Search results for: social innovation process

Authors: Qatawneh H., Yousef S., Shirvani H.

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The purpose of this article is to propose a model designed to achieve Total Knowledge Transfer in the public health sector. The Total Knowledge Transfer Model integrated four essential organizational factors which have been under examined in totality in the literature. The research design was inductive in nature and used a case study for accomplishing the research objectives. The researcher investigated the factors that created a base to design a framework for total knowledge transfer in the public health sector. The results of this study are drawn from a fairly large sample in only two hospitals. A further research can be conducted to cover more responses from a wider health sector. The Total Knowledge Transfer Model is essential to improve the transfer and application of total common health knowledge.

Keywords: Health Care, Knowledge Management, Knowledge Transfer.

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Authors: P. Waiyawuththanapoom, P. Tirastittam

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Thailand is the agriculture country as the weather and geography are suitable for agriculture environment. In 2011, the quantity of exported fresh vegetable was 126,069 tons which valued 117.1 million US dollars. Although the fresh vegetable has a high potential in exporting, there also have a lack of knowledge such as chemical usage, land usage, marketing and also the transportation and logistics. Nakorn Pathom province is the area which the farmer and manufacturer of fresh vegetable located. The objectives of this study are to study the basic information of the local fresh vegetable farmers in Nakorn Pathom province, to study the factor which effects the management of the fresh vegetable supply chain in Nakorn Pathom province and to study the problems and obstacle of the fresh vegetable supply chain in Nakorn Pathom province. This study is limited to the flow of the Nakorn Pathom province fresh vegetable from the farmers to the country which import the vegetable from Thailand. The populations of this study are 100 local farmers in Nakorn Pathom province. The result of this study shows that the key process of the fresh vegetable supply chain is in the supply sourcing process and manufacturing process.

Keywords: Exporting, Fresh Vegetable, Nakorn Pathom Province, Supply Chain.

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Authors: Kuen-Ming Shu, Cheng-Yu Chen

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A vibrating-fork sensor can measure the level height of solids and liquids and operates according to the principle that vibrations created by piezoelectric ceramics are transmitted to the vibrating fork, which produces resonance. When the vibrating fork touches an object, its resonance frequency changes and produces a signal that returns to a controller for immediate adjustment, so as to effectively monitor raw material loading. The design of the vibrating fork in a vibrating-fork material sensor is crucial. In this paper, ANSYS finite element analysis software is used to perform modal analysis on the vibrations of the vibrating fork. In addition, to design and produce a superior vibrating fork, the dimensions and welding shape of the vibrating fork are compared in a simulation performed using the Taguchi method.

Keywords: Vibrating fork, piezoelectric ceramics, sound wave, ANSYS, Taguchi method, modal analysis.

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Authors: Emre Ipekci Cetin, Ebru Tarcan Icigen

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Personnel selection process is considered as one of the most important and most difficult issues in human resources management. At the stage of personnel selection, the applicants are handled according to certain criteria, the candidates are dealt with, and efforts are made to select the most appropriate candidate. However, this process can be more complicated in terms of the managers who will carry out the staff selection process. Candidates should be evaluated according to different criteria such as work experience, education, foreign language level etc. It is crucial that a rational selection process is carried out by considering all the criteria in an integrated structure. In this study, the problem of choosing the front office manager of a 5 star accommodation enterprise operating in Antalya is addressed by using multi-criteria decision-making methods. In this context, SWARA (Step-wise weight assessment ratio analysis) and MOORA (Multi-Objective Optimization on the basis of ratio analysis) methods, which have relatively few applications when compared with other methods, have been used together. Firstly SWARA method was used to calculate the weights of the criteria and subcriteria that were determined by the business. After the weights of the criteria were obtained, the MOORA method was used to rank the candidates using the ratio system and the reference point approach. Recruitment processes differ from sector to sector, from operation to operation. There are a number of criteria that must be taken into consideration by businesses in accordance with the structure of each sector. It is of utmost importance that all candidates are evaluated objectively in the framework of these criteria, after these criteria have been carefully selected in the selection of suitable candidates for employment. In the study, staff selection process was handled by using SWARA and MOORA methods together.

Keywords: Accommodation establishments, human resource management, MOORA, multi criteria decision making, SWARA.

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Authors: Sabina Akter, Osiris Valdez Banda, Pentti Kujala, Jani Romanoff

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This paper examines the relationship between on-board environmental factors and customer overall satisfaction in the context of the cruise on-board experience. The on-board environmental factors considered are ambient, layout/design, social, product/service and on-board enjoyment factors. The study presents a data-driven framework and model for the on-board cruise experience. The data are collected from 893 respondents in an application of a self-administered online questionnaire of their cruise experience. This study reveals the cruise passengers’ on-board experience through the customer decision journey based on the publicly available data. Pearson correlation and regression analysis have been applied, and the results show a positive and a significant relationship between the environmental factors and on-board experience. These data help understand the cruise passengers’ on-board experience, which will be used for the ultimate decision-making process in cruise ship design.

Keywords: Cruise behavior, on-board environmental factors, on-board experience, user or customer satisfaction.

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Authors: A. Amrani, O. Allali, A. Ben Hamida, F. Defrance, S. Morland, E. Pineau, T. Lacroix

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The energy planning process is a very complex task that involves several stakeholders and requires the consideration of several local and global factors and constraints. In order to optimize and simplify this process, we propose a tool-based iterative approach applied to district heating planning. We build our tool with the collaboration of a French territory using actual district data and implementing the European incentives. We set up an iterative process including data visualization and analysis, identification and extraction of information related to the area concerned by the operation, design of sustainable planning scenarios leveraging local renewable and recoverable energy sources, and finally, the evaluation of scenarios. The last step is performed by a dynamic digital twin replica of the city. Territory’s energy experts confirm that the tool provides them with valuable support towards sustainable energy planning.

Keywords: Climate change, data management, decision support, digital twin, district heating, energy planning, renewables, smart city.

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Authors: Merve Sezer, Ismail Sahin, Ahmet Oguz Akturk

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With the use of developing technology, mostly in communication and entertainment, students spend considerable time on the Internet. In addition to the advantages provided by the Internet, social isolation brings problems such as addiction. This is one of the problems of the virtual violence. Cyber bullying is the common name of the intensities which students are exposed on the Internet. The purpose of this study designed as a qualitative research is to find out the cyber bullying varieties and its effects on elementary school students. The participants of this research are 6^th, 7^th and 8^th grade students of a primary school and 24 students agreed to participate in the study. The students were asked to fill an interview with semi-structured open-ended questions. According to the results obtained in the research, the most important statements determined by the participants are breaking passwords on social networking sites, slang insult to blasphemy and taking friendship offers from unfamiliar people. According to participants from the research, the most used techniques to prevent themselves from cyber bullying are to complain to the site administrator, closing accounts on social networking sites and countercharging. Also, suggestions were presented according to the findings.

Keywords: Bullying, cyber-bullying, elementary, peer-relationship, virtual victimization.

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Authors: Jeerapa Sappakitkamjorn, Sa-aat Niwitpong

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In many practical applications in various areas, such as engineering, science and social science, it is known that there exist bounds on the values of unknown parameters. For example, values of some measurements for controlling machines in an industrial process, weight or height of subjects, blood pressures of patients and retirement ages of public servants. When interval estimation is considered in a situation where the parameter to be estimated is bounded, it has been argued that the classical Neyman procedure for setting confidence intervals is unsatisfactory. This is due to the fact that the information regarding the restriction is simply ignored. It is, therefore, of significant interest to construct confidence intervals for the parameters that include the additional information on parameter values being bounded to enhance the accuracy of the interval estimation. Therefore in this paper, we propose a new confidence interval for the coefficient of variance where the population mean and standard deviation are bounded. The proposed interval is evaluated in terms of coverage probability and expected length via Monte Carlo simulation.  

Keywords: Bounded parameters, coefficient of variation, confidence interval, Monte Carlo simulation.

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Authors: Ahasanul Haque, Abdullah Sarwar, Khaliq Ahmad

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Networking is important among students to achieve better understanding. Social networking plays an important role in the education. Realizing its huge potential, various organizations, including institutions of higher learning have moved to the area of social networks to interact with their students especially through Facebook. Therefore, measuring the effectiveness of Facebook as a learning tool has become an area of interest to academicians and researchers. Therefore, this study tried to integrate and propose new theoretical and empirical evidences by linking the western idea of adopting Facebook as an alternative learning platform from a Malaysian perspective. This study, thus, aimed to fill a gap by being among the pioneering research that tries to study the effectiveness of adopting Facebook as a learning platform across other cultural settings, namely Malaysia. Structural equation modeling was employed for data analysis and hypothesis testing. This study finding has provided some insights that would likely affect students’ awareness towards using Facebook as an alternative learning platform in the Malaysian higher learning institutions. At the end, future direction is proposed.

Keywords: Learning Management Tool, Social Networking, Education, Malaysia.

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Authors: Roohi Shabrin S., Devi Prasad B., Prabu D., Pallavi R. S., Revathi P.

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Due to memory leaks, often-valuable system memory gets wasted and denied for other processes thereby affecting the computational performance. If an application-s memory usage exceeds virtual memory size, it can leads to system crash. Current memory leak detection techniques for clusters are reactive and display the memory leak information after the execution of the process (they detect memory leak only after it occur). This paper presents a Dynamic Memory Monitoring Agent (DMMA) technique. DMMA framework is a dynamic memory leak detection, that detects the memory leak while application is in execution phase, when memory leak in any process in the cluster is identified by DMMA it gives information to the end users to enable them to take corrective actions and also DMMA submit the affected process to healthy node in the system. Thus provides reliable service to the user. DMMA maintains information about memory consumption of executing processes and based on this information and critical states, DMMA can improve reliability and efficaciousness of cluster computing.

Keywords: Dynamic Memory Monitoring Agent (DMMA), Cluster Computing, Memory Leak, Fault Tolerant Framework, Dynamic Memory Leak Detection (DMLD).

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: Adaptive sampling, batch bulk methyl methacrylate polymerization, large margin nearest neighbor regression, machine learning.

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Authors: Zahra Banakar, Farzad Tahriri

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It has often been said that the strength of any country resides in the strength of its industrial sector, and Progress in industrial society has been accomplished by the creation of new technologies. Developments have been facilitated by the increasing availability of advanced manufacturing technology (AMT), in addition the implementation of advanced manufacturing technology (AMT) requires careful planning at all levels of the organization to ensure that the implementation will achieve the intended goals. Justification and implementation of advanced manufacturing technology (AMT) involves decisions that are crucial for the practitioners regarding the survival of business in the present days of uncertain manufacturing world. This paper assists the industrial managers to consider all the important criteria for success AMT implementation, when purchasing new technology. Concurrently, this paper classifies the tangible benefits of a technology that are evaluated by addressing both cost and time dimensions, and the intangible benefits are evaluated by addressing technological, strategic, social and human issues to identify and create awareness of the essential elements in the AMT implementation process and identify the necessary actions before implementing AMT.

Keywords: Advanced Manufacturing Technology (AMT), Justification and Classification.

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Authors: D. S. C. Soares, D. G. Costa, J. T. S., A. K. S. Abud, T. P. Nunes, A. M. Oliveira Júnior

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Mathematical models of drying are used for the purpose of understanding the drying process in order to determine important parameters for design and operation of the dryer. The jackfruit is a fruit with high consumption in the Northeast and perishability. It is necessary to apply techniques to improve their conservation for longer in order to diffuse it by regions with low consumption. This study aimed to analyze several mathematical models (Page, Lewis, and Midilli) to indicate one that best fits the conditions of convective drying process using performance indicators associated with each model: accuracy (Af) and noise factors (Bf), mean square error (RMSE) and standard error of prediction (% SEP). Jackfruit drying was carried out in convective type tray dryer at a temperature of 50°C for 9 hours. It is observed that the model Midili was more accurate with Af: 1.39, Bf: 1.33, RMSE: 0.01%, and SEP: 5.34. However, the use of the Model Midilli is not appropriate for purposes of control process due to need four tuning parameters. With the performance indicators used in this paper, the Page model showed similar results with only two parameters. It is concluded that the best correlation between the experimental and estimated data is given by the Page’s model.

Keywords: Drying, models, jackfruit.

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Authors: Mohamed Aymen Slim, Afef Abdelkrim, Mohamed Benrejeb

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The handwriting is a physical demonstration of a complex cognitive process learnt by man since his childhood. People with disabilities or suffering from various neurological diseases are facing so many difficulties resulting from problems located at the muscle stimuli (EMG) or signals from the brain (EEG) and which arise at the stage of writing. The handwriting velocity of the same writer or different writers varies according to different criteria: age, attitude, mood, writing surface, etc. Therefore, it is interesting to reconstruct an experimental basis records taking, as primary reference, the writing speed for different writers which would allow studying the global system during handwriting process. This paper deals with a new approach of the handwriting system modeling based on the velocity criterion through the concepts of artificial neural networks, precisely the Radial Basis Functions (RBF) neural networks. The obtained simulation results show a satisfactory agreement between responses of the developed neural model and the experimental data for various letters and forms then the efficiency of the proposed approaches.

Keywords: ElectroMyoGraphic (EMG) signals, Experimental approach, Handwriting process, Radial Basis Functions (RBF) neural networks, Velocity Modeling.

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Authors: Erika Martinez Ramirez, Rene V. Mayorga

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Nowadays, more engineering systems are using some kind of Artificial Intelligence (AI) for the development of their processes. Some well-known AI techniques include artificial neural nets, fuzzy inference systems, and neuro-fuzzy inference systems among others. Furthermore, many decision-making applications base their intelligent processes on Fuzzy Logic; due to the Fuzzy Inference Systems (FIS) capability to deal with problems that are based on user knowledge and experience. Also, knowing that users have a wide variety of distinctiveness, and generally, provide uncertain data, this information can be used and properly processed by a FIS. To properly consider uncertainty and inexact system input values, FIS normally use Membership Functions (MF) that represent a degree of user satisfaction on certain conditions and/or constraints. In order to define the parameters of the MFs, the knowledge from experts in the field is very important. This knowledge defines the MF shape to process the user inputs and through fuzzy reasoning and inference mechanisms, the FIS can provide an “appropriate" output. However an important issue immediately arises: How can it be assured that the obtained output is the optimum solution? How can it be guaranteed that each MF has an optimum shape? A viable solution to these questions is through the MFs parameter optimization. In this Paper a novel parameter optimization process is presented. The process for FIS parameter optimization consists of the five simple steps that can be easily realized off-line. Here the proposed process of FIS parameter optimization it is demonstrated by its implementation on an Intelligent Interface section dealing with the on-line customization / personalization of internet portals applied to E-commerce.

Keywords: Artificial Intelligence, Fuzzy Logic, Fuzzy InferenceSystems, Nonlinear Optimization.

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Authors: P. R. Prabhu, S. M. Kulkarni, S. S. Sharma

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Deep cold rolling (DCR) is a cold working process, which easily produces a smooth and work-hardened surface by plastic deformation of surface irregularities. In the present study, the influence of main deep cold rolling process parameters on the surface roughness and the hardness of AISI 4140 steel were studied by using fractional factorial design of experiments. The assessment of the surface integrity aspects on work material was done, in terms of identifying the predominant factor amongst the selected parameters, their order of significance and setting the levels of the factors for minimizing surface roughness and/or maximizing surface hardness. It was found that the ball diameter, rolling force, initial surface roughness and number of tool passes are the most pronounced parameters, which have great effects on the work piece-s surface during the deep cold rolling process. A simple, inexpensive and newly developed DCR tool, with interchangeable collet for using different ball diameters, was used throughout the experimental work presented in this paper.

Keywords: Deep cold rolling, design of experiments, surface hardness, surface roughness

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Authors: Hyeondal Jeong, Yoonjung Baek

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This research examines the effects of positive psychological capital (or PsyCap) on employee’s outcomes (satisfaction, commitment, organizational citizenship behavior, innovation behavior and individual creativity). This study conducted a meta-analysis of articles published in the Republic of Korea. As a result, positive psychological capital has a positive effect on the behavior of employees. Heterogeneity was identified among the studies included in the analysis and the context factors were analyzed; the study proposes contextual factors such as team tenure. The moderating effect of team tenure was not statistically significant. The implications were discussed based on the analysis results.

Keywords: Positive psychological capital, satisfaction, commitment, OCB, creativity, meta-analysis.

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Authors: Hanafizan Hussain

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This study shows that several projects will be conducted at the workshop in which using the conceptual model for knowledge sharing approach to create an idea for mobile application. The sharing idea has been done through the collaborative activity in which a group of different field sought to define the mobile application which will lead to new media approach of using social media platform. The collaborative activity will be provided and implemented in the form of one day workshop to determine the approach towards the theme given. The activity later will be continued for four weeks for the participant to prepare for the pitch day workshop. This paper shows the pitch of idea including the interface and prototype for the said products. The collaboration between the members with different field of study shows that social media influenced the knowledge sharing model and its creation or innovations. One of the projects supported a collaborative activity in which a group of young designers sought to define the knowledge sharing model of their ability in creating idea for mobile applications.

Keywords: Mobile application, collaborative activity, conceptual knowledge sharing model, social media platform.

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Authors: S. R. De Oliveira, A. De Almeida, I. M. Dal Fabbro

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Residues are produced in all stages of human activities in terms of composition and volume which vary according to consumption practices and to production methods. Forms of significant harm to the environment are associated to volume of generated material as well as to improper disposal of solid wastes, whose negative effects are noticed more frequently in the long term. The solution to this problem constitutes a challenge to the government, industry and society, because they involve economic, social, environmental and, especially, awareness of the population in general. The main concerns are focused on the impact it can have on human health and on the environment (soil, water, air and sights). The hazardous waste produced mainly by industry, are particularly worrisome because, when improperly managed, they become a serious threat to the environment. In view of this issue, this study aimed to evaluate the management system of solid waste of a coprocessing industrial waste company, to propose improvements to the rejects generation management in a specific step of the Blending production process.

Keywords: Blending, environment, industrial residues.

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Authors: Dmitriy Yu. Korulkin, Ravshan M. Nuraliev, Raissa A. Muzychkina

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In this research paper were investigated the main regularities of a radical bromination reaction of decalin. There had been studied the temperature effect, durations of reaction, frequency rate of process, a ratio of initial components, type and number of the initiator on decalin bromination degree. There were specified optimum conditions of synthesis of a perbromodecalin by the method of a decalin bromination. There are developed the technological flowchart of receiving a perbromodecalin and the mass balance of process on the first and the subsequent loadings of components. The results of research of antibacterial and antifungal activity of synthesized bromoderivatives have been represented.

Keywords: Decalin, optimum technology, perbromodecalin, radical bromination.

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Authors: Ab. Rashid M.F.F., Gan S.Y., Muhammad N.Y.

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Surface roughness (Ra) is one of the most important requirements in machining process. In order to obtain better surface roughness, the proper setting of cutting parameters is crucial before the process take place. This research presents the development of mathematical model for surface roughness prediction before milling process in order to evaluate the fitness of machining parameters; spindle speed, feed rate and depth of cut. 84 samples were run in this study by using FANUC CNC Milling α-Τ14ιE. Those samples were randomly divided into two data sets- the training sets (m=60) and testing sets(m=24). ANOVA analysis showed that at least one of the population regression coefficients was not zero. Multiple Regression Method was used to determine the correlation between a criterion variable and a combination of predictor variables. It was established that the surface roughness is most influenced by the feed rate. By using Multiple Regression Method equation, the average percentage deviation of the testing set was 9.8% and 9.7% for training data set. This showed that the statistical model could predict the surface roughness with about 90.2% accuracy of the testing data set and 90.3% accuracy of the training data set.

Keywords: Surface roughness, regression analysis.

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Authors: Tebogo Phetla, Edison Muzenda, M Belaid

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This study investigated possible ways to improve the efficiency of the platinum precipitation process using ammonium chloride by reducing the platinum content reporting to the effluent. The ore treated consist of five platinum group metals namely, ruthenium, rhodium, iridium, platinum, palladium and a precious metal gold. Gold, ruthenium, rhodium and iridium were extracted prior the platinum precipitation process. Temperature, reducing agent, flow rate and potential difference were the variables controlled to determine the operation conditions for optimum platinum precipitation efficiency. Hydrogen peroxide was added as the oxidizing agent at the temperature of 85-90oC and potential difference of 700-850mV was the variable used to check the oxidizing state of platinum. The platinum was further purified at temperature between 60-65oC, potential difference above 700 mV, ammonium chloride of 200 l, and at these conditions the platinum content reporting to the effluent was reduced to less than 300ppm, resulting in optimum platinum precipitation efficiency and purity of 99.9%.

Keywords: Platinum Group Metals (PGM), Potential difference, Precipitation, Redox reactions.

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Authors: Pattama Ratana-Arporn, Pongtep Wilaipun

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White scar oyster (Crassostrea belcheri) is often eaten raw and being the leading vehicle for foodborne disease, especially Salmonella Weltevreden which exposed the prominent and most resistant to radiation. Gamma irradiation at a low dose of 1 kGy was enough to eliminate S. Weltevreden contaminated in oyster meat at a level up to 5 log CFU/g while it still retain the raw characteristics and equivalent sensory quality as the non-irradiated one. Process development of ready-to-eat chilled oyster meat was conducted by shucking the meat, individually packed in plastic bags, subjected to 1 kGy gamma radiation at chilled condition and then stored in 4oC refrigerated temperature. Microbiological determination showed the absence of S. Weltevreden (5 log CFU/g initial inoculated) along the whole storage time of 30 days. Sensory evaluation indicated the decreasing in sensory scores along storage time which determining the product shelf life to be 18 days compared to 15 days of nonirradiated one. The most advantage of developed process was to provide the safe raw oyster to consumers and in addition sensory quality retained and 3-day extension shelf life also exist.

Keywords: decontamination, food safety, irradiation, oyster, Salmonella Weltevreden

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Authors: Muhammad Aqil, Ichiro Kita, Akira Yano, Nishiyama Soichi

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This paper presents an alternate approach that uses artificial neural network to simulate the flood level dynamics in a river basin. The algorithm was developed in a decision support system environment in order to enable users to process the data. The decision support system is found to be useful due to its interactive nature, flexibility in approach and evolving graphical feature and can be adopted for any similar situation to predict the flood level. The main data processing includes the gauging station selection, input generation, lead-time selection/generation, and length of prediction. This program enables users to process the flood level data, to train/test the model using various inputs and to visualize results. The program code consists of a set of files, which can as well be modified to match other purposes. This program may also serve as a tool for real-time flood monitoring and process control. The running results indicate that the decision support system applied to the flood level seems to have reached encouraging results for the river basin under examination. The comparison of the model predictions with the observed data was satisfactory, where the model is able to forecast the flood level up to 5 hours in advance with reasonable prediction accuracy. Finally, this program may also serve as a tool for real-time flood monitoring and process control.

Keywords: Decision Support System, Neural Network, Flood Level

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Authors: Cláudio Santos, Madalena Araújo, Nuno Correia

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The inherent complexity in nowadays- business environments is forcing organizations to be attentive to the dynamics in several fronts. Therefore, the management of technological innovation is continually faced with uncertainty about the future. These issues lead to a need for a systemic perspective, able to analyze the consequences of interactions between different factors. The field of technology foresight has proposed methods and tools to deal with this broader perspective. In an attempt to provide a method to analyze the complex interactions between events in several areas, departing from the identification of the most strategic competencies, this paper presents a methodology based on the Delphi method and Quality Function Deployment. This methodology is applied in a sheet metal processing equipment manufacturer, as a case study.

Keywords: Competencies, Delphi Method, Quality Function Deployment, Technology Foresight.

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Authors: E.Sasikumar, T.Viruthagiri

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Simultaneous Saccharification and Fermentation (SSF) of sugarcane bagasse by cellulase and Pachysolen tannophilus MTCC *1077 were investigated in the present study. Important process variables for ethanol production form pretreated bagasse were optimized using Response Surface Methodology (RSM) based on central composite design (CCD) experiments. A 23 five level CCD experiments with central and axial points was used to develop a statistical model for the optimization of process variables such as incubation temperature (25–45°) X1, pH (5.0–7.0) X2 and fermentation time (24–120 h) X3. Data obtained from RSM on ethanol production were subjected to the analysis of variance (ANOVA) and analyzed using a second order polynomial equation and contour plots were used to study the interactions among three relevant variables of the fermentation process. The fermentation experiments were carried out using an online monitored modular fermenter 2L capacity. The processing parameters setup for reaching a maximum response for ethanol production was obtained when applying the optimum values for temperature (32°C), pH (5.6) and fermentation time (110 h). Maximum ethanol concentration (3.36 g/l) was obtained from 50 g/l pretreated sugarcane bagasse at the optimized process conditions in aerobic batch fermentation. Kinetic models such as Monod, Modified Logistic model, Modified Logistic incorporated Leudeking – Piret model and Modified Logistic incorporated Modified Leudeking – Piret model have been evaluated and the constants were predicted.

Keywords: Sugarcane bagasse, ethanol, optimization, Pachysolen tannophilus.

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Authors: Afzeri, R. Muhida, Darmawan, A. N. Berahim

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Sharing the manufacturing facility through remote operation and monitoring of a machining process is challenge for effective use the production facility. Several automation tools in term of hardware and software are necessary for successfully remote operation of a machine. This paper presents a prototype of workpiece holding attachment for remote operation of milling process by self configuration the workpiece setup. The prototype is designed with mechanism to reorient the work surface into machining spindle direction with high positioning accuracy. Variety of parts geometry is hold by attachment to perform single setup machining. Pin type with array pattern additionally clamps the workpiece surface from two opposite directions for increasing the machining rigidity. Optimum pins configuration for conforming the workpiece geometry with minimum deformation is determined through hybrid algorithms, Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). Prototype with intelligent optimization technique enables to hold several variety of workpiece geometry which is suitable for machining low of repetitive production in remote operation.

Keywords: Optimization, Remote machining, GeneticAlgorithms, Machining Fixture.

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Authors: C de Almeida, I. M. Dal Fabbro

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The Brazilian Agricultural Products Wholesale Market fits well as example of residues generating system, reaching 750 metric tons per month of total residues, from which 600 metric tons are organic material and 150 metric tons are recyclable materials. Organic material is basically composed of fruit, vegetables and flowers leftovers from the products commercialization. The recyclable compounds are generate from packing material employed in the commercialization process. This research work devoted efforts in carrying quantitative analysis of the residues generated in the agricultural enterprise at its final destination. Data survey followed the directions implemented by the Residues Management Program issued by the agricultural enterprise. It was noticed from that analysis the necessity of changing the logistics applied to the recyclable material collecting process. However, composting process was elected as the organic compounds destination which is considered adequate for a material composed of significant percentage of organic matter far higher than wood, cardboard and plastics contents.

Keywords: Composting, environment, recycling, solid waste.

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Authors: S. Cagin, X. Fischer, E. Delacourt, N. Bourabaa, C. Morin, D. Coutellier, B. Carré, S. Loumé

Abstract:

The complexity of scavenging by ports and its impact on engine efficiency create the need to understand and to model it as realistically as possible. However, there are few empirical scavenging models and these are highly specialized. In a design optimization process, they appear very restricted and their field of use is limited. This paper presents a comparison of two methods to establish and reduce a model of the scavenging process in 2-stroke diesel engines. To solve the lack of scavenging models, a CFD model has been developed and is used as the referent case. However, its large size requires a reduction. Two techniques have been tested depending on their fields of application: The NTF method and neural networks. They both appear highly appropriate drastically reducing the model’s size (over 90% reduction) with a low relative error rate (under 10%). Furthermore, each method produces a reduced model which can be used in distinct specialized fields of application: the distribution of a quantity (mass fraction for example) in the cylinder at each time step (pseudo-dynamic model) or the qualification of scavenging at the end of the process (pseudo-static model).

Keywords: Diesel engine, Design optimization, Model reduction, Neural network, NTF algorithm, Scavenging.

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Authors: Francisco Aparisi, Marco A. de Luna

Abstract:

In some real applications of Statistical Process Control it is necessary to design a control chart to not detect small process shifts, but keeping a good performance to detect moderate and large shifts in the quality. In this work we develop a new quality control chart, the synthetic T2 control chart, that can be designed to cope with this objective. A multi-objective optimization is carried out employing Genetic Algorithms, finding the Pareto-optimal front of non-dominated solutions for this optimization problem.

Keywords: Multi-objective optimization, Quality Control, SPC, Synthetic T2 control chart.

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