Search results for: optimal overbooking level

Authors: Pallavi Bhogaram, Xiaolong Wu, Min He, Onyedikachi Okenwa

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A transportation network is a realization of a spatial network, describing a structure which permits either vehicular movement or flow of some commodity. Examples include road networks, railways, air routes, pipelines, and many more. The transportation network plays a vital role in maintaining the vigor of the nation’s economy. Hence, ensuring the network stays resilient all the time, especially in the face of challenges such as heavy traffic loads and large scale natural disasters, is of utmost importance. In this paper, we used the Neo4j application to develop the graph. Neo4j is the world's leading open-source, NoSQL, a native graph database that implements an ACID-compliant transactional backend to applications. The Southern California network model is developed using the Neo4j application and obtained the most critical and optimal nodes and paths in the network using centrality algorithms. The edge betweenness centrality algorithm calculates the critical or optimal paths using Yen's k-shortest paths algorithm, and the node betweenness centrality algorithm calculates the amount of influence a node has over the network. The preliminary study results confirm that the Neo4j application can be a suitable tool to study the important nodes and the critical paths for the major congested metropolitan area.

Keywords: critical path, transportation network, connectivity reliability, network model, Neo4j application, edge betweenness centrality index

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Authors: Mohammad Saeri, Zainal Arifin

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The purpose of this study is to obtain information on technical and social-economic feasibility of sugarcane-soybean. To achieve these objectives, soybeans intercropping study was conducted in sugar cane crops. This assessment was conducted in two locations with different agroecosystem,ie lowland of low plain in Mojokerto, East Java, with altitude of 50m above sea level and upland of medium plain in Malang, East Javawithaltitude of 500 m above the sea level. The design used was Split plot, with the main plots, is the soybean varieties, consisting of: (a) Anjasmoro, (b) Argomulyo, and (c) Dena-1, while the subplot is bio-fertilizer, consisting of : (1) Agrimeth, (2) Agrisoy, and (3) Biovarm. The variables observed were growth, yield and yield components and economic analysis. The yield of soybean in lowland reached 0.74 t/ha of seeds with farm profit of Indonesian Rupiah 359.200. This result is relatively low due to the delay of soybean cultivation from sugar cane soup time so that sugar cane cover soybean cultivation, while in upland obtained 0.92t/ha seeds with farm profit of Indonesian Rupiah 2,015,000. Therefore, it is suggested that soybeans are planted immediately after ratoon cane so that soybean growth can be optimal before the growth of sugarcane cover the soil surface. The yield of sugar cane in the lowland reached 124.5 tons with a profit of Indonesian Rupiah. 21,200,000,- while in upland obtained by sugarcane yield equal to 78,5 ton with profit equal to Indonesian Rupiah 8,900,000,-.

Keywords: intercropping, sugar cane, soybean, profit, farming

Procedia PDF Downloads 129

Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang

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For the pilot design of the sparse channel estimation model in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems, the observation matrix constructed according to the matrix cross-correlation criterion, total correlation criterion and other optimization criteria are not optimal, resulting in inaccurate channel estimation and high bit error rate at the receiver. This paper proposes a pilot design method combining high-power sum and high-power variance criteria, which can more accurately estimate the channel. First, the pilot insertion position is designed according to the high-power variance criterion under the condition of equal power. Then, according to the high power sum criterion, the pilot power allocation is converted into a cone programming problem, and the power allocation is carried out. Finally, the optimal pilot is determined by calculating the weighted sum of the high power sum and the high power variance. Compared with the traditional pilot frequency, under the same conditions, the constructed MIMO-OFDM system uses the optimal pilot frequency for channel estimation, and the communication bit error rate performance obtains a gain of 6~7dB.

Keywords: MIMO-OFDM, pilot optimization, compressed sensing, channel estimation

Procedia PDF Downloads 127

Authors: Fuad M. Alkoot

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DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

Procedia PDF Downloads 230

Authors: Ahmed E. Hodaib, Mohamed A. Hashem

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In engineering applications, a design has to be as fully perfect as possible in some defined case. The designer has to overcome many challenges in order to reach the optimal solution to a specific problem. This process is called optimization. Generally, there is always a function called “objective function” that is required to be maximized or minimized by choosing input parameters called “degrees of freedom” within an allowed domain called “search space” and computing the values of the objective function for these input values. It becomes more complex when we have more than one objective for our design. As an example for Multi-Objective Optimization Problem (MOP): A structural design that aims to minimize weight and maximize strength. In such case, the Pareto Optimal Frontier (POF) is used, which is a curve plotting two objective functions for the best cases. At this point, a designer should make a decision to choose the point on the curve. Engineers use algorithms or iterative methods for optimization. In this paper, we will discuss the Evolutionary Algorithms (EA) which are widely used with Multi-objective Optimization Problems due to their robustness, simplicity, suitability to be coupled and to be parallelized. Evolutionary algorithms are developed to guarantee the convergence to an optimal solution. An EA uses mechanisms inspired by Darwinian evolution principles. Technically, they belong to the family of trial and error problem solvers and can be considered global optimization methods with a stochastic optimization character. The optimization is initialized by picking random solutions from the search space and then the solution progresses towards the optimal point by using operators such as Selection, Combination, Cross-over and/or Mutation. These operators are applied to the old solutions “parents” so that new sets of design variables called “children” appear. The process is repeated until the optimal solution to the problem is reached. Reliable and robust computational fluid dynamics solvers are nowadays commonly utilized in the design and analyses of various engineering systems, such as aircraft, turbo-machinery, and auto-motives. Coupling of Computational Fluid Dynamics “CFD” and Multi-Objective Evolutionary Algorithms “MOEA” has become substantial in aerospace engineering applications, such as in aerodynamic shape optimization and advanced turbo-machinery design.

Keywords: mathematical optimization, multi-objective evolutionary algorithms "MOEA", computational fluid dynamics "CFD", aerodynamic shape optimization

Procedia PDF Downloads 237

Authors: B. B. Siswanto, A. Halimi, K. M. H. J. Tandayu, C. Abdillah, F. Nanda , E. Chandra

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Nowadays, modern cardiac biomarkers, such as ST2 and NT-proBNP, have important roles in predicting morbidity and mortality in heart failure patients. Abnormalities of serum electrolytes, sepsis or infection, and deteriorating renal function will worsen the conditions of patients with heart failure. It is intriguing to know whether cardiac biomarkers elevations are affected by laboratory findings in heart failure patients. We recruited 65 patients from the heart failure clinic in NCVC Harapan Kita in 2014-2015. All of them have consented for laboratory examination, including cardiac biomarkers. The findings were recorded in our Research and Development Centre and analyzed using linear regression to find whether there is a relationship between laboratory findings (sodium, potassium, creatinine, and leukocytes) and ST2 or NT-proBNP. From 65 patients, 26.9% of them are female, and 73.1% are male, 69.4% patients classified as NYHA I-II and 31.6% as NYHA III-IV. The mean age is 55.7+11.4 years old; mean sodium level is 136.1+6.5 mmol/l; mean potassium level is 4.7+1.9 mmol/l; mean leukocyte count is 9184.7+3622.4 /ul; mean creatinine level is 1.2+0.5 mg/dl. From linear regression logistics, the relationship between NT-proBNP and sodium level (p<0.001), as well as leukocyte count (p=0.002) are significant, while NT-proBNP and potassium level (p=0.05), as well as creatinine level (p=0.534) are not significant. The relationship between ST2 and sodium level (p=0.501), potassium level (p=0.76), leukocyte level (p=0.897), and creatinine level (p=0.817) are not significant. To conclude, laboratory findings are more sensitive in predicting NT-proBNP elevation than ST2 elevation. Larger studies are needed to prove that NT-proBNP correlation with laboratory findings is more superior than ST2.

Keywords: heart failure, laboratory, NT-proBNP, ST2

Procedia PDF Downloads 321

Authors: Dimitri Golenko-Ginzburg

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A CPM network project with deterministic activity durations, in which activities require homogenous resources with fixed capacities, is considered. The problem is to determine the optimal schedule of starting times for all network activities within their maximal allowable limits (in order not to exceed the network's critical time) to minimize the maximum required resources for the project at any point in time. In case when a non-critical activity may start only at discrete moments with the pregiven time span, the problem becomes NP-complete and an optimal solution may be obtained via a look-over algorithm. For the case when a look-over requires much computational time an approximate algorithm is suggested. The algorithm's performance ratio, i.e., the relative accuracy error, is determined. Experimentation has been undertaken to verify the suggested algorithm.

Keywords: resource smoothing problem, CPM network, lookover algorithm, lexicographical order, approximate algorithm, accuracy estimate

Procedia PDF Downloads 283

Authors: Dibyakanta Seth, Hari Niwas Mishra, Sankar Chandra Deka

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Microencapsulation is an established method of protecting bacteria from the adverse conditions. An improved extrusion spraying technique was used to encapsulate mixed bacteria culture of S. thermophilus and L. bulgaricus using sodium alginate as the coating material. The effect of nozzle air pressure (200, 300, 400 and 500 kPa), sodium alginate concentration (1%, 1.5%, 2%, 2.5% and 3% w/v), different concentration of calcium chloride (0.1, 0.2, 1 M) and initial cell loads (10⁷, 10⁸, 10⁹ cfu/ml) on the viability of encapsulated bacteria were investigated. With the increase in air pressure the size of microcapsules decreased, however the effect was non-significant. There was no significant difference (p > 0.05) in the viability of encapsulated cells when the concentration of calcium chloride was increased. Increased level of sodium alginate significantly increased the survival ratio of encapsulated bacteria (P < 0.01). Encapsulation with 3% alginate was treated as optimum since a higher concentration of alginate increased the gel strength of the solution and thus was difficult to spray. Under optimal conditions 3% alginate, 10⁹ cfu/ml cell load, 20 min hardening time in 0.1 M CaCl2 and 400 kPa nozzle air pressure, the viability of bacteria cells was maximum compared to the free cells. The microcapsules made at the optimal condition when mixed with yoghurt and subjected to spray drying at 148°C, the survival ratio was 2.48×10⁻¹ for S. thermophilus and 7.26×10⁻¹ for L. bulgaricus. In contrast, the survival ratio of free cells of S. thermophilus and L. bulgaricus were 2.36×10⁻³ and 8.27×10⁻³, respectively. This study showed a decline in viable cells count of about 0.5 log over a period of 7 weeks while there was a decline of about 1 log in cultures which were incorporated as free cells in yoghurt. Microencapsulation provided better protection at higher acidity compared to free cells. This study demonstrated that microencapsulation of yoghurt culture in sodium alginate is an effective technique of protection against extreme drying conditions.

Keywords: extrusion, microencapsulation, spray drying, sweetened yoghurt

Procedia PDF Downloads 232

Authors: Daoudi Abdelaziz, Mahmoudi Saïd, Chikh Mohamed Amine

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This paper presents a fully automatic segmentation method of the left ventricle at End Systolic (ES) and End Diastolic (ED) in the ultrasound images by means of an implicit deformable model (level set) based on Geodesic Active Contour model. A pre-processing Gaussian smoothing stage is applied to the image, which is essential for a good segmentation. Before the segmentation phase, we locate automatically the area of the left ventricle by using a detection approach based on the Hough Transform method. Consequently, the result obtained is used to automate the initialization of the level set model. This initial curve (zero level set) deforms to search the Endocardial border in the image. On the other hand, quantitative evaluation was performed on a data set composed of 15 subjects with a comparison to ground truth (manual segmentation).

Keywords: level set method, transform Hough, Gaussian smoothing, left ventricle, ultrasound images.

Procedia PDF Downloads 442

Authors: Neha Sharma, Kanthi K. Kondepudi, Naveen Gupta

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Phytases are phytate specific phosphatases catalyzing the step-wise dephosphorylation of phytate, which acts as an anti-nutritional factor in food due to its strong binding capacity to minerals. In recent years microbial phytases have been explored for improving nutritional quality of food. But the major limitation is acceptability of phytases from these microorganisms. Therefore, efforts are being made to isolate organisms which are generally regarded as safe for human consumption such as Lactic Acid Bacteria (LAB). Phytases from these organisms will have an edge over other phytase sources due to its probiotic attributes. Only few LAB have been reported to give phytase activity that too is generally seen as intracellular. LAB producing extracellular phytase will be more useful as it can degrade phytate more effectively. Moreover, enzyme from such isolate will have application in food processing also. Only few species of Lactobacillus producing extracellular phytase have been reported so far. This study reports the isolation of a probiotic strain of Lactobacillus fermentum spp KA1 which produces extracellular phytase. Conditions for the optimal production of phytase have been optimized and the enzyme production resulted in an approximately 13-fold increase in yield. The phytate degradation potential of extracellular phytase in rice bran has been explored and conditions for optimal degradation were optimized. Under optimal conditions, there was 43.26% release of inorganic phosphate and 6.45% decrease of phytate content.

Keywords: Lactobacillus, phytase, phytate reduction, rice bran

Procedia PDF Downloads 169

Authors: M. Farhaoui, M. Derraz

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Problem statement: In the water treatment processes, the coagulation and flocculation processes produce sludge according to the level of the water turbidity. The aluminum sulfate is the most common coagulant used in water treatment plants of Morocco as well as many countries. It is difficult to manage the sludge produced by the treatment plant. However, it can be used in the process to improve the quality of the treated water and reduce the aluminum sulfate dose. Approach: In this study, the effectiveness of sludge was evaluated at different turbidity levels (low, medium, and high turbidity) and coagulant dosage to find optimal operational conditions. The influence of settling time was also studied. A set of jar test experiments was conducted to find the sludge and aluminum sulfate dosages in order to improve the produced water quality for different turbidity levels. Results: Results demonstrated that using sludge produced by the treatment plant can improve the quality of the produced water and reduce the aluminum sulfate using. The aluminum sulfate dosage can be reduced from 40 to 50% according to the turbidity level (10, 20 and 40 NTU). Conclusions/Recommendations: Results show that sludge can be used in order to reduce the aluminum sulfate dosage and improve the quality of treated water. The highest turbidity removal efficiency is observed within 6 mg/l of aluminum sulfate and 35 mg/l of sludge in low turbidity, 20 mg/l of aluminum sulfate and 50 mg/l of sludge in medium turbidity and 20 mg/l of aluminum sulfate and 60 mg/l of sludge in high turbidity. The turbidity removal efficiency is 97.56%, 98.96% and 99.47% respectively for low, medium and high turbidity levels.

Keywords: coagulation process, coagulant dose, sludge, turbidity removal

Procedia PDF Downloads 306

Authors: Y. Ghiassi-Farrokhfal

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The number of electric vehicles (EVs) is increasing worldwide. Replacing gas fueled cars with EVs reduces carbon emission. However, the extensive energy consumption of EVs stresses the energy systems, requiring non-green sources of energy (such as gas turbines) to compensate for the new energy demand caused by EVs in the energy systems. To make EVs even a greener solution for the future energy systems, new EV charging stations are equipped with solar PV panels and batteries. This will help serve the energy demand of EVs through the green energy of solar panels. To ensure energy availability, solar panels are combined with batteries. The energy surplus at any point is stored in batteries and is used when there is not enough solar energy to serve the demand. While EV charging stations equipped with solar panels and batteries are green and ecologically optimal, they might not be financially viable solutions, due to battery prices. To make the system viable, we should size the battery economically and operate the system optimally. This is, in general, a challenging problem because of the stochastic nature of the EV arrivals at the charging station, the available solar energy, and the battery operating system. In this work, we provide a mathematical model for this problem and we compute the return on investment (ROI) of such a system, which is designed to be ecologically and financially optimal. We also quantify the minimum required investment in terms of battery and solar panels along with the operating strategy to ensure that a charging station has enough energy to serve its EV demand at any time.

Keywords: solar energy, battery storage, electric vehicle, charging stations

Procedia PDF Downloads 199

Authors: Aigul Manapova

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We consider an optimal control problem in the higher coefficient of nonlinear equations with a divergent elliptic operator and unbounded nonlinearity, and the Dirichlet boundary condition. The conditions imposed on the coefficients of the state equation are assumed to hold only in a small neighborhood of the exact solution to the original problem. This assumption suggests that the state equation involves nonlinearities of unlimited growth and considerably expands the class of admissible functions as solutions of the state equation. We obtain formulas for the first partial derivatives of the objective functional with respect to the control functions. To calculate the gradients the numerical solutions of the state and adjoint problems are used. We also prove that the gradient of the cost function is Lipchitz continuous.

Keywords: cost functional, differentiability, divergent elliptic operator, optimal control, unbounded nonlinearity

Procedia PDF Downloads 146

Authors: Valentina Alessandra Carvalho do Vale, Elmo Thiago Lins Cöuras Ford

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In view of the requirements of the current industrial processes, the instrumentation plays a critical role. In this context, this work aims to raise some the operating characteristics of the level and flow transmitters, in addition to observing their similarities and possible limitations for certain configurations.

Keywords: flow, level, instrumentation, configurations of meters, method of choice of the meters, instrumentation in the industrial processes

Procedia PDF Downloads 561

Authors: Pandega Gama Mahardika, Muhammad Rifki Al Iksan, Datuk Fachrul Razy

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Oil And Gas Tanker Driver is a high-risk jobdesc. drivers drive with sleep circadian rhythm disturbances. Therefore, FAMOUS (Fatigue Management Online Ultimate System) conducted a diagnostic test on the effectiveness and accuracy of the Psychomotor vigilance test (PVT) in the field to capture the fatigue level of Oil And Gas Tanker Driver. Fatigue examination with the PVP method for 3 minutes using the Pertamina FAMOUS system (Fatigue Management Online Ultimate System). The research sample was Oil And Gas Tanker Driver Elnusa petrofin drivers as many as 2205 people. PVT is categorical data that states a driver has a low or high fatigue level. The quality of sleep at home was recorded by filling in a score of 1 = not well, 2 = not well, 3 = well, per person. A total of 1852 (84%) driver had a low fatigue level, while 353 (16%) driver had a high fatigue level. Poor sleep quality was experienced by 68 (79%) driver who had a high fatigue level. Oil And Gas Tanker Driver who slept soundly at home as many as 1804 (87%) had a low fatigue level. The correlation coefficient of sleep quality home and fatigue level is significant because it shows a probability value of 0.00 (p <5%). Fatigue level can be diagnosed through examining sleep quality, using FAMOUS Program for occupational medicine, particularly in the oil and gas sector.

Keywords: psychomotor vigilance test, fatigue, sleep, oil and gas tanker driver drivers, pertamina FAMOUS

Procedia PDF Downloads 66

Authors: Radoslaw Pytlak, Damian Suski

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The aim of the paper is to provide a computational tool for planning a haemodialysis process. It is shown that optimization methods can be used to obtain the most effective treatment focused on removing both urea and phosphorus during the process. In order to achieve that, the IV–compartment model of phosphorus kinetics is applied. This kinetics model takes into account a rebound phenomenon that can occur during haemodialysis and results in a hybrid model of the process. Furthermore, vector fields associated with the model equations are such that it is very likely that using the most intuitive objective functions in the planning problem could lead to solutions which include sliding motions. Therefore, building computational tools for solving the problem of planning a haemodialysis process has required constructing numerical algorithms for solving optimal control problems with hybrid systems. The paper concentrates on minimum time control of hybrid systems since this control objective is the most suitable for the haemodialysis process considered in the paper. The presented approach to optimal control problems with hybrid systems is different from the others in several aspects. First of all, it is assumed that a hybrid system can exhibit sliding modes. Secondly, the system’s motion on the switching surface is described by index 2 differential–algebraic equations, and that guarantees accurate tracking of the sliding motion surface. Thirdly, the gradients of the problem’s functionals are evaluated with the help of adjoint equations. The adjoint equations presented in the paper take into account sliding motion and exhibit jump conditions at transition times. The optimality conditions in the form of the weak maximum principle for optimal control problems with hybrid systems exhibiting sliding modes and with piecewise constant controls are stated. The presented sensitivity analysis can be used to construct globally convergent algorithms for solving considered problems. The paper presents numerical results of solving the haemodialysis planning problem.

Keywords: haemodialysis planning process, hybrid systems, optimal control, sliding motion

Procedia PDF Downloads 172

Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat

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Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.

Keywords: feature extraction, feature selection, image annotation, classification

Procedia PDF Downloads 569

Authors: Tadesse Melaku Abegaz

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Background: there was paucity of data on the self-reported adverse drug reactions (ADRs), level of adherence and clinical outcomes with antidepressants among major depressive disorder (MDD) patients in Ethiopia. Hence, the present study sought to determine the level of adherence for and clinical outcome with antidepressants and the magnitude of ADRs. Methods: A prospective cross-sectional study was employed on MDD patients from September 2016 to January 2017 at Gondar university hospital psychiatry clinic. All patients who were available during the study period were included under the study population. The Naranjo adverse drug reaction probability scale was employed to assess the adverse drug reaction. The rate of medication adherence was determined using morisky medication adherence measurement scale eight. Clinical Outcome of patients was measured by using patient health questionnaire. Multivariable logistic carried out to determine factors for adherence and patient outcome. Results: two hundred seventy patients were participated in the study. More than half of the respondents were males 122(56.2%). The mean age of the participants was 30.94 ± 8.853. More than one-half of the subjects had low adherence to their medications 124(57.1%). About 186(85.7%) of patients encountered ADR. The most common ADR was weight gain 29(13.2). Around 198(92.2%) ADRs were probable and 19(8.8%) were possible. Patients with long standing MDD had high risk of non-adherence COR: 2.458[4.413-4.227], AOR: 2.424[1.185-4.961]. More than one-half 125(57.6) of respondents showed improved outcome. Optimal level of medication adherence was found to be associated with reduced risk of progression of the diseases COR: 0.37[0.110-5.379] and AOR: 0.432[0.201-0.909]. Conclusion: Patient reported adverse drug reactions were more prevalent in major depressive disorder patients. Adherence to medications was very poor in the setup. However, the clinical outcome was relatively higher. Long standing depression was associated with non-adherence. In addition, clinical outcome of patients were affected by non-adherence. Therefore, adherence enhancing interventions should be provided to improve medication adherence and patient outcome.

Keywords: adverse drug reactions, clinical outcomes, Ethiopia, prospective study, medication adherence

Procedia PDF Downloads 228

Authors: Paolo Russu

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The purpose of the present paper is to highlight some features of an economic growth model with environmental negative externalities, giving rise to a three-dimensional dynamic system. In particular, we show that the economy, which is based on a Perfect-Substitution Technologies function of production, has no neither indeterminacy nor poverty trap. This implies that equilibrium select by economy depends on the history (initial values of state variable) of the economy rather than on expectations of economies agents. Moreover, by contrast, we prove that the basin of attraction of locally equilibrium points may be very large, as they can extend up to the boundary of the system phase space. The infinite-horizon optimal control problem has the purpose of maximizing the representative agent’s instantaneous utility function depending on leisure and consumption.

Keywords: Hopf bifurcation, open-access natural resources, optimal control, perfect-substitution technologies, Poincarè compactification

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Authors: Alhusein Almahjoub, Dongyu Qiu

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This paper deals with the random access procedure in next-generation networks and presents the solution to reduce total service time (TST) which is one of the most important performance metrics in current and future internet of things (IoT) based networks. The proposed solution focuses on the calculation of optimal transmission probability which maximizes the success probability and reduces TST. It uses the information of several idle preambles in every time slot, and based on it, it estimates the number of backlogged IoT devices using Naïve Bayes estimation which is a type of supervised learning in the machine learning domain. The estimation of backlogged devices is necessary since optimal transmission probability depends on it and the eNodeB does not have information about it. The simulations are carried out in MATLAB which verify that the proposed solution gives excellent performance.

Keywords: random access, LTE/LTE-A, 5G, machine learning, Naïve Bayes estimation

Procedia PDF Downloads 127

Authors: E. Tandis, E. Assareh

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Designing the optimal shape of MW wind turbine blades is provided in a number of cases through evolutionary algorithms associated with mathematical modeling (Blade Element Momentum Theory). Evolutionary algorithms, among the optimization methods, enjoy many advantages, particularly in stability. However, they usually need a large number of function evaluations. Since there are a large number of local extremes, the optimization method has to find the global extreme accurately. The present paper introduces a new population-based hybrid algorithm called Genetic-Based Bees Algorithm (GBBA). This algorithm is meant to design the optimal shape for MW wind turbine blades. The current method employs crossover and neighborhood searching operators taken from the respective Genetic Algorithm (GA) and Bees Algorithm (BA) to provide a method with good performance in accuracy and speed convergence. Different blade designs, twenty-one to be exact, were considered based on the chord length, twist angle and tip speed ratio using GA results. They were compared with BA and GBBA optimum design results targeting the power coefficient and solidity. The results suggest that the final shape, obtained by the proposed hybrid algorithm, performs better compared to either BA or GA. Furthermore, the accuracy and speed convergence increases when the GBBA is employed

Keywords: Blade Design, Optimization, Genetic Algorithm, Bees Algorithm, Genetic-Based Bees Algorithm, Large Wind Turbine

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Authors: Pham Van Nha, Le Cam Binh

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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

Procedia PDF Downloads 188

Authors: Saeed Ahmed, Tamoor Abbas, M. Amir, M. S. Iqbal, D. Hussain

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This study was conducted to evaluate the effect of supplementation of different levels of yeast culture (Saccharomyces cerevisiae) in Beetal male goats diets on growth performance, digestibility of nutrients and selected blood metabolites. Another objective was to determine the inclusion level of yeast culture for optimal growth performance of Beetal male goats. Eighteen (n=18) Beetal male goats were randomly assigned to three total mixed ration treatments (n=6 goats/treatment): T1, T2 and T3 containing 0gm, 3gm and 6gm/day yeast culture (YC) mixed with total mixed ration (TMR). The diets were iso-nitrogenous and iso-caloric having crude protein 15.2% and ME 2.6Mcal/kg. The total duration of the experiment was 8 weeks. Beetal bucks were fed on TMR diets (T1, T2 and T3) having blend of oat silage, Lucerne hay and concentrate mixed with yeast culture (YC). Bucks were housed individually and feed was offered @ 4% of body weight on dry matter basis. Samples of fresh feed and refusal were collected twice weekly of moisture percentage using hot air oven. Data for daily dry matter intake, body weight gain, nutrient digestibility and selected blood metabolites were analyzed through one-way ANOVA technique under Complete randomised design (SAS Institute Inc, 2002-03). Results were declared significant at P≤0.05. Overall, DMI was not affected (P≥0.05) by dietary treatments. Body weight gain, digestibility of crude protein and crude fibre were improved. Blood glucose concentration was detected higher in the group having supplementation of yeast culture (YC) 6gm/day compared to other two dietary treatments. This study suggested the positive impact of inclusion of yeast culture (YC) up to 6gm/day in the TMR diet for optimal growth performance and digestibility of nutrients in Beetal male goats.

Keywords: yeast culture, growth performance, digestibility, beetle goat

Procedia PDF Downloads 166

Authors: Pius W. Molo Chin

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Real life problems such as the Huxley equation are always modeled as nonlinear differential equations. These problems need accurate and reliable methods for their solutions. In this paper, we propose a nonstandard finite difference method in time and the Galerkin combined with the compactness method in the space variables. This coupled method, is used to analyze a two dimensional Huxley equation for the existence and uniqueness of the continuous solution of the problem in appropriate spaces to be defined. We proceed to design a numerical scheme consisting of the aforementioned method and show that the scheme is stable. We further show that the stable scheme converges with the rate which is optimal in both the L2 as well as the H1-norms. Furthermore, we show that the scheme replicates the decaying qualities of the exact solution. Numerical experiments are presented with the help of an example to justify the validity of the designed scheme.

Keywords: Huxley equations, non-standard finite difference method, Galerkin method, optimal rate of convergence

Procedia PDF Downloads 192

Authors: L. Strauta, S. Muižniece-Brasava

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Even though legumes possess high nutritional value and have a rather high protein content for plant origin products, they are underutilized mostly due to their lengthy cooking time. To increase the presence of legume-based products in human diet, new extruded products were made of cow peas (Vigna unguiculata (L.) Walp.). But as it is known, adding different moisture content to flour before extrusion can change the physical properties of the extruded product. Experiments were carried out to estimate the optimal moisture content for cow pea extrusion. After extrusion, the pH level had dropped from 6.7 to 6.5 and the lowest hardness rate was observed in the samples with additional 9 g 100g^-1 of moisture - 28±4N, but the volume mass of the samples with additional 9 g100g^-1 of water was 263±3 g L^-1; all samples were approximately 7±1mm long.

Keywords: cow pea, extrusion–cooking, moisture, size

Procedia PDF Downloads 192

Authors: Waraphorn Sribuakaew, Chutikarn Sriviboon, Rosjana Chandhasa

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The purpose of this research is to study the satisfaction level of graduates and factors that affect the image of Suan Sunandha Rajabhat University based on the perceptions of graduates on the graduation ceremony day. By studying the satisfaction of graduates, the image of Suan Sunandha Rajabhat University according to the graduates' perceptions and the loyalty to the university (in the aspects of intention to continue studying at a higher level, intention to recommend the university to a friend), the sample group used in this study was 1,000 graduates of Suan Sunandha Rajabhat University who participated on the 2019 graduation ceremony day. A questionnaire was utilized as a tool for data collection. By the use of computing software, the statistics used for data analysis were frequencies, percentage, mean, and standard deviation, One-Way ANOVA, and multiple regression analysis. Most of the respondents were graduates with a bachelor's degree, followed by graduates with a master's degree and PhD graduates, respectively. Major participants graduated from the Faculty of Management Sciences, followed by the Faculty of Humanities and Social Sciences and Faculty of Education, respectively. The graduates were satisfied on the ceremony day as a whole and rated each aspect at a satisfactory level. Formality, steps, and procedures were the aspects that graduates were most satisfied with, followed by graduation ceremony personnel and staff, venue, and facilities. On the perception of the graduates, the image of Suan Sunandha Rajabhat University was at a good level, while loyalty to the university was at a very high level. The intention of recommendation to others was at the highest level, followed by the intention to pursue further education at a very high level. The graduates graduating from different faculties have different levels of satisfaction on the graduation day with statistical significance at the level of 0.05. The image of Suan Sunandha Rajabhat University affected the satisfaction of graduates with statistical significance at the level of 0.01. The satisfactory level of graduates on the graduation ceremony day influenced the level of loyalty to the university with statistical significance at the level of 0.05.

Keywords: university image, loyalty to the university, intention to study higher education, intention to recommend the university to others, graduates' satisfaction

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Authors: Anne Schattel, Mitja Echim, Christof Büskens

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Trajectory planning for deep space missions has become a recent topic of great interest. Flying to space objects like asteroids provides two main challenges. One is to find rare earth elements, the other to gain scientific knowledge of the origin of the world. Due to the enormous spatial distances such explorer missions have to be performed unmanned and autonomously. The mathematical field of optimization and optimal control can be used to realize autonomous missions while protecting recourses and making them safer. The resulting algorithms may be applied to other, earth-bound applications like e.g. deep sea navigation and autonomous driving as well. The project KaNaRiA ('Kognitionsbasierte, autonome Navigation am Beispiel des Ressourcenabbaus im All') investigates the possibilities of cognitive autonomous navigation on the example of an asteroid mining mission, including the cruise phase and approach as well as the asteroid rendezvous, landing and surface exploration. To verify and test all methods an interactive, real-time capable simulation using virtual reality is developed under KaNaRiA. This paper focuses on the specific challenge of the guidance during the cruise phase of the spacecraft, i.e. trajectory optimization and optimal control, including first solutions and results. In principle there exist two ways to solve optimal control problems (OCPs), the so called indirect and direct methods. The indirect methods are being studied since several decades and their usage needs advanced skills regarding optimal control theory. The main idea of direct approaches, also known as transcription techniques, is to transform the infinite-dimensional OCP into a finite-dimensional non-linear optimization problem (NLP) via discretization of states and controls. These direct methods are applied in this paper. The resulting high dimensional NLP with constraints can be solved efficiently by special NLP methods, e.g. sequential quadratic programming (SQP) or interior point methods (IP). The movement of the spacecraft due to gravitational influences of the sun and other planets, as well as the thrust commands, is described through ordinary differential equations (ODEs). The competitive mission aims like short flight times and low energy consumption are considered by using a multi-criteria objective function. The resulting non-linear high-dimensional optimization problems are solved by using the software package WORHP ('We Optimize Really Huge Problems'), a software routine combining SQP at an outer level and IP to solve underlying quadratic subproblems. An application-adapted model of impulsive thrusting, as well as a model of an electrically powered spacecraft propulsion system, is introduced. Different priorities and possibilities of a space mission regarding energy cost and flight time duration are investigated by choosing different weighting factors for the multi-criteria objective function. Varying mission trajectories are analyzed and compared, both aiming at different destination asteroids and using different propulsion systems. For the transcription, the robust method of full discretization is used. The results strengthen the need for trajectory optimization as a foundation for autonomous decision making during deep space missions. Simultaneously they show the enormous increase in possibilities for flight maneuvers by being able to consider different and opposite mission objectives.

Keywords: deep space navigation, guidance, multi-objective, non-linear optimization, optimal control, trajectory planning.

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Authors: Tomoaki Hashimoto

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Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial time and a moving terminal time. This paper examines the stability of model predictive control for linear discrete-time systems with additive stochastic disturbances. A sufficient condition for the stability of the closed-loop system with model predictive control is derived by means of a linear matrix inequality. The objective of this paper is to show the results of computational simulations in order to verify the validity of the obtained stability condition.

Keywords: computational simulations, optimal control, predictive control, stochastic systems, discrete-time systems

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Authors: A. W. J. Wong, I. H. Ibrahim

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Increasing urbanisation has driven building designers to incorporate natural ventilation in the designs of sustainable buildings. This project utilises Computational Fluid Dynamics (CFD) to investigate the natural ventilation of an academic building, SIT@SP, using an assessment criterion based on daily mean temperature and mean velocity. The areas of interest are the pedestrian level of first and fourth levels of the building. A reference case recommended by the Architectural Institute of Japan was used to validate the simulation model. The validated simulation model was then used for coupled simulations on SIT@SP and neighbouring geometries, under two wind speeds. Both steady and transient simulations were used to identify differences in results. Steady and transient results are agreeable with the transient simulation identifying peak velocities during flow development. Under a lower wind speed, the first level was sufficiently ventilated while the fourth level was not. The first level has excessive wind velocities in the higher wind speed and the fourth level was adequately ventilated. Fourth level flow velocity was consistently lower than those of the first level. This is attributed to either simulation model error or poor building design. SIT@SP is concluded to have a sufficiently ventilated first level and insufficiently ventilated fourth level. Future works for this project extend to modifying the urban geometry, simulation model improvements, evaluation using other assessment metrics and extending the area of interest to the entire building.

Keywords: buildings, CFD Simulations, natural ventilation, urban airflow

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Authors: Lana Dalawr Jalal

Abstract:

This paper addresses the problem of offline path planning for Unmanned Aerial Vehicles (UAVs) in complex three-dimensional environment with obstacles, which is modelled by 3D Cartesian grid system. Path planning for UAVs require the computational intelligence methods to move aerial vehicles along the flight path effectively to target while avoiding obstacles. In this paper Modified Particle Swarm Optimization (MPSO) algorithm is applied to generate the optimal collision free 3D flight path for UAV. The simulations results clearly demonstrate effectiveness of the proposed algorithm in guiding UAV to the final destination by providing optimal feasible path quickly and effectively.

Keywords: obstacle avoidance, particle swarm optimization, three-dimensional path planning unmanned aerial vehicles

Procedia PDF Downloads 384