Search results for: Croatian industries
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1916

Search results for: Croatian industries

1466 Integrating Historical Narratives with Merge Games as Tools for Pedagogy In Education

Authors: Aathira H.

Abstract:

Digital games can act as catalysts for educational transformation in the current scenario. Children and adolescence acquire this digital knowledge quickly and hence digital games can act as one of the most effective media for technology-mediated learning. Mobile gaming industries have seen the rise of a new trending genre of games, i.e., “Merge games” which is currently thriving in the market. This paper analysis on how gamifying historic and cultural narratives with merge mechanics can be an effective way to educate school children. Through the study of how merge mechanics in games have currently emerged as a trend., this paper argues how it can be integrated with a strong narrative which can convey history in an engaging way for education.

Keywords: game-based learning, merge mechanics, historical narratives, gaming innovations

Procedia PDF Downloads 104
1465 The Use of Cement Dust in the Glass Industry

Authors: Magda Kosmal, Anna A. Kuśnierz, Joanna Rybicka-Łada

Abstract:

In the case of waste glass cullet, a fully functioning recycling system for individual glass industries was developed, while recycling of cement dust encounters a number of difficulties and is conducted to a limited extent in the packaging and flat glass industry. The aim of the project was to examine the possibility of using dust arising in cement plants in the process of melting various types of glasses. Dust management has a positive effect on the aspect of environmental protection and ecology. Sets have been designed, and the parameters of the melting process have been optimized. Glasses were obtained with the addition of selected cement dust on a laboratory scale, using DTA, XRD, SEM tests, and a gradient furnace was conducted to check the tendency to crystallization.

Keywords: cement dust, crystallization, glass, XRD, SEM

Procedia PDF Downloads 85
1464 Purification of Bacillus Lipopeptides for Diverse Applications

Authors: Vivek Rangarajan, Kim G. Clarke

Abstract:

Bacillus lipopeptides are biosurfactants with wide ranging applications in the medical, food, agricultural, environmental and cosmetic industries. They are produced as a mix of three families, surfactin, iturin and fengycin, each comprising a large number of homologues of varying functionalities. Consequently, the method and degree of purification of the lipopeptide cocktail becomes particularly important if the functionality of the lipopeptide end-product is to be maximized for the specific application. However, downstream processing of Bacillus lipopeptides is particularly challenging due to the subtle variations observed in the different lipopeptide homologues and isoforms. To date, the most frequently used lipopeptide purification operations have been acid precipitation, solvent extraction, membrane ultrafiltration, adsorption and size exclusion. RP-HPLC (reverse phase high pressure liquid chromatography) also has potential for fractionation of the lipopeptide homologues. In the studies presented here, membrane ultrafiltration and RP-HPLC were evaluated for lipopeptide purification to different degrees of purities for maximum functionality. Batch membrane ultrafiltration using 50 kDa polyether sulphone (PES) membranes resulted in lipopeptide recovery of about 68% for surfactin and 82 % for fengycin. The recovery was further improved to 95% by using size-conditioned lipopeptide micelles. The conditioning of lipopeptides with Ca2+ ions resulted in uniformly sized micelles with average size of 96.4 nm and a polydispersity index of 0.18. The size conditioning also facilitated removal of impurities (molecular weight ranging between 2335-3500 Da) through operation of the system under dia-filtration mode, in a way similar to salt removal from protein by dialysis. The resultant purified lipopeptide was devoid of macromolecular impurities and could ideally suit applications in the cosmetic and food industries. Enhanced purification using RP-HPLC was carried out in an analytical C18 column, with the aim to fractionate lipopeptides into their constituent homologues. The column was eluted with mobile phase comprising acetonitrile and water over an acetonitrile gradient, 35% - 80%, over 70 minutes. The gradient elution program resulted in as many as 41 fractions of individual lipopeptide homologues. The efficacy test of these fractions against fungal phytopathogens showed that first 21 fractions, identified to be homologues of iturins and fengycins, displayed maximum antifungal activities, suitable for biocontrol in the agricultural industry. Thus, in the current study, the downstream processing of lipopeptides leading to tailor-made products for selective applications was demonstrated using two major downstream unit operations.

Keywords: bacillus lipopeptides, membrane ultrafiltration, purification, RP-HPLC

Procedia PDF Downloads 205
1463 Corporate Female Entrepreneurship, Moving Boundaries

Authors: Morena Paulisic, Marli Gonan Bozac

Abstract:

Business organization and management in theory are typically presented as gender- neutral. Although in practice female contribution to corporation is not questionable, gender diversity in top management of corporation is and that especially in emerging countries like Croatia. This paper brings insights into obstacles and problems which should be overcome. Furthermore, gives an introspective view on the most important promotion and motivation factors of powerful female CEOs in Croatia. The goal was to clarify perception and performance of female CEOs that contributed to their success and to determine mutual characteristics of women in corporate entrepreneurship regarding the motivation. For our study we used survey instrument that was developed for this research. The research methods used were: table research, field research, generalization method, comparative method, and statistical method (descriptive statistics and Pearson’s Chi-square test). Some result showed us that today even more women in corporations are not likely to accept more engagement at work if it harms their families (2003 – 31.9% in 2013 – 33.8%) although their main motivating factor is still interested job (2003 – 95.8%; in 2013-100%). It is also significant that 78.8 % of Croatian top managers (2013) think that women managers in Croatia are insufficiently spoken and written about, and that the reasons for this are that: (1) the society underestimates their ability (37.9%); (2) women underestimate themselves (22.4%); (3) the society still mainly focuses on male managers (20.7%) and (4) women managers avoid interviews and appearing on front pages (19%). The environment still “blocks” the natural course of advancement of women managers in organisations (entrepreneurship in general) and the main obstacle is that women must always or almost always be more capable than men in order to succeed (96.6%). Based on survey results on longitudinal research conducted in 2003 (return rate 30,8%) and 2013 (return rate 29,2%) in Croatia we expand understanding of determination indicators of corporate female entrepreneurship. Theoretically in practice gender structure at the management level (executive management, management board and supervisory board) throw years (2011- 2014) have positive score but still women remain significantly underrepresented at those positions. Findings from different sources have shown that diversity at the top of corporations’ correlates with better performance. In this paper, we have contributed to research on gender in corporate entrepreneurship by offering experiences from successful female CEOs and explanation why in social responsible society women with their characteristics can support needed changes and construct different way forward for corporations. Based on research result we can conclude that in future underrepresentation of female in corporate entrepreneurship should be overcome.

Keywords: Croatia, female entrepreneurship, glass ceiling, motivation

Procedia PDF Downloads 330
1462 Bamboo Fibre Extraction and Its Reinforced Polymer Composite Material

Authors: P. Zakikhani, R. Zahari, M. T. H. Sultan, D. L. Majid

Abstract:

Natural plant fibres reinforced polymeric composite materials have been used in many fields of our lives to save the environment. Especially, bamboo fibres due to its environmental sustainability, mechanical properties, and recyclability have been utilized as reinforced polymer matrix composite in construction industries. In this review study bamboo structure and three different methods such as mechanical, chemical and combination of mechanical and chemical to extract fibres from bamboo are summarized. Each extraction method has been done base on the application of bamboo. In addition Bamboo fibre is compared with glass fibre from various aspects and in some parts it has advantages over the glass fibre.

Keywords: bamboo fibres, natural fibres, bio composite, mechanical extraction, glass fibres

Procedia PDF Downloads 490
1461 UAV Based Visual Object Tracking

Authors: Vaibhav Dalmia, Manoj Phirke, Renith G

Abstract:

With the wide adoption of UAVs (unmanned aerial vehicles) in various industries by the government as well as private corporations for solving computer vision tasks it’s necessary that their potential is analyzed completely. Recent advances in Deep Learning have also left us with a plethora of algorithms to solve different computer vision tasks. This study provides a comprehensive survey on solving the Visual Object Tracking problem and explains the tradeoffs involved in building a real-time yet reasonably accurate object tracking system for UAVs by looking at existing methods and evaluating them on the aerial datasets. Finally, the best trackers suitable for UAV-based applications are provided.

Keywords: deep learning, drones, single object tracking, visual object tracking, UAVs

Procedia PDF Downloads 159
1460 An Approximation Algorithm for the Non Orthogonal Cutting Problem

Authors: R. Ouafi, F. Ouafi

Abstract:

We study the problem of cutting a rectangular material entity into smaller sub-entities of trapezoidal forms with minimum waste of the material. This problem will be denoted TCP (Trapezoidal Cutting Problem). The TCP has many applications in manufacturing processes of various industries: pipe line design (petro chemistry), the design of airfoil (aeronautical) or cuts of the components of textile products. We introduce an orthogonal build to provide the optimal horizontal and vertical homogeneous strips. In this paper we develop a general heuristic search based upon orthogonal build. By solving two one-dimensional knapsack problems, we combine the horizontal and vertical homogeneous strips to give a non orthogonal cutting pattern.

Keywords: combinatorial optimization, cutting problem, heuristic

Procedia PDF Downloads 541
1459 Exploitation behind the Development of Home Batik Industry in Lawean, Solo, Central Java

Authors: Mukhammad Fatkhullah, Ayla Karina Budita, Cut Rizka Al Usrah, Kanita Khoirun Nisa, Muhammad Alhada Fuadilah Habib, Siti Muslihatul Mukaromah

Abstract:

Batik industry has become one of the leading industries in the economy of Indonesia. Since the recognition of batik as one of cultural wealth and national identity of Indonesia by UNESCO, batik production keeps increasing as a result of increasing demands for batik, whether from domestically or abroad. One of the rapid development batik industries in Indonesia is batik industry in Lawean Village, Solo, Central Java, Indonesia. This batik industry generally uses putting-out system where batik workers work in their own houses. With the implementation of this system, therefore employers don’t have to prepare Environmental Impact Analysis (EIA), social security for workers, overtime payment, space for working, and equipment for working. The implementation of putting-out system causes many problems, starting from environmental pollution, the loss of social rights of workers, and even exploitation of workers by batik entrepreneurs. The data used to describe this reality is the primary data from qualitative research with in-depth interview data collection technique. Informants were determined purposively. The theory used to perform data interpretation is the phenomenology of Alfred Schutz. Both qualitative and phenomenology are used in this study to describe batik workers exploitation in terms of the implementation of putting-out system on home batik industry in Lawean. The research result showed that workers in batik industry sector in Lawean were exploited with the implementation of putting-out system. The workers were strictly employed by the entrepreneurs, so that their job cannot be called 'part-time' job anymore. In terms of labor and time, the workers often work more than 12 hours per day and they often work overtime without receiving any overtime payment. In terms of work safety, the workers often have contact with chemical substances contained in batik making materials without using any protection, such as clothes work, which is worsened by the lack of standard or procedure in work that can cause physical damage, such as burnt and peeled off skin. Moreover, exposure and contamination of chemical materials make the workers and their families vulnerable to various diseases. Meanwhile, batik entrepreneurs did not give any social security (including health cost aid). Besides that, the researchers found that batik industry in home industry sector is not environmentally friendly, even damaging ecosystem because industrial waste disposed without EIA.

Keywords: exploitation, home batik industry, occupational health and safety, putting-out system

Procedia PDF Downloads 317
1458 Information Technologies in Automotive Assembly Industry in Thailand

Authors: Jirarat Teeravaraprug, Usawadee Inklay

Abstract:

This paper gave an attempt in prioritizing information technologies that organizations should give concentration. The case study was organizations in the automotive assembly industry in Thailand. Data were first collected to gather all information technologies known and used in the automotive assembly industry in Thailand. Five experts from the industries were surveyed based on the concept of fuzzy DEMATEL. The information technologies were categorized into six groups, which were communication, transaction, planning, organization management, warehouse management, and transportation. The cause groups of information technologies for each group were analysed and presented. Moreover, the relationship between the used and the significant information technologies was given. Discussions based on the used information technologies and the research results are given.

Keywords: information technology, automotive assembly industry, fuzzy DEMATEL

Procedia PDF Downloads 346
1457 On the Resilience of Operational Technology Devices in Penetration Tests

Authors: Marko Schuba, Florian Kessels, Niklas Reitz

Abstract:

Operational technology (OT) controls physical processes in critical infrastructures and economically important industries. With the convergence of OT with classical information technology (IT), rising cybercrime worldwide and the increasingly difficult geopolitical situation, the risks of OT infrastructures being attacked are growing. Classical penetration testing, in which testers take on the role of an attacker, has so far found little acceptance in the OT sector - the risk that a penetration test could do more harm than good seems too great. This paper examines the resilience of various OT systems using typical penetration test tools. It is shown that such a test certainly involves risks, but is also feasible in OT if a cautious approach is taken. Therefore, OT penetration testing should be considered as a tool to improve the cyber security of critical infrastructures.

Keywords: penetration testing, OT, ICS, OT security

Procedia PDF Downloads 16
1456 CO2 Emissions Quantification of the Modular Bridge Superstructure

Authors: Chanhyuck Jeon, Jongho Park, Jinwoong Choi, Sungnam Hong, Sun-Kyu Park

Abstract:

Many industries put emphasis on environmentally-friendliness as environmental problems are on the rise all over the world. Among themselves, the Modular Bridge research is going on. Also performing cross-section optimization and duration reducing, this research aims at developing the modular bridge with Environment-Friendliness and economic feasibility. However, the difficulty lies in verifying environmental effectiveness because there are no field applications of the modular bridge until now. Therefore, this thesis is categorized according to the form of the modular bridge superstructure and assessed CO₂ emission quantification per work types and materials according to each form to verify the environmental effectiveness of the modular bridge.

Keywords: modular bridge, CO2 emission, environmentally friendly, quantification, carbon emission factor, LCA (Life Cycle Assessment)

Procedia PDF Downloads 555
1455 Energy Efficiency Measures in Canada’s Iron and Steel Industry

Authors: A. Talaei, M. Ahiduzzaman, A. Kumar

Abstract:

In Canada, an increase in the production of iron and steel is anticipated for satisfying the increasing demand of iron and steel in the oil sands and automobile industries. It is predicted that GHG emissions from iron and steel sector will show a continuous increase till 2030 and, with emissions of 20 million tonnes of carbon dioxide equivalent, the sector will account for more than 2% of total national GHG emissions, or 12% of industrial emissions (i.e. 25% increase from 2010 levels). Therefore, there is an urgent need to improve the energy intensity and to implement energy efficiency measures in the industry to reduce the GHG footprint. This paper analyzes the current energy consumption in the Canadian iron and steel industries and identifies energy efficiency opportunities to improve the energy intensity and mitigate greenhouse gas emissions from this industry. In order to do this, a demand tree is developed representing different iron and steel production routs and the technologies within each rout. The main energy consumer within the industry is found to be flared heaters accounting for 81% of overall energy consumption followed by motor system and steam generation each accounting for 7% of total energy consumption. Eighteen different energy efficiency measures are identified which will help the efficiency improvement in various subsector of the industry. In the sintering process, heat recovery from coolers provides a high potential for energy saving and can be integrated in both new and existing plants. Coke dry quenching (CDQ) has the same advantages. Within the blast furnace iron-making process, injection of large amounts of coal in the furnace appears to be more effective than any other option in this category. In addition, because coal-powered electricity is being phased out in Ontario (where the majority of iron and steel plants are located) there will be surplus coal that could be used in iron and steel plants. In the steel-making processes, the recovery of Basic Oxygen Furnace (BOF) gas and scrap preheating provides considerable potential for energy savings in BOF and Electric Arc Furnace (EAF) steel-making processes, respectively. However, despite the energy savings potential, the BOF gas recovery is not applicable in existing plants using steam recovery processes. Given that the share of EAF in steel production is expected to increase the application potential of the technology will be limited. On the other hand, the long lifetime of the technology and the expected capacity increase of EAF makes scrap preheating a justified energy saving option. This paper would present the results of the assessment of the above mentioned options in terms of the costs and GHG mitigation potential.

Keywords: Iron and Steel Sectors, Energy Efficiency Improvement, Blast Furnace Iron-making Process, GHG Mitigation

Procedia PDF Downloads 396
1454 Analysing Competitive Advantage of IoT and Data Analytics in Smart City Context

Authors: Petra Hofmann, Dana Koniel, Jussi Luukkanen, Walter Nieminen, Lea Hannola, Ilkka Donoghue

Abstract:

The Covid-19 pandemic forced people to isolate and become physically less connected. The pandemic has not only reshaped people’s behaviours and needs but also accelerated digital transformation (DT). DT of cities has become an imperative with the outlook of converting them into smart cities in the future. Embedding digital infrastructure and smart city initiatives as part of normal design, construction, and operation of cities provides a unique opportunity to improve the connection between people. The Internet of Things (IoT) is an emerging technology and one of the drivers in DT. It has disrupted many industries by introducing different services and business models, and IoT solutions are being applied in multiple fields, including smart cities. As IoT and data are fundamentally linked together, IoT solutions can only create value if the data generated by the IoT devices is analysed properly. Extracting relevant conclusions and actionable insights by using established techniques, data analytics contributes significantly to the growth and success of IoT applications and investments. Companies must grasp DT and be prepared to redesign their offerings and business models to remain competitive in today’s marketplace. As there are many IoT solutions available today, the amount of data is tremendous. The challenge for companies is to understand what solutions to focus on and how to prioritise and which data to differentiate from the competition. This paper explains how IoT and data analytics can impact competitive advantage and how companies should approach IoT and data analytics to translate them into concrete offerings and solutions in the smart city context. The study was carried out as a qualitative, literature-based research. A case study is provided to validate the preservation of company’s competitive advantage through smart city solutions. The results of the research contribution provide insights into the different factors and considerations related to creating competitive advantage through IoT and data analytics deployment in the smart city context. Furthermore, this paper proposes a framework that merges the factors and considerations with examples of offerings and solutions in smart cities. The data collected through IoT devices, and the intelligent use of it, can create competitive advantage to companies operating in smart city business. Companies should take into consideration the five forces of competition that shape industries and pay attention to the technological, organisational, and external contexts which define factors for consideration of competitive advantages in the field of IoT and data analytics. Companies that can utilise these key assets in their businesses will most likely conquer the markets and have a strong foothold in the smart city business.

Keywords: data analytics, smart cities, competitive advantage, internet of things

Procedia PDF Downloads 133
1453 Factors Influencing the Adoption of Interpersonal Communication Media to Maximize Business Competitiveness among Small and Medium Enterprises in Hong Kong: Industry Types and Entrepreneur Characteristics

Authors: Olivine Lo

Abstract:

Small- and Medium-Sized Enterprises (SMEs) consist of a broad variety of businesses, ranging from small grocery shops to manufacturing concerns. Some are dynamic and innovative, while others are more traditional. The definition of SMEs varies by country but is most determined by the number of employees, though business assets and sales revenues are alternative measures. There are eight main types of SME industries in Hong Kong: garment, electronics, plastics, metal and machinery, trading and logistics, building, manufacturing, and service industries. Information exchange is a key goal of human communication, and communicators have used a variety of media to maintain relationships through traditional face-to-face interactions and written forms like letters and faxes. With the advancement of mediated-interpersonal communication media from telephone to synchronic online tools like email, instant messaging, voice messaging, and video conferencing for sustaining relationships, particularly enabling geographically distanced relationships. Although these synchronous tools are gaining popularity, they are facilitating relationship maintenance in everyday life and complementing rather than replacing the more conventional face-to-face interactions. This study will test if there are any variances in effects by industry type among Hong Kong SMEs. The competitiveness of the business environment refers to the competition faced by a business within its particular industry. The more intense the competition in a given sector, the greater the potential for strategic uses of specific needs in a business. Both internal organization characteristics and external environments may affect firm performance and financial resources. The level of competitiveness within an industry will be a more reliable indicator to show how Hong Kong SMEs are striving to achieve their business goals using different techniques in their communication media preferences, rather than mere classification by industry type. This study thus divides the competitiveness of the business environment into internal and external: (1) the internal environment competition is the inherent competitiveness of the products or services provided by the SMEs, whereas (2) the external environment competition includes the economic and political realities and competitors joining the market. This study will test various organizational characteristics and competitiveness of the business environment to predict entrepreneurs’ communication media preferences.

Keywords: competitiveness of business environment, small- and medium-sized enterprises, organizational characteristics, communication media preference

Procedia PDF Downloads 30
1452 The Synergistic Effects of Blockchain and AI on Enhancing Data Integrity and Decision-Making Accuracy in Smart Contracts

Authors: Sayor Ajfar Aaron, Sajjat Hossain Abir, Ashif Newaz, Mushfiqur Rahman

Abstract:

Investigating the convergence of blockchain technology and artificial intelligence, this paper examines their synergistic effects on data integrity and decision-making within smart contracts. By implementing AI-driven analytics on blockchain-based platforms, the research identifies improvements in automated contract enforcement and decision accuracy. The paper presents a framework that leverages AI to enhance transparency and trust while blockchain ensures immutable record-keeping, culminating in significantly optimized operational efficiencies in various industries.

Keywords: artificial intelligence, blockchain, data integrity, smart contracts

Procedia PDF Downloads 55
1451 Internal and External Influences on the Firm Objective

Authors: A. Briseno, A, Zorrilla

Abstract:

Firms are increasingly responding to social and environmental claims from society. Practices oriented to attend issues such as poverty, work equality, or renewable energy, are being implemented more frequently by firms to address impacts on sustainability. However, questions remain on how the responses of firms vary across industries and regions between the social and the economic objectives. Using concepts from organizational theory and social network theory, this paper aims to create a theoretical framework that explains the internal and external influences that make a firm establish its objective. The framework explains why firms might have a different objective orientation in terms of its economic and social prioritization.

Keywords: organizational identity, social network theory, firm objective, value maximization, social responsibility

Procedia PDF Downloads 308
1450 Social Networks as a Tool for Sports Marketing

Authors: Márcia Aparecida Teixeira

Abstract:

Sports, in particular football, boosts considerably the financial market of a certain locality, be it city or even a country. The financial transactions involving this medium stand out from other existing businesses, such as small industries. Strategically, social networks are inserted in this sporting environment, in order to promote and attract new fans of this modality. The present study analyzes the use of social networks in Sports Marketing with a focus on football. For the object of this study, it was chosen a specific club, the Club Atlético Mineiro, a Brazilian club of great national notoriety. The social networks on focus will be: Facebook, Twitter, and Instagram. It will be analyzed the content and frequency of the posts, reception of the target public in relation to the content made available and its feedback.

Keywords: social network, sport, strategy, marketing

Procedia PDF Downloads 388
1449 Analyzing Competitive Advantage of Internet of Things and Data Analytics in Smart City Context

Authors: Petra Hofmann, Dana Koniel, Jussi Luukkanen, Walter Nieminen, Lea Hannola, Ilkka Donoghue

Abstract:

The Covid-19 pandemic forced people to isolate and become physically less connected. The pandemic hasnot only reshaped people’s behaviours and needs but also accelerated digital transformation (DT). DT of cities has become an imperative with the outlook of converting them into smart cities in the future. Embedding digital infrastructure and smart city initiatives as part of the normal design, construction, and operation of cities provides a unique opportunity to improve connection between people. Internet of Things (IoT) is an emerging technology and one of the drivers in DT. It has disrupted many industries by introducing different services and business models, and IoT solutions are being applied in multiple fields, including smart cities. As IoT and data are fundamentally linked together, IoT solutions can only create value if the data generated by the IoT devices is analysed properly. Extracting relevant conclusions and actionable insights by using established techniques, data analytics contributes significantly to the growth and success of IoT applications and investments. Companies must grasp DT and be prepared to redesign their offerings and business models to remain competitive in today’s marketplace. As there are many IoT solutions available today, the amount of data is tremendous. The challenge for companies is to understand what solutions to focus on and how to prioritise and which data to differentiate from the competition. This paper explains how IoT and data analytics can impact competitive advantage and how companies should approach IoT and data analytics to translate them into concrete offerings and solutions in the smart city context. The study was carried out as a qualitative, literature-based research. A case study is provided to validate the preservation of company’s competitive advantage through smart city solutions. The results of the researchcontribution provide insights into the different factors and considerations related to creating competitive advantage through IoT and data analytics deployment in the smart city context. Furthermore, this paper proposes a framework that merges the factors and considerations with examples of offerings and solutions in smart cities. The data collected through IoT devices, and the intelligent use of it, can create a competitive advantage to companies operating in smart city business. Companies should take into consideration the five forces of competition that shape industries and pay attention to the technological, organisational, and external contexts which define factors for consideration of competitive advantages in the field of IoT and data analytics. Companies that can utilise these key assets in their businesses will most likely conquer the markets and have a strong foothold in the smart city business.

Keywords: internet of things, data analytics, smart cities, competitive advantage

Procedia PDF Downloads 94
1448 Hybrid Model: An Integration of Machine Learning with Traditional Scorecards

Authors: Golnush Masghati-Amoli, Paul Chin

Abstract:

Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

Procedia PDF Downloads 134
1447 Comparing Two Non-Contact Squeeze Film Levitation Designs

Authors: Ahmed Almurshedi, Mark Atherton, Mares Cristinel, Tadeusz Stolarski, Masaaki Miyatake

Abstract:

Transportation and handling of delicate and lightweight objects is a significant issue in some industries. Two levitation prototype designs, a horn transducer design and surface-mounted piezoelectric actuator vibrating plate design, are compared. Both designs are based on the method of squeeze-film levitation (SFL) and the aim of this study is to evaluate the characteristics and performance of each. To this end, physical experiments are conducted and are demonstrated that the horn-type transducer prototype design produces better levitation performance but it design complexity and operating characteristics make it less suitable than the vibrating plate design for practical applications.

Keywords: floating, levitation, piezoelectric, squeeze-film, transducer

Procedia PDF Downloads 279
1446 Development of Intelligent Smart Multi Tracking Agent System to Support of Logistics Safety

Authors: Umarov Jamshid, Ju-Su Kim, Hak-Jun Lee, Man-Kyo Han, Ryum-Duck Oh

Abstract:

Recently, it becomes convenient to identify the location information of cargos by using GPS and wireless communication technologies. The development of IoT technologies and tracking system allows us to confirm site situation on an ad hoc basis in all the industries and social environments. Moreover, it allows us to apply IT technologies to a manageable extent. However, there have been many limitations for using the system due to the difficulty of identifying location information in real time and also due to the simple features. To globalize the logistics related tracking system, it is required to conduct a study to resolve the aforementioned problem. On that account, this paper designed and developed the IoT and RTLS based intelligent multi tracking agent system for more secure, accurate and reliable transportation in relation to logistics.

Keywords: GPS, tracking agent system, IoT, RTLS, Logistics

Procedia PDF Downloads 646
1445 The Cracks Propagation Monitoring of a Cantilever Beam Using Modal Analysis

Authors: Morteza Raki, Abolghasem Zabihollah, Omid Askari

Abstract:

Cantilever beam is a simplified sample of a lot of mechanical components used in a wide range of applications, including many industries such as gas turbine blade. Due to the nature of the operating conditions, beams are subject to variety of damages especially crack propagates. Crack propagation may lead to catastrophic failure during operation. Therefore, online detection of crack presence and its propagation is very important and may reduce possible significant cost of the whole system failure. This paper aims to investigate the effect of cracks presence and crack propagation on one end fixed beam`s vibration. A finite element model will be developed for the blade in which the modal response of the structure with and without crack will be studied. 

Keywords: blade, crack propagation, health monitoring, modal analysis

Procedia PDF Downloads 344
1444 Friction Stir Welding of Aluminum Alloys: A Review

Authors: S. K. Tiwari, Dinesh Kumar Shukla, R. Chandra

Abstract:

Friction stir welding is a solid state joining process. High strength aluminum alloys are widely used in aircraft and marine industries. Generally, the mechanical properties of fusion-welded aluminum joints are poor. As friction stir welding occurs in the solid state, no solidification structures are created thereby eliminating the brittle and eutectic phases common in fusion welding of high strength aluminum alloys. In this review, the process parameters, microstructural evolution and effect of friction stir welding on the properties of weld specific to aluminum alloys have been discussed.

Keywords: aluminum alloys, friction stir welding (FSW), microstructure, Properties.

Procedia PDF Downloads 418
1443 Process Capability Analysis by Using Statistical Process Control of Rice Polished Cylinder Turning Practice

Authors: S. Bangphan, P. Bangphan, T.Boonkang

Abstract:

Quality control helps industries in improvements of its product quality and productivity. Statistical Process Control (SPC) is one of the tools to control the quality of products that turning practice in bringing a department of industrial engineering process under control. In this research, the process control of a turning manufactured at workshops machines. The varying measurements have been recorded for a number of samples of a rice polished cylinder obtained from a number of trials with the turning practice. SPC technique has been adopted by the process is finally brought under control and process capability is improved.

Keywords: rice polished cylinder, statistical process control, control charts, process capability

Procedia PDF Downloads 489
1442 Designing AI-Enabled Smart Maintenance Scheduler: Enhancing Object Reliability through Automated Management

Authors: Arun Prasad Jaganathan

Abstract:

In today's rapidly evolving technological landscape, the need for efficient and proactive maintenance management solutions has become increasingly evident across various industries. Traditional approaches often suffer from drawbacks such as reactive strategies, leading to potential downtime, increased costs, and decreased operational efficiency. In response to these challenges, this paper proposes an AI-enabled approach to object-based maintenance management aimed at enhancing reliability and efficiency. The paper contributes to the growing body of research on AI-driven maintenance management systems, highlighting the transformative impact of intelligent technologies on enhancing object reliability and operational efficiency.

Keywords: AI, machine learning, predictive maintenance, object-based maintenance, expert team scheduling

Procedia PDF Downloads 58
1441 Genetic Algorithm for Solving the Flexible Job-Shop Scheduling Problem

Authors: Guilherme Baldo Carlos

Abstract:

The flexible job-shop scheduling problem (FJSP) is an NP-hard combinatorial optimization problem, which can be applied to model several applications in a wide array of industries. This problem will have its importance increase due to the shift in the production mode that modern society is going through. The demands are increasing and for products personalized and customized. This work aims to apply a meta-heuristic called a genetic algorithm (GA) to solve this problem. A GA is a meta-heuristic inspired by the natural selection of Charles Darwin; it produces a population of individuals (solutions) and selects, mutates, and mates the individuals through generations in order to find a good solution for the problem. The results found indicate that the GA is suitable for FJSP solving.

Keywords: genetic algorithm, evolutionary algorithm, scheduling, flexible job-shop scheduling

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1440 An Application of a Feedback Control System to Minimize Unforeseen Disruption in a Paper Manufacturing Industry in South Africa

Authors: Martha E. Ndeley

Abstract:

Operation management is the key element within the manufacturing process. However, during this process, there are a number of unforeseen disruptions that causes the process to a standstill which are, machine breakdown, employees absenteeism, improper scheduling. When this happens, it forces the shop flow to a rescheduling process and these strategy reschedules only a limited part of the initial schedule to match up with the pre-schedule at some point with the objective to create a new schedule that is reliable which in the long run gets disrupted. In this work, we have developed feedback control system that minimizes any form of disruption before the impact becomes severe, the model was tested in a paper manufacturing industries and the results revealed that, if the disruption is minimized at the initial state, the impact becomes unnoticeable.

Keywords: disruption, machine, absenteeism, scheduling

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1439 Potential Ecological Risk Index of the Northern Egyptian Lagoons, South of Mediterranean Sea, Egypt

Authors: Mohamed El-Bady

Abstract:

The Northern Egyptian Lagoons are (from east to west) Bardawil Lagoon, Manzala Lagoon, Burullus Lagoon, Edku Lagoons and Mariute Lagoon. These lagoons have been received the bulk of drainage water from the lands of Delta and from the other coastal areas. Where, the heavy metals can occur in Lagoons environments through a variety of sources, including industries, wastewaters and domestic effluents. The potential ecological risk index (RI) calculation of the bottom sediments of the northern lagoons depends on contamination factor (CF), potential ecological risk factor and proposed toxic response factor (Tr). Each lagoon with special indices according to its conditions.

Keywords: Northern Lagoons, Nile Delta, ecological risk index, contamination factor

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1438 Predictive Modelling of Aircraft Component Replacement Using Imbalanced Learning and Ensemble Method

Authors: Dangut Maren David, Skaf Zakwan

Abstract:

Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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1437 HPTLC Based Qualitative and Quantitative Evaluation of Uraria picta Desv: A Dashmool Species

Authors: Hari O. Saxena, Ganesh

Abstract:

In the present investigation, chemical fingerprints of methanolic extracts of roots, stem and leaves of Uraria picta were developed using HPTLC technique. These fingerprints will be useful for authentication as well as in differentiating the species from adulterants. These will also serve as a biochemical marker for this valuable species in pharmaceutical industries and plant systemic studies. Roots, stem and leaves of Uraria picta were further evaluated for quantification of an active ingredient lupeol to find out alternatives to roots. Results showed more content of lupeol in stem (0.048%, dry wt.) as compare to roots (0.017%, dry wt.) suggesting the utilization of stem in place of roots. It will avoid uprooting of this prestigious plant which ultimately will promote its conservation.

Keywords: chemical fingerprints, lupeol, quantification, Uraria picta

Procedia PDF Downloads 257