Search results for: model selection

Authors: W. Du, X. Wang, Jun Cao, H. F. Wang

Abstract:

Due to the randomness and uncertainty of wind energy, modern power systems integrating large-scale wind generation will be significantly impacted in terms of system performance and technical challenges. System inertia with high wind penetration is decreasing when conventional thermal generators are gradually replaced by wind turbines, which do not naturally contribute to inertia response. The power imbalance caused by wind power or demand fluctuations leads to the instability of system frequency. Accordingly, the need to attach the supplementary virtual inertia control to wind farms (WFs) strongly arises. When multi-wind farms are connected to the grid simultaneously, the selection of which critical WFs to install the virtual inertia control is greatly important to enhance the stability of system frequency. By building the small signal model of wind power systems considering frequency regulation, the installation locations are identified by the geometric measures of the mode observability of WFs. In addition, this paper takes the impacts of grid topology and selection of feedback control signals into consideration. Finally, simulations are conducted on a multi-wind farms power system and the results demonstrate that the designed virtual inertia control method can effectively assist the frequency regulation.

Keywords: frequency regulation, virtual inertia control, installation locations, observability, wind farms

Procedia PDF Downloads 368

Authors: Othoman Elsayah, Naren Gupta, Binsheng Zhang

Abstract:

The construction sector constitutes one of the most important sectors in the economy of any country. Contractor selection is a critical decision that is undertaken by client organizations and is central to the success of any construction project. Contractor selection (CS) is a process which involves investigating, screening and determining whether candidate contractors have the technical and financial capability to be accepted to formally tender for construction work. The process should be conducted prior to the award of contract, characterized by many factors such as: contactor’s skills, experience on similar projects, track- record in the industry, and financial stability. However, this paper evaluates the current state of knowledge in relation to contractor selection process and demonstrates the findings from the analysis of the data collected from the Delphi questionnaire survey. The survey was conducted with a group of 12 experts working in the Libyan construction industry (LCI). The paper starts by briefly explaining the general outline of the questionnaire including the survey participation rate, the different fields the experts came from, and the business titles of the participants. Then, the paper describes the tests used to determine when the experts had reached consensus. The paper is based on research which aims to develop rank contractor selection criteria with specific application to make construction projects in the Libyan context. The findings of this study will be utilized to establish the scope of work that will be used as part of a PhD research.

Keywords: contractor selection, Libyan construction industry, decision experts, Delphi technique

Procedia PDF Downloads 294

Authors: Rohit Gupta, Ravinder Agarwal

Abstract:

Surface electromyographic (sEMG) signal has the potential to identify the human activities and intention. This potential is further exploited to control the artificial limbs using the sEMG signal from residual limbs of amputees. The paper deals with the development of multichannel cost efficient sEMG signal interface for research application, along with evaluation of proposed class dependent statistical approach of the feature selection method. The sEMG signal acquisition interface was developed using ADS1298 of Texas Instruments, which is a front-end interface integrated circuit for ECG application. Further, the sEMG signal is recorded from two lower limb muscles for three locomotions namely: Plane Walk (PW), Stair Ascending (SA), Stair Descending (SD). A class dependent statistical approach is proposed for feature selection and also its performance is compared with 12 preexisting feature vectors. To make the study more extensive, performance of five different types of classifiers are compared. The outcome of the current piece of work proves the suitability of the proposed feature selection algorithm for locomotion recognition, as compared to other existing feature vectors. The SVM Classifier is found as the outperformed classifier among compared classifiers with an average recognition accuracy of 97.40%. Feature vector selection emerges as the most dominant factor affecting the classification performance as it holds 51.51% of the total variance in classification accuracy. The results demonstrate the potentials of the developed sEMG signal acquisition interface along with the proposed feature selection algorithm.

Keywords: classifiers, feature selection, locomotion, sEMG

Procedia PDF Downloads 261

Authors: C. Asha Poorna, P. G. Vinod, A. R. R. Menon

Abstract:

Currently increasing population and their activities like urbanization and industrialization generating the greatest environmental, issue called Waste. And the major problem in waste management is selection of an appropriate site for waste disposal. The selection of suitable site have constrains like environmental, economical and political considerations. In this paper we discuss the strategies to be followed while selecting a site for decentralized system for solid waste disposal, using Geographic Information System (GIS), the Analytical Hierarchy Process (AHP) and the remote sensing method for Thiruvananthapuram corporation area. It is located on the west coast of India near the extreme south of the mainland. It lies on the shores of Killiyar and Karamana River. Being on the basin the waste managements must be regulated with the water body. The different criteria considered for waste disposal site selection are lithology, surface water, aquifer, groundwater, land use, contours, aspect, elevation, slope, and distance to road, distance from settlement are examined in relation to land fill site selection. Each criterion was identified and weighted by AHP score and mapped using GIS technique and suitable map is prepared by overlay analysis.

Keywords: waste disposal, solid waste management, Geographic Information System (GIS), Analytical Hierarchy Process (AHP)

Procedia PDF Downloads 366

Authors: Tefera Kebede Leyu

Abstract:

The purpose of this study was to estimate the impact of LIVES project participation on the level of technical efficiency of farm households in three regions of Ethiopia. We used household-level data gathered by IRLI between February and April 2014 for the year 2013(retroactive). Data on 1,905 (754 intervention and 1, 151 control groups) sample households were analyzed using STATA software package version 14. Efforts were made to combine stochastic frontier modeling with impact evaluation methodology using the Heckman (1979) two-stage model to deal with possible selectivity bias arising from unobservable characteristics in the stochastic frontier model. Results indicate that farmers in the two groups are not efficient and operate below their potential frontiers i.e., there is a potential to increase crop productivity through efficiency improvements in both groups. In addition, the empirical results revealed selection bias in both groups of farmers confirming the justification for the use of selection bias corrected stochastic frontier model. It was also found that intervention farmers achieved higher technical efficiency scores than the control group of farmers. Furthermore, the selectivity bias-corrected model showed a different technical efficiency score for the intervention farmers while it more or less remained the same for that of control group farmers. However, the control group of farmers shows a higher dispersion as measured by the coefficient of variation compared to the intervention counterparts. Among the explanatory variables, the study found that farmer’s age (proxy to farm experience), land certification, frequency of visit to improved seed center, farmer’s education and row planting are important contributing factors for participation decisions and hence technical efficiency of farmers in the study areas. We recommend that policies targeting the design of development intervention programs in the agricultural sector focus more on providing farmers with on-farm visits by extension workers, provision of credit services, establishment of farmers’ training centers and adoption of modern farm technologies. Finally, we recommend further research to deal with this kind of methodological framework using a panel data set to test whether technical efficiency starts to increase or decrease with the length of time that farmers participate in development programs.

Keywords: impact evaluation, efficiency analysis and selection bias, stochastic frontier model, Heckman-two step

Procedia PDF Downloads 31

Authors: Priyesh Kumar Singh, S. K. Sharma, Sanjay Verma, C. Samuel

Abstract:

Supplier Relationship Management (SRM), is strategic planning and managing of all interactions with suppliers to maximize its value. Its application varies from construction industries to healthcare system and investment banks to aviation industries. Several buyer-supplier relationship models, as well as supplier selection and evaluation strategies, have been documented by many academicians and researchers. In this paper, through a comprehensive literature review of over 30 published papers, different theoretical models, empirical data and conclusions were analysed relating to SRM to find its role in establishing better supplier relationships. These journal articles were searched by using the keyword “supplier relationship management,” in databases of Mendeley Library, ProQuest, EBSCO and Google Scholar. This paper reviews the academic literature on different relationship models, supplier evaluation, and selection strategies to discuss its implications in different situations. It also describes the dominant factors responsible for buyer-supplier relationships such trust and power. Finally, conclusions have been drawn which can be validated by various researchers and can help practitioners in industries.

Keywords: supplier relationship management, supplier performance, supplier evaluation, supplier selection strategies

Procedia PDF Downloads 219

Authors: Rahma Fitriani, Zerlita Fahdha Pusdiktasari, Herman Cahyo Diartho

Abstract:

Spatial panel model is commonly used to specify more complicated behavior of economic agent distributed in space at an individual-spatial unit level. There are several spatial panel models which can be adapted based on certain assumptions. A package called splm in R has several functions, ranging from the estimation procedure, specification tests, and model selection tests. In the absence of prior assumptions, a comprehensive procedure which utilizes the available functions in splm must be formed, which is the objective of this study. In this way, the best specification and model can be fitted based on data. The implementation of the procedure works well. It specifies SARAR-FE as the best model for agricultural productivity growth of the 38 East Java’s Regencies/Municipalities.

Keywords: spatial panel, specification, splm, agricultural productivity growth

Procedia PDF Downloads 145

Authors: Karima Megdouli, Bourhan tachtouch

Abstract:

Ejector refrigeration cycles offer an alternative to conventional systems for producing cold from low-temperature heat. In this article, a thermodynamic model is presented. This model has the advantage of simplifying the calculation algorithm and describes the complex double-throttling mechanism that occurs in the ejector. The model assumption and calculation algorithm are presented first. The impact of each efficiency is evaluated. Validation is performed on several data sets. The ejector model is then used to simulate a RES (refrigeration ejector system), to validate its robustness and suitability for use in predicting thermodynamic cycle performance. A Taguchi and ANOVA optimization is carried out on a RES. TOPSIS analysis was applied to decide the optimum refrigerants with cost, safety, environmental and enviro economic concerns along with thermophysical properties.

Keywords: ejector, velocity distribution, shock circle, Taguchi and ANOVA optimization, TOPSIS analysis

Procedia PDF Downloads 44

Authors: Jianan Sun, Ziwen Ye

Abstract:

Multidimensional computerized adaptive testing (MCAT) is a popular research topic in psychometrics. It is important for practitioners to clearly know the item-trait patterns of administered items when a test like MCAT is operated. Item-trait pattern recognition refers to detecting which latent traits in a psychological test are measured by each of the specified items. If the item-trait patterns of the replenished items in MCAT item pool are well detected, the interpretability of the items can be improved, which can further promote the abilities of the examinees who attending the MCAT to be accurately estimated. This research explores to solve the item-trait pattern recognition problem of the replenished items in MCAT item pool from the perspective of statistical variable selection. The popular multidimensional item response theory model, multidimensional two-parameter logistic model, is assumed to fit the response data of MCAT. The proposed method uses the least absolute shrinkage and selection operator (LASSO) to detect item-trait patterns of replenished items based on the essential information of item responses and ability estimates of examinees collected from a designed MCAT procedure. Several advantages of the proposed method are outlined. First, the proposed method does not strictly depend on the relative order between the replenished items and the selected operational items, so it allows the replenished items to be mixed into the operational items in reasonable order such as considering content constraints or other test requirements. Second, the LASSO used in this research improves the interpretability of the multidimensional replenished items in MCAT. Third, the proposed method can exert the advantage of shrinkage method idea for variable selection, so it can help to check item quality and key dimension features of replenished items and saves more costs of time and labors in response data collection than traditional factor analysis method. Moreover, the proposed method makes sure the dimensions of replenished items are recognized to be consistent with the dimensions of operational items in MCAT item pool. Simulation studies are conducted to investigate the performance of the proposed method under different conditions for varying dimensionality of item pool, latent trait correlation, item discrimination, test lengths and item selection criteria in MCAT. Results show that the proposed method can accurately detect the item-trait patterns of the replenished items in the two-dimensional and the three-dimensional item pool. Selecting enough operational items from the item pool consisting of high discriminating items by Bayesian A-optimality in MCAT can improve the recognition accuracy of item-trait patterns of replenished items for the proposed method. The pattern recognition accuracy for the conditions with correlated traits is better than those with independent traits especially for the item pool consisting of comparatively low discriminating items. To sum up, the proposed data-driven method based on the LASSO can accurately and efficiently detect the item-trait patterns of replenished items in MCAT.

Keywords: item-trait pattern recognition, least absolute shrinkage and selection operator, multidimensional computerized adaptive testing, variable selection

Procedia PDF Downloads 91

Authors: Bambang Heliyanto, Rully Dyah Purwati, Hasnam, Fadjry Djufry

Abstract:

Jatropha curcas L., a drought tolerant and monoecious perennial shrub, has received attention worldwide during the past decade. Realizing the facts, the Indonesian government has decided to option for Jatropha and palm oil for in country biofuel production. To support the program development of high yielding jatropha varieties is necessary. This paper reviews Jatropha improvement program in Indonesia using mass selection and hybrid development. To start with, at the end of 2005, in-country germplasm collection was mobilized to Lampung and Nusa Tenggara Barat (NTB) provinces and successfully collected 15 provenances/sub-provenances which serves as a base population for selection. A significant improvement has been achieved through a simple recurrent breeding selection during 2006 to 2007. Seed yield productivity increased more than double, from 0.36 to 0.97 ton dry seed per hectare during the first selection cycle (IP-1), and then increased to 2.2 ton per hectare during the second cycles (IP-2) in Lampung provenance. Similar result was also observed in NTB provenance. Seed yield productivity increased from 0.43 ton to 1 ton dry seed per hectare in the first cycle (IP-1), and then 1.9 ton in the second cycle (IP-2). In 2008, the population IP-3 resulted from the third cycle of selection have been identified which were capable of producing 2.2 to 2.4 ton seed yield per hectare. To improve the seed yield per hectare, jatropha hybrid varieties was developed involving superior provenances. As a result a Jatropha Energy Terbarukan (JET) variety-2 was released in 2017 with seed yield potential of 2.6 ton per hectare. The use of this high yielding genotypes for biofuel is discussed.

Keywords: Jatropha curcas, provenance, biofuel, improve population, hybrid

Procedia PDF Downloads 135

Authors: Samir K. Safi

Abstract:

The purpose of this study was to compare the performance of two types of models, namely MIDAS and MIDAS-GARCH, in predicting the volatility of crude oil returns based on gold price returns and the COVID-19 pandemic. The study aimed to identify which model would provide more accurate short-term and long-term predictions and which model would perform better in handling the increased volatility caused by the pandemic. The findings of the study revealed that the MIDAS model performed better in predicting short-term and long-term volatility before the pandemic, while the MIDAS-GARCH model performed significantly better in handling the increased volatility caused by the pandemic. The study highlights the importance of selecting appropriate models to handle the complexities of real-world data and shows that the choice of model can significantly impact the accuracy of predictions. The practical implications of model selection and exploring potential methodological adjustments for future research will be highlighted and discussed.

Keywords: GARCH-MIDAS, MIDAS, crude oil, gold, COVID-19, volatility

Procedia PDF Downloads 13

Authors: Wafa’ Alma'Aitah, Khaled Almakadmeh

Abstract:

this study presents an information retrieval system of using genetic algorithm to increase information retrieval efficiency. Using vector space model, information retrieval is based on the similarity measurement between query and documents. Documents with high similarity to query are judge more relevant to the query and should be retrieved first. Using genetic algorithms, each query is represented by a chromosome; these chromosomes are fed into genetic operator process: selection, crossover, and mutation until an optimized query chromosome is obtained for document retrieval. Results show that information retrieval with adaptive crossover probability and single point type crossover and roulette wheel as selection type give the highest recall. The proposed approach is verified using (242) proceedings abstracts collected from the Saudi Arabian national conference.

Keywords: genetic algorithm, information retrieval, optimal queries, crossover

Procedia PDF Downloads 260

Authors: Mohammad Jalali Varnamkhasti

Abstract:

The genetic algorithms have been very successful in handling difficult optimization problems. The fundamental problem in genetic algorithms is premature convergence. This paper, present a new fuzzy genetic algorithm based on chaotic values instead of the random values in genetic algorithm processes. In this algorithm, for initial population is used chaotic sequences and then a new sexual selection proposed for selection mechanism. In this technique, the population is divided such that the male and female would be selected in an alternate way. The layout of the male and female chromosomes in each generation is different. A female chromosome is selected by tournament selection size from the female group. Then, the male chromosome is selected, in order of preference based on the maximum Hamming distance between the male chromosome and the female chromosome or The highest fitness value of male chromosome (if more than one male chromosome is having the maximum Hamming distance existed), or Random selection. The selections of crossover and mutation operators are achieved by running the fuzzy logic controllers, the crossover and mutation probabilities are varied on the basis of the phenotype and genotype characteristics of the chromosome population. Computational experiments are conducted on the proposed techniques and the results are compared with some other operators, heuristic and local search algorithms commonly used for solving p-median problems published in the literature.

Keywords: genetic algorithm, fuzzy system, chaos, sexual selection

Procedia PDF Downloads 356

Authors: Sudha T., Naveen C.

Abstract:

Dengue is a serious public health issue that causes significant annual economic and welfare burdens on nations. However, enhanced optimization techniques and quantitative modeling approaches can predict the incidence of dengue. By advocating for a data-driven approach, public health officials can make informed decisions, thereby improving the overall effectiveness of sudden disease outbreak control efforts. The National Oceanic and Atmospheric Administration and the Centers for Disease Control and Prevention are two of the U.S. Federal Government agencies from which this study uses environmental data. Based on environmental data that describe changes in temperature, precipitation, vegetation, and other factors known to affect dengue incidence, many predictive models are constructed that use different machine learning methods to estimate weekly dengue cases. The first step involves preparing the data, which includes handling outliers and missing values to make sure the data is prepared for subsequent processing and the creation of an accurate forecasting model. In the second phase, multiple feature selection procedures are applied using various machine learning models and optimization techniques. During the third phase of the research, machine learning models like the Huber Regressor, Support Vector Machine, Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR) are compared with several optimization techniques for feature selection, such as Harmony Search and Genetic Algorithm. In the fourth stage, the model's performance is evaluated using Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) as assistance. Selecting an optimization strategy with the least number of errors, lowest price, biggest productivity, or maximum potential results is the goal. In a variety of industries, including engineering, science, management, mathematics, finance, and medicine, optimization is widely employed. An effective optimization method based on harmony search and an integrated genetic algorithm is introduced for input feature selection, and it shows an important improvement in the model's predictive accuracy. The predictive models with Huber Regressor as the foundation perform the best for optimization and also prediction.

Keywords: deep learning model, dengue fever, prediction, optimization

Procedia PDF Downloads 14

Authors: Joseph Gear, Yue Xu, Ernest Foo, Praveen Gauravaran, Zahra Jadidi, Leonie Simpson

Abstract:

Deep learning methods have been seeing an increasing application to the long-standing security research goal of automatic vulnerability detection for source code. Attention, however, must still be paid to the task of producing vector representations for source code (code embeddings) as input for these deep learning models. Graphical representations of code, most predominantly Abstract Syntax Trees and Code Property Graphs, have received some use in this task of late; however, for very large graphs representing very large code snip- pets, learning becomes prohibitively computationally expensive. This expense may be reduced by intelligently pruning this input to only vulnerability-relevant information; however, little research in this area has been performed. Additionally, most existing work comprehends code based solely on the structure of the graph at the expense of the information contained by the node in the graph. This paper proposes Semantic-enhanced Code Embedding for Vulnerability Discovery (SCEVD), a deep learning model which uses semantic-based feature selection for its vulnerability classification model. It uses information from the nodes as well as the structure of the code graph in order to select features which are most indicative of the presence or absence of vulnerabilities. This model is implemented and experimentally tested using the SARD Juliet vulnerability test suite to determine its efficacy. It is able to improve on existing code graph feature selection methods, as demonstrated by its improved ability to discover vulnerabilities.

Keywords: code representation, deep learning, source code semantics, vulnerability discovery

Procedia PDF Downloads 125

Authors: Kaleb Shiferaw, Berhanu Geberemedhin, Dereje Legesse

Abstract:

Access to credit is often viewed as a key to transform semi-subsistence smallholders into market oriented producers. However, only a few studies have examined factors that affect farmers’ decision to allocate credit on farm activities in general and livestock production in particular. A trivariate probit model with double selection is employed to identify factors that affect farmers’ decision to allocate credit on livestock production using data collected from smallholder farmers in Ethiopia. After controlling for two sample selection bias – taking credit for the production season and decision to allocate credit on farm activities – land ownership and access to a livestock centered extension service are found to have a significant (p<0.001) effect on farmers decision to use credit for livestock production. The result showed farmers with large land holding, and access to a livestock centered extension services are more likely to utilize credit for livestock production. However since the effect of land ownership squared is negative the effect of land ownership for those who own a large plot of land lessens. The study highlights the fact that improving access to credit does not automatically translate into more productive households. Improving farmers’ access to credit should be followed by a focused extension services.

Keywords: livestock production, credit access, credit allocation, household decision, double sample selection

Procedia PDF Downloads 290

Authors: Y. Kourd, D. Lefebvre

Abstract:

The monitoring of industrial processes is required to ensure operating conditions of industrial systems through automatic detection and isolation of faults. This paper proposes a method of fault diagnosis based on a neuro-fuzzy hybrid structure. This hybrid structure combines the selection of threshold and decision tree. The validation of this method is obtained with the DAMADICS benchmark. In the first phase of the method, a model will be constructed that represents the normal state of the system to fault detection. Signatures of the faults are obtained with residuals analysis and selection of appropriate thresholds. These signatures provide groups of non-separable faults. In the second phase, we build faulty models to see the flaws in the system that cannot be isolated in the first phase. In the latest phase we construct the tree that isolates these faults.

Keywords: decision tree, residuals analysis, ANFIS, fault diagnosis

Procedia PDF Downloads 585

Authors: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

Abstract:

An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

Procedia PDF Downloads 275

Authors: Ali E. Abbas

Abstract:

Industrial Engineering is a broad multidisciplinary field with intersections and applications in numerous areas. When designing a product, it is important to determine the appropriate attributes of value and the preference function for which the product is optimized. This paper provides some guidelines on appropriate selection of attributes for preference and value functions for engineering design.

Keywords: decision analysis, industrial engineering, direct vs. indirect values, engineering management

Procedia PDF Downloads 271

Authors: Shahabeddin Sotudian, M. H. Fazel Zarandi, I. B. Turksen

Abstract:

Hepatitis is one of the most common and dangerous diseases that affects humankind, and exposes millions of people to serious health risks every year. Diagnosis of Hepatitis has always been a challenge for physicians. This paper presents an effective method for diagnosis of hepatitis based on interval Type-II fuzzy. This proposed system includes three steps: pre-processing (feature selection), Type-I and Type-II fuzzy classification, and system evaluation. KNN-FD feature selection is used as the preprocessing step in order to exclude irrelevant features and to improve classification performance and efficiency in generating the classification model. In the fuzzy classification step, an “indirect approach” is used for fuzzy system modeling by implementing the exponential compactness and separation index for determining the number of rules in the fuzzy clustering approach. Therefore, we first proposed a Type-I fuzzy system that had an accuracy of approximately 90.9%. In the proposed system, the process of diagnosis faces vagueness and uncertainty in the final decision. Thus, the imprecise knowledge was managed by using interval Type-II fuzzy logic. The results that were obtained show that interval Type-II fuzzy has the ability to diagnose hepatitis with an average accuracy of 93.94%. The classification accuracy obtained is the highest one reached thus far. The aforementioned rate of accuracy demonstrates that the Type-II fuzzy system has a better performance in comparison to Type-I and indicates a higher capability of Type-II fuzzy system for modeling uncertainty.

Keywords: hepatitis disease, medical diagnosis, type-I fuzzy logic, type-II fuzzy logic, feature selection

Procedia PDF Downloads 275

Authors: Nivedita Paul

Abstract:

The changing character of marriage be it arranged marriage, love marriage, polygamy, informal unions, all signify different gender relations in everyday lives. Marriages in India are part and parcel of the kinship and cultural practices. Arranged marriage is still the dominant form of marriage where spouse selection is the initiative and decision of the parents; but its form is changing, as women are now actively participating in spouse selection but with parental consent. Spouse selection related decision making is important because marriage as an institution brings social change and gender inequality; especially in a women’s life as marriages in India are mostly patrilocal. Moreover, the amount of say in spouse selection can affect a woman’s reproductive rights, domestic violence issues, household resource allocation, communication possibilities with the spouse/husband, marital life, etc. The present study uses data from Indian Human Development Survey II (2011-12) which is a nationally representative multitopic survey that covers 41,554 households. Currently, married women of age group 15-49 in their first marriage; whose year of marriage is from 1970s to 2000s have been taken for the study. Based on spouse selection experiences, the sample of women has been divided into three marriage categories-self, semi and family arranged. Women in self arranged or love marriage is the sole decision maker in choosing the partner, in semi arranged marriage or arranged marriage with consent both parents and women together take the decision, whereas in family arranged or arranged marriage without consent only parents take the decision. The main aim of the study is to find the relationship between spouse selection experiences and women’s autonomy in India. Decision making in economic matters, child and health related decision making, mobility and access to resources are taken to be proxies of autonomy. Method of ordinal regression has been used to find the relationship between spouse selection experiences and autonomy after marriage keeping other independent variables as control factors. Results show that women in semi arranged marriage have more decision making power regarding financial matters of the household, health related matters, mobility and accessibility to resources, when compared to women in family, arranged marriages. For freedom of movement and access to resources women in self arranged marriage have the highest say or exercise greatest power. Therefore, greater participation of women (even though not absolute control) in spouse selection may lead to greater autonomy after marriage.

Keywords: arranged marriage, autonomy, consent, spouse selection

Procedia PDF Downloads 120

Authors: Emmanuel U. Unuafe, Oyegoke T. Bukoye, Sandhya Sastry, Yanqing Duan

Abstract:

Globally, there is increasing interest in project management due to a shortage in infrastructure services supply capability. Hence, it is of utmost importance that organisations understand that choosing a particular project over another is an opportunity cost – tying up the organisations resources. In order to devise constructive ways to bring direction, structure, and oversight to the process of project selection has led to the development of tools and techniques by researchers and practitioners. However, despite the development of various frameworks to assist in the appraisal and selection of government projects, failures are still being recorded with government projects. In developing countries, where frameworks are rarely used, the problems are compounded. To improve the situation, this study will investigate the current practice of construction project selection processes within the Nigeria public sector in order to inform theories of decision making from the perspective of developing nations and project management practice. Unlike other research around construction projects in Nigeria this research concentrate on factors influencing the selection process within the Nigeria public sector, which has received limited study. The authors report the findings of semi-structured interviews of top management in the Nigerian public sector and draw conclusions in terms of decision making extant theory and current practice. Preliminary results from the data analysis show that groups make project selection decisions and this forces sub-optimal decisions due to pressure on time, clashes of interest, lack of standardised framework for selecting projects, lack of accountability and poor leadership. Consequently, because decision maker is usually drawn from different fields, religious beliefs, ethnic group and with different languages. The choice of a project by an individual will be greatly influence by experience, political precedence than by realistic investigation as well as his understanding of the desired outcome of the project, in other words, the individual’s ideology and their level of fairness.

Keywords: factors influencing project selection, public sector construction project selection, projects portfolio selection, strategic decision-making

Procedia PDF Downloads 305

Authors: Abdullah Eqal Al Mazrooei

Abstract:

In this work, a new nonlinear model will be introduced. The model is in the state-space form. The nonlinearity of this model is in the state equation where the state vector is multiplied by its self. This technique makes our model generalizes many famous models as Lotka-Volterra model and Lorenz model which have many applications in the real life. We will apply our new model to estimate the wind speed by using a new nonlinear estimator which suitable to work with our model.

Keywords: nonlinear systems, state-space model, Kronecker product, nonlinear estimator

Procedia PDF Downloads 651

Authors: Qiang Zhang, Xiaojian Hu

Abstract:

In multi-vehicle tracking, based on feature selection, the tracking system efficiently tracks vehicles in a video with minimal error in combination with color attribution, which focuses on presenting a simple and fast, yet accurate and robust solution to the problem such as inaccurately and untimely responses of statistics-based adaptive traffic control system in the intersection scenario. In this study, a real-time tracking system is proposed for multi-vehicle tracking in the intersection scene. Considering the complexity and application feasibility of the algorithm, in the object detection step, the detection result provided by virtual loops were post-processed and then used as the input for the tracker. For the tracker, lightweight methods were designed to extract and select features and incorporate them into the adaptive color tracking (ACT) framework. And the approbatory online feature selection algorithms are integrated on the mature ACT system with good compatibility. The proposed feature selection methods and multi-vehicle tracking method are evaluated on KITTI datasets and show efficient vehicle tracking performance when compared to the other state-of-the-art approaches in the same category. And the system performs excellently on the video sequences recorded at the intersection. Furthermore, the presented vehicle tracking system is suitable for surveillance applications.

Keywords: real-time, multi-vehicle tracking, feature selection, color attribution

Procedia PDF Downloads 115

Authors: Jalal Abdulkareem Sultan, Abdulhakeem Luqman Hasan

Abstract:

With the development of health care systems competition, hospitals face more and more pressures. Meanwhile, resource allocation has a vital effect on achieving competitive advantages in hospitals. Selecting the appropriate number of beds is one of the most important sections in hospital management. However, in real situation, bed allocation selection is a multiple objective problem about different items with vagueness and randomness of the data. It is very complex. Hence, research about bed allocation problem is relatively scarce under considering multiple departments, nursing hours, and stochastic information about arrival and service of patients. In this paper, we develop a fuzzy multiobjective bed allocation model for overcoming uncertainty and multiple departments. Fuzzy objectives and weights are simultaneously applied to help the managers to select the suitable beds about different departments. The proposed model is solved by using Artificial Bee Colony (ABC), which is a very effective algorithm. The paper describes an application of the model, dealing with a public hospital in Iraq. The results related that fuzzy multi-objective model was presented suitable framework for bed allocation and optimum use.

Keywords: bed allocation problem, fuzzy logic, artificial bee colony, multi-objective optimization

Procedia PDF Downloads 291

Authors: Emel Kızılkaya Aydogan, Mihrimah Ozmen, Yılmaz Delice

Abstract:

In recent days, there is a change and the ongoing development of the telecommunications sector in the global market. In this sector, churn analysis techniques are commonly used for analysing why some customers terminate their service subscriptions prematurely. In addition, customer churn is utmost significant in this sector since it causes to important business loss. Many companies make various researches in order to prevent losses while increasing customer loyalty. Although a large quantity of accumulated data is available in this sector, their usefulness is limited by data quality and relevance. In this paper, a cost-sensitive feature selection framework is developed aiming to obtain the feature reducts to predict customer churn. The framework is a cost based optional pre-processing stage to remove redundant features for churn management. In addition, this cost-based feature selection algorithm is applied in a telecommunication company in Turkey and the results obtained with this algorithm.

Keywords: churn prediction, data mining, decision-theoretic rough set, feature selection

Procedia PDF Downloads 410

Authors: Mehrshad Khosraviani, Faramarz Abbaspour Leyl Abadi

Abstract:

The fundamental component of the computer network of modern information society will be considered. These networks are connected to the network of the internet generally. Due to the fact that the primary purpose of the Internet is not designed for, in recent decades, none of these networks in many of the attacks has been very important. Today, for the provision of security, different security tools and systems, including intrusion detection systems are used in the network. A common diagnosis system based on artificial immunity, the designer, the Adhasaz Foundation has been evaluated. The idea of using artificial safety methods in the diagnosis of abnormalities in computer networks it has been stimulated in the direction of their specificity, there are safety systems are similar to the common needs of m, that is non-diagnostic. For example, such methods can be used to detect any abnormalities, a variety of attacks, being memory, learning ability, and Khodtnzimi method of artificial immune algorithm pointed out. Diagnosis of the common system of education offered in this paper using only the normal samples is required for network and any additional data about the type of attacks is not. In the proposed system of positive selection and negative selection processes, selection of samples to create a distinction between the colony of normal attack is used. Copa real data collection on the evaluation of ij indicates the proposed system in the false alarm rate is often low compared to other ir methods and the detection rate is in the variations.

Keywords: artificial immune system, abnormality detection, intrusion detection, computer networks

Procedia PDF Downloads 327

Authors: Shabnam Najafi, Metin Turkay

Abstract:

Network design problem (NDP) is used to determine the set of optimal values for certain pre-specified decision variables such as capacity expansion of nodes and links by optimizing various system performance measures including safety, congestion, and accessibility. The designed transportation network should improve objective functions defined for the system by considering the route choice behaviors of network users at the same time. The NDP studies mostly investigated the random demand and route selection constraints separately due to computational challenges. In this work, we consider both random demand and route selection constraints simultaneously. This work presents a nonlinear stochastic model for land use and road network design problem to address the development of different functional zones in urban areas by considering both cost function and air pollution. This model minimizes cost function and air pollution simultaneously with random demand and stochastic route selection constraint that aims to optimize network performance via road capacity expansion. The Bureau of Public Roads (BPR) link impedance function is used to determine the travel time function in each link. We consider a city with origin and destination nodes which can be residential or employment or both. There are set of existing paths between origin-destination (O-D) pairs. Case of increasing employed population is analyzed to determine amount of roads and origin zones simultaneously. Minimizing travel and expansion cost of routes and origin zones in one side and minimizing CO emission in the other side is considered in this analysis at the same time. In this work demand between O-D pairs is random and also the network flow pattern is subject to stochastic user equilibrium, specifically logit route choice model. Considering both demand and route choice, random is more applicable to design urban network programs. Epsilon-constraint is one of the methods to solve both linear and nonlinear multi-objective problems. In this work epsilon-constraint method is used to solve the problem. The problem was solved by keeping first objective (cost function) as the objective function of the problem and second objective as a constraint that should be less than an epsilon, where epsilon is an upper bound of the emission function. The value of epsilon should change from the worst to the best value of the emission function to generate the family of solutions representing Pareto set. A numerical example with 2 origin zones and 2 destination zones and 7 links is solved by GAMS and the set of Pareto points is obtained. There are 15 efficient solutions. According to these solutions as cost function value increases, emission function value decreases and vice versa.

Keywords: epsilon-constraint, multi-objective, network design, stochastic

Procedia PDF Downloads 609

Authors: Hanan Hayat, Russell Lock

Abstract:

The importance of usability in ensuring software quality has been well established in literature and widely accepted by software development practitioners. Consequently, numerous usability evaluation methods have been developed. However, the availability of large variety of evaluation methods alongside insufficient studies that critically analyse them resulted in an ambiguous process of selection amongst non-usability-expert practitioners. This study investigates the factors affecting the selection of usability evaluation methods within a project by interviewing a software development team. The results of the data gathered are then analysed and integrated in developing a framework. The framework developed poses a solution to the selection processes of usability evaluation methods by adjusting to individual projects resources and goals. It has the potential to be further evaluated to verify its applicability and usability within the domain of this study.

Keywords: usability evaluation, evaluating usability in non-user entered designs, usability evaluation methods (UEM), usability evaluation in projects

Procedia PDF Downloads 127

Authors: M. Maleki Sadabad, A. Pointing, N. Marashi

Abstract:

With respect to the role and increasing importance of technology for countries development, in recent decades technology development has paid attention in a systematic form. Nowadays the markets face with highly complicated and competitive conditions in foreign markets, therefore, evaluation and selection of technology effectiveness and also formulating technology strategy have changed into a vital subject for some organizations. The study introduces the standards of empowerment evaluation and technology attractiveness especially strategic technologies which explain the way of technology evaluation, selection and finally formulating suitable technology strategy in the field of drilling in South Azadegan oil field. The study firstly identifies the key challenges of oil fields in order to evaluate the technologies in field of drilling in South Azadegan oil field through an interview with the experts of industry and then they have been prioritised. In the following, the existing and new technologies were identified to solve the challenges of South Azadegan oil field. In order to explore the ability, availability, and attractiveness of every technology, a questionnaire based on Julie indices has been designed and distributed among the industry elites. After determining the score of ability, availability and attractiveness, every technology which has been obtained by the average of expert’s ideas, the technology package has been introduced by Morin’s model. The matrix includes four areas which will follow the especial strategy. Finally, by analysing the above matrix, the technology options have been suggested in order to select and invest.

Keywords: technology, technology identification, drilling technologies, technology capability

Procedia PDF Downloads 106