Search results for: fuzzy ranking

Authors: Jian-Na Zhang, Xiao-Li Chen, Si-Jian Li

Abstract:

Objective: In order to investigate current status on knowledge of disaster prevention and reduction in rural pupils, to explore education method on disaster prevention and reduction for rural pupils. Method: A questionnaire was designed based on literature review. Convenient sampling was used in the survey. The questionnaire survey was conducted among 180 students from Huodehong town central primary school which located in Ludian county of Zhaotong city in Yunnan province, where 6.5 magnitude earthquake happened in 2014. The result indicated that the pupils’ knowledge and skills on disaster prevention and reduction relevant poor. The source for them to obtain the knowledge of disaster prevention and reduction included TV (68.9%), followed by their parents (43.9%), while only 24.4% of knowledge is from the teachers. The scores about different natural disaster are ranking in descending order: earthquake (5.39 ±1.27), floods (3.77 ±1.17); debris flow (2.81 ±1.05), family fire (2.16± 0.96). And the disaster experience did not help the pupils enhance the knowledge reserves. There is no statistical significance (P > 0.05) in knowledge scores of disaster prevention and reduction between experienced and non-experienced group. Conclusion: The local disaster experiences did not draw the attention of parents and schools. Knowledge popularization of disaster for local pupils is extremely urgent. It is necessary to take advantage of more mediums to popularize the knowledge and skills about disaster prevention and reduction, for example, family education, school education, newspapers, brochures, etc. The training courses on disaster prevention and reduction which are based on the characteristics of the local rural pupils and the characteristics of the local disasters would be useful.

Keywords: rural, pupils, disaster prevention and reduction knowledge, popularization

Procedia PDF Downloads 324

Authors: I Made Ginarsa, Agung Budi Muljono, I Made Ari Nrartha

Abstract:

Transient voltage response appears in power system operation when an additional loading is forced to load bus of power systems. In this research, improvement of transient voltage response is done by using power system stabilizer-static var compensator (PSS-SVC) based on adaptive neuro-fuzzy inference system (ANFIS)-algorithm. The main function of the PSS is to add damping component to damp rotor oscillation through automatic voltage regulator (AVR) and excitation system. Learning process of the ANFIS is done by using off-line method where data learning that is used to train the ANFIS model are obtained by simulating the PSS-SVC conventional. The ANFIS model uses 7 Gaussian membership functions at two inputs and 49 rules at an output. Then, the ANFIS-PSS and ANFIS-SVC models are applied to power systems. Simulation result shows that the response of transient voltage is improved with settling time at the time of 4.25 s.

Keywords: improvement, transient voltage, PSS-SVC, ANFIS, settling time

Procedia PDF Downloads 548

Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammad Hossein Sedaaghi

Abstract:

Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.

Keywords: facial image, segmentation, PCM, FCM, skin error, facial surgery

Procedia PDF Downloads 561

Authors: D. Pinto, L. Castro, M. L. Cruzat, S. Barros, J. Gironás, C. Oberli, M. Torres, C. Escauriaza, A. Cipriano

Abstract:

Flash floods, together with landslides, are a common natural threat for people living in mountainous regions and foothills. One way to deal with this constant menace is the use of Early Warning Systems, which have become a very important mitigation strategy for natural disasters. In this work, we present our proposal for a pilot Flash Flood Early Warning System for Santiago, Chile, the first stage of a more ambitious project that in a future stage shall also include early warning of landslides. To give a context for our approach, we first analyze three existing Flash Flood Early Warning Systems, focusing on their general architectures. We then present our proposed system, with main focus on the decision support system, a system that integrates empirical models and fuzzy expert systems to achieve reliable risk estimations.

Keywords: decision support systems, early warning systems, flash flood, natural hazard

Procedia PDF Downloads 350

Authors: Gagandeep Singh, Navdeep Singh

Abstract:

Due to limited battery of sensor nodes, so energy efficiency found to be main constraint in WSN. Therefore the main focus of the present work is to find the ways to minimize the energy consumption problem and will results; enhancement in the network stability period and life time. Many researchers have proposed different kind of the protocols to enhance the network lifetime further. This paper has evaluated the issues which have been neglected in the field of the WSNs. WSNs are composed of multiple unattended ultra-small, limited-power sensor nodes. Sensor nodes are deployed randomly in the area of interest. Sensor nodes have limited processing, wireless communication and power resource capabilities Sensor nodes send sensed data to sink or Base Station (BS). I-LEACH gives adaptive clustering mechanism which very efficiently deals with energy conservations. This paper ends up with the shortcomings of various adaptive clustering based WSNs protocols.

Keywords: WSN, I-Leach, MATLAB, sensor

Procedia PDF Downloads 253

Authors: Vahid Anari, Leila Shahmohammadi

Abstract:

Diagnosing and interpreting manually from a large cohort dataset of immunohistochemically stained tissue of tumors using an optical microscope involves subjectivity and also is tedious for pathologist specialists. Moreover, digital pathology today represents more of an evolution than a revolution in pathology. In this paper, we develop and test an unsupervised algorithm that can automatically enhance the IHC image of a meningioma tumor and classify cells into positive (proliferative) and negative (normal) cells. A dataset including 150 images is used to test the scheme. In addition, a new adaptive color image enhancement method is proposed based on a vector directional filter (VDF) and statistical properties of filtering the window. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images.

Keywords: digital pathology, cell segmentation, immunohistochemically, noise reduction

Procedia PDF Downloads 45

Authors: Wiem Daoud Ben Amor, Luis Martínez López, Hela Moalla Frikha

Abstract:

Most of the multi-criteria group decision making (MCGDM) problems dealing with qualitative criteria require consideration of the large background of expert information. It is common that experts have different degrees of knowledge for giving their alternative assessments according to criteria. So, it seems logical that they use different evaluation scales to express their judgment, i.e., multi granular linguistic scales. In this context, we propose the extension of the classical additive ratio assessment (ARAS) method to the case of a hierarchical linguistics term for managing multi granular linguistic scales in uncertain contexts where uncertainty is modeled by means in linguistic information. The proposed approach is called the extended hierarchical linguistics-ARAS method (ARAS-ELH). Within the ARAS-ELH approach, the DM can diagnose the results (the ranking of the alternatives) in a decomposed style, i.e., not only at one level of the hierarchy but also at the intermediate ones. Also, the developed approach allows a feedback transformation i.e the collective final results of all experts able to be transformed at any level of the extended linguistic hierarchy that each expert has previously used. Therefore, the ARAS-ELH technique makes it easier for decision-makers to understand the results. Finally, An MCGDM case study is given to illustrate the proposed approach.

Keywords: additive ratio assessment, extended hierarchical linguistic, multi-criteria group decision making problems, multi granular linguistic contexts

Procedia PDF Downloads 186

Authors: Ashiqul Amin Khan, Mohsin Ul Amin Khan

Abstract:

The aim of this research is to find the relationship between good governance and shareholder wealth maximisation. The concept of good governance has become more objective in nature over time through various regulations, professionalisation, and practices. This has led to a number of methods for scoring and ranking corporate governance practices. Since shareholder wealth maximisation remains the key corporate goal for managers and governors alike, the effect of good governance in increasing the value of corporations is commented to be an important aspect. In measuring the value relevance of good governance, statistical measures of various yields of listed companies in the UK have been used in this research. Yields reflect required returns on investments from different investment tenets. Historical yields, calculated using historical fundamental data of such companies, reflect expected yields to a great extent. These yields, in turn, reflect the expected risk premium and growth associated with the stocks of the companies. Using fundamental data, the yields have been adjusted to reflect the risk premium required by the investors along various value paradigms. Good governance should naturally lead to lower required risk premium since good corporate governance provided assurance to the investors in terms of sustainability of future performance and desired financial conduct. This, in turn, increases the wealth of stockholders. The findings of this research confirm such nature of the relationship between good governance and value of the company in the long run.

Keywords: corporate governance, good governance practices, short-termism, shareholder value relevance, wealth maximisation, yield

Procedia PDF Downloads 336

Authors: Ceyda Dadali, Yeşim Elmaci

Abstract:

Coffee was introduced as an economic crop during the fifteenth century; nowadays it is the most important food commodity ranking second after crude oil. Desirable sensory properties make coffee one of the most often consumed and most popular beverages in the world. The coffee preparation method has a significant effect on flavor and composition of coffee brews. Three different extraction methodologies namely decoction, infusion and pressure methods have been used for coffee brew preparation. Each of these methods is related to specific granulation (coffee grind) of coffee powder, water-coffee ratio temperature and brewing time. Coffee is a mixture of 1500 chemical compounds. Chemical composition of coffee highly depends on brewing methods, coffee bean species and roasting time-temperature. Coffee contains a wide number of very important bioactive compounds, such as diterpenes: cafestol and kahweol, alkaloids: caffeine, theobromine and trigonelline, melanoidins, phenolic compounds. The phenolic compounds of coffee include chlorogenic acids (quinyl esters of hidroxycinnamic acids), caffeic, ferulic, p-coumaric acid. In coffee caffeoylquinic acids, feruloylquinic acids and di-caffeoylquinic acids are three main groups of chlorogenic acids constitues 6% -10% of dry weight of coffee. The bioavailability of chlorogenic acids in coffee depends on the absorption and metabolization to biomarkers in individuals. Also, the interaction of coffee polyphenols with other compounds such as dietary proteins affects the biomarkers. Since bioactive composition of coffee depends on brewing methods effect of coffee brewing method on bioactive compounds of coffee will be discussed in this study.

Keywords: bioactive compounds of coffee, biomarkers, coffee brew, effect of brewing

Procedia PDF Downloads 175

Authors: P. Venu, Joeju M. Issac

Abstract:

Quality Function Deployment (QFD) is a systematic technique that creates a platform where the customer responses can be positively converted to design attributes. The accuracy of a QFD process heavily depends on the data that it is handling which is captured from customers or QFD team members. Customized computer programs that perform Quality Function Deployment within a stipulated time have been used by various companies across the globe. These programs heavily rely on storage and retrieval of the data on a common database. This database must act as a perfect source with minimum missing values or error values in order perform actual prioritization. This paper introduces a missing/error data handler module which uses Genetic Algorithm and Fuzzy numbers. The prioritization of customer requirements of sesame oil is illustrated and a comparison is made between proposed data handler module-based deployment and manual deployment.

Keywords: hybrid data handler, QFD, prioritization, module-based deployment

Procedia PDF Downloads 272

Authors: Mokoena Oratilwe Penwell, Seeletse Solly Matshonisa

Abstract:

The demand for quality products is a vital factor determining the success of a producing company, and the reality of this demand influences customer satisfaction. In Sefako Makgatho Health Sciences University (SMU), concerns over the quality of food being sold have been raised by mostly students and staff who are primary consumers of food being sold by the cafeteria. Suspicions of food poisoning and the occurrence of diarrhea-related to food from the cafeteria, amongst others, have been raised. However, minimal measures have been taken to resolve the issue of food quality. New service providers have been appointed, and still, the same trends are being observed, the quality of food seems to depreciate continuously. This paper uses multi-attribute failure mode analysis (MAFMA) for failure detection and minimization on the machines used for food production by SMU catering company before being sold to both staff, and students so as to improve production plant reliability, and performance. Analytical Hierarchy Process (AHP) will be used for the severity ranking of the weight criterions and development of the hierarchical structure for the cafeteria company. Amongst other potential issues detected, maintenance of the machines and equipment used for food preparations was of concern. Also, the staff lacked sufficient hospitality skills, supervision, and management in the cafeteria needed greater attention to mitigate some of the failures occurring in the food production plant.

Keywords: MAFMA, food quality, maintenance, supervision

Procedia PDF Downloads 106

Authors: A. A. Behroozpoor, M. M. Mazarei

Abstract:

In this paper, a fuzzy recurrent neural network is proposed for solving the classical quadratic control problem subject to linear equality and bound constraints. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed.

Keywords: REFERENCES [1] Xia, Y, A new neural network for solving linear and quadratic programming problems. IEEE Transactions on Neural Networks, 7(6), 1996, pp.1544–1548. [2] Xia, Y., & Wang, J, A recurrent neural network for solving nonlinear convex programs subject to linear constraints. IEEE Transactions on Neural Networks, 16(2), 2005, pp. 379–386. [3] Xia, Y., H, Leung, & J, Wang, A projection neural network and its application to constrained optimization problems. IEEE Transactions Circuits and Systems-I, 49(4), 2002, pp.447–458.B. [4] Q. Liu, Z. Guo, J. Wang, A one-layer recurrent neural network for constrained seudoconvex optimization and its application for dynamic portfolio optimization. Neural Networks, 26, 2012, pp. 99-109.

Procedia PDF Downloads 618

Authors: Jonathan Doku

Abstract:

The study's goal was to evaluate construction site safety management in Ghana. The construction sector has long been seen as a high-risk business. It entails a variety of hazardous and challenging labor duties, such as lifting and working at a height, among others. The accident rate is a standard indicator for comparing the safety performance of construction projects. Because of its high-risk and fast-changing work environment, the construction business is regarded as one of the industries with the highest accident rates in the world. Many mishaps and work-related diseases have occurred there, and construction workers are particularly vulnerable to catastrophic calamities such as falls, collapses, and burial. The study's main goals were to discover characteristics that have a substantial impact on construction site safety, to evaluate the safety management methods utilized on construction sites, and to assess the obstacles associated with construction site safety management. The study was conducted using a quantitative research method and a purposive sampling strategy. Google forms were used to distribute self-administered surveys to 85 responders. 72 of the 85 questionnaires were completed and submitted for analysis, accounting for 84.7 percent of the total. The variables were analyzed using descriptive statistics, mean score ranking, and Cronbach's Alpha Coefficient to ensure the scale's reliability. The formal safety organization structure and the Safety checklist were identified as the key practices of safety management on site as part of the study goals. In addition, it was discovered that the most serious problem with safety management is ineffective supervision. To guarantee efficient monitoring and proper implementation of health and safety rules on building sites, management must be on the ball.

Keywords: construction, safety, risk, management

Procedia PDF Downloads 52

Authors: Irum Matloob, Shoab Ahmad Khan, Fahim Arif

Abstract:

As Indo-Pak has been the victim of heart diseases since many decades. Many surveys showed that percentage of cardiac patients is increasing in Pakistan day by day, and special attention is needed to pay on this issue. The framework is proposed for performing detailed analysis of ECG survey data which is conducted for measuring prevalence of heart diseases statistics in Pakistan. The ECG survey data is evaluated or filtered by using automated Minnesota codes and only those ECGs are used for further analysis which is fulfilling the standardized conditions mentioned in the Minnesota codes. Then feature selection is performed by applying proposed algorithm based on discernibility matrix, for selecting relevant features from the database. Clustering is performed for exposing natural clusters from the ECG survey data by applying spectral clustering algorithm using fuzzy c means algorithm. The hidden patterns and interesting relationships which have been exposed after this analysis are useful for further detailed analysis and for many other multiple purposes.

Keywords: arrhythmias, centroids, ECG, clustering, discernibility matrix

Procedia PDF Downloads 445

Authors: Mina Samizadeh

Abstract:

In the past few decades, there has been an explosion in the amount of available data produced from various sources with different topics. The availability of this enormous data necessitates us to adopt effective computational tools to explore the data. This leads to an intense growing interest in the research community to develop computational methods focused on processing this text data. A line of study focused on condensing the text so that we are able to get a higher level of understanding in a shorter time. The two important tasks to do this are keyword extraction and text summarization. In keyword extraction, we are interested in finding the key important words from a text. This makes us familiar with the general topic of a text. In text summarization, we are interested in producing a short-length text which includes important information about the document. The TextRank algorithm, an unsupervised learning method that is an extension of the PageRank (algorithm which is the base algorithm of Google search engine for searching pages and ranking them), has shown its efficacy in large-scale text mining, especially for text summarization and keyword extraction. This algorithm can automatically extract the important parts of a text (keywords or sentences) and declare them as a result. However, this algorithm neglects the semantic similarity between the different parts. In this work, we improved the results of the TextRank algorithm by incorporating the semantic similarity between parts of the text. Aside from keyword extraction and text summarization, we develop a topic clustering algorithm based on our framework, which can be used individually or as a part of generating the summary to overcome coverage problems.

Keywords: keyword extraction, n-gram extraction, text summarization, topic clustering, semantic analysis

Procedia PDF Downloads 47

Authors: Shiva Kumar, G. S. Vijay, Srinivas Pai P., Shrinivasa Rao B. R.

Abstract:

In the present study RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tech and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.

Keywords: radial basis function networks, emissions, performance parameters, fuzzy c means

Procedia PDF Downloads 534

Authors: Bahram Asghari Aghdam, Ali Mahjoub

Abstract:

The purpose of this study is to evaluate the effect of emotional intelligence on the motivation and performance of East Azarbaijan the Red Crescent staff. In this study, EI is determined as the independent variable component of self awareness, self management, social awareness, and relations management, motivation and performance as dependent variables. The research method is descriptive-survey. In this study, simple random sampling method is used and research sample consists of 130 East Azarbaijan the Red Crescent staff that uses Cochran's formula 100 of them were selected and questionnaires were filled by them. Three types of questionnaires were used in this study for emotional intelligence, consisting of the Bradbury Travis and Jane Greaves standard questionnaire; and for motivation and performance a questionnaire is regulated by the researcher with help of professionals and experts in this field that consists of 33 questions about the motivation and 15 questions about performance and content validity were used to obtain the necessary credit. Reliability by using the Cronbach's alpha coefficient /948 was approved. Also, in this study to test the hypothesis of the Spearman correlation coefficient and linear regressions and determine fitness of variables' of structural equation modeling is used. The results show that emotional intelligence with coefficient /865, motivation and performance of in East Azerbaijan the Red Crescent employees has a positive effect. Based on Friedman Test ranking the most influence in motivation and performance of staff in respondents' opinion is in order of self-awareness, relations management, social awareness and self-management.

Keywords: emotional intelligence, self-awareness, self-management, social awareness, relations management, motivation, performance

Procedia PDF Downloads 445

Authors: Li Ni, Pen ManMan, Li KenLi

Abstract:

Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.

Keywords: chemical reaction optimization, expection maimization, initia, objective function clustering

Procedia PDF Downloads 687

Authors: Mohit Taneja, Ravi Kiran, S. C. Bose

Abstract:

Entrepreneurs’ role in achieving Sustainable development goals is crucial as the growth potential of any region depends upon the number and the success rate of entrepreneurial firms. This paper is an effort to examine the relationship between Sustainable growth (SG) with Entrepreneurial attitude (EA) and Entrepreneurial intention (EI) in the context of the Indian economy. The mediation effect of EI between EA and SG has been considered. Partial least square (PLS) –Structural Equation Model (SEM) software was used to design the framework. Students enrolled in entrepreneurship courses of higher educational institutes (HEI) of Punjab, Haryana, and the National Capital Region NCR were contacted for data collection. The National Institutional Ranking Framework (NIRF) framework was used in selecting HEIs and data collected from 589 students was considered for analysis. McGee’s multi-dimensional scale for measuring ESE and the scale of Linan & Chen for measuring EI & ES (SG) was used. Results highlight that EA has a strong impact on EI (p≤ 0.001) and EI has a positive and strong relationship with SG (ES) as β value for the same is 0.683 (p≤ 0.001). The current study also reflects the mediating effect of EI among EA and ES, as the results show that the combined β value of both EA and EI (i.e.0.684*0.683= 0.467) is more than the direct influence of EA on ES (β=0.265). EA, with the mediating effect of EI can enhance the opportunity for achieving SG, which suggests that in order to increase the venture success rate and to attain SG, emphasis should be given to EI along with EA. The study has been investigated in three regions of India. Future studies can be extended to other South Asian countries for generalization.

Keywords: entrepreneurship, sustainable growth, entrepreneurship intention, entrepreneurship attitude

Procedia PDF Downloads 71

Authors: Irum Matloob, Shoab Ahmad Khan, Fahim Arif

Abstract:

As Indo-pak has been the victim of heart diseases since many decades. Many surveys showed that percentage of cardiac patients is increasing in Pakistan day by day, and special attention is needed to pay on this issue. The framework is proposed for performing detailed analysis of ECG survey data which is conducted for measuring the prevalence of heart diseases statistics in Pakistan. The ECG survey data is evaluated or filtered by using automated Minnesota codes and only those ECGs are used for further analysis which is fulfilling the standardized conditions mentioned in the Minnesota codes. Then feature selection is performed by applying proposed algorithm based on discernibility matrix, for selecting relevant features from the database. Clustering is performed for exposing natural clusters from the ECG survey data by applying spectral clustering algorithm using fuzzy c means algorithm. The hidden patterns and interesting relationships which have been exposed after this analysis are useful for further detailed analysis and for many other multiple purposes.

Keywords: arrhythmias, centroids, ECG, clustering, discernibility matrix

Procedia PDF Downloads 330

Authors: Jairson Barbosa Rodrigues, Paulo Romero Martins Maciel, Germano Crispim Vasconcelos

Abstract:

This paper presents an investigation of the performance impacts regarding the variation of five factors (input data size, node number, cores, memory, and disks) when applying a distributed implementation of Naïve Bayes for text classification of a large Corpus on the Spark big data processing framework. Problem: The algorithm's performance depends on multiple factors, and knowing before-hand the effects of each factor becomes especially critical as hardware is priced by time slice in cloud environments. Objectives: To explain the functional relationship between factors and performance and to develop linear predictor models for time and cost. Methods: the solid statistical principles of Design of Experiments (DoE), particularly the randomized two-level fractional factorial design with replications. This research involved 48 real clusters with different hardware arrangements. The metrics were analyzed using linear models for screening, ranking, and measurement of each factor's impact. Results: Our findings include prediction models and show some non-intuitive results about the small influence of cores and the neutrality of memory and disks on total execution time, and the non-significant impact of data input scale on costs, although notably impacts the execution time.

Keywords: big data, design of experiments, distributed machine learning, natural language processing, spark

Procedia PDF Downloads 92

Authors: Salima Smiti, Ines Gasmi, Makram Soui

Abstract:

Credit risk is the most important issue for financial institutions. Its assessment becomes an important task used to predict defaulter customers and classify customers as good or bad payers. To this objective, numerous techniques have been applied for credit risk assessment. However, to our knowledge, several evaluation techniques are black-box models such as neural networks, SVM, etc. They generate applicants’ classes without any explanation. In this paper, we propose to assess credit risk using rules classification method. Our output is a set of rules which describe and explain the decision. To this end, we will compare seven classification algorithms (JRip, Decision Table, OneR, ZeroR, Fuzzy Rule, PART and Genetic programming (GP)) where the goal is to find the best rules satisfying many criteria: accuracy, sensitivity, and specificity. The obtained results confirm the efficiency of the GP algorithm for German and Australian datasets compared to other rule-based techniques to predict the credit risk.

Keywords: credit risk assessment, classification algorithms, data mining, rule extraction

Procedia PDF Downloads 154

Authors: Punam Shaw

Abstract:

Relationship often refers to the acquaintance or association between two or more things, which are interrelated and interdependent. The socio-economic status is obviously a blending of two states, would, therefore, be a ranking of an individual by the society he or she lives in, and in terms of his/her material belonging, cultural possessions along with the degree of respect, power and influence wield. Hence, education, income and occupation of an individual play a significant role in society. Positive mental attitude leads to achieve the set goal, and improve performance particularly in team cohesiveness, which may be determined by various interrelated aspects, which can predict the future assessment in their respective field accordingly. The study intended to examine and explore the relationship between Socio-economic Status and Mental Toughness of cricketers. For the present study descriptive survey research method was used and selected 40 (male=20 female=20) U-17 years registered players under Cricket Association of Bengal (CAB), as the sample population. Modified Socio-Economic Status Scale was used to collect the data regarding players, socioeconomic Status and to assess the mental toughness; Scott Barry Kaufman questionnaire was used. The data had been analysed through applying Pearson’s Correlation Coefficient and t-test as statistical techniques. The findings of the study showed that there is a positive correlation between socioeconomic Status and Mental Toughness among cricketers, it was found that significant difference was presented between male and female SES group. It was further revealed that there is no significant difference between male and female cricketers and in their different socioeconomic class with respect to their mental toughness.

Keywords: cricketers, mental toughness, relationship, socio-economic status

Procedia PDF Downloads 99

Authors: Ghanim A. Bekr

Abstract:

Project success is what must be done for the project to be acceptable to the client, stakeholders and end-users who will be affected by the project. The study of project success and the critical success factors (CSFs) are the means adopted to improve the effectiveness of project. This research is conducted to make an attempt to identify which variables influence the success of project implementation. This study has selected, through an extensive literature review and interviews, (83) factors categorized in (7) groups that the questionnaire respondents were asked to score. The responses from 66 professionals with an average of 15 years of experience in different types of construction projects in Jordan were collected and analyzed using SPSS and most important factors for success for various success criteria are presented depending on the relative importance index to rank the categories. The research revealed the significant groups of factors are: Client related factors, Contractor’s related factors, Project Manager (PM) related factors, and Project management related factors. In addition the top ten sub factors are: Assertion of the client towards short time of the project, availability of skilled labor, Assertion of the client towards high level of the quality, capability of the client in taking risk, previous experience of the PM in similar projects, previous experience of the contractor in similar projects, decision making by the client/ the client’s representative at the right time, assertion of client towards low cost of project, experience in project management in previous projects, and flow of the information among parties. The results would be helpful to construction project professionals in taking proactive measures for successful completion of construction projects in Jordan.

Keywords: construction projects, critical success factors, Jordan, project success

Procedia PDF Downloads 133

Authors: Elham Dehghan, A. Shirzadi Javid, Mohsen Tadayon

Abstract:

Labor productivity is very important and gained special concerns among professionals in the construction industry, worldwide. Productivity improvements on labors achieve higher cost savings with minimal investment. Due to the fact that profit margins are small on construction projects, cost savings associated with productivity are crucial to become a successful contractor. This research program studies and highlights the factors affecting labor productivity in Iranian construction industry. A questionnaire was used to gather the relevant data from respondents who involve in managing various types of projects in wide areas in Iran. It involved ranking 57 predefined factors divided into 5 categories: Human/Labor; Financial; Management; Equipments/Materials and Environmental. Total 62 feedbacks were analyzed through the Relative Importance Index (RII) technique. The top ten factors affecting construction labor productivity in Iran are: 1) Professional capability of contractor project manager, 2) skills of contractor’s project management team, 3) professional capability of owner project manager, 4) professional capability of Consulting Project manager, 5) discipline working, 6) delay payments by the owner, 7) material shortages, 8) delays in delivery of materials, 9) turnover power of the owner, 10) poor site management. Recommendations have been made in the study to address these factors. The research has direct benefits to key stakeholders in Iranian construction industry.

Keywords: Iranian construction projects, labor, productivity, relative importance index

Procedia PDF Downloads 243

Authors: Lars Laußat, Manfred Helmus, Kamil Szczesny, Markus König

Abstract:

As one result of the project “Reactive Construction Project Scheduling using Real Time Construction Logistic Data and Simulation”, a procedure for using data about uncertain resource availability assumptions in reactive scheduling processes has been developed. Prediction data about resource availability is generated in a formalized way using real-time monitoring data e.g. from auto-ID systems on the construction site and in the supply chains. The paper focuses on the formalization of the procedure for monitoring construction logistic processes, for the detection of disturbance and for generating of new and uncertain scheduling assumptions for the reactive resource constrained simulation procedure that is and will be further described in other papers.

Keywords: auto-ID, construction logistic, fuzzy, monitoring, RFID, scheduling

Procedia PDF Downloads 488

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 308

Authors: David Nantes, George Gilbert

Abstract:

There are a lot of risks that might crop up as a tunneling project develops, and it's crucial to be aware of them. Due to the unexpected nature of tunneling projects and the interconnectedness of risk occurrences, the risk assessment approach presents a significant challenge. The purpose of this study is to provide a hybrid FDEMATEL-ANP model to help prioritize risks during tunnel construction projects. The ambiguity in expert judgments and the relative severity of interdependencies across risk occurrences are both taken into consideration by this model, thanks to the Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL). The Analytic Network Process (ANP) method is used to rank priorities and assess project risks. The authors provide a case study of a subway tunneling construction project to back up the validity of their methodology. The results showed that the proposed method successfully isolated key risk factors and elucidated their interplay in the case study. The proposed method has the potential to become a helpful resource for evaluating dangers associated with tunnel construction projects.

Keywords: risk, prioritization, FDEMATEL, ANP, tunneling construction projects

Procedia PDF Downloads 66

Authors: Murat Arıbaş, Uğur Özcan

Abstract:

Due to the increasing number of universities and academics, the fund of the universities for research activities and grants/supports given by government institutions have increased number and quality of academic research projects. Although every academic research project has a specific purpose and importance, limited resources (money, time, manpower etc.) require choosing the best ones from all (Amiri, 2010). It is a pretty hard process to compare and determine which project is better such that the projects serve different purposes. In addition, the evaluation process has become complicated since there are more than one evaluator and multiple criteria for the evaluation (Dodangeh, Mojahed and Yusuff, 2009). Mehrez and Sinuany-Stern (1983) determined project selection problem as a Multi Criteria Decision Making (MCDM) problem. If a decision problem involves multiple criteria and objectives, it is called as a Multi Attribute Decision Making problem (Ömürbek & Kınay, 2013). There are many MCDM methods in the literature for the solution of such problems. These methods are AHP (Analytic Hierarchy Process), ANP (Analytic Network Process), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation), UTADIS (Utilities Additives Discriminantes), ELECTRE (Elimination et Choix Traduisant la Realite), MAUT (Multiattribute Utility Theory), GRA (Grey Relational Analysis) etc. Teach method has some advantages compared with others (Ömürbek, Blacksmith & Akalın, 2013). Hence, to decide which MCDM method will be used for solution of the problem, factors like the nature of the problem, types of choices, measurement scales, type of uncertainty, dependency among the attributes, expectations of decision maker, and quantity and quality of the data should be considered (Tavana & Hatami-Marbini, 2011). By this study, it is aimed to develop a systematic decision process for the grant support applications that are expected to be evaluated according to their scientific adequacy by multiple evaluators under certain criteria. In this context, project evaluation process applied by The Scientific and Technological Research Council of Turkey (TÜBİTAK) the leading institutions in our country, was investigated. Firstly in the study, criteria that will be used on the project evaluation were decided. The main criteria were selected among TÜBİTAK evaluation criteria. These criteria were originality of project, methodology, project management/team and research opportunities and extensive impact of project. Moreover, for each main criteria, 2-4 sub criteria were defined, hence it was decided to evaluate projects over 13 sub-criterion in total. Due to superiority of determination criteria weights AHP method and provided opportunity ranking great number of alternatives TOPSIS method, they are used together. AHP method, developed by Saaty (1977), is based on selection by pairwise comparisons. Because of its simple structure and being easy to understand, AHP is the very popular method in the literature for determining criteria weights in MCDM problems. Besides, the TOPSIS method developed by Hwang and Yoon (1981) as a MCDM technique is an alternative to ELECTRE method and it is used in many areas. In the method, distance from each decision point to ideal and to negative ideal solution point was calculated by using Euclidian Distance Approach. In the study, main criteria and sub-criteria were compared on their own merits by using questionnaires that were developed based on an importance scale by four relative groups of people (i.e. TUBITAK specialists, TUBITAK managers, academics and individuals from business world ) After these pairwise comparisons, weight of the each main criteria and sub-criteria were calculated by using AHP method. Then these calculated criteria’ weights used as an input in TOPSİS method, a sample consisting 200 projects were ranked on their own merits. This new system supported to opportunity to get views of the people that take part of project process including preparation, evaluation and implementation on the evaluation of academic research projects. Moreover, instead of using four main criteria in equal weight to evaluate projects, by using weighted 13 sub-criteria and decision point’s distance from the ideal solution, systematic decision making process was developed. By this evaluation process, new approach was created to determine importance of academic research projects.

Keywords: Academic projects, Ahp method, Research projects evaluation, Topsis method.

Procedia PDF Downloads 570

Authors: Najla Althuniyan

Abstract:

Online discussions take place across different platforms. These discussions have the potential to extract crowd wisdom and capture the collective intelligence from a different perspective. However, certain phenomena, such as controversy, often appear in online argumentation that makes the discussion between participants heated. Heated discussions can be used to extract new knowledge. Therefore, detecting the presence of controversy is an essential task to determine if collective intelligence can be extracted from online discussions. This paper uses existing measures for estimating controversy quantitatively in cyber-argumentation. First, it defines controversy in different fields, and then it identifies the attributes of controversy in online discussions. The distributions of user opinions and the distance between opinions are used to calculate the controversial degree of a discussion. Finally, the results from each controversy measure are discussed and analyzed using an empirical study generated by a cyber-argumentation tool. This is an improvement over the existing measurements because it does not require ground-truth data or specific settings and can be adapted to distribution-based or distance-based opinions.

Keywords: online argumentation, controversy, collective intelligence, agreement analysis, collaborative decision-making, fuzzy logic

Procedia PDF Downloads 101