Search results for: fuzzy multiple objective programming

Authors: Taha Anjamrooz, Sareh Rajabi, Salwa Bheiry

Abstract:

Selection between the available projects in bidding processes for the contractor is one of the essential areas to concentrate on. It is important for the contractor to choose the right projects within its portfolio during the tendering stage based on certain criteria. It should align the bidding process with its origination strategies and goals as a screening process to have the right portfolio pool to start with. Secondly, it should set the proper framework and use a suitable technique in order to optimize its selection process for concertation purpose and higher efforts during the tender stage with goals of success and winning. In this research paper, a two steps framework proposed to increase the efficiency of the contractor’s bidding process and the winning chance of getting the new projects awarded. In this framework, initially, all the projects pass through the first stage screening process, in which the portfolio basket will be evaluated and adjusted in accordance with the organization strategies to the reduced version of the portfolio pool, which is in line with organization activities. In the second stage, the contractor uses linear programming to optimize the portfolio pool based on available resources such as manpower, light equipment, heavy equipment, financial capability, return on investment, and success rate of winning the bid. Therefore, this optimization model will assist the contractor in utilizing its internal resource to its maximum and increase its winning chance for the new project considering past experience with clients, built-relation between two parties, and complexity in the exertion of the projects. The objective of this research will be to increase the contractor's winning chance in the bidding process based on the success rate and expected return on investment.

Keywords: bidding process, internal resources, optimization, contracting portfolio management

Procedia PDF Downloads 142

Authors: Dale Dzemydiene, Aurelija Burinskiene, Arunas Miliauskas, Kristina Ciziuniene

Abstract:

Data flow and the purpose of reporting the data are different and dependent on business needs. Different parameters are reported and transferred regularly during freight delivery. This business practices form the dataset constructed for each time point and contain all required information for freight moving decisions. As a significant amount of these data is used for various purposes, an integrating methodological approach must be developed to respond to the indicated problem. The proposed methodology contains several steps: (1) collecting context data sets and data validation; (2) multi-objective analysis for optimizing freight transfer services. For data validation, the study involves Grubbs outliers analysis, particularly for data cleaning and the identification of statistical significance of data reporting event cases. The Grubbs test is often used as it measures one external value at a time exceeding the boundaries of standard normal distribution. In the study area, the test was not widely applied by authors, except when the Grubbs test for outlier detection was used to identify outsiders in fuel consumption data. In the study, the authors applied the method with a confidence level of 99%. For the multi-objective analysis, the authors would like to select the forms of construction of the genetic algorithms, which have more possibilities to extract the best solution. For freight delivery management, the schemas of genetic algorithms' structure are used as a more effective technique. Due to that, the adaptable genetic algorithm is applied for the description of choosing process of the effective transportation corridor. In this study, the multi-objective genetic algorithm methods are used to optimize the data evaluation and select the appropriate transport corridor. The authors suggest a methodology for the multi-objective analysis, which evaluates collected context data sets and uses this evaluation to determine a delivery corridor for freight transfer service in the multi-modal transportation network. In the multi-objective analysis, authors include safety components, the number of accidents a year, and freight delivery time in the multi-modal transportation network. The proposed methodology has practical value in the management of multi-modal transportation processes.

Keywords: multi-objective, analysis, data flow, freight delivery, methodology

Procedia PDF Downloads 180

Authors: Geetha Baskaran, Andrzej Barjiela, Rong Qu

Abstract:

Motivation: Nurse scheduling is a complex combinatorial optimization problem. It is also known as NP-hard. It needs an efficient re-scheduling to minimize some trade-off of the measures of violation by reducing selected constraints to soft constraints with measurements of their violations. Problem Statement: In this paper, we extend our novel approach to solve the nurse scheduling problem by transforming it through Information Granulation. Approach: This approach satisfies the rules of a typical hospital environment based on a standard benchmark problem. Generating good work schedules has a great influence on nurses' working conditions which are strongly related to the level of a quality health care. Domain transformation that combines the strengths of operation research and artificial intelligence was proposed for the solution of the problem. Compared to conventional methods, our approach involves judicious grouping (information granulation) of shifts types’ that transforms the original problem into a smaller solution domain. Later these schedules from the smaller problem domain are converted back into the original problem domain by taking into account the constraints that could not be represented in the smaller domain. An Integer Programming (IP) package is used to solve the transformed scheduling problem by expending the branch and bound algorithm. We have used the GNU Octave for Windows to solve this problem. Results: The scheduling problem has been solved in the proposed formalism resulting in a high quality schedule. Conclusion: Domain transformation represents departure from a conventional one-shift-at-a-time scheduling approach. It offers an advantage of efficient and easily understandable solutions as well as offering deterministic reproducibility of the results. We note, however, that it does not guarantee the global optimum.

Keywords: domain transformation, nurse scheduling, information granulation, artificial intelligence, simulation

Procedia PDF Downloads 397

Authors: Hyeon-Kyo Lim, Hyunjung Kim, Kune-Woo Lee

Abstract:

Decommissioning process of nuclear facilities can be said to consist of a sequence of problem solving activities, partly because there may exist working environments contaminated by radiological exposure, and partly because there may also exist industrial hazards such as fire, explosions, toxic materials, and electrical and physical hazards. As for an individual hazard factor, risk assessment techniques are getting known to industrial workers with advance of safety technology, but the way how to integrate those results is not. Furthermore, there are few workers who experienced decommissioning operations a lot in the past. Therefore, not a few countries in the world have been trying to develop appropriate counter techniques in order to guarantee safety and efficiency of the process. In spite of that, there still exists neither domestic nor international standard since nuclear facilities are too diverse and unique. In the consequence, it is quite inevitable to imagine and assess the whole risk in the situation anticipated one by one. This paper aimed to find out an appropriate technique to integrate individual risk assessment results from the viewpoint of experts. Thus, on one hand the whole risk assessment activity for decommissioning operations was modeled as a sequence of individual risk assessment steps, and on the other, a hierarchical risk structure was developed. Then, risk assessment procedure that can elicit individual hazard factors one by one were introduced with reference to the standard operation procedure (SOP) and hierarchical task analysis (HTA). With an assumption of quantification and normalization of individual risks, a technique to estimate relative weight factors was tried by using the conventional Analytic Hierarchical Process (AHP) and its result was reviewed with reference to judgment of experts. Besides, taking the ambiguity of human judgment into consideration, debates based upon fuzzy inference was added with a mathematical case study.

Keywords: decommissioning, risk assessment, analytic hierarchical process (AHP), fuzzy inference

Procedia PDF Downloads 425

Authors: Vijaya K. Srivastava, Davide Spinello

Abstract:

This paper presents performance of two robust gradient-based heuristic optimization procedures based on 3ⁿ enumeration and tunneling approach to seek global optimum of constrained integer problems. Both these procedures consist of two distinct phases for locating the global optimum of integer problems with a linear or non-linear objective function subject to linear or non-linear constraints. In both procedures, in the first phase, a local minimum of the function is found using the gradient approach coupled with hemstitching moves when a constraint is violated in order to return the search to the feasible region. In the second phase, in one optimization procedure, the second sub-procedure examines 3ⁿ integer combinations on the boundary and within hypercube volume encompassing the result neighboring the result from the first phase and in the second optimization procedure a tunneling function is constructed at the local minimum of the first phase so as to find another point on the other side of the barrier where the function value is approximately the same. In the next cycle, the search for the global optimum commences in both optimization procedures again using this new-found point as the starting vector. The search continues and repeated for various step sizes along the function gradient as well as that along the vector normal to the violated constraints until no improvement in optimum value is found. The results from both these proposed optimization methods are presented and compared with one provided by popular MS Excel solver that is provided within MS Office suite and other published results.

Keywords: constrained integer problems, enumerative search algorithm, Heuristic algorithm, Tunneling algorithm

Procedia PDF Downloads 326

Authors: Gaironeesa Hendricks, Shazly Savahl, Maria Florence

Abstract:

The aim of the study is to determine whether peer pressure and leisure boredom influence substance use among adolescents in low-income communities in Cape Town. Non-probability sampling was used to select 296 adolescents between the ages of 16–18 from schools located in two low-income communities. The measurement tools included the Drug Use Disorders Identification Test, the Resistance to Peer Influence and Leisure Boredom Scales. Multiple regression revealed that the combined influence of peer pressure and leisure boredom predicted substance use, while peer pressure emerged as a stronger predictor than leisure boredom on substance use among adolescents.

Keywords: substance use, peer pressure, leisure boredom, adolescents, multiple regression

Procedia PDF Downloads 599

Authors: Ahmed Moustapha Mfokeu

Abstract:

Agri-food VSEs in Cameroon are facing a succession of crises, lack of security, particularly in the Far North, South West, and North West regions, the consequences of the Covid 19 crisis, and the war in Ukraine . These multiple crises have benefited the reception of the prices of the raw materials. Moreover, the exacerbation of competitive pressures is driven by the technological acceleration of productive systems in emerging countries which increase the demands imposed on the markets. The Cameroonian VSE must therefore be able to meet the new challenges of international competition, especially through innovation. The objective of this research is to contribute to the knowledge of the effects of innovation on the performance of very small agribusinesses in Cameroon. On the methodological level, the data were provided from a sample of 153 companies in the cities of Douala and Yaoundé. This research uses structural equation models with latent variables. The main results show that there is a positive and significant link between innovation and the performance of very small agri-food companies, so if it is important for entrepreneurs to encourage and practice innovation, it is also necessary to make them understand and make them like this aspect in their strategic function.

Keywords: innovation, performance, very small enterprise, agrifood

Procedia PDF Downloads 113

Authors: Novawiguna Kemalasari, Ahmad Badawi Saluy

Abstract:

This research is a planned activity to find an objective answer to PT XYZ problem through scientific procedure. In this study, It was used quantitative research methods by using samples taken from a department selected by researchers. This study aims to analyze the influence of organizational culture, work discipline and work motivation on employee performance of Personal Care & Cosmetic Department (PCC) Flammable PT XYZ. This research was conducted at PT XYZ Personal Care & Cosmetic Department (PCC) Flammable involving 82 employees as respondents, the data were obtained by using questionnaires filled in self-rating by respondents. The data were analyzed by multiple linear regression model processed by using SPSS version 22. The result of research showed that organizational culture variable, work discipline and work motivation had significant effect to employee performance.

Keywords: organizational culture, work discipline, employee motivation, employees performance

Procedia PDF Downloads 252

Authors: Seongjun Kim, Sanghoon Shim, Jinwooung Kim, Jaehwan Jung, Sung-Ah Kim

Abstract:

As the development of information and communication technology, the convergence of machine learning of the ICT area and design is attempted. In this way, it is possible to grasp the correlation between various design elements, which was difficult to grasp, and to reflect this in the design result. In architecture, there is an attempt to predict the performance, which is difficult to grasp in the past, by finding the correlation among multiple factors mainly through machine learning. In architectural design area, some attempts to predict the performance affected by various factors have been tried. With machine learning, it is possible to quickly predict performance. The aim of this study is to propose a model that predicts performance according to the block arrangement of apartment housing through machine learning and the design alternative which satisfies the performance such as the daylight hours in the most similar form to the alternative proposed by the designer. Through this study, a designer can proceed with the design considering various design alternatives and accurate performances quickly from the early design stage.

Keywords: apartment housing, machine learning, multi-objective optimization, performance prediction

Procedia PDF Downloads 482

Authors: Agostinho Antunes

Abstract:

The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of selected marine animal species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: comparative genomics, adaptive evolution, bioinformatics, phylogenetics, genome mining

Procedia PDF Downloads 534

Authors: Amanda Cristina da Silva Reis, Bruno Paulino Venâncio, Cristina Theada Ferreira, Andrea Fialho do Prado, Lucimara Guedes dos Santos, Aline de Souza Gravatá, Larissa Lima Gonçalves, Isabella Aparecida Ferreira Moretto, João Carlos Ferrari Corrêa, Fernanda Ishida Corrêa

Abstract:

Objective: To compare two protocols of Transcranial Magnetic Stimulation (TMS) on quadriceps muscle spasticity in individuals diagnosed with Multiple Sclerosis (MS). Method: Clinical, crossover study, in which six adult individuals diagnosed with MS and spasticity in the lower limbs were randomized to receive one session of high-frequency (≥5Hz) and low-frequency (≤ 1Hz) TMS on motor cortex (M1) hotspot for quadriceps muscle, with a one-week interval between the sessions. To assess the spasticity was applied the Ashworth scale and were analyzed the latency time (ms) of the motor evoked potential (MEP) and the central motor conduction time (CMCT) of the bilateral quadriceps muscle. Assessments were performed before and after each intervention. The difference between groups was analyzed using the Friedman test, with a significance level of 0.05 adopted. Results: All statistical analyzes were performed using the SPSS Statistic version 26 programs, with a significance level established for the analyzes at p<0.05. Shapiro Wilk normality test. Parametric data were represented as mean and standard deviation for non-parametric variables, median and interquartile range, and frequency and percentage for categorical variables. There was no clinical change in quadriceps spasticity assessed using the Ashworth scale for the 1 Hz (p=0.813) and 5 Hz (p= 0.232) protocols for both limbs. Motor Evoked Potential latency time: in the 5hz protocol, there was no significant change for the contralateral side from pre to post-treatment (p>0.05), and for the ipsilateral side, there was a decrease in latency time of 0.07 seconds (p<0.05 ); for the 1Hz protocol there was an increase of 0.04 seconds in the latency time (p<0.05) for the contralateral side to the stimulus, and for the ipsilateral side there was a decrease in the latency time of 0.04 seconds (p=<0.05), with a significant difference between the contralateral (p=0.007) and ipsilateral (p=0.014) groups. Central motor conduction time in the 1Hz protocol, there was no change for the contralateral side (p>0.05) and for the ipsilateral side (p>0.05). In the 5Hz protocol for the contralateral side, there was a small decrease in latency time (p<0.05) and for the ipsilateral side, there was a decrease of 0.6 seconds in the latency time (p<0.05) with a significant difference between groups (p=0.019). Conclusion: A high or low-frequency session does not change spasticity, but it is observed that when the low-frequency protocol was performed, there was an increase in latency time on the stimulated side, and a decrease in latency time on the non-stimulated side, considering then that inhibiting the motor cortex increases cortical excitability on the opposite side.

Keywords: multiple sclerosis, spasticity, motor evoked potential, transcranial magnetic stimulation

Procedia PDF Downloads 91

Authors: Yue Huang, Yiheng Feng

Abstract:

Due to the global pressure on climate and energy, many countries are vigorously promoting electric vehicles and building charging (public) charging facilities. Faced with the supply-demand gap of existing electric vehicle charging stations and unreasonable space usage in China, this paper takes the central city of Nanjing as an example, establishes a site selection model through multivariate data integration, conducts multiple linear regression SPSS analysis, gives quantitative site selection results, and provides optimization models and suggestions for charging station layout planning.

Keywords: electric vehicle, charging station, allocation optimization, urban mobility, urban infrastructure, nanjing

Procedia PDF Downloads 93

Authors: Moiseenko F. V., Volkov N. M., Zhabina A. S., Stepanova E. O., Kirillov A. V., Myslik A. V., Artemieva E. V., Agranov I. R., Oganesyan A. P., Egorenkov V. V., Abduloeva N. H., Aleksakhina S. Yu., Ivantsov A. O., Kuligina E. S., Imyanitov E. N., Moiseyenko V. M.

Abstract:

Analysis of ctDNA in patients with NSCLC is an emerging biomarker. Multiple research efforts of quantitative or at least qualitative analysis before and during the first periods of treatment with TKI showed the prognostic value of ctDNA clearance. Still, these important results are not incorporated in clinical standards. We evaluated the role of ctDNA in EGFR-mutated NSCLC receiving first-line TKI. Firstly, we analyzed sequential plasma samples from 30 patients that were collected before intake of the first tablet (at baseline) and at 6, 12, 24, 36, and 48 hours after the “starting point.” EGFR-M+ allele was measured by ddPCR. Afterward, we included sequential qualitative analysis of ctDNA with cobas® EGFR Mutation Test v2 from 99 NSCLC patients before the first dose, after 2 and 4 months of treatment, and on progression. Early response analysis showed the decline of EGFR-M+ level in plasma within the first 48 hours of treatment in 11 subjects. All these patients showed objective tumor response. 10 patients showed either elevation of EGFR-M+ plasma concentration (n = 5) or stable content of circulating EGFR-M+ after the start of the therapy (n = 5); only 3 of these patients achieved an objective response (p = 0.026) when compared to the former group). The rapid decline of plasma EGFR-M+ DNA concentration also predicted for longer PFS (13.7 vs. 11.4 months, p = 0.030). Long-term ctDNA monitoring showed clinically significant heterogeneity of EGFR-mutated NSCLC treated with 1st line TKIs in terms of progression-free and overall survival. Patients without detectable ctDNA at baseline (N = 32) possess the best prognosis on the duration of treatment (PFS: 24.07 [16.8-31.3] and OS: 56.2 [21.8-90.7] months). Those who achieve clearance after two months of TKI (N = 42) have indistinguishably good PFS (19.0 [13.7 – 24.2]). Individuals who retain ctDNA after 2 months (N = 25) have the worst prognosis (PFS: 10.3 [7.0 – 13.5], p = 0.000). 9/25 patients did not develop ctDNA clearance at 4 months with no statistical difference in PFS from those without clearance at 2 months. Prognostic heterogeneity of EGFR-mutated NSCLC should be taken into consideration in planning further clinical trials and optimizing the outcomes of patients.

Keywords: NSCLC, EGFR, targeted therapy, ctDNA, prognosis

Procedia PDF Downloads 55

Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco

Abstract:

Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.

Keywords: evolutionary computation, feature selection, classification, clustering

Procedia PDF Downloads 372

Authors: Ishak Suleiman, Ahmad Kamsani Samingan, Yeoh Chun Yeow, Abdul Aziz Bin Abdul Rahman

Abstract:

In this paper, we evaluate the benefits of distributed 4x4 MIMO LTE downlink systems compared to that of the co-located 4x4 MIMO LTE downlink system. The performance evaluation was carried out experimentally by using Wireless Open-Access Research Platform (WARP), where the comparison between the 4x4 MIMO LTE transmission downlink system in distributed and co-located techniques was examined. The measured Error Vector Magnitude (EVM) results showed that the distributed technique achieved better system performance compared to the co-located arrangement.

Keywords: multiple-input-multiple-output (MIMO), distributed MIMO, co-located MIMO, LTE

Procedia PDF Downloads 424

Authors: Arezou Hajhashemi, Karim Asgari, Masoud Etemadifar, Maryam Keyvani, Ali Hekmatnia

Abstract:

Multiple Sclerosis (MS) is one of the most prevalent demyelinating diseases in CNS. As in other chronic cerebral diseases, impairment in cognitive functioning and in memory is popular. Because of the inflammatory and demyelinating nature of the disease, the localization of plaques in different parts of the Prefrontal and Limbic System, may lead to memorial symptoms. This investigation was intended to study relationship between frequency of plaques and memorial symptoms arising from dysfunction limbic system and prefrontal of patients with MS. The sample was selected randomly from patients with MS with memory problem, who have been referred to Isfahan Multiple Sclerosis Society. Brain System Test and Memory Test was administered to the sample, and their MRI's were analyzed by specialist in order to indentify two different parts of plaques. The data was analyzed by SPSS. The results showed that there were significant relationship between MS plaques and prefrontal's dysfunction and memorial symptom related to prefrontal area; however, there were no significant relationship between MS plaques and limbic system's dysfunction and memorial symptoms related to limbic system area. The results of this study suggest that memorial symptoms due to injury regions of the brain have the most significant relationship to prefrontal. Better judgment about these results needs more studies in future.

Keywords: multiple sclerosis, magnetic image, brain injury, behavior disorder

Procedia PDF Downloads 514

Authors: Meirav Eshkol, Miri Blaufeld, Rinat Basal

Abstract:

Aim: The working environment in rural clinics is often isolated and distant from major health centers. In these circumstances, rural health care faces numerous challenges. The hope is that, in the immediate future and in the medium and long range, the rural nursing staff will realize their full professional and personal potential to their own satisfaction and to the health and welfare of their patients. Background: Rural nurses work mostly alone or with very few colleagues, and have the authority to make professional decisions, a fact which often requires them to make critical decisions in pressure situations. In addition, the expectations set for these nurses are extremely high, a fact which requires them to be extremely skilled and to fulfill their professional potential. They are required to provide high-quality and comprehensive care to the individual, the family, and the community and to maintain close interaction with the community. Work in a rural setting requires the flexibility to perform multiple tasks in an isolated setting, often far removed from major health centers. In order to maintain professional satisfaction for the rural nurse, expanded direction and training are required in professional know-how, and in the development of new and existing skills, toward the goal of treating a diverse population and to obtain a comprehensive view of the components of a diagnosis for treatment and to develop an understanding appropriate to the presented reality. Objective: To provide knowledge and to expand and develop professional skills in the prevention and advancement of health in the care of a diverse patient population. The development of strategies and skills for work under pressure alone instills expertise in performing multiple tasks in diverse disciplines. To reduce feelings of stress and burnout. Methodology: This course is the first and one of a kind in Clalit - the biggest health organisation in Israel. Observing and identifying the needs of the nurses in the field relating to the development of professional and personal skills defining goals and objectives, and determining the content of a course designed for rural nurses and kibbutz nurses who are not Clalit employees. Results: 43 nurses participated and 30 answered the feedback questionnaire. The rating of their experience was 4.33 (on a scale of 1-5, with 5 being the highest ranking). 92% indicated the importance of meeting with additional nurses to teach their colleagues. 83% of the nurses indicated an increased sense of organizational belonging. 60% indicated that the course helped to reduce feelings of stress and burnout in becoming a better rural nurse. 80% indicated that the course helped them establish intra-organizational professional cooperation and initiating processes. Conclusion: The course is an instrument which aids in increasing the feeling of organizational belonging, reducing feelings of stress and burnout, creation of relationships and cooperation both within and outside of the organization, increased the realization of the potential of the village nurse.

Keywords: rural nurse, alone, burnout, multiple tasks

Procedia PDF Downloads 69

Authors: Ming-Jong Tsai, T. M. Wu, R. C. Chu

Abstract:

The purpose of this study is to develop an Advanced linear calibration Technique for air flow sensing by using CTA-based Hot wire Anemometry. It contains a host PC with Human Machine Interface, a wind tunnel, a wind speed controller, an automatic data acquisition module, and nonlinear calibration model. To improve the fitting error by using single fitting polynomial, this study proposes a Multiple three-order Polynomial Fitting Method (MPFM) for fitting the non-linear output of a CTA-based Hot wire Anemometry. The CTA-based anemometer with built-in fitting parameters is installed in the wind tunnel, and the wind speed is controlled by the PC-based controller. The Hot-Wire anemometer's thermistor resistance change is converted into a voltage signal or temperature differences, and then sent to the PC through a DAQ card. After completion measurements of original signal, the Multiple polynomial mathematical coefficients can be automatically calculated, and then sent into the micro-processor in the Hot-Wire anemometer. Finally, the corrected Hot-Wire anemometer is verified for the linearity, the repeatability, error percentage, and the system outputs quality control reports.

Keywords: flow rate sensing, hot wire, constant temperature anemometry (CTA), linear calibration, multiple three-order polynomial fitting method (MPFM), temperature compensation

Procedia PDF Downloads 416

Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

Abstract:

Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

Procedia PDF Downloads 88

Authors: Jaehong Yu, Seoung Bum Kim

Abstract:

Clustering analysis can facilitate the extraction of intrinsic patterns in a dataset and reveal its natural groupings without requiring class information. For effective clustering analysis in high dimensional datasets, unsupervised dimensionality reduction is an important task. Unsupervised dimensionality reduction can generally be achieved by feature extraction or feature selection. In many situations, feature selection methods are more appropriate than feature extraction methods because of their clear interpretation with respect to the original features. The unsupervised feature selection can be categorized as feature subset selection and feature ranking method, and we focused on unsupervised feature ranking methods which evaluate the features based on their importance scores. Recently, several unsupervised feature ranking methods were developed based on ensemble approaches to achieve their higher accuracy and stability. However, most of the ensemble-based feature ranking methods require the true number of clusters. Furthermore, these algorithms evaluate the feature importance depending on the ensemble clustering solution, and they produce undesirable evaluation results if the clustering solutions are inaccurate. To address these limitations, we proposed an ensemble-based feature ranking method with random subspace and multiple-k ensemble (FRRM). The proposed FRRM algorithm evaluates the importance of each feature with the random subspace ensemble, and all evaluation results are combined with the ensemble importance scores. Moreover, FRRM does not require the determination of the true number of clusters in advance through the use of the multiple-k ensemble idea. Experiments on various benchmark datasets were conducted to examine the properties of the proposed FRRM algorithm and to compare its performance with that of existing feature ranking methods. The experimental results demonstrated that the proposed FRRM outperformed the competitors.

Keywords: clustering analysis, multiple-k ensemble, random subspace-based feature evaluation, unsupervised feature ranking

Procedia PDF Downloads 339

Authors: Lin Zhang

Abstract:

Neighborhood redevelopment is vital to improve residents’ living environment, and there has been a national neighborhood micro-redevelopment initiative in China since 2020, which is largely different from the previous large-scale demolition and reconstruction projects. Yet, few studies systematically examine the new interactions of multiple actors in this initiative. China’s neighborhood (micro-) redevelopment is a kind of governance network, and the complexity perspective could reflect the dynamic nature of multiple actors and their relationships in governance networks. In order to better understand the fundamental shifts of governance networks in China’s neighborhood micro-redevelopment, this paper adopted a theoretical framework of complexity in governance networks and analyzed the new governance networks of neighborhood micro-redevelopment projects in Haikou accordingly.

Keywords: neighborhood redevelopment, governance, networks, Haikou

Procedia PDF Downloads 90

Authors: Agostinho Antunes

Abstract:

The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of selected marine animal species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: marine genomics, evolutionary bioinformatics, human genome sequencing, genomic analyses

Procedia PDF Downloads 613

Authors: Eui-Hak Lee, Jae-Hyun Ro, Hyoung-Kyu Song

Abstract:

In internet of things (IoT) system, the communication scheme with reliability and low power is required to connect a terminal. Cooperative communication can achieve reliability and lower power than multiple-input multiple-output (MIMO) system. Cooperative communication increases the reliability with low power, but decreases a throughput. It has a weak point that the communication throughput is decreased. In this paper, a novel scheme is proposed to increase the communication throughput. The novel scheme is a transmission structure that increases transmission rate. And a decoding scheme according to the novel transmission structure is proposed. Simulation results show that the proposed scheme increases the throughput without bit error rate (BER) performance degradation.

Keywords: cooperative communication, IoT, STBC, transmission rate

Procedia PDF Downloads 396

Authors: Estela Macedo Alves

Abstract:

This paper is an overview on public policy analysis focused on the study of Brazilian public policy making process. The methodology is based on the review of some theories on the subject, linking them to Brazilian reality. The study presents basic policy analysis concepts, such as policy, polity and politics. It is emphasized John Kingdon's Multiple Stream Model, because of its clarifying aspects concerning public policies formulation process in democratic countries. In this path it was possible to establish interpretations on environmental public policies in Brazil and understand its methods, instead of presenting only a case study. At the end, it is possible to connect theory with Brazilian reality, identifying negative and positive points of its political processes and structure.

Keywords: Brazilian policies, environmental public policy, multiple stream model, public policy analysis

Procedia PDF Downloads 409

Authors: Nicole Vlasman, Karamjeet Dhillon

Abstract:

Over the past four years, the Healthy Relationships Program has been delivered in community organizations and schools across Canada. More than 240 groups have been facilitated in collaboration with 33 organizations. As a result, 2157 youth have been engaged in the programming. The purpose and scope of the Healthy Relationships Program are to offer sustainable, evidence-based skills through small group implementation to prevent violence and promote positive, healthy relationships in youth. The program development has included extensive networking at regional and national levels. The Healthy Relationships Program is currently being implemented, adapted, and researched within the Resilience and Inclusion through Strengthening and Enhancing Relationships (RISE-R) project. Alongside the project’s research objectives, the RISE-R team has worked to virtually share the ongoing findings of the project through a slow ontology approach. Slow ontology is a practice integrated into project systems and structures whereby slowing the pace and volume of outputs offers creative opportunities. Creative production reveals different layers of success and complements the project, the building blocks for sustainability. As a result of integrating a slow ontology approach, the RISE-R team has developed a Geographic Information System (GIS) that documents local landscapes through a Story Map feature, and more specifically, video installations. Video installations capture the cartography of space and place within the context of singular diverse community spaces (case studies). By documenting spaces via human connections, the project captures narratives, which further enhance the voices and faces of the community within the larger project scope. This GIS project aims to create a visual and interactive flow of information that complements the project's mixed-method research approach. Conclusively, creative project development in the form of a geographic information system can provide learning and engagement opportunities at many levels (i.e., within community organizations and educational spaces or with the general public). In each of these disconnected spaces, fragmented stories are connected through a visual display of project outputs. A slow ontology practice within the context of the RISE-R project documents activities on the fringes and within internal structures; primarily through documenting project successes as further contributions to the Centre for School Mental Health framework (philosophy, recruitment techniques, allocation of resources and time, and a shared commitment to evidence-based products).

Keywords: community programming, geographic information system, project development, project management, qualitative, slow ontology

Procedia PDF Downloads 156

Authors: R. R. Ramsheeja, R. Sreeraj

Abstract:

For view the internal structures of the human body such as liver, brain, kidney etc have a wide range of different modalities for medical images are provided nowadays. Computer Tomography is one of the most significant medical image modalities. In this paper use CT liver images for study the use of automatic computer aided techniques to calculate the volume of the liver tumor. Segmentation method is used for the detection of tumor from the CT scan is proposed. Gaussian filter is used for denoising the liver image and Adaptive Thresholding algorithm is used for segmentation. Multiple Region Of Interest(ROI) based method that may help to characteristic the feature different. It provides a significant impact on classification performance. Due to the characteristic of liver tumor lesion, inherent difficulties appear selective. For a better performance, a novel proposed system is introduced. Multiple ROI based feature selection and classification are performed. In order to obtain of relevant features for Support Vector Machine(SVM) classifier is important for better generalization performance. The proposed system helps to improve the better classification performance, reason in which we can see a significant reduction of features is used. The diagnosis of liver cancer from the computer tomography images is very difficult in nature. Early detection of liver tumor is very helpful to save the human life.

Keywords: computed tomography (CT), multiple region of interest(ROI), feature values, segmentation, SVM classification

Procedia PDF Downloads 509

Authors: Lemuel David

Abstract:

This study aims to investigate The Impact of Tax Policies on Small Business Growth in Developing Countries: A Case Study of Montserrado Mount County, Republic of Liberia. Businesses in Liberia are crucial for job creation and the economic empowerment of its citizens, especially in Grand Cape Mount County where they provide 95% of all jobs and support local capital formation. However, many businesses face challenges that lead to premature closure, including tax-related issues such as multiple taxations and high tax burdens. This research aims to examine the effects of various taxation on business survival in Grand Cape Mount County. The study employed a survey research design with a population of 50 and a sample size of 74. Data was collected using a self-administered questionnaire and analyzed quantitatively with simple percentages, and the research hypotheses were tested with ANOVA. The study findings revealed that multiple taxations hurts business survival, and the relationship between business size and its ability to pay taxes is significant. Therefore, the study recommends that the government of Liberia should create uniform tax policies that support business development in Grand Cape Mount County, and consider the size of businesses when formulating tax policies.

Keywords: multiple taxations, businesses, mortality, growth

Procedia PDF Downloads 78

Authors: Zi-Yan Chao

Abstract:

With the rapid development of urbanization and increasing demand for efficient transportation systems, the interaction between land use diversity and transportation resource allocation has become a critical issue in urban planning. Achieving a balance of land use types, such as residential, commercial, and industrial areas, is crucial role in ensuring social equity and sustainable urban development. Simultaneously, optimizing multimodal transportation networks, including bus, subway, and car routes, is essential for minimizing total travel time and costs, while ensuring fairness for all social groups, particularly in meeting the transportation needs of low-income populations. This study develops a bilevel programming model to address these challenges, with land use diversity as the foundation for measuring equity. The upper-level model maximizes land use diversity for balanced land distribution across regions. The lower-level model optimizes multimodal transportation networks to minimize travel time and costs while maintaining user equilibrium. The model also incorporates constraints to ensure fair resource allocation, such as balancing transportation accessibility and cost differences across various social groups. A solution approach is developed to solve the bilevel optimization problem, ensuring efficient exploration of the solution space for land use and transportation resource allocation. This study maximizes social equity by maximizing land use diversity and achieving user equilibrium with optimal transportation resource distribution. The proposed method provides a robust framework for addressing urban planning challenges, contributing to sustainable and equitable urban development.

Keywords: bilevel programming model, genetic algorithms, land use diversity, multimodal transportation optimization, social equity

Procedia PDF Downloads 24

Authors: Felipe Azocar Simonet, Luis Acosta Espejo

Abstract:

In this article, we will try to find an efficient boundary approximation for the bi-objective location problem with coherent coverage for two levels of hierarchy (CCLP). We present the mathematical formulation of the model used. Supported efficient solutions and unsupported efficient solutions are obtained by solving the bi-objective combinatorial problem through the weights method using a Lagrangean heuristic. Subsequently, the results are validated through the DEA analysis with the GEM index (Global efficiency measurement).

Keywords: coherent covering location problem, efficient frontier, lagragian relaxation, data envelopment analysis

Procedia PDF Downloads 334

Authors: Anurag Saxena, Alkesh Agrawal, Dinesh Kumar

Abstract:

The next generation mobile communication systems i.e. fourth generation (4G) was developed to accommodate the quality of service and required data rate. This project focuses on multiple access technique proposed in 4G communication systems. It is attempted to demonstrate the IDMA (Interleave Division Multiple Access) technology. The basic principle of IDMA is that interleaver is different for each user whereas CDMA employs different signatures. IDMA inherits many advantages of CDMA such as robust against fading, easy cell planning; dynamic channel sharing and IDMA increase the spectral efficiency and reduce the receiver complexity. In this, performance of IDMA is analyzed using QC-LDPC coding scheme further it is compared with LDPC coding and at last BER is calculated and plotted in MATLAB.

Keywords: 4G, QC-LDPC, CDMA, IDMA

Procedia PDF Downloads 323