Search results for: multiple distribution supply chain network

Authors: Jesús Antonio Puente Fernández, Luis Javier Garcia Villalba

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New trends on streaming videos such as series or films require a high demand of network resources. This fact results in a huge problem within traditional IP networks due to the rigidity of its architecture. In this way, Software Defined Networks (SDN) is a new concept of network architecture that intends to be more flexible and it simplifies the management in networks with respect to the existing ones. These aspects are possible due to the separation of control plane (controller) and data plane (switches). Taking the advantage of this separated control, it is easy to deploy a monitoring tool independent of device vendors since the existing ones are dependent on the installation of specialized and expensive hardware. In this paper, we propose a framework that optimizes the traffic monitoring in SDN networks that decreases the number of monitoring queries to improve the network traffic and also reduces the overload. The performed experiments (with and without the optimization) using a video streaming delivery between two hosts demonstrate the feasibility of our monitoring proposal.

Keywords: optimization, monitoring, software defined networking, statistics, query

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Authors: Andrew John Zeller, Artjoms Formulevics

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Banking and financial services are rapidly transitioning from being monolithic structures focusing merely on their own financial offerings to becoming integrated players in multiple customer journeys and supply chains. Banks themselves are refocusing on being liquidity providers and underwriters in these networks, while the general concept of ‘embeddedness’ builds on the market readily available API (Application Programming Interface) architectures to flexibly deliver services to various requestors, i.e., online retailers who need finance and insurance products to better serve their customers, respectively. With this new flexibility come new requirements for enhanced cybersecurity. API structures are more decentralized and inherently prone to change. Unfortunately, this has not been comprehensively addressed in the literature. This paper tries to fill this gap by looking at security approaches and technologies relevant to API architectures found in embedded finance. After presenting the research methodology applied and introducing the major bodies of knowledge involved, the paper will discuss six dominating technology trends shaping high-level financial services architectures. Subsequently, embedded finance and the respective usage of API strategies will be described. Building on this, security considerations for APIs in financial and insurance services will be elaborated on before concluding with some ideas for possible further research.

Keywords: embedded finance, embedded banking strategy, cybersecurity, API management, data security, cybersecurity, IT management

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Authors: Prakash K. Aithal, U. Dinesh Acharya, Rajesh Gopakumar

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Edge is variation of brightness in an image. Edge detection is useful in many application areas such as finding forests, rivers from a satellite image, detecting broken bone in a medical image etc. The paper discusses about finding edge of multiple aerial images in parallel .The proposed work tested on 38 images 37 colored and one monochrome image. The time taken to process N images in parallel is equivalent to time taken to process 1 image in sequential. The proposed method achieves pixel level parallelism as well as image level parallelism.

Keywords: edge detection, multicore, gpu, opencl, mpi

Procedia PDF Downloads 462

Authors: M. A. At-Tasneem, N. T. Rao, T. M. Y. S. Tuan Ya, M. S. Idris, M. Ammar

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River flow over micro hydro power (MHP) turbines of multiple arrays arrangement is simulated with computational fluid dynamics (CFD) software to obtain the flow characteristics. In this paper, CFD software is used to simulate the water flow over MHP turbines as they are placed in a river. Multiple arrays arrangement of MHP turbines lead to generate large amount of power. In this study, a river model is created and simulated in CFD software to obtain the water flow characteristic. The process then continued by simulating different types of arrays arrangement in the river model. A MHP turbine model consists of a turbine outer body and static propeller blade in it. Five types of arrangements are used which are parallel, series, triangular, square and rhombus with different spacing sizes. The velocity profiles on each MHP turbines are identified at the mouth of each turbine bodies. This study is required to obtain the arrangement with increasing spacing sizes that can produce highest power density through the water flow variation.

Keywords: micro hydro power, CFD, arrays arrangement, spacing sizes, velocity profile, power

Procedia PDF Downloads 350

Authors: Chimezie P. Nnanwa, Thomas C. Urama, Patrick O. Ezepue

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In this paper we use Random Matrix Theory to analyze the eigen-structure of the empirical correlations of 82 stocks which are consistently traded in the Nigerian Stock Exchange (NSE) over a 4-year study period 3 August 2009 to 26 August 2013. We apply the Marchenko-Pastur distribution of eigenvalues of a purely random matrix to investigate the presence of investment-pertinent information contained in the empirical correlation matrix of the selected stocks. We use hypothesised standard normal distribution of eigenvector components from RMT to assess deviations of the empirical eigenvectors to this distribution for different eigenvalues. We also use the Inverse Participation Ratio to measure the deviation of eigenvectors of the empirical correlation matrix from RMT results. These preliminary results on the dynamics of asset price correlations in the NSE are important for improving risk-return trade-offs associated with Markowitz’s portfolio optimization in the stock exchange, which is pursued in future work.

Keywords: correlation matrix, eigenvalue and eigenvector, inverse participation ratio, portfolio optimization, random matrix theory

Procedia PDF Downloads 330

Authors: Mokrani Mohamed Amine

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In this paper, we have implemented successive interference cancellation algorithms in the 5G downlink. We have calculated the maximum throughput in Frequency Division Duplex (FDD) mode in the downlink, where we have obtained a value equal to 836932 b/ms. The transmitter is of type Multiple Input Multiple Output (MIMO) with eight transmitting and receiving antennas. Each antenna among eight transmits simultaneously a data rate of 104616 b/ms that contains the binary messages of the three users; in this case, the Cyclic Redundancy Check CRC is negligible, and the MIMO category is the spatial diversity. The technology used for this is called Non-Orthogonal Multiple Access (NOMA) with a Quadrature Phase Shift Keying (QPSK) modulation. The transmission is done in a Rayleigh fading channel with the presence of obstacles. The MIMO Successive Interference Cancellation (SIC) receiver with two transmitting and receiving antennas recovers its binary message without errors for certain values of transmission power such as 50 dBm, with 0.054485% errors when the transmitted power is 20dBm and with 0.00286763% errors for a transmitted power of 32 dBm(in the case of user 1) as well as with 0.0114705% errors when the transmitted power is 20 dBm also with 0.00286763% errors for a power of 24 dBm(in the case of user2) by applying the steps involved in SIC.

Keywords: 5G, NOMA, QPSK, TBS, LDPC, SIC, capacity

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Authors: Elizabeth Malebogo Mosepele

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Road transport has become increasingly common in the world; people rely on road networks for transportation purpose on a daily basis. However, environmental impact of roads on surrounding landscapes extends their potential effects even further. This study investigates the impact of road network on natural vegetation. The study will provide baseline knowledge regarding roadside vegetation and would be helpful in future for conservation of biodiversity along the road verges and improvements of road verges. The general hypothesis of this study is that the amount and condition of road side vegetation could be explained by road network conditions. Remote sensing techniques were used to analyze vegetation conditions. Landsat 8 OLI image was used to assess vegetation cover condition. NDVI image was generated and used as a base from which land cover classes were extracted, comprising four categories viz. healthy vegetation, degraded vegetation, bare surface, and water. The classification of the image was achieved using the supervised classification technique. Road networks were digitized from Google Earth. For observed data, transect based quadrats of 50*50 m were conducted next to road segments for vegetation assessment. Vegetation condition was related to road network, with the multinomial logistic regression confirming a significant relationship between vegetation condition and road network. The null hypothesis formulated was that 'there is no variation in vegetation condition as we move away from the road.' Analysis of vegetation condition revealed degraded vegetation within close proximity of a road segment and healthy vegetation as the distance increase away from the road. The Chi Squared value was compared with critical value of 3.84, at the significance level of 0.05 to determine the significance of relationship. Given that the Chi squared value was 395, 5004, the null hypothesis was therefore rejected; there is significant variation in vegetation the distance increases away from the road. The conclusion is that the road network plays an important role in the condition of vegetation.

Keywords: Chi squared, geographic information system, multinomial logistic regression, remote sensing, road side vegetation

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Authors: A. Bolaji Adesoye, Alimi Olorunfemi

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This paper examines the impact of small and medium-scale enterprises (SMEs) credit financing and financial market development and their shocks on the output growth of Nigeria. The study estimated a VAR model for Nigeria using 1970-2013 annual data series. Unit root tests and cointegration are carried out. The study also explores IRFs and FEVDs in a system that includes output, commercial bank loan to SMEs, domestic credit to private sector by banks, money supply, lending rate and investment. Findings suggest that shocks in commercial bank credit to SMEs has a major impact on the output changes of Nigeria. Money supply shocks also have a sizeable impact on output growth variations amidst other financial instruments. Lastly, neutrality of investment does not hold in Nigeria as it also has impact on output fluctuations.

Keywords: SMEs financing, financial development, investment, output, Nigeria

Procedia PDF Downloads 394

Authors: Eman H. El-Gamal, Mai E. Khedr, Randa Ghonim, Mohamed Rashad

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In the past few years, biochar - a highly carbon-rich material produced from agro-wastes by pyrolysis process - was used as an effective adsorbent for heavy metals removal from polluted water. In this study, different types of biochar (rice straw 'RSB', corn cob 'CCB', and Jatropha shell 'JSB' were used to evaluate the adsorption capacity of heavy metals removal from multiple-metal solutions (Cu, Mn, Zn, and Cd). Kinetics modeling has been examined to illustrate potential adsorption mechanisms. The results showed that the potential removal of metal is dependent on the metal and biochar types. The adsorption capacity of the biochars followed the order: RSB > JSB > CCB. In general, RSB and JSB biochars presented high potential removal of heavy metals from polluted water, which was higher than 90 and 80% after 2 hrs of contact time for all metals, respectively. According to the kinetics data, the pseudo-second-order model was agreed strongly with Cu, Mn, Zn, and Cd adsorption onto the biochars (R2 ≥ 0.97), indicating the dominance of specific adsorption process, i.e., chemisorption. In conclusion, this study revealed that RSB and JSB biochar have the potential to be a strong adsorbent for multiple-metal removal from wastewater.

Keywords: adsorption, biochar, chemisorption, polluted water

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Authors: M. Heydari Vini

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There is a complicated relation between effective input parameters of cold rolling and output rolling force and exit thickness of strips.in many mathematical models, the effect of some rolling parameters have been ignored and the outputs have not a desirable accuracy. In the other hand, there is a special relation among input thickness of strips,the width of the strips,rolling speeds,mandrill tensions and the required exit thickness of strips with rolling force and the real exit thickness of the rolled strip. First of all, in this paper the effective parameters of cold rolling process modeled using an artificial neural network according to the optimum network achieved by using a written program in MATLAB,it has been shown that the prediction of rolling stand parameters with different properties and new dimensions attained from prior rolled strips by an artificial neural network is applicable.

Keywords: cold rolling, artificial neural networks, rolling force, real rolled thickness of strips

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Authors: Jonathan Heng, Yoong Cheah Huei

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A strategic model that does not trigger any false alarms to detect anomalies in Secure Water Treatment (SWaT) test bed is presented. This model uses machine learning invariants formulated from streamlining the general form of Auto-Regressive models with eXogenous input. A creative generalized CUSUM algorithm to integrate the invariants and the detection strategy technique is successfully developed and tested in the SWaT Programmable Logic Controllers (PLCs). Three steps to fine-tune parameters, b and τ in the generalized algorithm are stated and an example used to demonstrate the tuning process is discussed. This approach can swiftly and effectively detect various scopes of cyber-attacks such as multiple points single stage and multiple points multiple stages in SWaT. This technique can be applied in water treatment plants and other cyber physical systems like power and gas plants too.

Keywords: machine learning invariants, generalized CUSUM algorithm with invariants and detection strategy, scope of cyber attacks, strategic model, tuning parameters

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Authors: Sharein El-Tourky, Sharon Smith, Gary Hitchcock

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Effective fisheries management is necessarily dependent on the accuracy of fisheries models, which can be limited if they omit critical elements. One critical element in the formulation of these models is the trophic interactions at the larval stage of fish development. At this stage, fish mortality rates are at their peak and survival is often determined by resource limitation. Thus it is crucial to identify and quantify essential prey resources and determine how they vary in abundance and availability. The main resources larval fish consume are mesozooplankton. In the Straits of Florida, little is known about temporal and spatial variability of the mesozooplankton community despite its importance as a spawning ground for fish such as the Blue Marlin. To investigate mesozooplankton distribution patterns in the Straits of Florida, a transect of 16 stations from Miami to the Bahamas was sampled once a month in 2003 and 2004 at four depths. We found marked temporal and spatial variability in mesozooplankton biomass, diversity, and depth distribution. Mesozooplankton biomass peaked on the western boundary of the SOF and decreased gradually across the straits to a minimum at eastern stations. Midcurrent stations appeared to be a region of enhanced year-round variability, but limited seasonality. Examination of dominant zooplankton groups revealed groups could be parsed into 6 clusters based on abundance. Of these zooplankton groups, copepods were the most abundant zooplankton group, with the 20 most abundant species making up 86% of the copepod community. Copepod diversity was lowest at midcurrent stations and highest in the Eastern SOF. Interestingly, one copepods species, previously identified to compose up to 90% of larval blue marlin and sailfish diets in the SOF, had a mean abundance of less than 7%. However, the unique spatial and vertical distribution patterns of this copepod coincide with peak larval fish spawning periods and larval distribution, suggesting an important relationship requiring further investigation.

Keywords: mesozooplankton biodiversity, larval fish diet, food web, Straits of Florida, vertical distribution, spatiotemporal variability, cross-current comparisons, Gulf Stream

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Authors: Nishant Parashar, Sawan S. Sinha, Balaji Srinivasan

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We perform an investigation of the unclosed terms in the evolution equation of the velocity gradient tensor (VGT) in compressible decaying turbulent flow. Velocity gradients in a compressible turbulent flow field influence several important nonlinear turbulent processes like cascading and intermittency. In an attempt to understand the dynamics of the velocity gradients various researchers have tried to model the unclosed terms in the evolution equation of the VGT. The existing models proposed for these unclosed terms have limited applicability. This is mainly attributable to the complex structure of the higher order gradient terms appearing in the evolution equation of VGT. We investigate these higher order gradients using the data from direct numerical simulation (DNS) of compressible decaying isotropic turbulent flow. The gas kinetic method aided with weighted essentially non-oscillatory scheme (WENO) based flow- reconstruction is employed to generate DNS data. By applying neural-network to the DNS data, we map the structure of the unclosed higher order gradient terms in the evolution of the equation of the VGT with VGT itself. We validate our findings by performing alignment based study of the unclosed higher order gradient terms obtained using the neural network with the strain rate eigenvectors.

Keywords: compressible turbulence, neural network, velocity gradient tensor, direct numerical simulation

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Authors: Vakhtang Geladze, Nana Bolashvili, Tamazi Karalashvili, Nino Machavariani, Vajha Neidze, Nana Kvirkvelia, Tamar Chichinadze

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Deficiency of fresh water is a vital global problem today. It must be taken into consideration that in the nearest future fresh water crisis will become even more acute owing to the global climate warming and fast desertification processes in the world. Georgia has signed the association agreement with Euro Union last year where the priority spheres of cooperation are the management of water resources, development of trans-boundary approach to the problem and active participation in the “Euro Union water initiative” component of “the East Europe, Caucasus and the Central Asia”. Fresh water resources are the main natural wealth of Georgia. According to the average water layer height, Georgia is behind such European countries only as Norway, Switzerland and Austria. The annual average water provision of Georgia is 4-8 times higher than in its neighbor countries Armenia and Azerbaijan. Despite abundant water resources in Georgia, there is considerable discrepancy between their volume and use in some regions because of the uneven territorial distribution. In the East Georgia, water supply of the territory and population is four times less than in the West Georgia.

Keywords: GIS, water consumption, water management, water resources

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Authors: Hamed Najafi, Ghasem Nikjou

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Nowadays, there is an increasing attention to the resources scarcity issues. Because of failure in present patterns in the field of the allocation of exhaustible resources between generations and the challenges related to economic justice supply, it is supposed, to present a pattern from the Islamic perspective in this essay. By using content analysis of religious texts, we conclude that governments should remove the gap which is exists between the per capita income of the poor and their minimum consumption (necessary consumption). In order to preserve the exhaustible resources for poor people) not for all), between all generations, government should invest exhaustible resources on endless resources according to Hartwick’s criteria and should spend these benefits for poor people. But, if benefits did not cover the gap between minimum consumption and per capita income of poor levels in one generation, in this case, the government is responsible for covering this gap through the direct consumption of exhaustible resources. For an exact answer to this question, ‘how much of exhaustible resources should expense to maintain justice between generations?’ The theoretical and mathematical modeling has been used and proper function has been provided. The consumption pattern is presented for economic policy makers in Muslim countries, and non-Muslim even, it can be useful.

Keywords: exhaustible resources, Islamic justice, intergenerational justice, distribution of resources, Hartwick criteria

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Authors: Khitem Amiri, Mohamed Farah

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Image classification is a challenging task and is gaining lots of interest since it helps us to understand the content of images. Recently Deep Learning (DL) based methods gave very interesting results on several benchmarks. For Hyperspectral images (HSI), the application of DL techniques is still challenging due to the scarcity of labeled data and to the curse of dimensionality. Among other approaches, Deep Belief Network (DBN) based approaches gave a fair classification accuracy. In this paper, we address the problem of the curse of dimensionality by reducing the number of bands and replacing the HSI channels by the channels representing radiometric indices. Therefore, instead of using all the HSI bands, we compute the radiometric indices such as NDVI (Normalized Difference Vegetation Index), NDWI (Normalized Difference Water Index), etc, and we use the combination of these indices as input for the Deep Belief Network (DBN) based classification model. Thus, we keep almost all the pertinent spectral information while reducing considerably the size of the image. In order to test our image representation, we applied our method on several HSI datasets including the Indian pines dataset, Jasper Ridge data and it gave comparable results to the state of the art methods while reducing considerably the time of training and testing.

Keywords: hyperspectral images, deep belief network, radiometric indices, image classification

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Authors: Vivian Wu

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During the mating season, honeybee drones make mating fights to congregation areas where they face fierce competition to mate with a queen. Drones have developed distinct anatomical and functional features in order to optimize their chances of success. Flight activities of western honeybee (Apis mellifera) drones and foragers were monitored using radio frequency identification (RFID) to test if drones have also developed distinct flight behaviors. Drone flight durations showed a bimodal distribution dividing the flights into short flights and long flights while forager flight durations showed a left-skewed unimodal distribution. Interestingly, the short trips occurred prior to the long trips on a daily basis. The first trips of the day the drones made were primarily short trips, and the distribution significantly shifted to long trips as the drones made more trips. In contrast, forager trips showed no such shift of distribution. In addition, drones made short trips but no long mating trips on days associated with a significant drop in temperature and increase of clouds compared to the previous day. These findings suggest that drones may have developed a unique flight behavior making short trips first to survey the weather conditions before flying out to the congregation area to pursue a successful mating.

Keywords: apis mellifera, drone, flight behavior, weather, RFID

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Authors: Adhitya Mangala, Yobel

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Bittuang geothermal prospect area located at Tana Toraja district, South Sulawesi. The geothermal system of the area related to Karua Volcano eruption product. This area has surface manifestation such as fumarole, hot springs, sinter silica and mineral alteration. Those prove that there are hydrothermal activities in the subsurface. However, the project and development of the area have not implemented yet. One of the important elements in geothermal exploration is to determine upflow and outflow zone. This information very useful to identify the target for geothermal wells and development which it is a risky task. The methods used in this research were Mercury (Hg) anomalies in soil, soil and manifestation temperature distribution and fault fracture density from 93 km² research area. Hg anomalies performed to determine the distribution of hydrothermal alteration. Soil and manifestation temperature distribution were conducted to estimate heat distribution. Fault fracture density (FFD) useful to determine fracture intensity and trend from surface observation. Those deliver Hg anomaly map, soil and manifestation temperature map that combined overlayed to fault fracture density map and geological map. Then, the conceptual model made from north – south, and east – west cross section to delineate upflow and outflow zone in this area. The result shows that upflow zone located in northern – northeastern of the research area with the increase of elevation and decrease of Hg anomalies and soil temperature. The outflow zone located in southern - southeastern of the research area which characterized by chloride, chloride - bicarbonate geothermal fluid type, higher soil temperature, and Hg anomalies. The range of soil temperature distribution from 16 – 19 °C in upflow and 19 – 26.5 °C in the outflow. The range of Hg from 0 – 200 ppb in upflow and 200 – 520 ppb in the outflow. Structural control of the area show northwest – southeast trend. The boundary between upflow and outflow zone in 1550 – 1650 m elevation. This research delivers the conceptual model with innovative methods that useful to identify a target for geothermal wells, project, and development in Bittuang geothermal prospect area.

Keywords: Bittuang geothermal prospect area, Hg anomalies, soil temperature, upflow and outflow zone

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Authors: An-Jui. Li, Kelvin Lim, Chien-Kuo Chiu, Benson Hsiung

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This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.

Keywords: landslide, limit analysis, artificial neural network, soil properties

Procedia PDF Downloads 187

Authors: M. Ebrahimi, E. Maroufyan, M. Shakeri, E. Oskoueian, A. F Soleimani, Y. M. Goh

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Lipid peroxidation is a main reason of low quality in meat and meat products. The free radical chain reaction is the major process of lipid peroxidation and reactive oxygen species (ROS) such as hydroxyl radical and hydroperoxyl radical are the main starter of the chain reaction. Papaya leaf contains several secondary metabolites which can be used as a potential antioxidant in broiler feed. Hence, this research was carried out to evaluate the potential of papaya leaf to prevent lipid peroxidation and enhance the antioxidant activity of breast meat of broiler chicken. The results showed that supplementation of papaya leaf at 5%, significantly (p < 0.05) reduced the lipid peroxidation compared to control group. The supplementation of papaya leaf prevented from lipid peroxidation and enhanced the antioxidant activity of the broiler breast meat significantly (p < 0.05) after different storage periods. Papaya leaf reduced the lipid oxidation of meat during storage with strong free radical-scavenging ability. In conclusion, supplementation of papaya leaf in broiler diet to have high quality meat is recommended.

Keywords: antioxidant activity, papaya leaf, breast meat, lipid peroxidation

Procedia PDF Downloads 587

Authors: J. K Adedeji, O. H Olowomofe, C. O Alo, S.T Ijatuyi

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The issue of high blood sugar level, the effects of which might end up as diabetes mellitus, is now becoming a rampant cardiovascular disorder in our community. In recent times, a lack of awareness among most people makes this disease a silent killer. The situation calls for urgency, hence the need to design a device that serves as a monitoring tool such as a wrist watch to give an alert of the danger a head of time to those living with high blood glucose, as well as to introduce a mechanism for checks and balances. The neural network architecture assumed 8-15-10 configuration with eight neurons at the input stage including a bias, 15 neurons at the hidden layer at the processing stage, and 10 neurons at the output stage indicating likely symptoms cases. The inputs are formed using the exclusive OR (XOR), with the expectation of getting an XOR output as the threshold value for diabetic symptom cases. The neural algorithm is coded in Java language with 1000 epoch runs to bring the errors into the barest minimum. The internal circuitry of the device comprises the compatible hardware requirement that matches the nature of each of the input neurons. The light emitting diodes (LED) of red, green, and yellow colors are used as the output for the neural network to show pattern recognition for severe cases, pre-hypertensive cases and normal without the traces of diabetes mellitus. The research concluded that neural network is an efficient Accu-Chek design tool for the proper monitoring of high glucose levels than the conventional methods of carrying out blood test.

Keywords: Accu-Check, diabetes, neural network, pattern recognition

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Authors: Yuxin Wu, Yu-Shing Wang, Zitao Zhang

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A high-speed and time-lapse S-wave velocity measurement system has been built up for S-wave tomography in sand. This system is based on bender elements and applied to model pile tests in a tailor-made pressurized chamber to monitor the shear wave velocity distribution during pile installation in sand. Tactile pressure sensors are used parallel together with bender elements to monitor the stress changes during the tests. Strain gages are used to monitor the shaft resistance and toe resistance of pile. Since the shear wave velocity (Vs) is determined by the shear modulus of sand and the shaft resistance of pile is also influenced by the shear modulus of sand around the pile, the purposes of this study are to time-lapse monitor the S-wave velocity distribution change at a certain horizontal section during pile installation and to correlate the S-wave velocity distribution and shaft resistance of pile in sand.

Keywords: bender element, pile, shaft resistance, shear wave velocity, tomography

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Authors: Kyugneun Lee, Ikjin Lee

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Parameter estimation with inverse problem often suffers from unfavorable conditions in the real world. Useless data and many input parameters make the problem complicated or insoluble. Data refinement and reformulation of the problem can solve that kind of difficulties. In this research, a method to solve the rank deficient inverse problem is suggested. A multi-physics system which has rank deficiency caused by response correlation is treated. Impeditive information is removed and the problem is reformulated to sequential estimations using Bayesian network (BN) and subset groups. At first, subset grouping of the responses is performed. Feature selection with singular value decomposition (SVD) is used for the grouping. Next, BN inference is used for sequential conditional estimation according to the group hierarchy. Directed acyclic graph (DAG) structure is organized to maximize the estimation ability. Variance ratio of response to noise is used to pairing the estimable parameters by each response.

Keywords: Bayesian network, feature selection, rank deficiency, statistical inverse analysis

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Authors: Esra Arici, Duygu Olmez, Murat Ozkan, Nurcan Topcu, Furkan Capraz, Gokhan Deniz, Arman Altinyay

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Engineered quartz stone is a composite material comprising approximately 90 wt.% fine quartz aggregate with a variety of particle size ranges and `10 wt.% unsaturated polyester resin (UPR). In this study, the objective is to investigate the influence of particle size distribution on mechanical strength and physical properties of the engineered stone slabs. For this purpose, granular quartz with two particle size ranges of 63-200 µm and 100-300 µm were used individually and mixed with a difference in ratios of mixing. The void volume of each granular packing was measured in order to define the amount of filler; quartz powder with the size of less than 38 µm, and UPR required filling inter-particle spaces. Test slabs were prepared using vibration-compression under vacuum. The study reports that both impact strength and flexural strength of samples increased as the mix ratio of the particle size range of 63-200 µm increased. On the other hand, the values of water absorption rate, apparent density and abrasion resistance were not affected by the particle size distribution owing to vacuum compaction. It is found that increasing the mix ratio of the particle size range of 63-200 µm caused the higher porosity. This led to increasing in the amount of the binder paste needed. It is also observed that homogeneity in the slabs was improved with the particle size range of 63-200 µm.

Keywords: engineered quartz stone, fine quartz aggregate, granular packing, mechanical strength, particle size distribution, physical properties.

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Authors: Jacob Wahl, Jane Zhang

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This paper describes the development and characterization of a prototype IoT network for use with agricultural imaging and monitoring applications. The sensor and gateway nodes are designed using the ESP32 SoC with integrated Bluetooth Low Energy 4.2 and Wi-Fi. A development board, the Arducam IoTai ESP32, is used for prototyping, testing, and power measurements. Google’s Firebase is used as the cloud storage site for image data collected by the sensor. The sensor node captures images using the OV2640 2MP camera module and transmits the image data to the gateway via Bluetooth Low Energy. The gateway then uploads the collected images to Firebase via a known nearby Wi-Fi network connection. This image data can then be processed and analyzed by computer vision and machine learning pipelines to assess crop growth or other needs. The sensor node achieves a wireless transmission data throughput of 220kbps while consuming 150mA of current; the sensor sleeps at 162µA. The sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day based on the development board power measurements. This network can be utilized by any application that requires high data rates, low power consumption, short-range communication, and large amounts of data to be transmitted at low-frequency intervals.

Keywords: Bluetooth low energy, ESP32, firebase cloud, IoT, smart farming

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Authors: Jude K. Safo

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Knowledge Graphs KG) and their relation to Graph Embeddings (GE) represent a unique data structure in the landscape of machine learning (relative to image, text and acoustic data). Unlike the latter, GEs are the only data structure sufficient for representing hierarchically dense, semantic information needed for use-cases like supply chain data and protein folding where the search space exceeds the limits traditional search methods (e.g. page-rank, Dijkstra, etc.). While GEs are effective for compressing low rank tensor data, at scale, they begin to introduce a new problem of ’data retreival’ which we observe in Large Language Models. Notable attempts by transE, TransR and other prominent industry standards have shown a peak performance just north of 57% on WN18 and FB15K benchmarks, insufficient practical industry applications. They’re also limited, in scope, to next node/link predictions. Traditional linear methods like Tucker, CP, PARAFAC and CANDECOMP quickly hit memory limits on tensors exceeding 6.4 million nodes. This paper outlines a topological framework for linear mapping between concepts in KG space and GE space that preserve cardinality. Most importantly we introduce a traceable framework for composing dense linguistic strcutures. We demonstrate performance on WN18 benchmark this model hits. This model does not rely on Large Langauge Models (LLM) though the applications are certainy relevant here as well.

Keywords: representation theory, large language models, graph embeddings, applied algebraic topology, applied knot theory, combinatorics

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Authors: Walter W. Loo

Abstract:

China declared the “zero discharge rules which leave no toxics into our living environment and deliver blue sky, green land and clean water to many generations to come”. The achievement of ZWD will provide conservation of water, soil and energy and provide drastic increase in Gross Domestic Products (GDP). Our society’s engine needs a major tune up; it is sputtering. ZWD is achieved in world’s space stations – no toxic air emission and the water is totally recycled and solid wastes all come back to earth. This is all done with solar power. These are all achieved under extreme temperature, pressure and zero gravity in space. ZWD can be achieved on earth under much less fluctuations in temperature, pressure and normal gravity environment. ZWD systems are not expensive and will have multiple beneficial returns on investment which are both financially and environmentally acceptable. The paper will include successful case histories since the mid-1970s. ZWD discharge can be applied to the following types of projects: nuclear and coal fire power plants with a closed loop system that will eliminate thermal water discharge; residential communities with wastewater treatment sump and recycle the water use as a secondary water supply; waste water treatment Plants with complete water recycling including water distillation to produce distilled water by very economical 24-hours solar power plant. Landfill remediation is based on neutralization of landfilled gas odor and preventing anaerobic leachate formation. It is an aerobic condition which will render landfill gas emission explosion proof. Desert development is the development of recovering soil moisture from soil and completing a closed loop water cycle by solar energy within and underneath an enclosed greenhouse. Salt-alkali land development can be achieved by solar distillation of salty shallow water into distilled water. The distilled water can be used for soil washing and irrigation and complete a closed loop water cycle with energy and water conservation. Heavy metals remediation can be achieved by precipitation of dissolved toxic metals below the plant or vegetation root zone by solar electricity without pumping and treating. Soil and groundwater remediation - abandoned refineries, chemical and pesticide factories can be remediated by in-situ electrobiochemical and bioventing treatment method without pumping or excavation. Toxic organic chemicals are oxidized into carbon dioxide and heavy metals precipitated below plant and vegetation root zone. New water sources: low temperature distilled water can be recycled for repeated use within a greenhouse environment by solar distillation; nano bubble water can be made from the distilled water with nano bubbles of oxygen, nitrogen and carbon dioxide from air (fertilizer water) and also eliminate the use of pesticides because the nano oxygen will break the insect growth chain in the larvae state. Three dimensional high yield greenhouses can be constructed by complete water recycling using the vadose zone soil as a filter with no farming wastewater discharge.

Keywords: greenhouses, no discharge, remediation of soil and water, wastewater

Procedia PDF Downloads 335

Authors: Rahman Mofidi, Sina Rahimi, Farnoosh Darban

Abstract:

Communication plays a key role in today’s world, and to support it, the quality of service has the highest priority. It is very important to differentiate between traffic based on priority level. Some traffic classes should be a higher priority than other classes. It is also necessary to give high priority to customers who have more payment for better service, however, without influence on other customers. So to realize that, we will require effective quality of service methods. To ensure the optimal performance of the network in accordance with the quality of service is an important goal for all operators in the mobile network. In this work, we propose an algorithm based on control parameters which it’s based on user feedback that aims at minimizing the access to system transmit power and thus improving the network key performance indicators and increasing the quality of service. This feedback that is known as channel quality indicator (CQI) indicates the received signal level of the user. We aim at proposing an algorithm in control parameter criterion to study improving the quality of service and throughput in a cellular network at the simulated environment. In this work we tried to parameter values have close to their actual level. Simulation results show that the proposed algorithm improves the system throughput and thus satisfies users' throughput and improves service to set up a successful call.

Keywords: quality of service, key performance indicators, control parameter, channel quality indicator

Procedia PDF Downloads 183

Authors: Safayat Ali Shaikh

Abstract:

Software has been developed for optimal cropping pattern in an irrigation project considering land constraint, water availability constraint and pick up flow constraint using modified Simplex Algorithm. Artificial Neural Network Models (ANN) have been developed to predict rainfall. AR (1) model used to generate 1000 years rainfall data to train the ANN. Simulation has been done with expected rainfall data. Eight number crops and three types of soil class have been considered for optimization model. Area under each crop and each soil class have been quantified using Modified Simplex Algorithm to get optimum net return. Efficacy of the software has been tested using data of large irrigation project in India.

Keywords: artificial neural network, large irrigation project, modified simplex algorithm, optimal cropping pattern

Procedia PDF Downloads 192

Authors: Titin Handayani, Endang Yuniastuti

Abstract:

Kepuh (Sterculia foetida L.) is a potential plant contain mainly oil seeds that can be used as a source of alternative bioenergy and medicine. The main problem of kepuh cultivation is the limited supply of seed plants. Seeds development were very easy, but to produce fruit have to wait for approximately 5 years. The objective of this research was to obtain kepuh plants through direct in vitro regeneration. Hypocotyls and shoot tips explants were excised from sterile germinated seedlings and placed on shoot induction medium containing basal salts of Murashige and Skoog (MS) and various concentrations of plant growth regulators. The results showed that shoots induction from the apical and axillary buds on MS medium + 1.5 and 2 mg/L BAP and 0.5 and 1 mg/L IAA was growth very slowly. Increasing of BAP concentrations was increased shoot formation. The first subcultures were increased the rate of shoots growth on MS medium supplemented with 2 mg/L BAP and 0.5 mg/L IAA. The second of shoots subculture on MS medium + 1.5 to 2 mg/L BAP + 0.5 mg/L IAA was increased the number of shoots up to 4.8 in average. The best medium of shoots elongation were MS + 1 mgL-1 kinetin + 5 mg/L GA3. The highest percentage of roots (65%) occurred on MS medium with 5 mg/L IBA which average number of roots was 3.1. High percentages of survival and plants of normal appearance were obtained after five weeks of acclimatization.

Keywords: Kepuh, Sterculia foetida L, shoot multiplication, rooting, acclimatization, bioenergy, medicine

Procedia PDF Downloads 281