Search results for: fuzzy delphi technique

Authors: Niyongabo Elyse

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Prefabricated building construction is a pioneering approach that combines design, production, and assembly to attain energy efficiency, environmental sustainability, and economic feasibility. Despite continuous development in the industry in China, the low technical maturity of standardized design, factory production, and construction assembly introduces uncertainties affecting prefabricated component production and on-site assembly processes. This research focuses on enhancing project management performance under uncertainty to help enterprises navigate these challenges and optimize project resources. The study introduces a perspective on how uncertain factors influence the implementation of prefabricated building construction projects. It proposes a theoretical model considering project process management ability, adaptability to uncertain environments, and collaboration ability of project participants. The impact of uncertain factors is demonstrated through case studies and quantitative analysis, revealing constraints on implementation time, cost, quality, and safety. To address uncertainties in prefabricated component production scheduling, a fuzzy model is presented, expressing processing times in interval values. The model utilizes a cooperative co-evolution evolution algorithm (CCEA) to optimize scheduling, demonstrated through a real case study showcasing reduced project duration and minimized effects of processing time disturbances. Additionally, the research addresses on-site assembly construction scheduling, considering the relationship between task processing times and assigned resources. A multi-objective model with fuzzy activity durations is proposed, employing a hybrid cooperative co-evolution evolution algorithm (HCCEA) to optimize project scheduling. Results from real case studies indicate improved project performance in terms of duration, cost, and resilience to processing time delays and resource changes. The study also introduces a multistage dynamic process control model, utilizing IoT technology for real-time monitoring during component production and construction assembly. This approach dynamically adjusts schedules when constraints arise, leading to enhanced project management performance, as demonstrated in a real prefabricated housing project. Key contributions include a fuzzy prefabricated components production scheduling model, a multi-objective multi-mode resource-constrained construction project scheduling model with fuzzy activity durations, a multi-stage dynamic process control model, and a cooperative co-evolution evolution algorithm. The integrated mathematical model addresses the complexity of prefabricated building construction project management, providing a theoretical foundation for practical decision-making in the field.

Keywords: prefabricated construction, project management performance, uncertainty, fuzzy scheduling

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Authors: Yasunori Kobori, Futoshi Fukaya, Takuya Arafune, Nobukazu Tsukiji, Nobukazu Takai, Haruo Kobayashi

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This paper proposes an EMI spread spectrum technique to enable to set notch frequencies using pulse coding method for DC-DC switching converters of communication equipment. The notches in the spectrum of the switching pulses appear at the frequencies obtained from empirically derived equations with the proposed spread spectrum technique using the pulse coding methods, the PWM (Pulse Width Modulation) coding or the PCM (Pulse Cycle Modulation) coding. This technique would be useful for the switching converters in the communication equipment which receives standard radio waves, without being affected by noise from the switching converters. In our proposed technique, the notch frequencies in the spectrum depend on the pulse coding method. We have investigated this technique to apply to the switching converters and found that there is good relationship agreement between the notch frequencies and the empirical equations. The notch frequencies with the PWM coding is equal to the equation F=k/(WL-WS). With the PCM coding, that is equal to the equation F=k/(TL-TS).

Keywords: notch frequency, pulse coding, spread spectrum, switching converter

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Authors: Kenechi Kurtis Onochie

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This paper shows the use of filter paper technique in the measurement of matric suction of unsaturated expansive soil around the Haspolat region of Lefkosa, North Cyprus in other to establish the soil water characteristics curve (SWCC) or soil water retention curve (SWRC). The dry filter paper approach which is standardized by ASTM, 2003, D 5298-03 in which the filter paper is initially dry was adopted. The whatman No. 42 filter paper was used in the matric suction measurement. The maximum dry density of the soil was obtained as 2.66kg/cm³ and the optimum moisture content as 21%. The soil was discovered to have high air entry value of 1847.46KPa indicating finer particles and 25% hydraulic capacity using filter paper technique. The filter paper technique proved to be very useful for measuring the hydraulic capacity of unsaturated expansive soil.

Keywords: SWCC, matric suction, filter paper, expansive soil

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Authors: Julio Macedo

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Several methodologies are now available to conceive the improvements of a process so that it becomes competitive as for example total quality, process reengineering, six sigma, define measure analysis improvement control method. These improvements are of different nature and can be external to the process represented by an optimization model or a discrete simulation model. In addition, the process stakeholders are several and have different desired performances for the process. Hence, the methodologies above do not have a tool to aid in the conception of the required improvements. In order to fill this void we suggest the use of intelligent reference models. A reference model is a set of qualitative differential equations and an objective function that minimizes the gap between the current and the desired performance indexes of the process. The reference models are intelligent so when they receive the current state of the problematic process and the desired performance indexes they generate the required improvements for the problematic process. The reference models are fuzzy cognitive maps added with an objective function and trained using the improvements implemented by the high performance firms. Experiments done in a set of students show the reference models allow them to conceive more improvements than students that do not use these models.

Keywords: continuous improvement, fuzzy cognitive maps, process competitiveness, qualitative simulation, system dynamics

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Authors: Priyanka Verma, Vijaya Dixit, Rishabh Bajpai

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This research paper is aimed at selecting appropriate material handling equipment among the given choices so that the automation level in material handling can be enhanced. This work is a practical case scenario of material handling systems in consumer electronic appliances manufacturing organization. The choices of material handling equipment among which the decision has to be made are Automated Guided Vehicle’s (AGV), Autonomous Mobile Robots (AMR), Overhead Conveyer’s (OC) and Battery Operated Trucks/Vehicle’s (BOT). There is a need of attaining a certain level of automation in order to reduce human interventions in the organization. This requirement of achieving certain degree of automation can be attained by material handling equipment’s mentioned above. The main motive for selecting above equipment’s for study was solely based on corporate financial strategy of investment and return obtained through that investment made in stipulated time framework. Since the low cost automation with respect to material handling devices has to be achieved hence these equipment’s were selected. Investment to be done on each unit of this equipment is less than 20 lakh rupees (INR) and the recovery period is less than that of five years. Fuzzy analytic hierarchic process (FAHP) is applied here for selecting equipment where the four choices are evaluated on basis of four major criteria’s and 13 sub criteria’s, and are prioritized on the basis of weight obtained. The FAHP used here make use of triangular fuzzy numbers (TFN). The inability of the traditional AHP in order to deal with the subjectiveness and impreciseness in the pair-wise comparison process has been improved in the FAHP. The range of values for general rating purposes for all decision making parameters is kept between 0 and 1 on the basis of expert opinions captured on shop floor. These experts were familiar with operating environment and shop floor activity control. Instead of generating exact value the FAHP generates the ranges of values to accommodate the uncertainty in decision-making process. The four major criteria’s selected for the evaluation of choices of material handling equipment’s available are materials, technical capabilities, cost and other features. The thirteen sub criteria’s listed under these following four major criteria’s are weighing capacity, load per hour, material compatibility, capital cost, operating cost and maintenance cost, speed, distance moved, space required, frequency of trips, control required, safety and reliability issues. The key finding shows that among the four major criteria selected, cost is emerged as the most important criteria and is one of the key decision making aspect on the basis of which material equipment selection is based on. While further evaluating the choices of equipment available for each sub criteria it is found that AGV scores the highest weight in most of the sub-criteria’s. On carrying out complete analysis the research shows that AGV is the best material handling equipment suiting all decision criteria’s selected in FAHP and therefore it is beneficial for the organization to carry out automated material handling in the facility using AGV’s.

Keywords: fuzzy analytic hierarchy process (FAHP), material handling equipment, subjectiveness, triangular fuzzy number (TFN)

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Authors: V. K. Banga

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Robots are now playing a very promising role in industries. Robots are commonly used in applications in repeated operations or where operation by human is either risky or not feasible. In most of the industrial applications, robotic arm manipulators are widely used. Robotic arm manipulator with two link or three link structures is commonly used due to their low degrees-of-freedom (DOF) movement. As the DOF of robotic arm increased, complexity increases. Instrumentation involved with robotics plays very important role in order to interact with outer environment. In this work, optimal control for movement of various DOFs of robotic arm using various soft computing techniques has been presented. We have discussed about different robotic structures having various DOF robotics arm movement. Further stress is on kinematics of the arm structures i.e. forward kinematics and inverse kinematics. Trajectory planning of robotic arms using soft computing techniques is demonstrating the flexibility of this technique. The performance is optimized for all possible input values and results in optimized movement as resultant output. In conclusion, soft computing has been playing very important role for achieving optimized movement of robotic arm. It also requires very limited knowledge of the system to implement soft computing techniques.

Keywords: artificial intelligence, kinematics, robotic arm, neural networks, fuzzy logic

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Authors: Ashish Trivedi, Amol Singh

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In the recent years, the magnitude and frequency of disasters have increased at an alarming rate. Every year, more than 400 natural disasters affect global population. A large-scale disaster leads to destruction or damage to houses, thereby rendering a notable number of residents homeless. Since humanitarian response and recovery process takes considerable time, temporary establishments are arranged in order to provide shelter to affected population. These shelter areas are vital for an effective humanitarian relief; therefore, they must be strategically planned. Choosing the locations of temporary shelter areas for accommodating homeless people is critical to the quality of humanitarian assistance provided after a large-scale emergency. There has been extensive research on the facility location problem both in theory and in application. In order to deliver sufficient relief aid within a relatively short timeframe, humanitarian relief organisations pre-position warehouses at strategic locations. However, such approaches have received limited attention from the perspective of providing shelters to disaster-affected people. In present research work, this aspect of humanitarian logistics is considered. The present work proposes a hybrid decision support model to determine relative preference of potential shelter locations by assessing them based on key subjective criteria. Initially, the factors that are kept in mind while locating potential areas for establishing temporary shelters are identified by reviewing extant literature and through consultation from a panel of disaster management experts. In order to determine relative importance of individual criteria by taking into account subjectivity of judgements, a hybrid approach of fuzzy sets and Analytic Hierarchy Process (AHP) was adopted. Further, Technique for order preference by similarity to ideal solution (TOPSIS) was applied on an illustrative data set to evaluate potential locations for establishing temporary shelter areas for homeless people in a disaster scenario. The contribution of this work is to propose a range of possible shelter locations for a humanitarian relief organization, using a robust multi criteria decision support framework.

Keywords: AHP, disaster preparedness, fuzzy set theory, humanitarian logistics, TOPSIS, temporary shelters

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Authors: I. M. Abd Rahim, H. Abdul Rahim, R. Ghazali

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There is numerous non-invasive blood glucose measurement technique developed by researchers, and near infrared (NIR) is the potential technique nowadays. However, there are some disagreements on the optimal wavelength range that is suitable to be used as the reference of the glucose substance in the blood. This paper focuses on the experimental data collection technique and also the analysis method used to analyze the data gained from the experiment. The selection of suitable linear and non-linear model structure is essential in prediction system, as the system developed need to be conceivably accurate.

Keywords: linear, near-infrared (NIR), non-invasive, non-linear, prediction system

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Authors: Shahzamani Kiana, Esmaeil Lashgarian Hamed, Merat Shahin

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HCV and GBV-C belong to the Flaviviridae family of viruses and GBV-C is the closest virus to HCV genetically. Accumulative research is in progress all over the world to clarify clinical aspects of GBV-C. Possibility of interaction between HCV and GBV-C and also its consequence with other liver diseases are the most important clinical aspects which encourage researchers to develop a technique for simultaneous detection of these viruses. In this study a SYBR Green multiplex real time RT-PCR technique as a new economical and sensitive method was optimized for simultaneous detection of HCV/GBV-C in HCV positive plasma samples. After designing and selection of two pairs of specific primers for HCV and GBV-C, SYBR Green Real time RT-PCR technique optimization was performed separately for each virus. Establishment of multiplex PCR was the next step. Finally our technique was performed on positive and negative plasma samples. 89 cirrhotic HCV positive plasma samples (29 of genotype 3 a and 27 of genotype 1a) were collected from patients before receiving treatment. 14% of genotype 3a and 17.1% of genotype 1a showed HCV/GBV-C co-infection. As a result, 13.48% of 89 samples had HCV/GBV-C co-infection that was compatible with other results from all over the world. Data showed no apparent influence of HGV co-infection on the either clinical or virological aspect of HCV infection. Furthermore, with application of multiplex Real time RT-PCR technique, more time and cost could be saved in clinical-research settings.

Keywords: HCV, GBV-C, cirrhotic patients, multiplex real time RT- PCR

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Authors: Hanadi Mohamed Shawgi Gamal, Claus Thomas Bues

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Wood density is a variable influencing many of the technological and quality properties of wood. Understanding the pattern of wood density radial variation is important for its end-use. The X-ray technique, traditionally applied to softwood species to assess the wood quality properties, due to its simple and relatively uniform wood structure. On the other hand, very limited information is available about the validation of using this technique for hardwood species. The suitability of using the X-ray technique for the determination of hardwood density has a special significance in countries like Sudan, where only a few timbers are well known. This will not only save the time consumed by using the traditional methods, but it will also enhance the investigations of the great number of the lesser known species, the thing which will fill the huge cap of lake information of hardwood species growing in Sudan. The current study aimed to evaluate the validation of using the X-ray densitometry technique to determine the radial variation of wood density of Acacia seyal var. seyal. To this, a total of thirty trees were collected randomly from four states in Sudan. The wood density radial trend was determined using the basic density as well as density obtained by the X-ray densitometry method in order to assess the validation of X-ray technique in wood density radial variation determination. The results showed that the pattern of radial trend of density obtained by X-ray technique is very similar to that achieved by basic density. These results confirmed the validation of using the X-ray technique for Acacia seyal var. seyal density radial trend determination. It also promotes the suitability of using this method in other hardwood species.

Keywords: x-ray densitometry, wood density, Acacia seyal var. seyal, radial variation

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Authors: Diaa Othman, Muhammad Adil Khan, Muhammad Riaz

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Without an early intervention to correct the unilateral complete cleft lip and palate deformity, nasal architecture can progress to an exaggerated cleft nose deformity. We present the results of a modified unilateral cleft rhinoplasty procedure ‘the Gujrat technique’ to correct this deformity. Ninety pediatric and adult patients with non-syndromic unilateral cleft lip underwent primary and secondary composite cleft rhinoplasty using the Gujrat technique as a single stage operation over a 10-year period. The technique involved an open rhinoplasty with Tennison lip repair, and employed a combination of three autologous cartilage grafts, seven cartilage-molding sutures and a prolene mesh graft for alar base support. Post-operative evaluation of nasal symmetry was undertaken using the validated computer program ‘SymNose’. Functional outcome and patient satisfaction were assessed using the NOSE scale and ROE (rhinoplasty outcome evaluation) questionnaires. The single group study design used the non-parametric matching pairs Wilcoxon Sign test (p < 0.001), and showed overall good to excellent functional and aesthetic outcomes, including nasal projection and tip definition, and higher scores of the digital SymNose grading system. Objective assessment of the Gujrat cleft rhinoplasty technique demonstrates its aesthetic appeal and functional versatility. Overall it is a simple and reproducible technique, with no significant complications.

Keywords: cleft lip and palate, congenital rhinoplasty, nasal deformity, secondary rhinoplasty

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Authors: Mohammad Reza Ostad Ali Naghi Kashani, Esfanji Elia

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Nowadays, the amounts of companies which tend to have an Enterprise Resource Planning (ERP) application are increasing particularly in developing countries like Iran. ERP projects are expensive, time consuming, and complex, in addition the failure rate is high among these projects. It is important to know whether these projects could meet their goals or not. Furthermore, the area which should be improved should be identified. In this paper we made a framework to evaluate ERP projects success implementation. First, based on literature review we made a framework based on BSC model, financial, customer, processes, learning and knowledge, because of the importance of change management it was added to model. Then an organization was divided in three layers. We choose corporate, managerial, and operational levels. Then to find criteria to assess each aspect, we use Delphi method in two rounds. And for the second round we made a questionnaire and did some statistical tasks on them. Based on the statistical results some of them are accepted and others are rejected.

Keywords: ERP, BSC, ERP project evaluation, IT projects

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Authors: Michał Maksimczuk, Łukasz Kaczmarek, Tomasz Wejrzanowski

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This study concerns high-resolution X-ray computed microtomography (µCT) and ultrasonic pulse analysis of Cambrian sandstones from a borehole located in the Baltic Sea Coast of northern Poland. µCT and ultrasonic technique are non-destructive methods commonly used to determine the internal structure of reservoir rock sample. The spatial resolution of the µCT images obtained was 27 µm, which enabled the author to create accurate 3-D visualizations of structure geometry and to calculate the ratio of pores volume to the total sample volume. A copper X-ray source filter was used to reduce image artifacts. Furthermore, samples Young’s modulus and Poisson ratio were obtained with use of ultrasonic pulse technique. µCT and ultrasonic pulse technique provide complex information which can be used for explorations and characterization of reservoir rocks.

Keywords: elastic parameters, linear absorption coefficient, northern Poland, tight gas

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Authors: Kaushikk Iyer, Richard M Hall, David Keeling

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Hardware-in-the-loop (HIL) simulation is an advanced technique for developing and testing complex real-time control systems. This paper presents the benefits of HIL simulation and how it can be implemented and used effectively to develop, test, and validate advanced control algorithms used in a spinal joint Wear simulator for the Tribological testing of spinal disc prostheses. spinal wear simulator is technologically the most advanced machine currently employed For the in-vitro testing of newly developed spinal Discimplants. However, the existing control techniques, such as a simple position control Does not allow the simulator to test non-sinusoidal waveforms. Thus, there is a need for better and advanced control methods that can be developed and tested Rigorouslybut safely before deploying it into the real simulator. A benchtop HILsetupis was created for experimentation, controller verification, and validation purposes, allowing different control strategies to be tested rapidly in a safe environment. The HIL simulation aspect in this setup attempts to replicate similar spinal motion and loading conditions. The spinal joint wear simulator containsa four-Barlinkpowered by electromechanical actuators. LabVIEW software is used to design a kinematic model of the spinal wear Simulator to Validatehow each link contributes towards the final motion of the implant under test. As a result, the implant articulates with an angular motion specified in the international standards, ISO-18192-1, that define fixed, simplified, and sinusoid motion and load profiles for wear testing of cervical disc implants. Using a PID controller, a velocity-based position control algorithm was developed to interface with the benchtop setup that performs HIL simulation. In addition to PID, a fuzzy logic controller (FLC) was also developed that acts as a supervisory controller. FLC provides intelligence to the PID controller by By automatically tuning the controller for profiles that vary in amplitude, shape, and frequency. This combination of the fuzzy-PID controller is novel to the wear testing application for spinal simulators and demonstrated superior performance against PIDwhen tested for a spectrum of frequency. Kaushikk Iyer is a Ph.D. Student at the University of Leeds and an employee at Key Engineering Solutions, Leeds, United Kingdom, (e-mail: [email protected], phone: +44 740 541 5502). Richard M Hall is with the University of Leeds, the United Kingdom as a professor in the Mechanical Engineering Department (e-mail: [email protected]). David Keeling is the managing director of Key Engineering Solutions, Leeds, United Kingdom (e-mail: [email protected]). Results obtained are successfully validated against the load and motion tolerances specified by the ISO18192-1 standard and fall within limits, that is, ±0.5° at the maxima and minima of the motion and ±2 % of the complete cycle for phasing. The simulation results prove the efficacy of the test setup using HIL simulation to verify and validate the accuracy and robustness of the prospective controller before its deployment into the spinal wear simulator. This method of testing controllers enables a wide range of possibilities to test advanced control algorithms that can potentially test even profiles of patients performing various dailyliving activities.

Keywords: Fuzzy-PID controller, hardware-in-the-loop (HIL), real-time simulation, spinal wear simulator

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Authors: G. Blázquez, A. Gálvez-Pérez, M. Calero, I. Iáñez-Rodríguez, M. A. Martín-Lara, A. Pérez

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The production of olive oil is considered as one of the most important agri-food industries. However, some of the by-products generated in the process are potential pollutants and cause environmental problems. Consequently, the management of these by-products is currently considered as a challenge for the olive oil industry. In this context, several technologies have been developed and tested. In this sense, the autohydrolysis of these by-products could be considered as a promising technique. Therefore, this study focused on autohydrolysis treatments of a solid residue from the olive oil industry denominated olive cake. This one comes from the olive pomace extraction with hexane. Firstly, a water washing was carried out to eliminate the water soluble compounds. Then, an experimental design was developed for the autohydrolysis experiments carried out in the hydrothermal pressure reactor. The studied variables were temperature (30, 60 and 90 ºC) and time (30, 60, 90 min). On the other hand, aliquots of liquid obtained fractions were analysed by HPLC to determine the fructose and sucrose contents present in the liquid fraction. Finally, the obtained results of sugars contents and the yields of the different experiments were fitted to a neuro-fuzzy and to a polynomial model.

Keywords: ANFIS, olive cake, polyols, saccharides

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Authors: Alexander Guzman Urbina, Atsushi Aoyama

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The sustainability of traditional technologies employed in energy and chemical infrastructure brings a big challenge for our society. Making decisions related with safety of industrial infrastructure, the values of accidental risk are becoming relevant points for discussion. However, the challenge is the reliability of the models employed to get the risk data. Such models usually involve large number of variables and with large amounts of uncertainty. The most efficient techniques to overcome those problems are built using Artificial Intelligence (AI), and more specifically using hybrid systems such as Neuro-Fuzzy algorithms. Therefore, this paper aims to introduce a hybrid algorithm for risk assessment trained using near-miss accident data. As mentioned above the sustainability of traditional technologies related with energy and chemical infrastructure constitutes one of the major challenges that today’s societies and firms are facing. Besides that, the adaptation of those technologies to the effects of the climate change in sensible environments represents a critical concern for safety and risk management. Regarding this issue argue that social consequences of catastrophic risks are increasing rapidly, due mainly to the concentration of people and energy infrastructure in hazard-prone areas, aggravated by the lack of knowledge about the risks. Additional to the social consequences described above, and considering the industrial sector as critical infrastructure due to its large impact to the economy in case of a failure the relevance of industrial safety has become a critical issue for the current society. Then, regarding the safety concern, pipeline operators and regulators have been performing risk assessments in attempts to evaluate accurately probabilities of failure of the infrastructure, and consequences associated with those failures. However, estimating accidental risks in critical infrastructure involves a substantial effort and costs due to number of variables involved, complexity and lack of information. Therefore, this paper aims to introduce a well trained algorithm for risk assessment using deep learning, which could be capable to deal efficiently with the complexity and uncertainty. The advantage point of the deep learning using near-miss accidents data is that it could be employed in risk assessment as an efficient engineering tool to treat the uncertainty of the risk values in complex environments. The basic idea of using a Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines is focused in the objective of improve the validity of the risk values learning from near-miss accidents and imitating the human expertise scoring risks and setting tolerance levels. In summary, the method of Deep Learning for Neuro-Fuzzy Risk Assessment involves a regression analysis called group method of data handling (GMDH), which consists in the determination of the optimal configuration of the risk assessment model and its parameters employing polynomial theory.

Keywords: deep learning, risk assessment, neuro fuzzy, pipelines

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Authors: Feng-Sheng Wang, Chao-Ting Cheng

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Developing a drug from conception to launch is costly and time-consuming. Computer-aided methods can reduce research costs and accelerate the development process during the early drug discovery and development stages. This study developed a fuzzy multi-objective hierarchical optimization framework for identifying potential anticancer targets in a metabolic model. First, RNA-seq expression data of colorectal cancer samples and their healthy counterparts were used to reconstruct tissue-specific genome-scale metabolic models. The aim of the optimization framework was to identify anticancer targets that lead to cancer cell death and evaluate metabolic flux perturbations in normal cells that have been caused by cancer treatment. Four objectives were established in the optimization framework to evaluate the mortality of cancer cells for treatment and to minimize side effects causing toxicity-induced tumorigenesis on normal cells and smaller metabolic perturbations. Through fuzzy set theory, a multiobjective optimization problem was converted into a trilevel maximizing decision-making (MDM) problem. The applied nested hybrid differential evolution was applied to solve the trilevel MDM problem using two nutrient media to identify anticancer targets in the genome-scale metabolic model of colorectal cancer, respectively. Using Dulbecco’s Modified Eagle Medium (DMEM), the computational results reveal that the identified anticancer targets were mostly involved in cholesterol biosynthesis, pyrimidine and purine metabolisms, glycerophospholipid biosynthetic pathway and sphingolipid pathway. However, using Ham’s medium, the genes involved in cholesterol biosynthesis were unidentifiable. A comparison of the uptake reactions for the DMEM and Ham’s medium revealed that no cholesterol uptake reaction was included in DMEM. Two additional media, i.e., a cholesterol uptake reaction was included in DMEM and excluded in HAM, were respectively used to investigate the relationship of tumor cell growth with nutrient components and anticancer target genes. The genes involved in the cholesterol biosynthesis were also revealed to be determinable if a cholesterol uptake reaction was not induced when the cells were in the culture medium. However, the genes involved in cholesterol biosynthesis became unidentifiable if such a reaction was induced.

Keywords: Cancer metabolism, genome-scale metabolic model, constraint-based model, multilevel optimization, fuzzy optimization, hybrid differential evolution

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Authors: Ravi Patel, Krishna K. Krishnan

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In global supply chains, appropriate and sustainable suppliers play a vital role in supply chain development and feasibility. In a larger organization with huge number of suppliers, it is necessary to divide suppliers based on their past history of quality and delivery of each product category. Since performance of any organization widely depends on their suppliers, well evaluated selection criteria and decision-making models lead to improved supplier assessment and development. In this paper, SCOR® performance evaluation approach and ISO standards are used to determine selection criteria for better utilization of supplier assessment by using hybrid model of Analytic Hierchchy Problem (AHP) and Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (FTOPSIS). AHP is used to determine the global weightage of criteria which helps TOPSIS to get supplier score by using triangular fuzzy set theory. Both qualitative and quantitative criteria are taken into consideration for the proposed model. In addition, a multi-product and multi-time period model is selected for order allocation. The optimization model integrates multi-objective integer linear programming (MOILP) for order allocation and a hybrid approach for supplier selection. The proposed MOILP model optimizes order allocation based on manufacturing process and product tolerances as per manufacturer’s requirement for quality product. The integrated model and solution approach are tested to find optimized solutions for different scenario. The detailed analysis shows the superiority of proposed model over other solutions which considered individual decision making models.

Keywords: AHP, fuzzy set theory, multi-criteria decision making, multi-objective integer linear programming, TOPSIS

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Authors: Minsu Kim, Hae-Chang Cho, Jae Hoon Chung, Inwook Heo, Kang Su Kim

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For safe design of the UHPC flexural members, accurate estimations of their shear strengths are very important. However, since the shear strengths are significantly affected by various factors such as tensile strength of concrete, shear span to depth ratio, volume ratio of steel fiber, and steel fiber factor, the accurate estimations of their shear strengths are very challenging. In this study, therefore, the Adaptive Neuro-Fuzzy System (ANFIS), which has been widely used to solve many complex problems in engineering fields, was introduced to estimate the shear strengths of UHPC flexural members. A total of 32 experimental results has been collected from previous studies for training of the ANFIS algorithm, and the well-trained ANFIS algorithm provided good estimations on the shear strengths of the UHPC test specimens. Acknowledgement: This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future Planning(NRF-2016R1A2B2010277).

Keywords: ultra-high-performance concrete, ANFIS, shear strength, flexural member

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Authors: Sameh Abaza, Mohamed Ibrahim, Tarek Mahmoud

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Due to the development in the digital image processing, its wide use in many applications such as medical, security, and others, the need for more accurate techniques that are reliable, fast and robust is vehemently demanded. In the field of security, in particular, speed is of the essence. In this paper, a pattern recognition technique that is based on the use of Hidden Markov Model (HMM), K-means and the Sobel operator method is developed. The proposed technique is proved to be fast with respect to some other techniques that are investigated for comparison. Moreover, it shows its capability of recognizing the normal face (center part) as well as face boundary.

Keywords: HMM, K-Means, Sobel, accuracy, face recognition

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Authors: Michael N. O'Sullivan, Con Sheahan

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Researchers have spent decades developing tools and techniques to aid teams in the new product development (NPD) process. Despite this, it is evident that there is a huge gap between their academic prevalence and their industry adoption. For the fuzzy front-end, in particular, there is a wide range of tools to choose from, including the Kano Model, the House of Quality, and many others. In fact, there are so many tools that it can often be difficult for teams to know which ones to use and how they interact with one another. Moreover, while the benefits of using these tools are obvious to industrialists, they are rarely used as they carry a learning curve that is too steep and they become too complex to manage over time. In essence, it is commonly believed that they are simply not worth the effort required to learn and use them. This research explores a streamlined process for the fuzzy front-end, assembling the most effective tools and making them accessible to everyone. The process was developed iteratively over the course of 3 years, following over 80 final year NPD teams from engineering, design, technology, and construction as they carried a product from concept through to production specification. Questionnaires, focus groups, and observations were used to understand the usability issues with the tools involved, and a human-centred design approach was adopted to produce a solution to these issues. The solution takes the form of physical toolkit, similar to a board game, which allows the team to play through an example of a new product development in order to understand the process and the tools, before using it for their own product development efforts. A complimentary website is used to enhance the physical toolkit, and it provides more examples of the tools being used, as well as deeper discussions on each of the topics, allowing teams to adapt the process to their skills, preferences and product type. Teams found the solution very useful and intuitive and experienced significantly less confusion and mistakes with the process than teams who did not use it. Those with a design background found it especially useful for the engineering principles like Quality Function Deployment, while those with an engineering or technology background found it especially useful for design and customer requirements acquisition principles, like Voice of the Customer. Products developed using the toolkit are added to the website as more examples of how it can be used, creating a loop which helps future teams understand how the toolkit can be adapted to their project, whether it be a small consumer product or a large B2B service. The toolkit unlocks the potential of these beneficial tools to those in industry, both for large, experienced teams and for inexperienced start-ups. It allows users to assess the market potential of their product concept faster and more effectively, arriving at the product design stage with technical requirements prioritized according to their customers’ needs and wants.

Keywords: new product development, fuzzy front-end, usability, Kano model, quality function deployment, voice of customer

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Authors: Rahul S. Raj

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Electro-mechanical impedance technique is a recently developed non-destructive method for structural health monitoring. This system comprises of piezo electric patch, bonded to the structure using an adhesive/epoxy and electrically excited to determine the health of the component. The subjected electric field actuates the PZT patch harmonically and imparts a force on the host structure. The structural response thus produced by the host component is in the form of peaks and valleys which further shows the admittance signatures of the structure for the given excitation frequency. Adhesives have the capability to change the structural signatures, in EMI technique, by transforming conductance and susceptance signatures. The static approximation provide a justifiable result where adhesive bond lines are thin and stiff. The epoxy adhesive bonds limits design flexibility due to poor bond strengths, hence to enhance the performance of the joints, a new technique is developed for joining PZT, i.e. the alloy bonding technique. It is a metallic joining compound which contains many active elements including Titanium, that reacts with the tenacious surface films of the ceramic and composites to create excellent bonds. This alloy-based bonding technique will be used for better strain interaction and rigorous stress transfer between PZT patch and the host structure.

Keywords: EMI technique, conductance, susceptance, admittance, alloy bonding

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Authors: Seyed Abbas Tabatabaei, Fereydoon Moghadas Nejad, Mohammad Saed

Abstract:

The bleeding prediction of the asphalt is one of the most complex subjects in the pavement engineering. In this paper, an Adaptive Neuro Fuzzy Inference System (ANFIS) is used for modeling the effect of important parameters on bleeding is trained and tested with the experimental results. bleeding index based on the asphalt film thickness differential as target parameter,asphalt content, temperature depth of two centemeter, heavy traffic, dust to effective binder, Marshall strength, passing 3/4 sieves, passing 3/8 sieves,passing 3/16 sieves, passing NO8, passing NO50, passing NO100, passing NO200 as input parameters. Then, we randomly divided empirical data into train and test sections in order to accomplish modeling. We instructed ANFIS network by 72 percent of empirical data. 28 percent of primary data which had been considered for testing the approprativity of the modeling were entered into ANFIS model. Results were compared by two statistical criterions (R2, RMSE) with empirical ones. Considering the results, it is obvious that our proposed modeling by ANFIS is efficient and valid and it can also be promoted to more general states.

Keywords: bleeding, asphalt film thickness differential, Anfis Modeling

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Authors: Javeria Arain, Saad Malik

Abstract:

The management of solid waste is a crucial and essential aspect of urban environmental management especially in a city with an ever increasing population such as Karachi. The total amount of municipal solid waste generated from Gulshan e Iqbal town on average is 444.48 tons per day and landfill sites are a widely accepted solution for final disposal of this waste. However, an improperly selected site can have immense environmental, economical and ecological impacts. To select an appropriate landfill site a number of factors should be kept into consideration to minimize the potential hazards of solid waste. The purpose of this research is to analyse the study area for the construction of an appropriate landfill site for disposal of municipal solid waste generated from Gulshan e-Iqbal Town by using geospatial techniques considering hydrological, geological, social and geomorphological factors. This was achieved using analytical hierarchy process and fuzzy analysis as a decision support tool with integration of geographic information sciences techniques. Eight most critical parameters, relevant to the study area, were selected. After generation of thematic layers for each parameter, overlay analysis was performed in ArcGIS 10.0 software. The results produced by both methods were then compared with each other and the final suitability map using AHP shows that 19% of the total area is Least Suitable, 6% is Suitable but avoided, 46% is Moderately Suitable, 26% is Suitable, 2% is Most Suitable and 1% is Restricted. In comparison the output map of fuzzy set theory is not in crisp logic rather it provides an output map with a range of 0-1, where 0 indicates least suitable and 1 indicates most suitable site. Considering the results it is deduced that the northern part of the city is appropriate for constructing the landfill site though a final decision for an optimal site could be made after field survey and considering economical and political factors.

Keywords: Analytical Hierarchy Process (AHP), fuzzy set theory, Geographic Information Sciences (GIS), Multi-Criteria Decision Analysis (MCDA)

Procedia PDF Downloads 497

Authors: S. Jagadeesh Kumar

Abstract:

Face detection and recognition is an authoritative technology for image database management, video surveillance, and human computer interface (HCI). Face recognition is a rapidly nascent method, which has been extensively discarded in forensics such as felonious identification, tenable entree, and custodial security. This paper recommends an erudite technique using curvature analysis (CA) that has less false positives incidence, operative in different light environments and confiscates the artifacts that are introduced during image acquisition by ring correction in polar coordinate (RCP) method. This technique affronts mean and median filtering technique to remove the artifacts but it works in polar coordinate during image acquisition. Investigational fallouts for face detection and recognition confirms decent recitation even in diagonal orientation and stance variation.

Keywords: curvature analysis, ring correction in polar coordinate method, face detection, face recognition, human computer interaction

Procedia PDF Downloads 276

Authors: Kittipob Kondee, Chutima Prommak

Abstract:

In this paper, we propose an optimization technique that can be used to optimize the placements of reference nodes and improve the location determination performance for the multi-floor building. The proposed technique is based on Simulated Annealing algorithm (SA) and is called MSMR-M. The performance study in this work is based on simulation. We compare other node-placement techniques found in the literature with the optimal node-placement solutions obtained from our optimization. The results show that using the optimal node-placement obtained by our proposed technique can improve the positioning error distances up to 20% better than those of the other techniques. The proposed technique can provide an average error distance within 1.42 meters.

Keywords: indoor positioning system, optimization system design, multi-floor building, wireless sensor networks

Procedia PDF Downloads 236

Authors: R. Karami, A. Gharaei

Abstract:

The aim of this study was to investigate ecotourism status in Chabahar coastal zone using swot analysis and strategic planning. Firstly, the current status of region was studied by literature review, field survey and statistical analysis. Then strengths and weaknesses (internal factors) were identified as well as opportunities and threats (external factors) using Delphi Method. Based on the obtained results, the total score of 2.46 in IFE matrix and 2.33 in the EFE matrix represents poor condition related to the internal and external factors respectively. This condition means both external and internal factors have not been utilized properly and the zone needs defensive plan; thus appropriate planning and organizational management practices are required to deal with these factors. Furthermore strategic goals, objectives and action plans in short, medium and long term schedule were formulated in attention to swot analysis.

Keywords: tourism, SWOT analysis, strategic planning, Chabahar

Procedia PDF Downloads 507

Authors: Muhammad Yousaf Sadiq

Abstract:

The complexity arises in defining the construction quality due to its perception, based on inherent market conditions and their requirements, the diversified stakeholders itself and their desired output. An quantitative survey based approach was adopted in this constructive study. A questionnaire-based survey was conducted for the assessment of construction Quality perception and expectations in the context of quality improvement technique. The survey feedback of professionals of the leading construction organizations/companies of Pakistan construction industry were analyzed. The financial capacity, organizational structure, and construction experience of the construction firms formed basis for their selection. The quality perception was found to be project-scope-oriented and considered as an excess cost for a construction project. Any quality improvement technique was expected to maximize the profit for the employer, by improving the productivity in a construction project. The study is beneficial for the construction professionals to assess the prevailing construction quality perception and the expectations from implementation of any quality improvement technique in construction projects.

Keywords: construction quality, expectation, improvement, perception

Procedia PDF Downloads 459

Authors: Hiesik Kim, Yong-Beom Kim, Jaheon Gu

Abstract:

Internet of Things (IoT) applications are widely serviced and spread worldwide. Local wireless data transmission technique must be developed to rate up with some technique. Bluetooth wireless data communication is wireless technique is technique made by Special Inter Group (SIG) using the frequency range 2.4 GHz, and it is exploiting Frequency Hopping to avoid collision with a different device. To implement experiment, equipment for experiment transmitting measured data is made by using Arduino as open source hardware, gas sensor, and Bluetooth module and algorithm controlling transmission rate is demonstrated. Experiment controlling transmission rate also is progressed by developing Android application receiving measured data, and controlling this rate is available at the experiment result. It is important that in the future, improvement for communication algorithm be needed because a few error occurs when data is transferred or received.

Keywords: Arduino, Bluetooth, gas sensor, IoT, transmission

Procedia PDF Downloads 272

Authors: Kuang-Hsiung Tan, Chih-Chan Hu, Chien-Wu Lan, Shih-Sung Lin, Te-Jen Chang

Abstract:

An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.

Keywords: distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone

Procedia PDF Downloads 382