (70%) of patients were authorized exclusively medical cannabis products, 27% were authorized a combination of pharmaceutical cannabinoids and medical cannabis and 3% were prescribed only pharmaceutical cannabinoids. This pattern was recurrent over the one-year follow-up. Overall, oil was the preferred formulation (average over visits 72.5%) followed by a combination of oil and dry (average 19%), other routes of administration accounted for less than 4%. Patients were predominantly prescribed products with a balanced THC:CBD ratio (59%-75% across visits). 28% of patients reported at least one adverse effect (AE) at the 3-month follow-up visit and 12% at the six-month FUP visit. 84.8% of total AEs were mild and transient. No serious AE was reported. Overall, the most common side effects reported were dizziness (11.95% of total AEs), drowsiness (11.4%), dry mouth (5.5%), nausea (4.8%), headaches (4.6%), cough (4.4%), anxiety (4.1%) and euphoria (3.5%). Other adverse effects accounted for less than 3% of total AE. Conclusion: Our results confirm that the primary area of clinical use for medical cannabis is in pain management. Patients in this cohort are largely utilizing plant-based cannabis oil products with a balanced ratio of THC:CBD. Reported adverse effects were mild and included dizziness and drowsiness. This real-world data confirms the tolerable safety profile of medical cannabis and suggests medical indications not yet validated in controlled clinical trials. Such data offers an important opportunity for the investigation of the long-term effects of cannabinoid exposure in real-life conditions. Real-world evidence can be used to direct clinical trial research efforts on specific indications and dosing patterns for product development.

Keywords: medical cannabis, safety, real-world data, Canada

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Authors: Trapond Hiransalee

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The technology of mobile devices has changed our daily lives. Since smartphone have become a multi-functional device, many people spend unnecessary time on them, and could be interrupted by inappropriate notifications such as unimportant messages from social media. Notifications from smartphone could draw people’s attention and distract them from their priorities and current tasks. This research investigated that if the users were notified by their surroundings instead of smartphone, would it create less distraction and keep their focus on the present task. The experiment was a simulation of a lamp and door notification. Notifications related to work will be embedded in the lamp such as an email from a colleague. A notification that is useful when going outside such as weather information, traffic information, and schedule reminder will be embedded in the door. The experiment was conducted by sending notifications to the participant while he or she was working on a primary task and the working performance was measured. The results show that the lamp notification had fewer interruption effects than the smartphone. For the door notification, it was simulated in order to gain opinions and insights on ambient notifications from participants. Many participants agreed that the ambient notifications are useful and being informed by them could lessen the usage of their smartphone. The results and insights from this research could be used to guide the design process of ambient notifications.

Keywords: HCI, interaction, interaction design, usability testing

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Authors: Jagdish Prasad Maurya, Sanjay Kumar Pandey

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Inadequate understanding of the complex nature of flow features in tornado vortex is a major problem in modelling tornadoes. Tornadoes are violent atmospheric phenomenon that appear all over the world. Modelling tornadoes aim to reduce the loss of the human lives and material damage caused by the tornadoes. Dynamics of tornado is investigated by a numerical technique, the improved version of the projection method. In this paper, authors solve the problem for axisymmetric tornado vortex by the said method that uses a finite difference approach for getting an accurate and stable solution. The conclusions drawn are that large radial inflow velocity occurs near the ground that leads to increase the tangential velocity. The increased velocity phenomenon occurs close to the boundary and absolute maximum wind is obtained near the vortex core. The results validate previous numerical and theoretical models.

Keywords: computational fluid dynamics, mathematical model, Navier-Stokes equations, tornado

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Authors: Tesfaye Alamirew, Delele Worku, Solomon W. Fanta, Nigus Gabbiye

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Recently graphen based nanocomposites are become an emerging research areas for fabrication of enzymatic biosensors due to their property of large surface area, conductivity and biocompatibility. This review summarizes recent research reports of graphen based nanocomposites for the fabrication of glucose and ethanol enzymatic biosensors. The newly fabricated enzyme free microwave treated nitrogen doped graphen (MN-d-GR) had provided highest sensitivity towards glucose and GCE/rGO/AuNPs/ADH composite had provided far highest sensitivity towards ethanol compared to other reported graphen based nanocomposites. The MWCNT/GO/GOx and GCE/ErGO/PTH/ADH nanocomposites had also enhanced wide linear range for glucose and ethanol detection respectively. Generally, graphen based nanocomposite enzymatic biosensors had fast direct electron transfer rate, highest sensitivity and wide linear detection ranges during glucose and ethanol sensing.

Keywords: glucose, ethanol, enzymatic biosensor, graphen, nanocomposite

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Authors: B. Chandra

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In Association Rule Mining, much attention has been paid for developing algorithms for large (frequent/closed/maximal) itemsets but very little attention has been paid to improve the performance of rule generation algorithms. Rule generation is an important part of Association Rule Mining. In this paper, a novel approach named NARG (Association Rule using Antecedent Support) has been proposed for rule generation that uses memory resident data structure named FCET (Frequent Closed Enumeration Tree) to find frequent/closed itemsets. In addition, the computational speed of NARG is enhanced by giving importance to the rules that have lower antecedent support. Comparative performance evaluation of NARG with fast association rule mining algorithm for rule generation has been done on synthetic datasets and real life datasets (taken from UCI Machine Learning Repository). Performance analysis shows that NARG is computationally faster in comparison to the existing algorithms for rule generation.

Keywords: knowledge discovery, association rule mining, antecedent support, rule generation

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Authors: T. Gayen

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Although, there are several software reliability models existing today there does not exist any versatile model even today which can be used for the reliability assessment of software. Complex software has a large number of states (unlike the hardware) so it becomes practically difficult to completely test the software. Irrespective of the amount of testing one does, sometimes it becomes extremely difficult to assure that the final software product is fault free. The Black Box Software Reliability models are found be quite uncertain for the reliability assessment of various systems. As mission critical applications need to be highly reliable and since it is not always possible to ensure the development of highly reliable system. Hence, in order to achieve fault-free operation of software one develops some mechanism to handle faults remaining in the system even after the development. Although, several such techniques are currently in use to achieve fault tolerance, yet these mechanisms may not always be very suitable for various systems. Hence, this discussion is focused on analyzing the issues and challenges faced with the existing techniques for reliability assessment and fault tolerance of various software systems.

Keywords: black box, fault tolerance, failure, software reliability

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Authors: Sunil Chandra, Triparna Barman, Vikas Gusain, Himanshu Rawat

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Forest fires are a recurrent phenomenon in the Himalayan region owing to the presence of vulnerable forest types, topographical gradients, climatic weather conditions, and anthropogenic pressure. The present study focuses on the identification of forest fire-affected areas in a small part of the West Himalayan region using a differential normalized burnt ratio method and spectral unmixing methods. The study area has a rugged terrain with the presence of sub-tropical pine forest, montane temperate forest, and sub-alpine forest and scrub. The major reason for fires in this region is anthropogenic in nature, with the practice of human-induced fires for getting fresh leaves, scaring wild animals to protect agricultural crops, grazing practices within the reserved forest, and igniting fires for cooking and other reasons. The fires caused by the above reasons affect a large area on the ground, necessitating its precise estimation for further management and policy making. In the present study, two approaches have been used for carrying out a burnt area analysis. The first approach followed for burnt area analysis uses a differential burnt normalized ratio index (dNBR) approach that uses the burnt ratio values generated using Short Wave Infra Red (SWIR) band and Near Infra Red (NIR) bands of the Sentinel-2A image. The results of the dNBR have been compared with the outputs of the spectral mixing methods. It has been found that the dNBR is able to create good results in fire-affected areas having homogenous forest stratum and with slope degree <5 degrees. However, in a rugged terrain where the landscape is largely influenced by the topographical variations, vegetation types, tree density, the results may be largely influenced by the effects of topography, complexity in tree composition, fuel load composition, and soil moisture. Hence, such variations in the factors influencing burnt area assessment may not be effectively carried out using a dNBR approach which is commonly followed for burnt area assessment over a large area. Hence, another approach that has been attempted in the present study utilizes a spectral mixing method where the individual pixel is tested before assigning an information class to it. The method uses a neural network approach utilizing Sentinel 2A bands. The training and testing data are generated from the sentinel-2A data and the national field inventory, which is further used for generating outputs using ML tools. The analysis of the results indicates that the fire-affected regions and their severity can be better estimated in rugged terrain using spectral unmixing methods which have the capability to resolve the noise in the data and can classify the individual pixel to the precise burnt/unburnt class.

Keywords: dNBR, spectral unmixing, neural network, forest stratum

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Authors: Adnan I. O. Zaid

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As aluminum solidifies in columnar structure with large grain size which reduces its surface quality and mechanical strength; therefore it is normally grain refined either by titanium or titanium + boron (Ti or Ti + B). In this paper, the effect of addition of either Ti or Ti + B to commercially pure aluminum on its grain size, Vickers hardness, mechanical strength and fatigue strength and life is presented and discussed. Similarly, the effect of vanadium addition to Al grain refined by Ti or Ti+ B is presented and discussed. Two binary master alloys Al-Ti and Al-Vi were laboratory prepared from which five different micro-alloys in addition to the commercially pure aluminum namely Al-Ti, Al-Ti-B, Al-V, Al-Ti-V and Al-Ti-B-V were prepared for the investigation. Finally, the effect of their addition on the fatigue cracks initiation and propagation, using scanning electron microscope, SEM, is also presented and discussed. Photomirographs and photoscans are included in the paper.

Keywords: aluminum, fatigue, grain refinement, titanium, titanium+boron, vanadium

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Authors: Najla Althuniyan

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Online discussions take place across different platforms. These discussions have the potential to extract crowd wisdom and capture the collective intelligence from a different perspective. However, certain phenomena, such as controversy, often appear in online argumentation that makes the discussion between participants heated. Heated discussions can be used to extract new knowledge. Therefore, detecting the presence of controversy is an essential task to determine if collective intelligence can be extracted from online discussions. This paper uses existing measures for estimating controversy quantitatively in cyber-argumentation. First, it defines controversy in different fields, and then it identifies the attributes of controversy in online discussions. The distributions of user opinions and the distance between opinions are used to calculate the controversial degree of a discussion. Finally, the results from each controversy measure are discussed and analyzed using an empirical study generated by a cyber-argumentation tool. This is an improvement over the existing measurements because it does not require ground-truth data or specific settings and can be adapted to distribution-based or distance-based opinions.

Keywords: online argumentation, controversy, collective intelligence, agreement analysis, collaborative decision-making, fuzzy logic

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Authors: Abdelkader Elhanaoui, Mhamed Hadji, Rachid Skouri, Said Agounad

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In this paper, altera de1-SoC FPGA board technology is utilized as a distinguished tool for nondestructive characterization of an aluminum circular cylindrical shell of radius ratio b/a (a: outer radius; b: inner radius). The acoustic backscattered signal processing system has been developed using OpenMP architecture. The design is built in three blocks; it is implemented per functional block, in a heterogeneous Intel-Altera system running under Linux. The useful data to determine the performances of SoC FPGA is computed by the analytical method. The exploitation of SoC FPGA has lead to obtain the backscattering form function and resonance spectra. A0 and S0 modes of propagation in the tube are shown. The findings are then compared to those achieved from the Matlab simulation of analytical method. A good agreement has, therefore, been noted. Moreover, the detailed SoC FPGA-based system has shown that acoustic spectra are performed at up to 5 times faster than the Matlab implementation using almost the same data. This FPGA-based system implementation of processing algorithms is realized with a coefficient of correlation R and absolute error respectively about 0.962 and 5 10⁻⁵.

Keywords: OpenMP, signal processing system, acoustic backscattering, nondestructive characterization, thin tubes

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Authors: Saadelnour Abdueljabbar Adam

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Wastes from slaughterhouses in most towns in Sudan are often poorly managed and sometimes discharged into adjoining streams due to poor implementation of standards, thus causing environmental and public health hazards and also there is a large amount of manure from dairy farms. This paper presents a solution of organic waste from cow dairy farms and slaughterhouse. We present the findings of experimental investigation of biogas production using cow manure, blood and rumen content were mixed at three proportions :72.3%, 61%, 39% manure, 6%, 8.5%, 22% blood; and 21.7%, 30.5%, 39% rumen content in volume for bio-digester 1,2,3 respectively. This paper analyses the quantitative and qualitative composition of biogas: gas content, and the concentration of methane. The highest biogas output 0.116L/g dry matter from bio-digester1 together with a high-quality biogas of 85% methane Was from the mixture of cow manure with blood and rumen content were mixed at 72.3%manure, 6%blood and 21.7%rumen content which is useful for combustion and energy production. While bio-digester 2 and 3 gave 0.012L/g dry matter and 0.013L/g dry matter respectively with the weak concentration of methane (50%).

Keywords: anaerobic digestion, bio-digester, blood, cow manure, rumen content

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Authors: M. H. Korayem, N. Sangsefidi

Abstract:

Magnetically guided soft robots have emerged as a promising technology in minimally invasive surgery due to their ability to adapt to complex environments. However, one of the main challenges in this field is damage to the vascular structure caused by unwanted stress on the vessel wall and deformation of the vessel due to improper control of the shape of the robot body during surgery. Therefore, this article proposes an approach for controlling the form of a magnetic, soft, continuous robot body using a PID controller. The magnetic soft continuous robot is modelled using Cosserat theory in static mode and solved numerically. The designed controller adjusts the position of each part of the robot to match the desired shape. The PID controller is considered to minimize the robot's contact with the vessel wall and prevent unwanted vessel deformation. The simulation results confirmed the accuracy of the numerical solution of the static Cosserat model. Also, they showed the effectiveness of the proposed contouring method in achieving the desired shape with a maximum error of about 0.3 millimetres.

Keywords: PID, magnetic soft continuous robot, soft robot shape control, Cosserat theory, minimally invasive surgery

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Authors: Ananta Kumar Das, Sujit Kumar Chakrabarti

Abstract:

Architectural tactics such as heartbeat, ping-echo, encapsulate, encrypt data are techniques that are used to achieve quality attributes of a system. Detecting architectural tactics has several benefits: it can aid system comprehension (e.g., legacy systems) and in the estimation of quality attributes such as safety, security, maintainability, etc. Architectural tactics are typically spread over the source code and are implicit. For large codebases, manual detection is often not feasible. Therefore, there is a need for automated methods of detection of architectural tactics. This paper presents a formalization of the heartbeat architectural tactic and a program analytic approach to detect this tactic in source code. The experiment of the proposed method is done on a set of Java applications. The outcome of the experiment strongly suggests that the method compares well with a manual approach in terms of its sensitivity and specificity, and far supersedes a manual exercise in terms of its scalability.

Keywords: software architecture, architectural tactics, detecting architectural tactics, program analysis, AST, alias analysis

Procedia PDF Downloads 146

Authors: Ghada S. Moussa

Abstract:

With the increase in population along with economic prosperity, an enormous increase in the number and types of vehicles on the roads occurred. This fact brings a growing need for efficiently yet effectively classifying vehicles into their corresponding categories, which play a crucial role in many areas of infrastructure planning and traffic management. This paper presents two vehicle-type classification approaches; 1) geometric-based and 2) appearance-based. The two classification approaches are used for two tasks: multi-class and intra-class vehicle classifications. For the evaluation purpose of the proposed classification approaches’ performance and the identification of the most effective yet efficient one, 10-fold cross-validation technique is used with a large dataset. The proposed approaches are distinguishable from previous research on vehicle classification in which: i) they consider both geometric and appearance attributes of vehicles, and ii) they perform remarkably well in both multi-class and intra-class vehicle classification. Experimental results exhibit promising potentials implementations of the proposed vehicle classification approaches into real-world applications.

Keywords: appearance attributes, geometric attributes, support vector machine, vehicle classification

Procedia PDF Downloads 328