Search results for: processing and manufacturing technologies

Authors: Jamila Garba Audu, Shehu Usman Hassan

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The widespread failure in the financial information quality has created the need to improve the financial information quality and to strengthen the control of managers by setting up good firms structures. Published accounting information in financial statements is required to provide various users - shareholders, employees, suppliers, creditors, financial analysts, stockbrokers and government agencies – with timely and reliable information useful for making prudent, effective and efficient decisions. The relationship between corporate governance and performance to financial reporting quality is imperative; this is because despite rapid researches in this area the findings obtained from these studies are constantly inconclusive. Data for the study were extracted from the firms’ annual reports and accounts. After running the OLS regression, a robustness test was conducted for the validity of statistical inferences; the data was empirically tested. A multiple regression was employed to test the model as a technique for data analysis. The results from the analysis revealed a negative association between all the regressors and financial reporting quality except the performance of listed manufacturing firms in Nigeria. This indicates that corporate governance plays a significant role in mitigating earnings management and improving financial reporting quality while performance does not. The study recommended among others that the composition of audit committee should be made in accordance with the provision for code of corporate governance which is not more than six (6) members with at least one (1) financial expert.

Keywords: corporate governance, financial reporting quality, manufacturing firms, Nigeria, performance

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Authors: Ying Guo, Miaochan Li, David Yang, Xiao-Yan Li

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This paper examines the relevance of accounting information to stock prices at different periods using manufacturing companies listed in China’s Growth Enterprise Market (GEM). We find that both the average stock price at fiscal year-end and the average stock price one month after fiscal year-end are more relevant to the accounting information than the closing stock price four months after fiscal year-end. This implies that Chinese stock markets react before the public disclosure of accounting information, which may be due to information leak before official announcements. Our findings confirm that accounting information is relevant to stock prices for Chinese listed manufacturing companies, which is a critical question to answer for investors who have interest in Chinese companies.

Keywords: accounting information, response time, value relevance, stock price

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Authors: F. Stephen Joe, V. Sathya Narayanan, V. R. Sanal Kumar

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A comprehensive review of the literature on photovoltaic cells has been carried out for exploring the better options for cost efficient technologies for future solar cell applications. Literature review reveals that the Bulk Heterojunction (BHJ) Polymer Solar cells offer special opportunities as renewable energy resources. It is evident from the previous studies that the device fabricated with TiOx layer shows better power conversion efficiency than that of the device without TiOx layer. In this paper, authors designed a controlled BHJ solar cell using a modified organic vapor spray deposition technique facilitated with a vertical-moving gun named as 'Stephen Joe Technique' for getting a desirable surface pattern over the substrate to improving its efficiency over the years for industrial applications. We comprehended that the efficient processing and the interface engineering of these solar cells could increase the efficiency up to 5-10 %.

Keywords: BHJ polymer solar cell, photovoltaic cell, solar cell, Stephen Joe technique

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Authors: Surabhi Maiti, Prajakta Tamhankar, Prachi Uttam Mehta

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Since the accomplishment of the Human Genome Project, there has been an unparalled escalation in the sequencing of genomic data. This project has been the first major vault in the field of medical research, especially in genomics. This project won accolades by using a concept called Bigdata which was earlier, extensively used to gain value for business. Bigdata makes use of data sets which are generally in the form of files of size terabytes, petabytes, or exabytes and these data sets were traditionally used and managed using excel sheets and RDBMS. The voluminous data made the process tedious and time consuming and hence a stronger framework called Hadoop was introduced in the field of genetic sciences to make data processing faster and efficient. This paper focuses on using SPARK which is gaining momentum with the advancement of BigData technologies. Cloud Storage is an effective medium for storage of large data sets which is generated from the genetic research and the resultant sets produced from SPARK analysis.

Keywords: human genome project, Bigdata, genomic data, SPARK, cloud storage, Hadoop

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Authors: Neumoin Anton Ivanovich, Opra Denis Pavlovich

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Materials based on titanium oxide compounds are widely used in such areas as solar energy, photocatalysis, food industry and hygiene products, biomedical technologies, etc. Demand for them has also formed in the battery industry (an example of this is the commercialization of Li4Ti5O12), where much attention has recently been paid to the development of next-generation systems and technologies, such as sodium-ion batteries. This dictates the need to search for new materials with improved characteristics, as well as ways to obtain them that meet the requirements of scalability. One of the ways to solve these problems can be the creation of nanomaterials that often have a complex of physicochemical properties that radically differ from the characteristics of their counterparts in the micro- or macroscopic state. At the same time, it is important to control the texture (specific surface area, porosity) of such materials. In view of the above, among other methods, the hydrothermal technique seems to be suitable, allowing a wide range of control over the conditions of synthesis. In the present study, a method was developed for the preparation of mesoporous nanostructured sodium trititanate (Na2Ti3O7) with a hierarchical architecture. The materials were synthesized by hydrothermal processing and exhibit a complex hierarchically organized two-layer architecture. At the first level of the hierarchy, materials are represented by particles having a roughness surface, and at the second level, by one-dimensional nanotubes. The products were found to have high specific surface area and porosity with a narrow pore size distribution (about 6 nm). As it is known, the specific surface area and porosity are important characteristics of functional materials, which largely determine the possibilities and directions of their practical application. Electrochemical impedance spectroscopy data show that the resulting sodium trititanate has a sufficiently high electrical conductivity. As expected, the synthesized complexly organized nanoarchitecture based on sodium trititanate with a porous structure can be practically in demand, for example, in the field of new generation electrochemical storage and energy conversion devices.

Keywords: sodium trititanate, hierarchical materials, mesoporosity, nanotubes, hydrothermal synthesis

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Authors: Halil Ibrahim Demir, Caner Erden, Mumtaz Ipek, Ozer Uygun

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Traditionally, the three important manufacturing functions, which are process planning, scheduling and due-date assignment, are performed separately and sequentially. For couple of decades, hundreds of studies are done on integrated process planning and scheduling problems and numerous researches are performed on scheduling with due date assignment problem, but unfortunately the integration of these three important functions are not adequately addressed. Here, the integration of these three important functions is studied by using genetic, random-genetic hybrid, simulated annealing, random-simulated annealing hybrid and random search techniques. As well, the importance of the integration of these three functions and the power of meta-heuristics and of hybrid heuristics are studied.

Keywords: process planning, weighted scheduling, weighted due-date assignment, genetic search, simulated annealing, hybrid meta-heuristics

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Authors: Jose Cristiano Pereira, Gilson Brito Alves Lima

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Ergonomics is a key factor affecting the operational safety and quality in the aircraft engine manufacturing industry and evidence shows that the lack of attention to it can increase the risk of accidents. In order to emphasize the importance of ergonomics, this paper systematically reviews the critical processes used in the aircraft engine production industry with focus on the ergonomic factors. about the subject to identify key ergonomic factors. Experts validated the factors and used AHP to rank the factors in order of significance. From the six key risk factors identified, the ones with the highest weight are psychological demand followed by understanding of operational side. These factors suggest that measures must be taken to improve ergonomic factors, quality and safety in the manufacturing of aircraft engines.

Keywords: ergonomics, safety, aviation, aircraft engine production

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Authors: Abisuga Oluwayemisi Adebola, Kerri Akiwowo, Deon de Beer, Kobus Van Der Walt

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The convergence of additive manufacturing (AM) and traditional textile dyeing techniques has initiated innovative possibilities for improving the visual application and customization potential of 3D-printed polymer objects. Textile dyeing techniques have progressed to transform fabrics with vibrant colours and complex patterns over centuries. The layer-by-layer deposition characteristic of AM necessitates adaptations in dye application methods to ensure even colour penetration across complex surfaces. Compatibility between dye formulations and polymer matrices influences colour uptake and stability, demanding careful selection and testing of dyes for optimal results. This study investigates the development interaction between these areas, revealing the challenges and opportunities of applying textile dyeing methods to colour 3D-printed polymer materials. The method explores three innovative approaches to colour the 3D-printed polymer object: (a) Additive Manufacturing of a Prototype, (b) the traditional dyebath method, and (c) the contemporary digital sublimation technique. The results show that the layer lines inherent to AM interact with dyes differently and affect the visual outcome compared to traditional textile fibers. Skillful manipulation of textile dyeing methods and dye type used for this research reduced the appearance of these lines to achieve consistency and desirable colour outcomes. In conclusion, integrating textile dyeing techniques into colouring 3D-printed polymer materials connects historical craftsmanship with innovative manufacturing. Overcoming challenges of colour distribution, compatibility, and layer line management requires a holistic approach that blends the technical consistency of AM with the artistic sensitivity of textile dyeing. Hence, applying textile dyeing methods to 3D-printed polymers opens new dimensions of aesthetic and functional possibilities.

Keywords: polymer, 3D-printing, sublimation, textile, dyeing, additive manufacturing

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Authors: José Luis Carrillo-Medina, Roberto Latorre

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Experimental evidence has revealed that different living neural systems can sign their output signals with some specific neural signature. Although experimental and modeling results suggest that neural signatures can have an important role in the activity of neural networks in order to identify the source of the information or to contextualize a message, the functional meaning of these neural fingerprints is still unclear. The existence of cellular mechanisms to identify the origin of individual neural signals can be a powerful information processing strategy for the nervous system. We have recently built different models to study the ability of a neural network to process information based on the emission and recognition of specific neural fingerprints. In this paper we further analyze the features that can influence on the information processing ability of this kind of networks. In particular, we focus on the role that the duration of a refractory period in each neuron after emitting a signed message can play in the network collective dynamics.

Keywords: neural signature, neural fingerprint, processing based on signal identification, self-organizing neural network

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Authors: Jingjing Ye, Cijun Fan, Yan Dong

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The development of financial sector plays an important role in shaping industrial structure. However, evidence on the micro-level channels through which this relation manifest remains relatively sparse, particularly for developing countries. In this paper, we compile an industry-by-city dataset based on manufacturing firms and registered banks in 287 Chinese cities from 1998 to 2008. Based on a difference-in-difference approach, we find the highly concentrated banking sector decreases the competitiveness of firms in each manufacturing industry. There are two main reasons: i) bank accessibility successfully fosters firm expansion within each industry, however, only for sufficiently large enterprises; ii) state-owned enterprises are favored by the banking industry in China. The results are robust after considering alternative concentration and external finance dependence measures.

Keywords: bank concentration, China, difference-in-difference, industry structure

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Authors: Leonid Zhukov, Dmytro Petrenko

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Optical thermometry has no alternative in many cases of industrial most effective continuous temperature control. Classical optical thermometry technologies can be used on available for pyrometers controlled objects with stable radiation characteristics and transmissivity of the intermediate medium. Without using temperature corrections, it is possible in the case of a “black” body for energy pyrometry and the cases of “black” and “grey” bodies for spectral ratio pyrometry or with using corrections – for any colored bodies. Consequently, with increasing the number of operating waves, optical thermometry possibilities to reduce methodical errors significantly expand. That is why, in recent 25-30 years, research works have been reoriented on more perfect spectral (multicolor) thermometry technologies. There are two physical material substances, i.e., substance (controlled object) and electromagnetic field (thermal radiation), to be operated in optical thermometry. Heat is transferred by radiation; therefore, radiation has the energy, entropy, and temperature. Optical thermometry was originating simultaneously with the developing of thermal radiation theory when the concept and the term "radiation temperature" was not used, and therefore concepts and terms "conditional temperatures" or "pseudo temperature" of controlled objects were introduced. They do not correspond to the physical sense and definitions of temperature in thermodynamics, molecular-kinetic theory, and statistical physics. Launched by the scientific thermometric society, discussion about the possibilities of temperature measurements of objects, including colored bodies, using the temperatures of their radiation is not finished. Are the information about controlled objects transferred by their radiation enough for temperature measurements? The positive and negative answers on this fundamental question divided experts into two opposite camps. Recent achievements of spectral thermometry develop events in her favour and don’t leave any hope for skeptics. This article presents the results of investigations and developments in the field of spectral thermometry carried out by the authors in the Department of Thermometry and Physics-Chemical Investigations. The authors have many-year’s of experience in the field of modern optical thermometry technologies. Innovative technologies of optical continuous temperature control have been developed: symmetric-wave, two-color compensative, and based on obtained nonlinearity equation of spectral emissivity distribution linear, two-range, and parabolic. Тhe technologies are based on direct measurements of physically substantiated and proposed by Prof. L. Zhukov, radiation temperatures with the next calculation of the controlled object temperature using this radiation temperatures and corresponding mathematical models. Тhe technologies significantly increase metrological characteristics of continuous contactless and light-guide temperature control in energy, metallurgical, ceramic, glassy, and other productions. For example, under the same conditions, the methodical errors of proposed technologies are less than the errors of known spectral and classical technologies in 2 and 3-13 times, respectively. Innovative technologies provide quality products obtaining at the lowest possible resource-including energy costs. More than 600 publications have been published on the completed developments, including more than 100 domestic patents, as well as 34 patents in Australia, Bulgaria, Germany, France, Canada, the USA, Sweden, and Japan. The developments have been implemented in the enterprises of USA, as well as Western Europe and Asia, including Germany and Japan.

Keywords: emissivity, radiation temperature, object temperature, spectral thermometry

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Authors: Svetlana Strinyuk, Viacheslav Lanin

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Academic English has become lingua franca for international scientific community which stimulates universities to introduce English for Specific Purposes (EAP) courses into curriculum. Teaching L2 EAP students might be fulfilled with corpus technologies and digital stylistics. A special software developed to reach the manifold task of teaching, assessing and researching academic writing of L2 students on basis of digital stylistics and multidimensional analysis was created. A set of annotations (style markers) – grammar, lexical and syntactic features most significant of academic writing was built. Contrastive comparison of two corpora “model corpus”, subject domain limited papers published by competent writers in leading academic journals, and “students’ corpus”, subject domain limited papers written by last year students allows to receive data about the features of academic writing underused or overused by L2 EAP student. Both corpora are tagged with a special software created in GATE Developer. Style markers within the framework of research might be replaced depending on the relevance and validity of the result which is achieved from research corpora. Thus, selecting relevant (high frequency) style markers and excluding less relevant, i.e. less frequent annotations, high validity of the model is achieved. Software allows to compare the data received from processing model corpus to students’ corpus and get reports which can be used in teaching and assessment. The less deviation from the model corpus students demonstrates in their writing the higher is academic writing skill acquisition. The research showed that several style markers (hedging devices) were underused by L2 EAP students whereas lexical linking devices were used excessively. A special software implemented into teaching of EAP courses serves as a successful visual aid, makes assessment more valid; it is indicative of the degree of writing skill acquisition, and provides data for further research.

Keywords: corpus technologies in EAP teaching, multidimensional analysis, GATE Developer, corpus stylistics

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Authors: Vaida Zemlickiene

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Scientists around the world and practitioners are working to identify the factors that influence the results of technology commercialization and to propose the ideal model for the technology commercialization process. In other words, all stakeholders of technology commercialization seek to find a formula or set of rules to succeed in commercializing technologies in order to avoid unproductive investments. In this article, the process of commercialization technology is understood as the process of transforming inventions into marketable products, services, and processes, or the path from the idea of using an invention to a product that incorporates process from 1 to 9 technology readiness level (TRL). There are many publications in the field of management literature, which are aimed at managing the commercialization process. However, there is an apparent lack of research for communication in decision-making in the process of technology commercialization. Works were done in the past, and the last decade's global research analysis led to the unambiguous conclusion that the methodological framework is not mature enough to be of practical use in business. The process of technology commercialization and the decisions made in the process should be explored in-depth. An archival analysis is performed to find insights into decision-making communication in the process of technologies commercialization, to find out the content of technology commercialization process: decision-making stages and participants, to analyze the internal factors of technology commercialization, to perform their critical analysis, to analyze the concept of successful/unsuccessful technology commercialization.

Keywords: the process of technology commercialization, communication in decision-making process, the content of technology commercialization process, successful/unsuccessful technology commercialization

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Authors: Ali Reza Ghaffari, Hassan Saghi

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Given the limitation of fossil resources to supply energy to buildings, recent years have seen a revival of interest in new technologies that produce the energy using new forms of energy in many developed countries. In this research, first the potentials of new energies in Iran are discussed and then based on case studies undertaken in a building in Tehran, the effects of utilizing new solar energy technology for supplying the energy of buildings are investigated. Then, by analyzing the data recorded over a four-year period, the technical performance of this system is investigated. According to the experimental operation plan, this system requires an auxiliary heating circuit for continuous operation over a year. Also, in the economic analysis, real conditions are considered and the results are recorded based on long-term data. Considering the purchase and commissioning building, supplementary energy consumption, etc. a comparison is drawn between the costs of using a solar water heater in a residential unit with the energy costs of a similar unit equipped with a conventional gas water heater. Given the current price of energy, using a solar water heater in the country will not economical, but considering the global energy prices, this system will have a return on investment after 4.5 years. It also produces 81% less pollution and saves about $21.5 on environmental pollution cleanup.

Keywords: energy supply, new energies, new technologies, buildings

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Authors: Theresa Slump, Paula Neumeister, Katharina Feldker, Carina Y. Heitmann, Thomas Straube

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A characteristic feature of post-traumatic stress disorder (PTSD) is the automatic processing of disorder-specific stimuli that expresses itself in intrusive symptoms such as intense physical and psychological reactions to trauma-associated stimuli. That automatic processing plays an essential role in the development and maintenance of symptoms. The aim of our study was, therefore, to investigate the behavioral and neural correlates of automatic processing of trauma-related stimuli in PTSD. Although interpersonal traumatization is a form of traumatization that often occurs, it has not yet been sufficiently studied. That is why, in our study, we focused on patients suffering from interpersonal traumatization. While previous imaging studies on PTSD mainly used faces, words, or generally negative visual stimuli, our study presented complex trauma-related and neutral visual scenes. We examined 19 female subjects suffering from PTSD and examined 19 healthy women as a control group. All subjects did a geometric comparison task while lying in a functional-magnetic-resonance-imaging (fMRI) scanner. Trauma-related scenes and neutral visual scenes that were not relevant to the task were presented while the subjects were doing the task. Regarding the behavioral level, there were not any significant differences between the task performance of the two groups. Regarding the neural level, the PTSD patients showed significant hyperactivation of the hippocampus for task-irrelevant trauma-related stimuli versus neutral stimuli when compared with healthy control subjects. Connectivity analyses revealed altered connectivity between the hippocampus and other anxiety-related areas in PTSD patients, too. Overall, those findings suggest that fear-related areas are involved in PTSD patients' processing of trauma-related stimuli even if the stimuli that were used in the study were task-irrelevant.

Keywords: post-traumatic stress disorder, automatic processing, hippocampus, functional magnetic resonance imaging

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Authors: Mahyar Mehrafarin, Reza Mehrafarin

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The Sistan region in eastern Iran is a significant archaeological area in Iran and the Middle East, encompassing 10,000 square kilometers. Previous archeological field surveys have identified 1662 ancient sites dating from prehistoric periods to the Islamic period. Research Aim: This article aims to explore the utilization of modern technologies and computers in archaeological field surveys in Sistan, Iran, and the benefits derived from their implementation. Methodology: The research employs a descriptive-analytical approach combined with field methods. New technologies and software, such as GPS, drones, magnetometers, equipped cameras, satellite images, and software programs like GIS, Map source, and Excel, were utilized to collect information and analyze data. Findings: The use of modern technologies and computers in archaeological field surveys proved to be essential. Traditional archaeological activities, such as excavation and field surveys, are time-consuming and costly. Employing modern technologies helps in preserving ancient sites, accurately recording archaeological data, reducing errors and mistakes, and facilitating correct and accurate analysis. Creating a comprehensive and accessible database, generating statistics, and producing graphic designs and diagrams are additional advantages derived from the use of efficient technologies in archaeology. Theoretical Importance: The integration of computers and modern technologies in archaeology contributes to interdisciplinary collaborations and facilitates the involvement of specialists from various fields, such as geography, history, art history, anthropology, laboratory sciences, and computer engineering. The utilization of computers in archaeology spanned across diverse areas, including database creation, statistical analysis, graphics implementation, laboratory and engineering applications, and even artificial intelligence, which remains an unexplored area in Iranian archaeology. Data Collection and Analysis Procedures: Information was collected using modern technologies and software, capturing geographic coordinates, aerial images, archeogeophysical data, and satellite images. This data was then inputted into various software programs for analysis, including GIS, Map source, and Excel. The research employed both descriptive and analytical methods to present findings effectively. Question Addressed: The primary question addressed in this research is how the use of modern technologies and computers in archeological field surveys in Sistan, Iran, can enhance archaeological data collection, preservation, analysis, and accessibility. Conclusion: The utilization of modern technologies and computers in archaeological field surveys in Sistan, Iran, has proven to be necessary and beneficial. These technologies aid in preserving ancient sites, accurately recording archaeological data, reducing errors, and facilitating comprehensive analysis. The creation of accessible databases, statistics generation, graphic designs, and interdisciplinary collaborations are further advantages observed. It is recommended to explore the potential of artificial intelligence in Iranian archaeology as an unexplored area. The research has implications for cultural heritage organizations, archaeology students, and universities involved in archaeological field surveys in Sistan and Baluchistan province. Additionally, it contributes to enhancing the understanding and preservation of Iran's archaeological heritage.

Keywords: archaeological surveys, computer use, iran, modern technologies, sistan

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Authors: Albert W. K. Tan

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This research consolidates a comprehensive array of publications from peer-reviewed journals, case studies, and seminar reports focused on reverse logistics and network design. By synthesizing this secondary knowledge, our objective is to identify and articulate key decision factors crucial to reverse logistics network design for e-commerce. Through this exploration, we aim to present a refined mathematical model that offers valuable insights for companies seeking to optimize their reverse logistics operations. The primary goal of this research endeavor is to develop a comprehensive framework tailored to advising organizations and companies on crafting effective networks for their reverse logistics operations, thereby facilitating the achievement of their organizational goals. This involves a thorough examination of various network configurations, weighing their advantages and disadvantages to ensure alignment with specific business objectives. The key objectives of this research include: (i) Identifying pivotal factors pertinent to network design decisions within the realm of reverse logistics across diverse supply chains. (ii) Formulating a structured framework designed to offer informed recommendations for sound network design decisions applicable to relevant industries and scenarios. (iii) Propose a mathematical model to optimize its reverse logistics network. A conceptual framework for designing a reverse logistics network has been developed through a combination of insights from the literature review and information gathered from company websites. This framework encompasses four key stages in the selection of reverse logistics operations modes: (1) Collection, (2) Sorting and testing, (3) Processing, and (4) Storage. Key factors to consider in reverse logistics network design: I) Centralized vs. decentralized processing: Centralized processing, a long-standing practice in reverse logistics, has recently gained greater attention from manufacturing companies. In this system, all products within the reverse logistics pipeline are brought to a central facility for sorting, processing, and subsequent shipment to their next destinations. Centralization offers the advantage of efficiently managing the reverse logistics flow, potentially leading to increased revenues from returned items. Moreover, it aids in determining the most appropriate reverse channel for handling returns. On the contrary, a decentralized system is more suitable when products are returned directly from consumers to retailers. In this scenario, individual sales outlets serve as gatekeepers for processing returns. Considerations encompass the product lifecycle, product value and cost, return volume, and the geographic distribution of returns. II) In-house vs. third-party logistics providers: The decision between insourcing and outsourcing in reverse logistics network design is pivotal. In insourcing, a company handles the entire reverse logistics process, including material reuse. In contrast, outsourcing involves third-party providers taking on various aspects of reverse logistics. Companies may choose outsourcing due to resource constraints or lack of expertise, with the extent of outsourcing varying based on factors such as personnel skills and cost considerations. Based on the conceptual framework, the authors have constructed a mathematical model that optimizes reverse logistics network design decisions. The model will consider key factors identified in the framework, such as transportation costs, facility capacities, and lead times. The authors have employed mixed LP to find the optimal solutions that minimize costs while meeting organizational objectives.

Keywords: reverse logistics, supply chain management, optimization, e-commerce

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Authors: Bahman Ghorashi

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The immense awareness of the global climate change has compelled traditional fossil fuel companies to develop strategies to reduce their carbon footprint and simultaneously consider the production of various sources of clean energy in order to mitigate the environmental impact of their operations. Similarly, supply chain issues, the scarcity of certain raw materials, energy costs as well as market needs, and changing consumer expectations have forced the traditional chemical industry to reexamine their time-honored modes of operation. This study examines how such transformative change might occur through the applications of agile principles as well as industry 4.0 technologies. Clearly, such a transformation is complex, costly, and requires a total commitment on the part of the top leadership and the entire management structure. Factors that need to be considered include organizational speed of change, a restructuring that would lend itself toward collaboration and the selling of solutions to customers’ problems, rather than just products, integrating ‘along’ as well as ‘across’ value chains, mastering change and uncertainty as well as a recognition of the importance of concept-to-cash time, i.e., the velocity of introducing new products to market, and the leveraging of people and information. At the same time, parallel to implementing such major shifts in the ethos, and the fabric of the organization, the change leaders should remain mindful of the companies’ DNA while incorporating the necessary DNA defying shifts. Furthermore, such strategic maneuvers should inevitably incorporate the managing of the upstream and downstream operations, harnessing future opportunities, preparing and training the workforce, implementing faster decision making and quick adaptation to change, managing accelerated response times, as well as forming autonomous and cross-functional teams. Moreover, the leaders should establish the balance between high-value solutions versus high-margin products, fully implement digitization of operations and, when appropriate, incorporate the latest relevant technologies, such as: AI, IIoT, ML, and immersive technologies. This study presents a summary of the agile principles and the relevant technologies and draws lessons from some of the best practices that are already implemented within the chemical industry in order to establish a roadmap to agility. Finally, the critical role of educational institutions in preparing the future workforce for Industry 4.0 is addressed.

Keywords: agile principles, immersive technologies, industry 4.0, workforce preparation

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Authors: Widhi Hanantyo Suryadinata

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Efforts undertaken by Indonesia and China to shift the strategies and security of renewable energy on a global stage involve approaches through policy construction related to rare minerals processing or value-adding in Indonesia and manufacturing policies through the New Energy Vehicles (NEVs) policy in China. Both policies encompass several practical regulations and policies that can be utilized for the implementation of Indonesia and China's grand efforts and ideas. Policy development in Indonesia and China can be analyzed using a comparative analysis method, as well as employing a pyramid illustration to identify policy construction phases based on the real conditions of the domestic market and implemented policies. This approach also helps to identify the potential integration of policies needed to enhance the policy development phase of a country within the pyramid. It also emphasizes the significance of integration policy to redefine renewable energy strategy and security on the global stage.

Keywords: global renewable energy security, global energy security, policy development, comparative analysis, shifting of global energy security, Indonesia, China

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Authors: Mohammed Agbali, Claudia Trillo, Yusuf Arayici, Terrence Fernando

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The wide-spread adoption of the Smart City concept has introduced a new era of computing paradigm with opportunities for city administrators and stakeholders in various sectors to re-think the concept of urbanization and development of healthy cities. With the world population rapidly becoming urban-centric especially amongst the emerging economies, social innovation will assist greatly in deploying emerging technologies to address the development challenges in core sectors of the future cities. In this context, sustainable health-care delivery and improved quality of life of the people is considered at the heart of the healthy city agenda. This paper examines the Boston innovation landscape from the perspective of smart services and innovation ecosystem for sustainable development, especially in transportation and healthcare. It investigates the policy implementation process of the Healthy City agenda and eHealth economy innovation based on the experience of Massachusetts’s City of Boston initiatives. For this purpose, three emerging areas are emphasized, namely the eHealth concept, the innovation hubs, and the emerging technologies that drive innovation. This was carried out through empirical analysis on results of public sector and industry-wide interviews/survey about Boston’s current initiatives and the enabling environment. The paper highlights few potential research directions for service integration and social innovation for deploying emerging technologies in the healthy city agenda. The study therefore suggests the need to prioritize social innovation as an overarching strategy to build sustainable Smart Cities in order to avoid technology lock-in. Finally, it concludes that the Boston example of innovation economy is unique in view of the existing platforms for innovation and proper understanding of its dynamics, which is imperative in building smart and healthy cities where quality of life of the citizenry can be improved.

Keywords: computing paradigm, emerging technologies, equitable healthcare, healthy cities, open data, smart city, social innovation

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Authors: Amir Jalalian-Khakshour, T. N. Croft

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Vertical Axis Wind Turbine (VAWT) systems are becoming increasingly popular as they have a number of advantages over traditional wind turbines. The advantages are reliability, ease of transportation and manufacturing. These attributes could make these technologies useful in developing economies. The performance characteristics of a VAWT are different from a horizontal axis wind turbine, which can be attributed to the low tip speed ratio operation. To unlock the potential of these VAWT systems, the operational behaviour in a number of system topologies and environmental conditions needs to be understood. In this study, a non-linear dynamic simulation method was developed in Matlab and validated against in field data of a large scale, 8-meter rotor diameter prototype. This simulation method has been utilised to determine the performance characteristics of a number of control methods and system topologies. The motivation for this research was to develop a simulation method which accurately captures the operating behaviour and is computationally inexpensive. The model was used to evaluate the performance through parametric studies and optimisation techniques. The study gave useful insights into the applications and energy generation potential of this technology.

Keywords: power generation, renewable energy, rotordynamics, wind energy

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Authors: Jonas Kahlert

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Blockchain technology has gained importance and momentum in the energy sector. Yet, there is no structured analysis of how specific features of the blockchain technology can create value in the energy sector. We employ a qualitative analysis on insights gained from the current literature and expert interviews. Along the four most prevalent use cases of blockchain technology in the energy sector, we discuss the potential of blockchain technology to support a transition to a more affordable, sustainable and reliable energy system. We show that in its current state, blockchain and adjacent technologies are not a necessity but a sufficiency towards this transition. We also show how current limitations of the blockchain and adjacent technologies can be even counterproductive. Finally, we discuss implications for policy makers and managers.

Keywords: blockchain technology, affordance theory, energy trilemma, sustainability

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Authors: V. Reyes, P. Ferreira

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In response to high levels of competitiveness, industrial systems have evolved to improve productivity. As a consequence, a rapid increase in volume production and simultaneously, a customization process require lower costs, more variety, and accurate quality of products. Reducing time-cycle production, enabling customizability, and ensure continuous quality improvement are key features in advance intelligent industry. In this scenario, customers and producers will be able to participate in the ongoing production life cycle through real-time interaction. To achieve this vision, transparency, predictability, and adaptability are key features that provide the industrial systems the capability to adapt to customer demands modifying the manufacturing process through an autonomous response and acting preventively to avoid errors. The industrial system incorporates a diversified number of components that in advanced industry are expected to be decentralized, end to end communicating, and with the capability to make own decisions through feedback. The evolving process towards advanced intelligent industry defines a set of stages to empower components of intelligence and enhancing efficiency to achieve the decision-making stage. The integrated system follows an industrial cyber-physical system (CPS) architecture whose real-time integration, based on a set of enabler technologies, links the physical and virtual world generating the digital twin (DT). This instance allows incorporating sensor data from real to virtual world and the required transparency for real-time monitoring and control, contributing to address important features of the advanced intelligent industry and simultaneously improve sustainability. Assuming the industrial CPS as the core technology toward the latest advanced intelligent industry stage, this paper reviews and highlights the correlation and contributions of the enabler technologies for the operationalization of each stage in the path toward advanced intelligent industry. From this research, a real-time integration architecture for a cyber-physical system with applications to collaborative robotics is proposed. The required functionalities and issues to endow the industrial system of adaptability are identified.

Keywords: cyber-physical systems, digital twin, sensor data, system integration, virtual model

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Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

Procedia PDF Downloads 102

Authors: M. Nadeem, Y. K. Chang, C. Diallo, U. Venkatadri, P. Havard, T. Nguyen-Quang

Abstract:

Uniform distribution of agro-chemicals is highly important because there is a significant loss of agro-chemicals, for example from pesticide, during spraying due to non-uniformity of droplet and off-target drift. Improving the efficiency of spray pattern for different cropping systems would reduce energy, costs and to minimize environmental pollution. In this paper, we examine the water jet patterns in order to study the performance and uniformity of water distribution during the spraying process. We present a method to quantify the water amount from a sprayer jet by using the Particle Image Velocimetry (PIV) system. The results of the study will be used to optimize sprayer or nozzles design for chemical application. For this study, ten sets of images were acquired by using the following PIV system settings: double frame mode, trigger rate is 4 Hz, and time between pulsed signals is 500 µs. Each set of images contained different numbers of double-framed images: 10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 at eight different pressures 25, 50, 75, 100, 125, 150, 175 and 200 kPa. The PIV images obtained were analysed using custom-made image processing software for droplets and volume calculations. The results showed good agreement of both manual and PIV measurements and suggested that the PIV technique coupled with image processing can be used for a precise quantification of flow through nozzles. The results also revealed that the method of measuring fluid flow through PIV is reliable and accurate for sprayer patterns.

Keywords: image processing, PIV, quantifying the water volume from nozzle, spraying pattern

Procedia PDF Downloads 229

Authors: Mohamad Alnajem

Abstract:

Purpose: To measure the readiness of the Kuwaiti small and medium sized manufacturing industries (K-SMMIs) to implement the lean system (LS) through an evaluation of their existing quality practices, and compare such readiness among different product sectors and ownership types. Design/methodology/approach: This study adopts the measurement framework developed by Al-Najem et al. (2013), which establishes six constructs related to lean quality practices, namely: process, planning and control, customer relations, suppliers relations, HR, and top management and leadership. Data were collected from a survey of 50 K-SMMIs operating in different industrial sectors. One research question and two hypotheses were developed and tested using t-test and Levene’s test, descriptive analysis, and one-way ANOVA. Findings: The results demonstrate that the K-SMMIs are far from being ready to implement lean. In addition, the study found that product sector and ownership type have no significant impact on the lean readiness in the K-SMMIs. Practical implications: This research provides insight into preparing Kuwaiti, and other SMMIs, to implement the LS by creating an assessment of their existing lean practices and readiness. Originality/value: This research is among a limited number of studies that have addressed lean within the Arab region, and only the second to examine the level of lean readiness of the K-SMMIs. It expands the literature on lean in developing countries, particularly in the Arab region, and can provide guidance to research within other countries in the region.

Keywords: Kuwaiti small and medium sized industries, lean system, lean readiness, manufacturing industries

Procedia PDF Downloads 191

Authors: U. Borasi, Amit Kr. Jain, Rakesh, Piyush Jain

Abstract:

Data collection, data preparation, model training, model evaluation, and deployment are all processes in a typical machine learning workflow. Training data needs to be gathered and organised. This often entails collecting a sizable dataset and cleaning it to remove or correct any inaccurate or missing information. Preparing the data for use in the machine learning model requires pre-processing it after it has been acquired. This often entails actions like scaling or normalising the data, handling outliers, selecting appropriate features, reducing dimensionality, etc. This pre-processed data is then used to train a model on some machine learning algorithm. After the model has been trained, it needs to be assessed by determining metrics like accuracy, precision, and recall, utilising a test dataset. Every time a new model is built, both data pre-processing and model training—two crucial processes in the Machine learning (ML) workflow—must be carried out. Thus, there are various Machine Learning algorithms that can be employed for every single approach to data pre-processing, generating a large set of combinations to choose from. Example: for every method to handle missing values (dropping records, replacing with mean, etc.), for every scaling technique, and for every combination of features selected, a different algorithm can be used. As a result, in order to get the optimum outcomes, these tasks are frequently repeated in different combinations. This paper suggests a simple architecture for organizing this largely produced “combination set of pre-processing steps and algorithms” into an automated workflow which simplifies the task of carrying out all possibilities.

Keywords: machine learning, automation, AUTOML, architecture, operator pool, configuration, scheduler

Procedia PDF Downloads 51

Authors: Leila Jafari, Viliam Makis

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In this paper, the joint optimization of the economic manufacturing quantity (EMQ), safety stock level, and condition-based maintenance (CBM) is presented for a partially observable, deteriorating system subject to random failure. The demand is stochastic and it is described by a Poisson process. The stochastic model is developed and the optimization problem is formulated in the semi-Markov decision process framework. A modification of the policy iteration algorithm is developed to find the optimal policy. A numerical example is presented to compare the optimal policy with the policy considering zero safety stock.

Keywords: condition-based maintenance, economic manufacturing quantity, safety stock, stochastic demand

Procedia PDF Downloads 459

Authors: Daniel Li

Abstract:

We present a novel application of neural rendering methods to confocal microscopy. Neural rendering and implicit neural representations have developed at a remarkable pace, and are prevalent in modern 3D computer vision literature. However, they have not yet been applied to optical microscopy, an important imaging field where 3D volume information may be heavily sought after. In this paper, we employ neural rendering on confocal microscopy focus stack data and share the results. We highlight the benefits and potential of adding neural rendering to the toolkit of microscopy image processing techniques.

Keywords: neural rendering, implicit neural representations, confocal microscopy, medical image processing

Procedia PDF Downloads 650

Authors: Jiwon Lee, Chanho Jung, Si-Hwan Jang, Kyung-Ill Kim, Sanghyun Joo, Wook-Ho Son

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Since the advances in digital imaging technologies have led to development of high quality digital devices, there are a lot of illegal copies of copyrighted video content on the internet. Thus, we propose a high-quality (HQ) video watermarking scheme that can prevent these illegal copies from spreading out. The proposed scheme is applied spatial and temporal gradient methods to improve the fidelity and detection performance. Also, the scheme duplicates the watermark signal temporally to alleviate the signal reduction caused by geometric and signal-processing distortions. Experimental results show that the proposed scheme achieves better performance than previously proposed schemes and it has high fidelity. The proposed scheme can be used in broadcast monitoring or traitor tracking applications which need fast detection process to prevent illegally recorded video content from spreading out.

Keywords: editing prevention technique, gradient method, luminance change, video watermarking

Procedia PDF Downloads 452