Search results for: Business process

Authors: Chun-Ying Lee, Kun-Hsien Lee, Bor-Wei Wang

Abstract:

The process of post-supercritical CO₂ electroplating uses the electrolyte solution after being mixed with supercritical CO₂ and released to atmospheric pressure. It utilizes the microbubbles that form when oversaturated CO₂ in the electrolyte returns to gaseous state, which gives the similar effect of pulsed electroplating. Under atmospheric pressure, the CO₂ bubbles gradually diffuse. Therefore, the introduction of ultrasound and/or other agitation can potentially excite the CO₂ microbubbles to achieve an electroplated surface of even higher quality. In this study, during the electroplating process, three different modes of agitation: magnetic stirrer agitation, ultrasonic agitation and a combined mode (magnetic + ultrasonic) were applied, respectively, in order to obtain an optimal surface morphology and mechanical properties for the electroplated Ni coating. It is found that the combined agitation mode at a current density of 40 A/dm² achieved the smallest grain size, lower surface roughness, and produced an electroplated Ni layer that achieved hardness of 320 HV, much higher when compared with conventional method, which were usually in the range of 160 to 300 HV. However, at the same time, the electroplating with combined agitation developed a higher internal stress of 320 MPa due to the lower current efficiency of the process and finer grain in the coating. Moreover, a new control methodology for tailoring the coating’s mechanical property through its thickness was demonstrated by the timely introduction of ultrasonic agitation during the electroplating process with post supercritical CO₂ mixed electrolyte.

Keywords: Nickel electroplating, micro-bubbles, supercritical carbon dioxide, ultrasonic agitation, magnetic stirring.

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Authors: Ondruska Marek

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The article presents the whole model of IS/IT architecture exception governance. As first, the assumptions of presented model are set. As next, there is defined a generic governance model that serves as a basis for the architecture exception governance. The architecture exception definition and its attributes follow. The model respects well known approaches to the area that are described in the text, but it adopts higher granularity in description and expands the process view with all the next necessary governance components as roles, principles and policies, tools to enable the implementation of the model into organizations. The architecture exception process is decomposed into a set of processes related to the architecture exception lifecycle consisting of set of phases and architecture exception states. Finally, there is information about my future research related to this area.

Keywords: Architecture, dispensation, exception, governance, model

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Authors: Ibrahim Hamidu Magem

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Employee engagement has continued to gain popularity among practitioners, consultants and academicians recent years. This is due to the fact that the engaged employees are central to organizational success in today’s highly competitive and rapidly changing business environment. Employee engagement depicts a situation whereby employee’s harnessed themselves to their work roles. The importance of employee engagement to organizations cannot be overemphasized in today’s rapidly changing business environment. Organizations both large and small are constantly striving to improve their performance, retain employees, reduce absenteeism, and create loyal customers among others. To be able to achieve these organizations need a team of highly engaged employees. In line with this, the study attempts to provide a valuable framework for understanding the antecedents and consequences of employee engagement in organizations. The paper categorizes the antecedents of employee engagement into individual and organizational factors which it is assumed that the existence of such factors could result into engaged employees that will be of benefit to organizations. Therefore, it is recommended that organizations should revisit and redesign its employee engagement system to enable them attain their organizational goals and objectives. In addition, organizations should note that engagement is personal but organizational engagement programmes should be about everyone in the organization. The findings from this paper adds to existing studies about employee engagement and also provide awareness to academics and practitioners about the importance of employee engagement to improve organizations efficiency and effectiveness, as well as to impact to overall firm performance.

Keywords: Antecedent, employee engagement, job involvement, organization.

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Authors: K. Sontaya, B. Pitiyont, V. Punsuvon

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The objective of this study is to investigate the performance of the electrocoagulation process for color and COD removal in palm oil wastewater using a 10 L batch reactor. Iron was used as electrodes and the distance between electrodes was 2 cm. The effects of operating parameters: current voltage (6, 12 and 18 volt), reaction time (5, 15, 30, 45 and 60 min) and initial pH (4 and 9) of treatment efficiency were examine. The result showed that decolorization and COD removal efficiency increased with the increase in current voltage and reaction time. The proper condition for decolorization achieved at initial pH 4 and 9 were current voltage of 12 volt, reaction time 30 min. The decolorization efficiency reached 90.4% and 88.9%, respectively. COD removal was achiveved at current voltage 12 volt, reaction time 15 min. COD removal efficiency was 89.2 % and 83.0%, respectively. From the results, to show electrocoagulation process can treat palm oil mill wastewater in both acidic and basic condition at high efficiency for color and COD removal. Consequently, electrocoagulation process can be used or applied as a post-treatment step to improve the quality of the final discharge in term of color and residual COD removal.

Keywords: COD removal, decolorizaton, electrocoagulation, iron electrode, palm oil mill wastewater.

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Authors: Michael R. Johnson, Ian P. McCarthy

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There is a growing body of evidence to support the proposition of product take back for remanufacturing particularly within the context of Extended Producer Responsibility (EPR). Remanufacturing however presents challenges unlike that of traditional manufacturing environments due to its high levels of uncertainty which may further distract organizations from considering its potential benefits. This paper presents a novel modeling approach for evaluating the uncertainty of part failures within the remanufacturing process and its impact on economic and environmental performance measures. This paper presents both the theoretical modeling approach and an example of its use in application.

Keywords: Remanufacturing, Demanufacturing, Extended Producer Responsibility, Sustainability, Uncertainty.

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Authors: Rifah Ediati, Jajang

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The quality of Ribbed Smoked Sheets (RSS) primarily based on color, dryness, and the presence or absence of fungus and bubbles. This quality is strongly influenced by the drying and fumigation process namely smoking process. Smoking that is held in high temperature long time will result scorched dark brown sheets, whereas if the temperature is too low or slow drying rate would resulted in less mature sheets and growth of fungus. Therefore need to find the time and temperature for optimum quality of sheets. Enhance, unmonitored heat and mass transfer during smoking process lead to high losses of energy balance. This research aims to generate simple empirical mathematical model describing the effect of smoking time and temperature to RSS quality of color, water content, fungus and bubbles. The second goal of study was to analyze energy balance during smoking process. Experimental study was conducted by measuring temperature, residence time and quality parameters of 16 sheets sample in smoking rooms. Data for energy consumption balance such as mass of fuel wood, mass of sheets being smoked, construction temperature, ambient temperature and relative humidity were taken directly along the smoking process. It was found that mathematical model correlating smoking temperature and time with color is Color = -169 - 0.184 T4 - 0.193 T3 - 0.160 0.405 T1 + T2 + 0.388 t1 +3.11 t2 + 3.92t3 + 0.215 t4 with R square 50.8% and with moisture is Moisture = -1.40-0.00123 T4 + 0.00032 T3 + 0.00260 T2 - 0.00292 T1 - 0.0105 t1 + 0.0290 t2 + 0.0452 t3 + 0.00061 t4 with R square of 49.9%. Smoking room energy analysis found useful energy was 27.8%. The energy stored in the material construction 7.3%. Lost of energy in conversion of wood combustion, ventilation and others were 16.6%. The energy flowed out through the contact of material construction with the ambient air was found to be the highest contribution to energy losses, it reached 48.3%.

Keywords: RSS quality, temperature, time, smoking room, energy

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Authors: Teerawach Khamkorn, Laongtip Mathurasa, Savittree Rochanasmita Arnold, Witthaya Mekhum

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The objective of this research intends to create a suitable model of distance training for community leaders in the upper northeastern region of Thailand. The implementation of the research process is divided into four steps: The first step is to analyze relevant documents. The second step deals with an interview in depth with experts. The third step is concerned with constructing a model. And the fourth step takes aim at model validation by expert assessments. The findings reveal the two important components for constructing an appropriate model of distance training for community leaders in the upper northeastern region. The first component consists of the context of technology management, e.g., principle, policy and goals. The second component can be viewed in two ways. Firstly, there are elements comprising input, process, output and feedback. Secondly, the sub-components include steps and process in training. The result of expert assessments informs that the researcher-s constructed model is consistent and suitable and overall the most appropriate.

Keywords: Constructing, Distance Training, Management, Technology.

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Authors: Somaye Abdollahi Pour, Mohsen Saneei

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This paper describes a novel monitoring scheme to minimize total active power in digital circuits depend on the demand frequency, by adjusting automatically both supply voltage and threshold voltages based on circuit operating conditions such as temperature, process variations, and desirable frequency. The delay monitoring results, will be control and apply so as to be maintained at the minimum value at which the chip is able to operate for a given clock frequency. Design details of power monitor are examined using simulation framework in 32nm BTPM model CMOS process. Experimental results show the overhead of proposed circuit in terms of its power consumption is about 40 μW for 32nm technology; moreover the results show that our proposed circuit design is not far sensitive to the temperature variations and also process variations. Besides, uses the simple blocks which offer good sensitivity, high speed, the continuously feedback loop. This design provides up to 40% reduction in power consumption in active mode.

Keywords: active mode, delay monitor, body biasing, VDD scaling, low power.

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Authors: Indrijuli Magsari Putri, Dicky R. Munaf

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The purpose of this paper is to guide the effort in improving the economic added value of Indonesian fisheries product through post fishing program, which is cold storage program. Indonesia's fisheries potential has been acknowledged by the world. FAO (2009) stated that Indonesia is one of the tenth highest producers of fishery products in the world. Based on BPS (Statistics Indonesia data), the national fisheries production in 2011 reached 5.714 million tons, which 93.55% came from marine fisheries and 6.45% from open waters. Indonesian territory consist of 2/3 of Indonesian waters, has given enormous benefits for Indonesia, especially fishermen. To improve the economic level of fishermen requires efforts to develop fisheries business unit. On of the efforts is by improving the quality of products which are marketed in the regional and international levels. It is certainly need the support of the existence of various fishery facilities (infrastructure to superstructure), one of which is cold storage. Given the many benefits of cold storage as a means of processing of fishery resources, Indonesia Maritime Security Coordinating Board (IMSCB) as one of the maritime institutions for maritime security and safety, has a program to empower the coastal community through encourages the development of cold storage in the middle and lower fishery business unit. The development of cold storage facilities which able to run its maximum role requires synergistic efforts of various parties.

Keywords: Cold Storage, Fish, Regulation.

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Authors: A. R. Tavakolpour-Saleh, H. Jokar

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Liquid level control of conical tank system is known to be a great challenge in many industries such as food processing, hydrometallurgical industries and wastewater treatment plant due to its highly nonlinear characteristics. In this research, an adaptive fuzzy PID control scheme is applied to the problem of liquid level control in a nonlinear tank process. A conical tank process is first modeled and primarily simulated. A PID controller is then applied to the plant model as a suitable benchmark for comparison and the dynamic responses of the control system to different step inputs were investigated. It is found that the conventional PID controller is not able to fulfill the controller design criteria such as desired time constant due to highly nonlinear characteristics of the plant model. Consequently, a nonlinear control strategy based on gain-scheduling adaptive control incorporating a fuzzy logic observer is proposed to accurately control the nonlinear tank system. The simulation results clearly demonstrated the superiority of the proposed adaptive fuzzy control method over the conventional PID controller.

Keywords: Adaptive control, fuzzy logic, conical tank, PID controller.

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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: Tiina Brandt, Isaac Wanasika

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Culturally diverse global companies need to understand cultural differences between leaders and employees from different backgrounds. Communication is culturally contingent and has a significant impact on effective execution of leadership goals. The awareness of cultural variations related to communication and interactions will help leaders modify their own behavior, and consequently improve the execution of goals and avoid unnecessary faux pas. Our focus is on young adults that have experienced cultural integration, culturally diverse surroundings in schools and universities, and cultural travels. Our central research problem is to understand the impact of different national cultures on communication. We focus on four countries with distinct national cultures and spatial distribution. The countries are Finland, Indonesia, Russia and USA. Our sample is based on business students (n = 225) from various backgrounds in the four countries. Their responses of communication and leadership styles were analyzed using ANOVA and post-hoc test. Results indicate that culture impacts on communication behavior. Even young culturally-exposed adults with cultural awareness and experience demonstrate cultural differences in their behavior. Apparently, culture is a deeply seated trait that cannot be completely neutralized by environmental variables. Our study offers valuable input for leadership training programs and for expatriates when recognizing specific differences on leaders’ behavior due to culture.

Keywords: Culture, communication, Finland, Indonesia, Russia, USA.

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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: 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: 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: C. Manjula, Lilly Florence

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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: Decision tree, genetic algorithm, machine learning, software defect prediction.

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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: Emine Demiray, Şensu Curabay

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Distance education program is a dimension of contemporary and new education technologies. Concepts and applications in this field are the results of a series of educational demands and developments in various communication and education technologies. Distance education applications have some conceptual bases. These are creating new education opportunities, realizing work-education unity, getting democratic in education, lifelong education, tendency to individual matters, effective use of institutions, integration of technology and education, tendency to individual and social needs, taking three dimensional integration as the main principle (publishing, printed materials and face to face education), reaching maximum mass, individual and mass education integrity and education demand and financial matters balance. Economics, Business Administration and Open Education faculties, which have been giving education within Anadolu University since 1982 in Turkey, are carrying on education with nearly 1.000.000 students. The aim of this study is to determine organizational commitment levels of students who have been studying at Anadolu University Economics, Business Administration and Open Education faculties in the scope of affective, continuance and nominative commitment in Allen&Meyer model. In the study, organizational commitment of the Economics, Business Administration and Open Education faculty students, who are receiving education by means of distance education, to their faculties is dealt after introducing Anadolu University Distance Education system which gives higher education via distance education method in Turkey. In order to increase the success level of faculties it is required for students to have high level of organizational commitment to their faculties. A questionnaire has been applied by using “Organizational Commitment Scale", developed by Meyer&Allen to determine organizational commitments of Economics, Business Administration and Open Education students. Organizational commitment is dealt with as affective, continuance and nominative commitment. The questionnaire was applied face to face to randomly chosen 500 students living in Eskişehir and the data was downloaded to the computer by using SPSS program and the results were analyzed in terms of demographic features (gender, age, marital status, years of study, work and income level) of students by using frequency test, ttest and ANOVA test. As a result of these analyses, when the comments of Open Education Faculty students on levels of affective, continuance and nominative commitment to their faculties were examined, it has been revealed that continuance commitment level has the highest rate. Among the female participants; continuance commitment is high in the age range of 30-40, for normative commitment it is 17-22. However no dominant age range was defined for affective commitment. Regarding the marital status; continuance commitment average is higher among married participants; but nominative affective commitment average is higher among single participants. As to the years of study, affective and continuance commitment is higher among senior students while normative commitment is higher among junior students. Moreover; in terms of continuance, affective and normative commitment, those who do not work and have low income have higher level of all there commitment types than those who work and have relatively high income.

Keywords: Open education, Organizational commitment, Distance education.

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Authors: Hebberly Ahatlan

Abstract:

The process of digitizing energy systems involves transforming traditional energy infrastructure into interconnected, data-driven systems that enhance efficiency, sustainability, and responsiveness. As smart grids become increasingly integral to the efficient distribution and management of electricity from both fossil and renewable energy sources, the energy industry faces strategic challenges associated with digitalization and interoperability — particularly in the context of modern energy business models, such as virtual power plants (VPPs). The critical challenge in modern smart grids is to seamlessly integrate diverse technologies and systems, including virtualization, grid computing and service-oriented architecture (SOA), across the entire energy ecosystem. Achieving this requires addressing issues like semantic interoperability, Information Technology (IT) and Operational Technology (OT) convergence, and digital asset scalability, all while ensuring security and risk management. This paper proposes a four-layer digitalization framework to tackle these challenges, encompassing persistent data protection, trusted key management, secure messaging, and authentication of IoT resources. Data assets generated through this framework enable AI systems to derive insights for improving smart grid operations, security, and revenue generation. Furthermore, this paper also proposes a Trusted Energy Interoperability Alliance as a universal guiding standard in the development of this digitalization framework to support more dynamic and interoperable energy markets.

Keywords: Digitalization, IT/OT convergence, semantic interoperability, TEIA alliance, VPP.

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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: Eugene Allevato

Abstract:

Developing a responsible personal worldview is central to sustainable development, but achieving quality education to promote transformative learning for sustainability is thus far, poorly understood. Most programs involving education for sustainable development rely on changing behavior, rather than attitudes. The emphasis is on the scientific and utilitarian aspect of sustainability with negligible importance on the intrinsic value of nature. Campus sustainability projects include building sustainable gardens and implementing energy-efficient upgrades, instead of focusing on educating for sustainable development through exploration of students’ values and beliefs. Even though green technology adoption maybe the right thing to do, most schools are not targeting the root cause of the environmental crisis; they are just providing palliative measures. This study explores the under-examined factors that lead to pro-environmental behavior by investigating the environmental perceptions of both college business students and personnel of green organizations. A mixed research approach of qualitative, based on structured interviews, and quantitative instruments was developed including 30 college-level students’ interviews and 40 green organization staff members involved in sustainable activities. The interviews were tape-recorded and transcribed for analysis. Categorization of the responses to the open‐ended questions was conducted with the purpose of identifying the main types of factors influencing attitudes and correlating with behaviors. Overall the findings of this study indicated a lack of appreciation for nature, and inability to understand interconnectedness and apply critical thinking. The results of the survey conducted on undergraduate students indicated that the responses of business and liberal arts students by independent t-test were significantly different, with a p‐value of 0.03. While liberal arts students showed an understanding of human interdependence with nature and its delicate balance, business students seemed to believe that humans were meant to rule over the rest of nature. This result was quite intriguing from the perspective that business students will be defining markets, influencing society, controlling and managing businesses that supposedly, in the face of climate change, shall implement sustainable activities. These alarming results led to the focus on green businesses in order to better understand their motivation to engage in sustainable activities. Additionally, a probit model revealed that childhood exposure to nature has a significantly positive impact in pro-environmental attitudes to most of the New Ecological Paradigm scales. Based on these findings, this paper discusses educators including Socrates, John Dewey and Paulo Freire in the implementation of eco-pedagogy and transformative learning following a curriculum with emphasis on critical and systems thinking, which are deemed to be key ingredients in quality education for sustainable development.

Keywords: Eco-pedagogy, environmental behavior, quality education for sustainable development, transformative learning.

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Authors: Pattama Ratana-Arporn, Pongtep Wilaipun

Abstract:

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

Abstract:

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: E.Sasikumar, T.Viruthagiri

Abstract:

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

Abstract:

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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