Search results for: control area network (CAN)

Authors: Xiaohua Zhu, Lingling Ma, Yongguang Zhao

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Leaf Area Index (LAI) is a key structural characteristic of crops and plays a significant role in precision agricultural management and farmland ecosystem modeling. However, LAI retrieved from different resolution data contain a scaling bias due to the spatial heterogeneity and model non-linearity, that is, there is scale effect during multi-scale LAI estimate. In this article, a typical farmland in semi-arid regions of Chinese Inner Mongolia is taken as the study area, based on the combination of PROSPECT model and SAIL model, a multiple dimensional Look-Up-Table (LUT) is generated for multiple crops LAI estimation from unmanned aerial vehicle (UAV) hyperspectral data. Based on Taylor expansion method and computational geometry model, a scale transfer model considering both difference between inter- and intra-class is constructed for scale effect analysis of LAI inversion over inhomogeneous surface. The results indicate that, (1) the LUT method based on classification and parameter sensitive analysis is useful for LAI retrieval of corn, potato, sunflower and melon on the typical farmland, with correlation coefficient R2 of 0.82 and root mean square error RMSE of 0.43m2/m-2. (2) The scale effect of LAI is becoming obvious with the decrease of image resolution, and maximum scale bias is more than 45%. (3) The scale effect of inter-classes is higher than that of intra-class, which can be corrected efficiently by the scale transfer model established based Taylor expansion and Computational geometry. After corrected, the maximum scale bias can be reduced to 1.2%.

Keywords: leaf area index (LAI), scale effect, UAV-based hyperspectral data, look-up-table (LUT), remote sensing

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Authors: E. M. Vieira, C. S. Vieira, L. P. Bonifácio, L. M. de Oliveira Ciabati, A. C. A. Franzon, F. S. Zaratini, J. A. C. Sanchez, M. S. Andrade, J. P. Dias de Souza

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The quality of prenatal care is key to reduce maternal morbidity and mortality. Communication between the health service and users can stimulate prevention and care. M-health has been an important and low cost strategy to health education. The PRENACEL programme (prenatal in the cell phone) was developed. It consists of a programme of information via SMS from the 20^th week of pregnancy up to 12^th week after delivery. Messages were about prenatal care, birth, contraception and breastfeeding. Communication of the pregnant woman asking questions about their health was possible. The objective of this study was to evaluate the implementation of PRENACEL as a useful complement to the standard prenatal care. Twenty health clinics were selected and randomized by cluster, 10 as the intervention group and 10 as the control group. In the intervention group, women and their partner were invited to participate. The control group received the standard prenatal care. All women were interviewed in the immediate post-partum and in the 12^th and 24^th week post-partum. Most women were married, had more than 8 years of schooling and visit the clinic more than 6 times during prenatal care. The intervention group presented lowest percentage of higher economic participants (5.6%), less single mothers and no drug user. It also presented more prenatal care visits than the control group and it was less likely to present Severe Acute Maternal Mortality when compared to control group as well as higher percentage of partners (75.4%) was present at the birth compared to control group. Although the study is still being carried out, preliminary data are showing positive results of the compliance of women to prenatal care.

Keywords: cellphone, health technology, prenatal care, prevention

Procedia PDF Downloads 382

Authors: Elena Kalcheva, Ahmad Taki, Yuri Hadi

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Urban regeneration often includes residential high-rises as a way of optimum use of land. However, high-rises are in many cases connected to placelessness, this is not due to some intrinsic characteristic of the typology, but more to a failure to provide meaningful places in connection to them. The reason to study the Isle of the Dogs regeneration is the successful process that led to vibrant area with strong identity and social sustainability. Therefore, the purpose of this research is to identify the gaps into the sound strategy for the development of the area and in its implementation which will make the place more sustainable. The paper addresses four research questions: are the residential high-rises supporting a proper physical form; is there deployed properly scaled mix of land uses and functions in connection with residential high-rises; are there possible quality activities in quality places near the residential high-rises; and is there a strong sense of place created with the residential high-rise buildings and their surroundings. The methodology relies on observational survey of the researched area together with structured questions, to evaluate the external qualities of the residential high-rises and their surroundings. Visual information can help identify the mistakes and the omissions of the provided project examples. It can provide insight on how can be improved imageability, legibility and human scale. In this connection, the paper argues that although the quality of the architecture of the high-rises is superb, there is a failure to create meaningful, high quality public realm in connection with them. As such, it does not function as well as the designers intended to do: the functional quality of the public realm is quite low. The implications of the study suggest that actions need to take place in order to improve and foster further regeneration of the area.

Keywords: high-rises, isle of the dogs, public realm, regeneration

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Authors: Juan Heredia, Naci Dilekli

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The Ecuadorian Rainforest has been polluted for almost 60 years with little to no regard to oversight, law, or regulations. The consequences have been vast environmental damage such as pollution and deforestation, as well as sickness and the death of many people and animals. The aim of this paper is to quantify and localize the polluted zones, which something that has not been conducted and is the first step for remediation. To approach this problem, multi-spectral Remote Sensing imagery was utilized using a novel algorithm developed for this study, based on four normalized indices available in the literature. The algorithm classifies the pixels in polluted or healthy ones. The results of this study include a new algorithm for pixel classification and quantification of the polluted area in the selected image. Those results were finally validated by ground control points found in the literature. The main conclusion of this work is that using hyperspectral images, it is possible to identify polluted vegetation. The future work is environmental remediation, in-situ tests, and more extensive results that would inform new policymaking.

Keywords: remote sensing, oil pollution quatification, amazon forest, hyperspectral remote sensing

Procedia PDF Downloads 147

Authors: Pulcherie Matsodoum Nguemte, Adrien Wanko Ngnien, Guy Valerie Djumyom Wafo, Ives Magloire Kengne Noumsi, Pierre Francois Djocgoue

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The identification of plant species with the capacity to grow on hydrocarbon-polluted soils is an essential step for phytoremediation. In view of developing phytoremediation in Cameroon, floristic surveys have been conducted in 4 cities (Douala, Yaounde, Limbe, and Kribi). In each city, 13 hydrocarbon-polluted, as well as unpolluted sites (control), have been investigated using quadrat method. 106 species belonging to 76 genera and 30 families have been identified on hydrocarbon-polluted sites, unlike the control sites where floristic diversity was much higher (166 species contained in 125 genera and 50 families). Poaceae, Cyperaceae, Asteraceae and Amaranthaceae have higher taxonomic richness on polluted sites (16, 15,10 and 8 taxa, respectively). Shannon diversity index of the hydrocarbon-polluted sites (1.6 to 2.7 bits/ind.) were significantly lower than the control sites (2.7 to 3.2 bits/ind.). Based on a relative frequency > 10% and abundance > 7%, this study highlights more than ten plants predisposed to be effective in the cleaning-up attempts of soils contaminated by hydrocarbons. Based on the floristic indicators, 6 species (Eleusine indica (L.) Gaertn., Cynodon dactylon (L.) Pers., Alternanthera sessilis (L.) R. Br. ex DC †, Commelinpa benghalensis L., Cleome ciliata Schum. & Thonn. and Asystasia gangetica (L.) T. Anderson) were selected for a study to determine their capacity to remediate a soil contaminated with fuel oil (82.5 ml/ kg of soil). The experiments lasting 150 days takes into account three modalities - Tn: uncontaminated soils planted (6) To contaminated soils unplanted (3) and Tp: contaminated soil planted (18) – randomized arranged. 3 on 6 species (Eleusine indica, Cynodon dactylon, and Alternanthera sessilis) survived the climatic and soil conditions. E. indica presents a significantly higher growth rate for density and leaf area while C. dactylon had a significantly higher growth rate for stem size and leaf numbers. A. sessilis showed stunted growth and development throughout the experimental period. The species Eleusine indica (L.) Gaertn. and Cynodon dactylon (L.) Pers. can be qualified as polluo-tolerant plant species; polluo-tolerance being the ability of a species to survive and develop in the midst subject to extreme physical and chemical disturbances.

Keywords: Cameroon, cleaning-up, floristic surveys, phytoremediation

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Authors: Oyebade K. Oyedotun

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The cardiotocogram is a technical recording of the heartbeat rate and uterine contractions of a fetus during pregnancy. During pregnancy, several complications can occur to both the mother and the fetus; hence it is very crucial that medical experts are able to find technical means to check the healthiness of the mother and especially the fetus. It is very important that the fetus develops as expected in stages during the pregnancy period; however, the task of monitoring the health status of the fetus is not that which is easily achieved as the fetus is not wholly physically available to medical experts for inspection. Hence, doctors have to resort to some other tests that can give an indication of the status of the fetus. One of such diagnostic test is to obtain cardiotocograms of the fetus. From the analysis of the cardiotocograms, medical experts can determine the status of the fetus, and therefore necessary medical interventions. Generally, medical experts classify examined cardiotocograms into ‘normal’, ‘suspect’, or ‘pathological’. This work presents an artificial neural network based decision support system which can filter cardiotocograms data, producing the corresponding statuses of the fetuses. The capability of artificial neural network to explore the cardiotocogram data and learn features that distinguish one class from the others has been exploited in this research. In this research, feedforward and radial basis neural networks were trained on a publicly available database to classify the processed cardiotocogram data into one of the three classes: ‘normal’, ‘suspect’, or ‘pathological’. Classification accuracies of 87.8% and 89.2% were achieved during the test phase of the trained network for the feedforward and radial basis neural networks respectively. It is the hope that while the system described in this work may not be a complete replacement for a medical expert in fetus status evaluation, it can significantly reinforce the confidence in medical diagnosis reached by experts.

Keywords: decision support, cardiotocogram, classification, neural networks

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Authors: R. R. Mankbadi

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There are several technologically-important flow situations in which there is a need to control the outcome of the fluid flow. This could include flow separation, drag, noise, as well as particulate separations, to list only a few. One possible approach is the passive control, in which the design geometry is changed. An alternative approach is the Active Flow Control (AFC) technology in which an actuator is embedded in the flow field to change the outcome. Examples of AFC are pulsed jets, synthetic jets, plasma actuators, heating, and cooling, etc. In this work will present an overview of the development of this field. Some examples will include Airfoil Noise Suppression: Large-Eddy Simulations (LES) is used to simulate the effect of synthetic jet actuator on controlling the far field sound of a transitional airfoil. The results show considerable suppression of the noise if the synthetic jet is operated at frequencies. Mixing Enhancement and suppression: Results will be presented to show that imposing acoustic excitations at the nozzle exit can lead to enhancement or reduction of the jet plume mixing. In vertical takeoff of Aircrafts or in Space Launch, we will present results on the effects of water injection on reducing noise, and on protecting the structure and payload from fatigue damage. Other applications will include airfoil-gust interaction and propulsion systems optimizations.

Keywords: aeroacoustics, flow control, aerodynamics, large eddy simulations

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Authors: Johanna Schumacher, Toribio F. Otero, Victor H. Pascual

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Bending dual sensing-actuators based on electroactive polymers are faradaic motors meaning the consumed charge determines the actuator’s tip position. During actuation, consumed charges during oxidation and reduction result in different tip positions showing dynamic hysteresis effects with errors up to 25%. For a precise position control of these actuators, the characterization of the hysteresis effect due to irreversible reactions is crucial. Here, the investigation and modelling of dynamic hysteresis effects of polypyrrole-dodezylbenzenesulfonate (PPyDBS) actuators under ambient working conditions are presented. The hysteresis effect is studied for charge consumption at different frequencies and a rate-dependent hysteresis model is derived. The hysteresis model is implemented as closed loop system and is verified experimentally.

Keywords: dual sensing-actuator, electroactive polymers, hysteresis, position control

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Authors: Wennan Long, Yuhao Nie, Yunan Li, Adam Brandt

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To fight against climate change, California government issued the Senate Bill No. 100 (SB-100) in 2018 September, which aims at achieving a target of 100% renewable electricity by the end of 2045. A capacity expansion problem is solved in this case study using a binary quadratic programming model. The optimal locations and capacities of the potential renewable power plants (i.e., solar, wind, biomass, geothermal and hydropower), the phase-out schedule of existing fossil-based (nature gas) power plants and the transmission of electricity across the entire network are determined with the minimal total annualized cost measured by net present value (NPV). The results show that the renewable electricity contribution could increase to 85.9% by 2030 and reach 100% by 2035. Fossil-based power plants will be totally phased out around 2035 and solar and wind will finally become the most dominant renewable energy resource in California electricity mix.

Keywords: 100% renewable electricity, California, capacity expansion, mixed integer non-linear programming

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Authors: W. M. Ng, O. B. Iskender, L. Simonini, J. M. Gonzalez

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A multitude of factors, including mechanical imperfections of the deployment system and separation instance of satellites from launchers, oftentimes results in highly uncontrolled initial tumbling motion immediately after deployment. In particular, small satellites which are characteristically launched as a piggyback to a large rocket, are generally allocated a large time window to complete detumbling within the early orbit phase. Because of the saturation risk of the actuators, current algorithms are conservative to avoid draining excessive power in the detumbling phase. This work aims to enable time-optimal switching of control modes during the early phase, reducing the time required to transit from launch to sun-pointing mode for power budget conscious satellites. This assumes the usage of B-dot controller for detumbling and PD controller for pointing. Nonlinear Euler's rotation equations are used to represent the attitude dynamics of satellites and Commercial-off-the-shelf (COTS) reaction wheels and magnetorquers are used to perform the manoeuver. Simulation results will be based on a spacecraft attitude simulator and the use case will be for multiple orbits of launch deployment general to Low Earth Orbit (LEO) satellites.

Keywords: attitude control, detumbling, small satellites, spacecraft autonomy, time optimal control

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Authors: Constantin Haita

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The chalcolithic tell settlements from south-eastern Romania, attributed to Gumelnița culture, are characterised by a well-defined surface, marked often by delimitation structures, a succession of many layers of construction, destruction, and rebuilding, and a well-structured area of occupation: built spaces, passage areas, waste zones. Settlements of tell type are located in the river valleys –on erosion remnants, alluvial bars or small islands, at the border of the valleys– on edges or prominences of Pleistocene terraces, lower Holocene terraces, and banks of lakes. This study integrates data on the geographical position, the morphological background, and the general stratigraphy of these important settlements. The correlation of the spatial distribution with the geomorphological units of each area of evolution creates an image of the natural landscape in which they occurred. The sedimentological researches achieved in the floodplain area of Balta Ialomiței showed important changes in the alluvial activity of Danube, after the Chalcolithic period (ca. 6500 - 6000 BP), to Iron Age and Middle Ages. The micromorphological analysis, consisting in thin section interpretation, at the microscopic scale, of sediments and soils in an undisturbed state, allowed the interpretation of the identified sedimentary facies, in terms of mode of formation and anthropic activities. Our studied cases reflect some distinct situations, correlating either with the geomorphological background or with the vertical development, the presence of delimiting structures and the internal organization. The characteristics of tells from this area bring significant information about the human habitation of Lower Danube in Prehistory.

Keywords: chalcolithic, micromorphology, Romania, sedimentology, tell settlements

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Authors: N. Tumenbayeva

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At the present time in Kazakhstan, the area for saxaul growing is strongly depopulateddue to anthropogenic and other factors. To prevent further reduction of natural haloxylon forest area their artificial crops are offered. Seed germination and survival of young plants in such haloxylon crops are very low. Insects, as one of the most important nutrient factors have appreciable effect on seed germination and saxaul productivity at the all stages of its formation. Insects, feeding on leaves, flowers, seeds and developing inside the trunk, branches, twigs, roots have a change in its formation and influence on the lifespan of saxaul. Representatives of Lepidoptera troop (Lepidopteraare the most harmful pests forsaxaul. As a result of our research we have identified 15 species of Lepidoptera living on haloxylon which display very different cycles and different types of food relations. It allows them to inhabit a variety of habitats, and feeding on various parts of saxaul. Some of them cause significant and sometimes very heavy damage for saxaul. There are 17identified species of Lepidoptera from the Coleophoridaefamily - 1, Gelechidae - 5, Pyralidae - 4, Noctuidae - 4, Lymantridae- 1, Cossidae - 2 species. At the same time we found 8 species for the first time, which have not been mentioned in the literature before. According to food specialization they are divided into monophages (2 types), oligophages (6 species) and polyphages (3 species). By affinity to plant parts, leaves and seeds are fed by 8 species, shoots by 1 specie, scions by 5 species, flowers, scions, seeds by 1, and 2species damage the roots and trunks. In whole installed seasonal groups of Lepidoptera - saxaul pests in the desert area, confined to the certain parts of the year, as well as certain parts of the plant for feeding. Harmfulness, depending on their activity appear during the growing season is also different.

Keywords: saxaul, Lepidoptera, insecta, haloxylon

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Authors: Noor Farizah Ibrahim, Christopher Durugbo

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This study aims to investigate how the Twittersphere reacted during the recent historical event of robotic landing on a comet. The news is about Philae, a robotic lander from European Space Agency (ESA), which successfully made the first-ever rendezvous and touchdown of its kind on a nucleus comet on November 12, 2014. In order to understand how Twitter is practically used in spreading messages on historical events, we conducted an analysis of one-week tweet feeds that contain the #CometLanding hashtag. We studied the trends of tweets, the diffusion of the information and the characteristics of the social network created. The results indicated that the use of Twitter as a platform enables online communities to engage and spread the historical event through social media network (e.g. tweets, retweets, mentions and replies). In addition, it was found that comprehensible and understandable hashtags could influence users to follow the same tweet stream compared to other laborious hashtags which were difficult to understand by users in online communities.

Keywords: diffusion of information, hashtag, social media, Twitter

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Authors: A. Y. Mukhtar, J. B. Munyakazi, R. Ouifki

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Over the past few decades, the unprecedented increase in mobility has raised considerable concern about the relationship between mobility and vector-borne diseases and malaria in particular. Thus, one can claim that human mobility is one of the contributing factors to the resurgence of malaria. To assess human mobility on malaria burden among hosts, we formulate a movement-based model on a network of patches. We then extend human multi-group SEIAR deterministic epidemic models into a system of stochastic differential equations (SDEs). Our quantitative stochastic model which is expressed in terms of average rates of movement between compartments is fitted to time-series data (weekly malaria data of 2011 for each patch) using the maximum likelihood approach. Using the metapopulation (multi-group) model, we compute and analyze the basic reproduction number. The result shows that human movement is sufficient to preserve malaria disease firmness in the patches with the low transmission. With these results, we concluded that the sensitivity of malaria to the human mobility is turning to be greatly important over the implications of future malaria control in South Sudan.

Keywords: basic reproduction number, malaria, maximum likelihood, movement, stochastic model

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Authors: M. H. Korayem, Sh. Ameri, N. Yousefi Lademakhi

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To ensure the stability of closed-loop nonlinear model predictive control (NMPC) within a finite horizon, there is a need for appropriate design terminal ingredients, which can be a time-consuming and challenging effort. Otherwise, in order to ensure the stability of the control system, it is necessary to consider an infinite predictive horizon. Increasing the prediction horizon increases computational demand and slows down the implementation of the method. In this study, a new technique has been proposed to ensure system stability without terminal ingredients. This technique has been employed in the design of the NMPC algorithm, leading to a reduction in the computational complexity of designing terminal ingredients and computational burden. The studied system is a wheeled mobile robot (WMR) subjected to non-holonomic constraints. Simulation has been investigated for two problems: trajectory tracking and adjustment mode.

Keywords: wheeled mobile robot, nonlinear model predictive control, stability, without terminal ingredients

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Authors: Juang R. Matangaran, Qi Adlan

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Industrial plantation forest in Indonesia was developed in 1983, and since then, several companies have been successfully planted a total area of concessionaire approximately 10 million hectares. Currently, these plantation forests have their annual harvesting period. In the timber harvesting process, amount part of the trees generally become logging residue. Tree parts such as branches, twigs, defected stem and leaves are unused section of tree on the ground after timber harvesting. The use of heavy machines in timber harvesting area has caused damage to the forest soil. The negative impact of such machines includes loss of topsoil, soil erosion, and soil compaction. Forest soil compaction caused reduction of forest water infiltration, increase runoff and causes difficulty for root penetration. In this study, we used logging residue as soil covers on the passages passed by skidding machines in order to observe the reduction soil compaction. Bulk density of soil was measured and analyzed after several times of skidding machines passage on skid trail. The objective of the research was to analyze the effect of logging residue on reducing soil compaction. The research was taken place at one of the industrial plantation forest area of South Sumatra Indonesia. The result of the study showed that percentage increase of soil compaction bare soil was larger than soil surface covered by logging residue. The maximum soil compaction occurred after 4 to 5 passes on soil without logging residue or bare soil and after 7 to 8 passes on soil cover by logging residue. The use of logging residue coverings could reduce soil compaction from 45% to 60%. The logging residue was effective in decreasing soil disturbance of timber harvesting at the plantation forest area.

Keywords: bulk density, logging residue, plantation forest, soil compaction, timber harvesting

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Authors: Sharon Lopez

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Much of critical thought dismisses the notion of subaltern women engaging in resistance because of her complex colonial identity. She is seen in postcolonial theory as being "doubly effaced" and removed from exercising control to speak up and taking part in defiance. This line of reasoning suggests a critical area in which engaging with issues unavoidably excludes subaltern women from the emerging resistance discourse. A position like this also suggests a closed-minded view of human experience and a desire to maintain subalternity. The argument here is that subaltern women might be understood as achieving agency when they engage in resistance and speak out about their circumstances, whether aloud or in silence. Using deductions from Mahasweta Devi's literary narratives such as Imaginary Maps and Breast Stories, the study investigates the tactics Devi employs to engage marginalised women into resistance and establishes that the 'body' emerges in her stories not just as a site of oppression but also as an important motif of power and resistance.

Keywords: subaltern woman, reproductive docy, breast giver, devi

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Authors: Yu Zhang, Ye Tian, Fang Ye Yixuan Kang

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The capacity of conventional cellular networks has reached its upper bound and it can be well handled by introducing femtocells with low-cost and easy-to-deploy. Spectrum interference issue becomes more critical in peace with the value-added multimedia services growing up increasingly in two-tier cellular networks. Spectrum allocation is one of effective methods in interference mitigation technology. This paper proposes a game-theory-based on OFDMA downlink spectrum allocation aiming at reducing co-channel interference in two-tier femtocell networks. The framework is formulated as a non-cooperative game, wherein the femto base stations are players and frequency channels available are strategies. The scheme takes full account of competitive behavior and fairness among stations. In addition, the utility function reflects the interference from the standpoint of channels essentially. This work focuses on co-channel interference and puts forward a negative logarithm interference function on distance weight ratio aiming at suppressing co-channel interference in the same layer network. This scenario is more suitable for actual network deployment and the system possesses high robustness. According to the proposed mechanism, interference exists only when players employ the same channel for data communication. This paper focuses on implementing spectrum allocation in a distributed fashion. Numerical results show that signal to interference and noise ratio can be obviously improved through the spectrum allocation scheme and the users quality of service in downlink can be satisfied. Besides, the average spectrum efficiency in cellular network can be significantly promoted as simulations results shown.

Keywords: femtocell networks, game theory, interference mitigation, spectrum allocation

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Authors: Serges Mendomo Meye, Li Guowei, Shen Zhenzhong, Gan Lei, Xu Liqun

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Given the limitations of the original whale optimization algorithm (WAO) in local optimum and low convergence accuracy in truss structure optimization problems, based on the fundamental whale algorithm, an improved whale optimization algorithm (SWAO) based on information entropy is proposed. The information entropy itself is an uncertain measure. It is used to control the range of whale searches in path selection. It can overcome the shortcomings of the basic whale optimization algorithm (WAO) and can improve the global convergence speed of the algorithm. Taking truss structure as the optimization research object, the mathematical model of truss structure optimization is established; the cross-sectional area of truss is taken as the design variable; the objective function is the weight of truss structure; and an improved whale optimization algorithm (SWAO) is used for optimization design, which provides a new idea and means for its application in large and complex engineering structure optimization design.

Keywords: information entropy, structural optimization, truss structure, whale algorithm

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Authors: İsmail Şimşekoğlu, Serkan Yılmaz

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There have been great improvements in technology that caused epoch-making changes in aviation. Thus, we can control air vehicles from ground without pilots in them: The UAVs. Due to UAV’s lack of need of pilots and their small size make them have crucial importance for us. UAVs have variety of usage area, especially in military. However, as soldiers we believe that we can use UAVs for better purposes. In this essay we indicate the usage of UAVs for the sake of saving nature from destruction of disasters by expressing what happened in the past and what can possibly happen in the future, especially in firefighting, preventing avalanches and decreasing the effects of floods. These three disasters cause hazardous consequences to the nature. Wildfires endanger so many lives by burning and destroying what comes in their paths. The numbers of avalanches are increased with the global warming. The changes of seasons triggered floods all over the world that threaten the city life. Besides all of these people may lose their lives in order to intrude these disasters. Drones will do the job without involving people lives. Thus it will diminish the risks so drones will be used for the sake of nature and people.

Keywords: unmanned air vehicles, nature, firefighting, avalanche, flood

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Authors: Alexandre M. Brighenti

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The experiment was carried out in Valença, Rio de Janeiro State, Brazil, to evaluate the selectivity and weed control of carotenoid biosynthesis inhibiting herbicides applied alone or in combination with atrazine in elephant grass crop. The treatments were as follows: mesotrione (0.072 and 0.144 kg ha^-1 + 0.5% v/v mineral oil - Assist®), tembotrione (0.075 and 0.100 kg ha^-1 + 0.5% v/v mineral oil - Aureo®), atrazine + mesotrione (1.25 + 0.072 kg ha^-1 + 0.5% v/v mineral oil - Assist®), atrazine + tembotrione (1.25 + 0.100 kg ha^-1 + 0.5% v/v mineral oil - Aureo®), atrazine + mesotrione (1.25 + 0.072 kg ha^-1), atrazine + tembotrione (1.25 + 0.100 kg ha^-1) and two controls (hoed and unhoed check). Two application rates of mesotrione with the addition of mineral oil or the tank mixture of atrazine plus mesotrione, with or without the addition of mineral oil, did not provide injuries capable to reduce elephant grass forage yield. Tembotrione was phytotoxic to elephant grass when applied with mineral oil. Atrazine and tembotrione in a tank-mix, with or without mineral oil, were also phytotoxic to elephant grass. All treatments provided satisfactory weed control.

Keywords: forage, Napier grass, pasture, Pennisetum purpureum, weeds

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Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

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To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

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Authors: A. Mansouri, F. Krim

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This paper discusses the implementation and design of both linear PI and fuzzy controllers for DC-DC boost converters. Design of PI controllers is based on temporal response of closed-loop converters, while fuzzy controllers design is based on heuristic knowledge of boost converters. Linear controller implementation is quite straightforward relying on mathematical models, while fuzzy controller implementation employs one or more artificial intelligences techniques. Comparison between these boost controllers is made in design aspect. Experimental results show that the proposed fuzzy controller system is robust against input voltage and load resistance changing and in respect of start-up transient. Results indicate that fuzzy controller can achieve best control performance concerning faster transient response, steady-state response good stability and accuracy under different operating conditions. Fuzzy controller is more suitable to control boost converters.

Keywords: boost DC-DC converter, fuzzy, PI controllers, power electronics and control system

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Authors: Motahareh Fadaei

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Wireless sensor networks that are used to monitor a special environment, are formed from a large number of sensor nodes. The role of these sensors is to sense special parameters from ambient and to make connection. In these networks, the most important challenge is the management of energy usage. Clustering is one of the methods that are broadly used to face this challenge. In this paper, a distributed clustering protocol based on learning automata is proposed for underwater wireless sensor networks. The proposed algorithm that is called LA-Clustering forms clusters in the same energy level, based on the energy level of nodes and the connection radius regardless of size and the structure of sensor network. The proposed approach is simulated and is compared with some other protocols with considering some metrics such as network lifetime, number of alive nodes, and number of transmitted data. The simulation results demonstrate the efficiency of the proposed approach.

Keywords: clustering, energy consumption‎, learning automata, underwater sensor networks

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Authors: Vytautas Galvanauskas, Rimvydas Simutis, Donatas Levisauskas, Vykantas Grincas, Renaldas Urniezius

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The paper deals with model-based development and implementation of efficient control strategies for recombinant protein synthesis in fed-batch E.coli cultivation processes. Based on experimental data, a kinetic dynamic model for cultivation process was developed. This model was used to determine substrate feeding strategies during the cultivation. The proposed feeding strategy consists of two phases – biomass growth phase and recombinant protein production phase. In the first process phase, substrate-limited process is recommended when the specific growth rate of biomass is about 90-95% of its maximum value. This ensures reduction of glucose concentration in the medium, improves process repeatability, reduces the development of secondary metabolites and other unwanted by-products. The substrate limitation can be enhanced to satisfy restriction on maximum oxygen transfer rate in the bioreactor and to guarantee necessary dissolved carbon dioxide concentration in culture media. In the recombinant protein production phase, the level of substrate limitation and specific growth rate are selected within the range to enable optimal target protein synthesis rate. To account for complex process dynamics, to efficiently exploit the oxygen transfer capability of the bioreactor, and to maintain the required dissolved oxygen concentration, adaptive control algorithms for dissolved oxygen control have been proposed. The developed model-based control strategies are useful in scale-up of cultivation processes and accelerate implementation of innovative biotechnological processes for industrial applications.

Keywords: adaptive algorithms, model-based control, recombinant E. coli, scale-up of bioprocesses

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Authors: Navneet Kalia, Lalit Mohan Verma, Vinay Guleria

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Introduction: Design Flood studies are essential for effective planning and functioning of water resource projects. Design flood estimation for Sunni Dam Hydro Electric Project located in State of Himachal Pradesh, India, on the river Satluj, was a big challenge in view of the river flowing in the Himalayan region from Tibet to India, having a large catchment area of varying topography, climate, and vegetation. No Discharge data was available for the part of the river in Tibet, whereas, for India, it was available only at Khab, Rampur, and Luhri. The estimation of Design Flood using standard methods was not possible. This challenge was met using two different approaches for upper (snow-fed) and lower (rainfed) catchment using Flood Frequency Approach and Hydro-metrological approach. i) For catchment up to Khab Gauging site (Sub-Catchment, C1), Flood Frequency approach was used. Around 90% of the catchment area (46300 sqkm) up to Khab is snow-fed which lies above 4200m. In view of the predominant area being snow-fed area, 1 in 10000 years return period flood estimated using Flood Frequency analysis at Khab was considered as Probable Maximum Flood (PMF). The flood peaks were taken from daily observed discharges at Khab, which were increased by 10% to make them instantaneous. Design Flood of 4184 cumec thus obtained was considered as PMF at Khab. ii) For catchment between Khab and Sunni Dam (Sub-Catchment, C2), Hydro-metrological approach was used. This method is based upon the catchment response to the rainfall pattern observed (Probable Maximum Precipitation - PMP) in a particular catchment area. The design flood computation mainly involves the estimation of a design storm hyetograph and derivation of the catchment response function. A unit hydrograph is assumed to represent the response of the entire catchment area to a unit rainfall. The main advantage of the hydro-metrological approach is that it gives a complete flood hydrograph which allows us to make a realistic determination of its moderation effect while passing through a reservoir or a river reach. These studies were carried out to derive PMF for the catchment area between Khab and Sunni Dam site using a 1-day and 2-day PMP values of 232 and 416 cm respectively. The PMF so obtained was 12920.60 cumec. Final Result: As the Catchment area up to Sunni Dam has been divided into 2 sub-catchments, the Flood Hydrograph for the Catchment C1 has been routed through the connecting channel reach (River Satluj) using Muskingum method and accordingly, the Design Flood was computed after adding the routed flood ordinates with flood ordinates of catchment C2. The total Design Flood (i.e. 2-Day PMF) with a peak of 15473 cumec was obtained. Conclusion: Even though, several factors are relevant while deciding the method to be used for design flood estimation, data availability and the purpose of study are the most important factors. Since, generally, we cannot wait for the hydrological data of adequate quality and quantity to be available, flood estimation has to be done using whatever data is available. Depending upon the type of data available for a particular catchment, the method to be used is to be selected.

Keywords: design flood, design storm, flood frequency, PMF, PMP, unit hydrograph

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Authors: Jungyeol Hong, Dongjoo Park

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The primary purpose of this study is to develop a methodological framework to predict daily subway ridership at a station-level and to examine the association between subway ridership and bus demand incorporating commercial business facility in the vicinity of each subway station. The socio-economic characteristics, land-use, and built environment as factors may have an impact on subway ridership. However, it should be considered not only the endogenous relationship between bus and subway demand but also the characteristics of commercial business within a subway station’s sphere of influence, and integrated transit network topology. Regarding a statistical approach to estimate subway ridership at a station level, therefore it should be considered endogeneity and heteroscedastic issues which might have in the subway ridership prediction model. This study focused on both discovering the impacts of bus demand, commercial business characteristics, and network topology on subway ridership and developing more precise subway ridership estimation accounting for its statistical bias. The spatial scope of the study covers entire Seoul city in South Korea and includes 243 stations with the temporal scope set at twenty-four hours with one-hour interval time panels each. The data for subway and bus ridership was collected Seoul Smart Card data from 2015 and 2016. Three-Stage Least Square(3SLS) approach was applied to develop daily subway ridership model as capturing the endogeneity and heteroscedasticity between bus and subway demand. Independent variables incorporating in the modeling process were commercial business characteristics, social-economic characteristics, safety index, transit facility attributes, and dummies for seasons and time zone. As a result, it was found that bus ridership and subway ridership were endogenous each other and they had a significantly positive sign of coefficients which means one transit mode could increase another transportation mode’s ridership. In other words, two transit modes of subway and bus have a mutual relationship instead of the competitive relationship. The commercial business characteristics are the most critical dimension among the independent variables. The variables of commercial business facility rate in the paper containing six types; medical, educational, recreational, financial, food service, and shopping. From the model result, a higher rate in medical, financial buildings, shopping, and food service facility lead to increment of subway ridership at a station, while recreational and educational facility shows lower subway ridership. The complex network theory was applied for estimating integrated network topology measures that cover the entire Seoul transit network system, and a framework for seeking an impact on subway ridership. The centrality measures were found to be significant and showed a positive sign indicating higher centrality led to more subway ridership at a station level. The results of model accuracy tests by out of samples provided that 3SLS model has less mean square error rather than OLS and showed the methodological approach for the 3SLS model was plausible to estimate more accurate subway ridership. Acknowledgement: This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science and ICT (2017R1C1B2010175).

Keywords: subway ridership, bus ridership, commercial business characteristic, endogeneity, network topology

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Authors: Randy Price, Harbir Antil, Rainald Löhner, Fumiya Togashi

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Chemically reacting flows are common in engineering applications such as hypersonic flow, combustion, explosions, manufacturing process, and environmental assessments. The number of reactions in combustion simulations can exceed 100, making a large number of flow and combustion problems beyond the capabilities of current supercomputers. Motivated by this, deep neural networks (DNNs) will be introduced with the goal of eventually replacing the existing chemistry software packages with DNNs. The DNNs used in this paper are motivated by the Residual Neural Network (ResNet) architecture. In the continuum limit, ResNets become an optimization problem constrained by an ODE. Such a feature allows the use of ODE control techniques to enhance the DNNs. In this work, DNNs are constructed, which update the species un at the nᵗʰ timestep to uⁿ⁺¹ at the n+1ᵗʰ timestep. Parallel DNNs are trained for each species, taking in uⁿ as input and outputting one component of uⁿ⁺¹. These DNNs are applied to multiple species and reactions common in chemically reacting flows such as H₂-O₂ reactions. Experimental results show that the DNNs are able to accurately replicate the dynamics in various situations and in the presence of errors.

Keywords: chemical reacting flows, computational fluid dynamics, ODEs, residual neural networks, ResNets

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Authors: Sagir M. Yusuf, Chris Baber

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We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: Mohammed Seyam, Faridah Othman, Ahmed El-Shafie

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The early warning of high stream flow events (HSF) and floods is an important aspect in the management of surface water and rivers systems. This process can be performed using either process-based models or data driven-based models such as artificial intelligence (AI) techniques. The main goal of this study is to develop efficient AI-based model for predicting the real-time hourly stream flow (Q) and apply it as early warning tool of HSF and floods in the downstream area of the Selangor River basin, taken here as a paradigm of humid tropical rivers in Southeast Asia. The performance of AI-based models has been improved through the integration of the lag time (Lt) estimation in the modelling process. A total of 8753 patterns of Q, water level, and rainfall hourly records representing one-year period (2011) were utilized in the modelling process. Six hydrological scenarios have been arranged through hypothetical cases of input variables to investigate how the changes in RF intensity in upstream stations can lead formation of floods. The initial SF was changed for each scenario in order to include wide range of hydrological situations in this study. The performance evaluation of the developed AI-based model shows that high correlation coefficient (R) between the observed and predicted Q is achieved. The AI-based model has been successfully employed in early warning throughout the advance detection of the hydrological conditions that could lead to formations of floods and HSF, where represented by three levels of severity (i.e., alert, warning, and danger). Based on the results of the scenarios, reaching the danger level in the downstream area required high RF intensity in at least two upstream areas. According to results of applications, it can be concluded that AI-based models are beneficial tools to the local authorities for flood control and awareness.

Keywords: floods, stream flow, hydrological modelling, hydrology, artificial intelligence

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