Search results for: capability maturity model integration
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19595

Search results for: capability maturity model integration

19025 Enhancing Email Security: A Multi-Layered Defense Strategy Approach and an AI-Powered Model for Identifying and Mitigating Phishing Attacks

Authors: Anastasios Papathanasiou, George Liontos, Athanasios Katsouras, Vasiliki Liagkou, Euripides Glavas

Abstract:

Email remains a crucial communication tool due to its efficiency, accessibility and cost-effectiveness, enabling rapid information exchange across global networks. However, the global adoption of email has also made it a prime target for cyber threats, including phishing, malware and Business Email Compromise (BEC) attacks, which exploit its integral role in personal and professional realms in order to perform fraud and data breaches. To combat these threats, this research advocates for a multi-layered defense strategy incorporating advanced technological tools such as anti-spam and anti-malware software, machine learning algorithms and authentication protocols. Moreover, we developed an artificial intelligence model specifically designed to analyze email headers and assess their security status. This AI-driven model examines various components of email headers, such as "From" addresses, ‘Received’ paths and the integrity of SPF, DKIM and DMARC records. Upon analysis, it generates comprehensive reports that indicate whether an email is likely to be malicious or benign. This capability empowers users to identify potentially dangerous emails promptly, enhancing their ability to avoid phishing attacks, malware infections and other cyber threats.

Keywords: email security, artificial intelligence, header analysis, threat detection, phishing, DMARC, DKIM, SPF, ai model

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19024 A Multi-Layer Based Architecture for the Development of an Open Source CAD/CAM Integration Virtual Platform

Authors: Alvaro Aguinaga, Carlos Avila, Edgar Cando

Abstract:

This article proposes a n-layer architecture, with a web client as a front-end, for the development of a virtual platform for process simulation on CNC machines. This Open-Source platform includes a CAD-CAM interface drawing primitives, and then used to furnish a CNC program that triggers a touch-screen virtual simulator. The objectives of this project are twofold. First one is an educational component that fosters new alternatives for the CAD-CAM/CNC learning process in undergrad and grade schools and technical and technological institutes emphasizing in the development of critical skills, discussion and collaborative work. The second objective puts together a research and technological component that will take the state of the art in CAD-CAM integration to a new level with the development of optimal algorithms and virtual platforms, on-line availability, that will pave the way for the long-term goal of this project, that is, to have a visible and active graduate school in Ecuador and a world wide Open-Innovation community in the area of CAD-CAM integration and operation of CNC machinery. The virtual platform, developed as a part of this study: (1) delivers improved training process of students, (2) creates a multidisciplinary team and a collaborative work space that will push the new generation of students to face future technological challenges, (3) implements industry standards for CAD/CAM, (4) presents a platform for the development of industrial applications. A protoype of this system was developed and implemented in a network of universities and technological institutes in Ecuador.

Keywords: CAD-CAM integration, virtual platforms, CNC machines, multi-layer based architecture

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19023 Re-thinking Trust in Refugee Resettlement: A Contextual Perspective and Proposal for Reciprocal Integration

Authors: Mahfoudha Sid'Elemine

Abstract:

The refugee resettlement process profoundly shapes the trajectories of individuals in their new host countries, exerting lasting effects on their long-term integration. Prevailing literature underscores the pivotal role of trust in facilitating successful refugee resettlement. However, this research challenges the notion of trust as universally paramount, contending that its significance is contingent upon variables such as the nature of resettlement programs and the diverse backgrounds and perspectives of refugees. Rather than advocating for a blanket approach to trust-building, this research contends that for certain resettlement programs, trust may prove counterproductive amidst resource constraints and tight service timelines. Moreover, trust may not uniformly emerge as a primary requisite for all refugees, presenting formidable challenges in its establishment. Focusing specifically on resettlement in the United States, this study illustrates how the temporal constraints of resettlement services, coupled with refugees' varied cultural experiences, can impede the cultivation of trust between aid workers and refugees. As an alternative paradigm, this research proposes an approach centered on fostering opportunities for reciprocal engagement, positioning refugees as active contributors within their newfound communities. Embracing reciprocity as the cornerstone of burgeoning relationships promises to fortify refugees' ties with the broader community, bolster their autonomy, and facilitate sustained integration over time. The research draws upon qualitative analyses of in-depth interviews conducted with a subset of resettled refugees, as well as aid workers and volunteers involved in refugee resettlement endeavors within Hampton Roads, Virginia, over the past decade. Through this nuanced examination, the study offers insights into the complexities of trust dynamics in refugee resettlement contexts and advocates for a paradigm shift towards reciprocal integration strategies.

Keywords: Resettlement programs, Trust dynamics, Reciprocity, Long-term integration

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19022 Optimization of Cutting Forces in Drilling of Polimer Composites via Taguchi Methodology

Authors: Eser Yarar, Fahri Vatansever, A. Tamer Erturk, Sedat Karabay

Abstract:

In this study, drilling behavior of multi-layer orthotropic polyester composites reinforced with woven polyester fiber and PTFE particle was investigated. Conventional drilling methods have low cost and ease of use. Therefore, it is one of the most preferred machining methods. The increasing range of use of composite materials in many areas has led to the investigation of the machinability performance of these materials. The drilling capability of the synthetic polymer composite material was investigated by measuring the cutting forces using different tool diameters, feed rate and high cutting speed parameters. Cutting forces were measured using a dynamometer in the experiments. In order to evaluate the results of the experiment, the Taguchi experimental design method was used. According to the results, the optimum cutting parameters were obtained for 0.1 mm/rev, 1070 rpm and 2 mm diameter drill bit. Verification tests were performed for the optimum cutting parameters obtained according to the model. Verification experiments showed the success of the established model.

Keywords: cutting force, drilling, polimer composite, Taguchi

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19021 Predict Suspended Sediment Concentration Using Artificial Neural Networks Technique: Case Study Oued El Abiod Watershed, Algeria

Authors: Adel Bougamouza, Boualam Remini, Abd El Hadi Ammari, Feteh Sakhraoui

Abstract:

The assessment of sediments being carried by a river is importance for planning and designing of various water resources projects. In this study, Artificial Neural Network Techniques are used to estimate the daily suspended sediment concentration for the corresponding daily discharge flow in the upstream of Foum El Gherza dam, Biskra, Algeria. The FFNN, GRNN, and RBNN models are established for estimating current suspended sediment values. Some statistics involving RMSE and R2 were used to evaluate the performance of applied models. The comparison of three AI models showed that the RBNN model performed better than the FFNN and GRNN models with R2 = 0.967 and RMSE= 5.313 mg/l. Therefore, the ANN model had capability to improve nonlinear relationships between discharge flow and suspended sediment with reasonable precision.

Keywords: artificial neural network, Oued Abiod watershed, feedforward network, generalized regression network, radial basis network, sediment concentration

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19020 Modeling Residential Electricity Consumption Function in Malaysia: Time Series Approach

Authors: L. L. Ivy-Yap, H. A. Bekhet

Abstract:

As the Malaysian residential electricity consumption continued to increase rapidly, effective energy policies, which address factors affecting residential electricity consumption, is urgently needed. This study attempts to investigate the relationship between residential electricity consumption (EC), real disposable income (Y), price of electricity (Pe) and population (Po) in Malaysia for 1978-2011 periods. Unlike previous studies on Malaysia, the current study focuses on the residential sector, a sector that is important for the contemplation of energy policy. The Phillips-Perron (P-P) unit root test is employed to infer the stationary of each variable while the bound test is executed to determine the existence of co-integration relationship among the variables, modeled in an Autoregressive Distributed Lag (ARDL) framework. The CUSUM and CUSUM of squares tests are applied to ensure the stability of the model. The results suggest the existence of long-run equilibrium relationship and bidirectional Granger causality between EC and the macroeconomic variables. The empirical findings will help policy makers of Malaysia in developing new monitoring standards of energy consumption. As it is the major contributing factor in economic growth and CO2 emission, there is a need for more proper planning in Malaysia to attain future targets in order to cut emissions.

Keywords: co-integration, elasticity, granger causality, Malaysia, residential electricity consumption

Procedia PDF Downloads 258
19019 An Approach for Determination of Shotcrete Thickness in Underground Structures

Authors: Mohammad Mohammadi, Mojtaba Askari, Mohammad Farouq Hossaini

Abstract:

An intrinsic property of rock mass known as rock bolt supporting factor (RSF) or rock bolting capability of rock mass was developed and used for explanation of the mechanism of rock bolting practice. Based on the theory of RSF, numeral values can be assigned to each given rock mass to show the capability of that rock mass to be reinforced by rock bolting. For determination of shotcrete thickness, both safety and cost must be taken into account. The present paper introduces a scientific approach for determination of the necessary shotcrete thickness in underground structures for support purposes using the concept of rock bolt supporting factor (RSF). The proposed approach makes the outcome of shotcrete design one step more accurate than before. The actual dataset of 500 meters of Alborz Tunnel length is used as an example of the application of the approach.

Keywords: rock bolt supporting factor (RSF), shotcrete design, underground excavation, Alborz Tunnel

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19018 Enhancing Intercultural Competencies Through Digital Integration in South Africa

Authors: Naziema Begum Jappie

Abstract:

In higher education, particularly within South African universities engaged in regional and global collaborations, the integration of intercultural competencies into teaching, learning, and assessment is essential for student success. Intercultural competencies and the digital platform are intwined in the fabric of teaching, learning, and assessments for student success in higher education. These are integral to virtual learning and exchange within higher education, which are expected to develop these competencies. However, this is not always the case because these are not always explicitly integrated into the academic agenda. Despite the prevalence of international students and exchange programmes, there is often a lack of deliberate integration of these competencies into academic agendas, even for South African students from different cultural, ethnic and language groups. This research addresses this gap by examining the impact of infusing intercultural activities into both face-to-face and digital learning platforms. Adopting an intersectional perspective, the study recognizes how social identities interact to shape individuals' self-perceptions and experiences in a university. Methodologically, this study employs a mixed-methods approach, combining quantitative surveys and qualitative interviews to assess the effectiveness of integrating intercultural competencies into digital platforms. Surveys administered to students and faculty measure changes in intercultural skills and attitudes before and after the implementation of targeted interventions. In-depth interviews with participants will provide further insights into the qualitative aspects of these changes, including their experiences and perceptions of the integration process. The research evaluates whether the strategic integration of intercultural competencies into digital platforms enhances students' intercultural skills and social justice awareness. The findings provide valuable insights for higher education academics and internationalization practitioners seeking to develop effective strategies for cultivating intercultural competencies among students.

Keywords: digital platform, higher education, intercultural competencies, interventions

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19017 Integrated Information Approach to Inbound Logistics in Indian Steel Sector

Authors: N. Jena, Nitin Seth

Abstract:

Globalization and free trade has forced the organizations to continuously rethink and rework on the increasing cost of logistics. World wide, it is visualized that on one side the steel sector is witnessing rapid growth and on the other side it is facing huge challenges in terms of availability of raw materials for uninterrupted production. Inbound logistics also gains significant importance for ensuring the timely availability of raw materials. It is seen that in Indian steel sector logistic cost is still very large and challenging. Effectively managing the inbound logistics in steel decides the profitability and serviceability of the organization. Effective management of inbound logistics also has a major role on the inventory of the organization. Since, the logistics for the steel industry in India is evolving rapidly and it is the interplay of infrastructure, technology and new types of service providers that will define whether the industry is able to help its customers to reduce their logistics costs. Integration of Logistics has been treated as one of the most potential area for the companies to provide a base for cost reduction. In spite of the proven area for benefits for the industry, it is very surprising that none of the researchers have explored this area. Although, many researchers explored the subject of logistics in steel industry, but their perspective varied from exploring and understanding the associated cost and finding out the relations between them. Visualizing a potential gap, the present research is under taken to explore the integration opportunities in inbound logistics for steel sector. Typically in Indian steel sector where in most of the manufacturers depend on imported materials for processing the logistics is very challenging and accounts for transactions at supplier – who is situated in different country, shipper- who is transporting the material to the host country, regulators in both countries-that include customs and various clearing agents, local logistics service providers and local transporters/handlers. It is seen that In bound logistics cost in the steel sector is very high and accounts for about 15-16% of the turn over, integration of information across different channels provides and opportunity for improvements and growth of the organization. In the present paper, a case of leading steel manufacturer has been taken and the potentials for integration of information across various partners have been identified. The paper provides the identification of grey area in steel sector for major improvements in cycle time and lowering the inventories by integration of information. Finally, based on integration of information, the paper presents a business information framework for steel sector.

Keywords: integration, steel sectors, suppliers, shippers, customs and cargo agents, transporters

Procedia PDF Downloads 335
19016 Decentralised Edge Authentication in the Industrial Enterprise IoT Space

Authors: C. P. Autry, A.W. Roscoe

Abstract:

Authentication protocols based on public key infrastructure (PKI) and trusted third party (TTP) are no longer adequate for industrial scale IoT networks thanks to issues such as low compute and power availability, the use of widely distributed and commercial off-the-shelf (COTS) systems, and the increasingly sophisticated attackers and attacks we now have to counter. For example, there is increasing concern about nation-state-based interference and future quantum computing capability. We have examined this space from first principles and have developed several approaches to group and point-to-point authentication for IoT that do not depend on the use of a centralised client-server model. We emphasise the use of quantum resistant primitives such as strong cryptographic hashing and the use multi-factor authentication.

Keywords: authentication, enterprise IoT cybersecurity, PKI/TTP, IoT space

Procedia PDF Downloads 160
19015 Improvement on a CNC Gantry Machine Structure Design for Higher Machining Speed Capability

Authors: Ahmed A. D. Sarhan, S. R. Besharaty, Javad Akbaria, M. Hamdi

Abstract:

The capability of CNC gantry milling machines in manufacturing long components has caused the expanded use of such machines. On the other hand, the machines’ gantry rigidity can reduce under severe loads or vibration during operation. Indeed, the quality of machining is dependent on the machine’s dynamic behavior throughout the operating process. For this reason, this type of machines has always been used prudently and are non efficient. Therefore, they can usually be employed for rough machining and may not produce adequate surface finishing. In this paper, a CNC gantry milling machine with the potential to produce good surface finish has been designed and analyzed. The lowest natural frequency of this machine is 202 Hz at all motion amplitudes with a full range of suitable frequency responses. Meanwhile, the maximum deformation under dead loads for the gantry machine is 0.565µm, indicating that this machine tool is capable of producing higher product quality.

Keywords: frequency response, finite element, gantry machine, gantry design, static and dynamic analysis

Procedia PDF Downloads 350
19014 Response of Caldeira De Tróia Saltmarsh to Sea Level Rise, Sado Estuary, Portugal

Authors: A. G. Cunha, M. Inácio, M. C. Freitas, C. Antunes, T. Silva, C. Andrade, V. Lopes

Abstract:

Saltmarshes are essential ecosystems both from an ecological and biological point of view. Furthermore, they constitute an important social niche, providing valuable economic and protection functions. Thus, understanding their rates and patterns of sedimentation is critical for functional management and rehabilitation, especially in an SLR scenario. The Sado estuary is located 40 km south of Lisbon. It is a bar built estuary, separated from the sea by a large sand spit: the Tróia barrier. Caldeira de Tróia is located on the free edge of this barrier, and encompasses a salt marsh with ca. 21,000 m². Sediment cores were collected in the high and low marshes and in the mudflat area of the North bank of Caldeira de Tróia. From the low marsh core, fifteen samples were chosen for ²¹⁰Pb and ¹³⁷Cs determination at University of Geneva. The cores from the high marsh and the mudflat are still being analyzed. A sedimentation rate of 2.96 mm/year was derived from ²¹⁰Pb using the Constant Flux Constant Sedimentation model. The ¹³⁷Cs profile shows a peak in activity (1963) between 15.50 and 18.50 cm, giving a 3.1 mm/year sedimentation rate for the past 53 years. The adopted sea level rise scenario was based on a model built with the initial rate of SLR of 2.1 mm/year in 2000 and an acceleration of 0.08 mm/year². Based on the harmonic analysis of Setubal-Tróia tide gauge of 2005 data, the tide model was estimated and used to build the tidal tables to the period 2000-2016. With these tables, the average mean water levels were determined for the same time span. A digital terrain model was created from LIDAR scanning with 2m horizontal resolution (APA-DGT, 2011) and validated with altimetric data obtained with a DGPS-RTK. The response model calculates a new elevation for each pixel of the DTM for 2050 and 2100 based on the sedimentation rates specific of each environment. At this stage, theoretical values were chosen for the high marsh and the mudflat (respectively, equal and double the low marsh rate – 2.92 mm/year). These values will be rectified once sedimentation rates are determined for the other environments. For both projections, the total surface of the marsh decreases: 2% in 2050 and 61% in 2100. Additionally, the high marsh coverage diminishes significantly, indicating a regression in terms of maturity.

Keywords: ¹³⁷Cs, ²¹⁰Pb, saltmarsh, sea level rise, response model

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19013 A Critical Evaluation of Building Information Modelling in New Zealand: Deepening Our Understanding of the Benefits and Drawbacks

Authors: Garry Miller, Thomas Alexander, Cameron Lee

Abstract:

There is belief that Building Information Modelling (BIM) will improve performance of the New Zealand (NZ) Architecture, Engineering and Construction (AEC) sector, however, widespread use of BIM is yet to be seen. Previous research indicates there are many issues affecting the uptake of BIM in NZ; nevertheless the underlying benefits, drawbacks, and barriers preventing more widespread uptake are not fully understood. This investigation aimed to understand these factors more clearly and make suggestions on how to improve the uptake of BIM in NZ. Semi-structured interviews were conducted with a range of industry professionals to gather a qualitative understanding. Findings indicated the ability to incorporate better information into a BIM model could drive many benefits. However scepticism and lack of positive incentives in NZ are affecting its widespread use. This concluded that there is a need for the government to produce a number of BIM case studies and develop a set of BIM standards to resolve payment issues surrounding BIM use. This study provides useful information for those interested in BIM and members of government interested in improving the performance of the construction industry. This study may also be of interest to small, developed countries such as NZ where the level of BIM maturity is relatively low.

Keywords: BIM, New Zealand, AEC sector, building information modelling

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19012 Process Integration of Natural Gas Hydrate Production by CH₄-CO₂/H₂ Replacement Coupling Steam Methane Reforming

Authors: Mengying Wang, Xiaohui Wang, Chun Deng, Bei Liu, Changyu Sun, Guangjin Chen, Mahmoud El-Halwagi

Abstract:

Significant amounts of natural gas hydrates (NGHs) are considered potential new sustainable energy resources in the future. However, common used methods for methane gas recovery from hydrate sediments require high investment but with low gas production efficiency, and may cause potential environment and security problems. Therefore, there is a need for effective gas production from hydrates. The natural gas hydrate production method by CO₂/H₂ replacement coupling steam methane reforming can improve the replacement effect and reduce the cost of gas separation. This paper develops a simulation model of the gas production process integrated with steam reforming and membrane separation. The process parameters (i.e., reactor temperature, pressure, H₂O/CH₄ ratio) and the composition of CO₂ and H₂ in the feed gas are analyzed. Energy analysis is also conducted. Two design scenarios with different composition of CO₂ and H₂ in the feed gas are proposed and evaluated to assess the energy efficiency of the novel system. Results show that when the composition of CO₂ in the feed gas is between 43 % and 72 %, there is a certain composition that can meet the requirement that the flow rate of recycled gas is equal to that of feed gas, so as to ensure that the subsequent production process does not need to add feed gas or discharge recycled gas. The energy efficiency of the CO₂ in feed gas at 43 % and 72 % is greater than 1, and the energy efficiency is relatively higher when the CO₂ mole fraction in feed gas is 72 %.

Keywords: Gas production, hydrate, process integration, steam reforming

Procedia PDF Downloads 178
19011 The Relationship of Building Information Modeling (BIM) Capability in Quantity Surveying Practice and Project Performance

Authors: P. F. Wong, H. Salleh, F. A. Rahim

Abstract:

The adoption of building information modeling (BIM) is increasing in the construction industry. However, quantity surveyors are slow in adoption compared to other professions due to lack of awareness of the BIM’s potential in their profession. It is still unclear on how BIM application can enhance quantity surveyors’ work performance and project performance. The aim of this research is to identify the capabilities of BIM in quantity surveying practices and examine the relationship between BIM capabilities and project performance. Questionnaire survey and interviews were adopted for data collection. Literature reviews identified there are eleven BIM capabilities in quantity surveying practice. Questionnaire results showed that there are several BIM capabilities significantly correlated with project performance in time, cost and quality aspects and the results were validated through interviews. These findings show that BIM has the capabilities to enhance quantity surveyors’ performances and subsequently improved project performance.

Keywords: Building Information Modeling (BIM), quantity surveyors, capability, project performance

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19010 Grid and Market Integration of Large Scale Wind Farms using Advanced Predictive Data Mining Techniques

Authors: Umit Cali

Abstract:

The integration of intermittent energy sources like wind farms into the electricity grid has become an important challenge for the utilization and control of electric power systems, because of the fluctuating behaviour of wind power generation. Wind power predictions improve the economic and technical integration of large amounts of wind energy into the existing electricity grid. Trading, balancing, grid operation, controllability and safety issues increase the importance of predicting power output from wind power operators. Therefore, wind power forecasting systems have to be integrated into the monitoring and control systems of the transmission system operator (TSO) and wind farm operators/traders. The wind forecasts are relatively precise for the time period of only a few hours, and, therefore, relevant with regard to Spot and Intraday markets. In this work predictive data mining techniques are applied to identify a statistical and neural network model or set of models that can be used to predict wind power output of large onshore and offshore wind farms. These advanced data analytic methods helps us to amalgamate the information in very large meteorological, oceanographic and SCADA data sets into useful information and manageable systems. Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility customers. An accurate forecast allows grid operators to schedule economically efficient generation to meet the demand of electrical customers. This study is also dedicated to an in-depth consideration of issues such as the comparison of day ahead and the short-term wind power forecasting results, determination of the accuracy of the wind power prediction and the evaluation of the energy economic and technical benefits of wind power forecasting.

Keywords: renewable energy sources, wind power, forecasting, data mining, big data, artificial intelligence, energy economics, power trading, power grids

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19009 High Frequency Memristor-Based BFSK and 8QAM Demodulators

Authors: Nahla Elazab, Mohamed Aboudina, Ghada Ibrahim, Hossam Fahmy, Ahmed Khalil

Abstract:

This paper presents the developed memristor based demodulators for eight circular Quadrature Amplitude Modulation (QAM) and Binary Frequency Shift Keying (BFSK) operating at relatively high frequency. In our implementations, the experimental-based ‘nonlinear’ dopant drift model is adopted along with the proposed circuits providing incorporation of all known non-idealities of practically realized memristor and gaining high operation frequency. The suggested designs leverage the distinctive characteristics of the memristor device, definitely, its changeable average memristance versus the frequency, phase and amplitude of the periodic excitation input. The proposed demodulators feature small integration area, low power consumption, and easy implementation. Moreover, the proposed QAM demodulator precludes the requirement for the carrier recovery circuits. In doing so, the designs were validated by transient simulations using the nonlinear dopant drift memristor model. The simulations results show high agreement with the theory presented.

Keywords: BFSK, demodulator, high frequency memristor applications, memristor based analog circuits, nonlinear dopant drift model, QAM

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19008 Assessing the Efficacy of Artificial Intelligence Integration in the FLO Health Application

Authors: Reema Alghamdi, Rasees Aleisa, Layan Sukkar

Abstract:

The primary objective of this research is to conduct an examination of the Flo menstrual cycle application. We do that by evaluating the user experience and their satisfaction with integrated AI features. The study seeks to gather data from primary resources, primarily through surveys, to gather different insights about the application, like its usability functionality in addition to the overall user satisfaction. The focus of our project will be particularly directed towards the impact and user perspectives regarding the integration of artificial intelligence features within the application, contributing to an understanding of the holistic user experience.

Keywords: period, women health, machine learning, AI features, menstrual cycle

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19007 Towards a Model of Support in the Areas of Services of Educational Assistance and Mentoring in Middle Education in Mexico

Authors: Margarita Zavala, Gabriel Chavira, José González, Jorge Orozco, Julio Rolón, Roberto Pichardo

Abstract:

Adolescence is a neuralgic stage in the formation of every human being, generally this stage is when the middle school level is studied. In 2006, Mexico incorporated 'mentoring' space to assist students in their integration and participation in life. In public middle schools, it is sometimes difficult to be aware of situations that affect students because of the number of them and traditional records management. With this, they lose the opportunity to provide timely support as a preventive way. In order to provide this support, it is required to know the students by detecting the relevant information that has greater impact on their learning process. This research is looking to check if it is possible to identify student’s relevant information to detect when it is at risk, and then to propose a model to manage in a proper way such information.

Keywords: adolescence, mentoring, middle school students, mentoring system support

Procedia PDF Downloads 475
19006 Transformer Fault Diagnostic Predicting Model Using Support Vector Machine with Gradient Decent Optimization

Authors: R. O. Osaseri, A. R. Usiobaifo

Abstract:

The power transformer which is responsible for the voltage transformation is of great relevance in the power system and oil-immerse transformer is widely used all over the world. A prompt and proper maintenance of the transformer is of utmost importance. The dissolved gasses content in power transformer, oil is of enormous importance in detecting incipient fault of the transformer. There is a need for accurate prediction of the incipient fault in transformer oil in order to facilitate the prompt maintenance and reducing the cost and error minimization. Study on fault prediction and diagnostic has been the center of many researchers and many previous works have been reported on the use of artificial intelligence to predict incipient failure of transformer faults. In this study machine learning technique was employed by using gradient decent algorithms and Support Vector Machine (SVM) in predicting incipient fault diagnosis of transformer. The method focuses on creating a system that improves its performance on previous result and historical data. The system design approach is basically in two phases; training and testing phase. The gradient decent algorithm is trained with a training dataset while the learned algorithm is applied to a set of new data. This two dataset is used to prove the accuracy of the proposed model. In this study a transformer fault diagnostic model based on Support Vector Machine (SVM) and gradient decent algorithms has been presented with a satisfactory diagnostic capability with high percentage in predicting incipient failure of transformer faults than existing diagnostic methods.

Keywords: diagnostic model, gradient decent, machine learning, support vector machine (SVM), transformer fault

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19005 Branding Capability Developed from Country-Specific and Firm-Specific Resources for Internationalizing Small and Medium Enterprises

Authors: Hsing-Hua Stella Chang, Mong-Ching Lin, Cher-Min Fong

Abstract:

There has recently been a notable rise in the number of emerging-market industrial small and medium-sized enterprises (SMEs) that have managed to upgrade their operations. Evolving from original equipment manufacturing (OEM) into value-added original or own brand manufacturing (OBM) in such firms represents a specific process of internationalization. The OEM-OBM upgrade requires development of a firm’s own brand. In this respect, the extant literature points out that emerging-market industrial marketers (latecomers) have developed some marketing capabilities, of which branding has been identified as one of the most important. In specific, an industrial non-brand marketer (OEM) marks the division of labor between manufacturing and branding (as part of marketing). In light of this discussion, this research argues that branding capability plays a critical role in supporting the evolution of manufacture upgrade. This is because a smooth transformation from OEM to OBM entails the establishment of strong brands through which branding capability is developed. Accordingly, branding capability can be exemplified as a series of processes and practices in relation to mobilizing branding resources and orchestrating branding activities, which will result in the establishment of business relationships, greater acceptance of business partners (channels, suppliers), and increased industrial brand equity in the firm as key resource advantages). For the study purpose, Taiwan was chosen as the research context, representing a typical case that exemplifies the industrial development path of more-established emerging markets, namely, transformation from OEM to OBM. This research adopted a two-phase research design comprising exploratory (a qualitative study) and confirmatory approaches (a survey study) The findings show that: Country-specific advantage is positively related to branding capability for internationalizing SMEs. Firm-specific advantage is positively related to branding capability for internationalizing SMEs. Hsing-Hua Stella Chang is Assistant Professor with National Taichung University of Education, International Master of Business Administration, (Yingcai Campus) No.227, Minsheng Rd., West Dist., Taichung City 40359, Taiwan, R.O.C. (phone: 886-22183612; e-mail: [email protected]). Mong-Ching Lin is PhD candidate with National Sun Yat-Sen University, Department of Business Management, 70 Lien-hai Rd., Kaohsiung 804, Taiwan, R.O.C. (e-mail: [email protected]). Cher-Min Fong is Full Professor with National Sun Yat-Sen University, Department of Business Management, 70 Lien-hai Rd., Kaohsiung 804, Taiwan, R.O.C. (e-mail: [email protected]). Branding capability is positively related to international performance for internationalizing SMEs. This study presents a pioneering effort to distinguish industrial brand marketers from non-brand marketers in exploring the role of branding capability in the internationalizing small and medium-sized industrial brand marketers from emerging markets. Specifically, when industrial non-brand marketers (OEMs) enter into a more advanced stage of internationalization (i.e., OBM), they must overcome disadvantages (liabilities of smallness, foreignness, outsidership) that do not apply in the case of incumbent developed-country MNEs with leading brands. Such critical differences mark the urgency and significance of distinguishing industrial brand marketers from non-brand marketers on issues relating to their value-adding branding and marketing practices in international markets. This research thus makes important contributions to the international marketing, industrial branding, and SME internationalization literature.

Keywords: brand marketers, branding capability, emerging markets, SME internationalization

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19004 SIF Computation of Cracked Plate by FEM

Authors: Sari Elkahina, Zergoug Mourad, Benachenhou Kamel

Abstract:

The main purpose of this paper is to perform a computations comparison of stress intensity factor 'SIF' evaluation in case of cracked thin plate with Aluminum alloy 7075-T6 and 2024-T3 used in aeronautics structure under uniaxial loading. This evaluation is based on finite element method with a virtual power principle through two techniques: the extrapolation and G−θ. The first one consists to extrapolate the nodal displacements near the cracked tip using a refined triangular mesh with T3 and T6 special elements, while the second, consists of determining the energy release rate G through G−θ method by potential energy derivation which corresponds numerically to the elastic solution post-processing of a cracked solid by a contour integration computation via Gauss points. The SIF obtained results from extrapolation and G−θ methods will be compared to an analytical solution in a particular case. To illustrate the influence of the meshing kind and the size of integration contour position simulations are presented and analyzed.

Keywords: crack tip, SIF, finite element method, concentration technique, displacement extrapolation, aluminum alloy 7075-T6 and 2024-T3, energy release rate G, G-θ method, Gauss point numerical integration

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19003 Sinhala Sign Language to Grammatically Correct Sentences using NLP

Authors: Anjalika Fernando, Banuka Athuraliya

Abstract:

This paper presents a comprehensive approach for converting Sinhala Sign Language (SSL) into grammatically correct sentences using Natural Language Processing (NLP) techniques in real-time. While previous studies have explored various aspects of SSL translation, the research gap lies in the absence of grammar checking for SSL. This work aims to bridge this gap by proposing a two-stage methodology that leverages deep learning models to detect signs and translate them into coherent sentences, ensuring grammatical accuracy. The first stage of the approach involves the utilization of a Long Short-Term Memory (LSTM) deep learning model to recognize and interpret SSL signs. By training the LSTM model on a dataset of SSL gestures, it learns to accurately classify and translate these signs into textual representations. The LSTM model achieves a commendable accuracy rate of 94%, demonstrating its effectiveness in accurately recognizing and translating SSL gestures. Building upon the successful recognition and translation of SSL signs, the second stage of the methodology focuses on improving the grammatical correctness of the translated sentences. The project employs a Neural Machine Translation (NMT) architecture, consisting of an encoder and decoder with LSTM components, to enhance the syntactical structure of the generated sentences. By training the NMT model on a parallel corpus of Sinhala wrong sentences and their corresponding grammatically correct translations, it learns to generate coherent and grammatically accurate sentences. The NMT model achieves an impressive accuracy rate of 98%, affirming its capability to produce linguistically sound translations. The proposed approach offers significant contributions to the field of SSL translation and grammar correction. Addressing the critical issue of grammar checking, it enhances the usability and reliability of SSL translation systems, facilitating effective communication between hearing-impaired and non-sign language users. Furthermore, the integration of deep learning techniques, such as LSTM and NMT, ensures the accuracy and robustness of the translation process. This research holds great potential for practical applications, including educational platforms, accessibility tools, and communication aids for the hearing-impaired. Furthermore, it lays the foundation for future advancements in SSL translation systems, fostering inclusive and equal opportunities for the deaf community. Future work includes expanding the existing datasets to further improve the accuracy and generalization of the SSL translation system. Additionally, the development of a dedicated mobile application would enhance the accessibility and convenience of SSL translation on handheld devices. Furthermore, efforts will be made to enhance the current application for educational purposes, enabling individuals to learn and practice SSL more effectively. Another area of future exploration involves enabling two-way communication, allowing seamless interaction between sign-language users and non-sign-language users.In conclusion, this paper presents a novel approach for converting Sinhala Sign Language gestures into grammatically correct sentences using NLP techniques in real time. The two-stage methodology, comprising an LSTM model for sign detection and translation and an NMT model for grammar correction, achieves high accuracy rates of 94% and 98%, respectively. By addressing the lack of grammar checking in existing SSL translation research, this work contributes significantly to the development of more accurate and reliable SSL translation systems, thereby fostering effective communication and inclusivity for the hearing-impaired community

Keywords: Sinhala sign language, sign Language, NLP, LSTM, NMT

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19002 Knowledge Management Best Practice Model in Higher Learning Institution: A Systematic Literature Review

Authors: Ismail Halijah, Abdullah Rusli

Abstract:

Introduction: This systematic literature review aims to identify the Knowledge Management Best Practice components in the Knowledge Management Model for Higher Learning Institutions environment. Study design: Systematic literature review. Methods: A systematic literature re-view of Knowledge Management Best Practice to identify and define the components of Best Practice from the Knowledge Management models was conducted recently. Results: This review of published papers of conference and journals’ articles shows the components of Best Practice in Knowledge Management are basically divided into two aspect which is the soft aspect and the hard aspect. The lacks of combination of these two aspects into an integrated model decelerate Knowledge Management Best Practice to fully throttle. Evidence from the literature shows the lack of integration of this two aspects leads to the immaturity of the Higher Learning Institution (HLI) towards the implementation of Knowledge Management System. Conclusion: The first steps of identifying the attributes to measure the Knowledge Management Best Practice components from the models in the literature will led to the definition of the Knowledge Management Best Practice component for the higher learning environment.

Keywords: knowledge management, knowledge management system, knowledge management best practice, knowledge management higher learning institution

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19001 Correlation between Defect Suppression and Biosensing Capability of Hydrothermally Grown ZnO Nanorods

Authors: Mayoorika Shukla, Pramila Jakhar, Tejendra Dixit, I. A. Palani, Vipul Singh

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Biosensors are analytical devices with wide range of applications in biological, chemical, environmental and clinical analysis. It comprises of bio-recognition layer which has biomolecules (enzymes, antibodies, DNA, etc.) immobilized over it for detection of analyte and transducer which converts the biological signal into the electrical signal. The performance of biosensor primarily the depends on the bio-recognition layer and therefore it has to be chosen wisely. In this regard, nanostructures of metal oxides such as ZnO, SnO2, V2O5, and TiO2, etc. have been explored extensively as bio-recognition layer. Recently, ZnO has the attracted attention of researchers due to its unique properties like high iso-electric point, biocompatibility, stability, high electron mobility and high electron binding energy, etc. Although there have been many reports on usage of ZnO as bio-recognition layer but to the authors’ knowledge, none has ever observed correlation between optical properties like defect suppression and biosensing capability of the sensor. Here, ZnO nanorods (ZNR) have been synthesized by a low cost, simple and low-temperature hydrothermal growth process, over Platinum (Pt) coated glass substrate. The ZNR have been synthesized in two steps viz. initially a seed layer was coated over substrate (Pt coated glass) followed by immersion of it into nutrient solution of Zinc nitrate and Hexamethylenetetramine (HMTA) with in situ addition of KMnO4. The addition of KMnO4 was observed to have a profound effect over the growth rate anisotropy of ZnO nanostructures. Clustered and powdery growth of ZnO was observed without addition of KMnO4, although by addition of it during the growth, uniform and crystalline ZNR were found to be grown over the substrate. Moreover, the same has resulted in suppression of defects as observed by Normalized Photoluminescence (PL) spectra since KMnO4 is a strong oxidizing agent which provides an oxygen rich growth environment. Further, to explore the correlation between defect suppression and biosensing capability of the ZNR Glucose oxidase (Gox) was immobilized over it, using physical adsorption technique followed by drop casting of nafion. Here the main objective of the work was to analyze effect of defect suppression over biosensing capability, and therefore Gox has been chosen as model enzyme, and electrochemical amperometric glucose detection was performed. The incorporation of KMnO4 during growth has resulted in variation of optical and charge transfer properties of ZNR which in turn were observed to have deep impact on biosensor figure of merits. The sensitivity of biosensor was found to increase by 12-18 times, due to variations introduced by addition of KMnO4 during growth. The amperometric detection of glucose in continuously stirred buffer solution was performed. Interestingly, defect suppression has been observed to contribute towards the improvement of biosensor performance. The detailed mechanism of growth of ZNR along with the overall influence of defect suppression on the sensing capabilities of the resulting enzymatic electrochemical biosensor and different figure of merits of the biosensor (Glass/Pt/ZNR/Gox/Nafion) will be discussed during the conference.

Keywords: biosensors, defects, KMnO4, ZnO nanorods

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19000 The Correlation between Territory Planning and Logistics Development: Methodological Approach

Authors: Ebtissem Sassi, Abdellatif Benabdelhafid, Sami Hammami

Abstract:

Congestion, pollution and space misuse are the major risks in the hinterland. Management of these risks is a major issue for all the actors intervening in territory management. A good mastery of these risks is based on the consideration of environmental and physical constraints since the implementation of a policy integrates simultaneously an efficient use, territorial resources, and financial resources which become increasingly rare. Yet, this balance can be difficult to establish simultaneously by all the actors. Indeed, every actor has often the tendency to favor these objectives in detriment to others. In this framework, we have fixed the objective of designing and achieving a model which will centralize multidisciplinary data and serve the analysis tool as well as a decision support tool. In this article, we will elaborate some methodological axes allowing the good management of the territory system through (i) determination of the structural factors of the decision support system, (ii) integration of methods tools favoring the territorial decisional process. Logistics territory geographic information system is a model dealing with this issue. The objective of this model is to facilitate the exchanges between the actors around a common question which was the research subject of human sciences researchers (geography, economy), nature sciences (ecology) as well as finding an optimal solution for simultaneous responses to all these objectives.

Keywords: complexity, territory, logistics, territory planning, conceptual model, GIS, MCA

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18999 An Integration of Genetic Algorithm and Particle Swarm Optimization to Forecast Transport Energy Demand

Authors: N. R. Badurally Adam, S. R. Monebhurrun, M. Z. Dauhoo, A. Khoodaruth

Abstract:

Transport energy demand is vital for the economic growth of any country. Globalisation and better standard of living plays an important role in transport energy demand. Recently, transport energy demand in Mauritius has increased significantly, thus leading to an abuse of natural resources and thereby contributing to global warming. Forecasting the transport energy demand is therefore important for controlling and managing the demand. In this paper, we develop a model to predict the transport energy demand. The model developed is based on a system of five stochastic differential equations (SDEs) consisting of five endogenous variables: fuel price, population, gross domestic product (GDP), number of vehicles and transport energy demand and three exogenous parameters: crude birth rate, crude death rate and labour force. An interval of seven years is used to avoid any falsification of result since Mauritius is a developing country. Data available for Mauritius from year 2003 up to 2009 are used to obtain the values of design variables by applying genetic algorithm. The model is verified and validated for 2010 to 2012 by substituting the values of coefficients obtained by GA in the model and using particle swarm optimisation (PSO) to predict the values of the exogenous parameters. This model will help to control the transport energy demand in Mauritius which will in turn foster Mauritius towards a pollution-free country and decrease our dependence on fossil fuels.

Keywords: genetic algorithm, modeling, particle swarm optimization, stochastic differential equations, transport energy demand

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18998 Conceptualizing IoT Based Framework for Enhancing Environmental Accounting By ERP Systems

Authors: Amin Ebrahimi Ghadi, Morteza Moalagh

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This research is carried out to find how a perfect combination of IoT architecture (Internet of Things) and ERP system can strengthen environmental accounting to incorporate both economic and environmental information. IoT (e.g., sensors, software, and other technologies) can be used in the company’s value chain from raw material extraction through materials processing, manufacturing products, distribution, use, repair, maintenance, and disposal or recycling products (Cradle to Grave model). The desired ERP software then will have the capability to track both midpoint and endpoint environmental impacts on a green supply chain system for the whole life cycle of a product. All these enable environmental accounting to calculate, and real-time analyze the operation environmental impacts, control costs, prepare for environmental legislation and enhance the decision-making process. In this study, we have developed a model on how to use IoT devices in life cycle assessment (LCA) to gather emissions, energy consumption, hazards, and wastes information to be processed in different modules of ERP systems in an integrated way for using in environmental accounting to achieve sustainability.

Keywords: ERP, environmental accounting, green supply chain, IOT, life cycle assessment, sustainability

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18997 Verification of a Simple Model for Rolling Isolation System Response

Authors: Aarthi Sridhar, Henri Gavin, Karah Kelly

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Rolling Isolation Systems (RISs) are simple and effective means to mitigate earthquake hazards to equipment in critical and precious facilities, such as hospitals, network collocation facilities, supercomputer centers, and museums. The RIS works by isolating components acceleration the inertial forces felt by the subsystem. The RIS consists of two platforms with counter-facing concave surfaces (dishes) in each corner. Steel balls lie inside the dishes and allow the relative motion between the top and bottom platform. Formerly, a mathematical model for the dynamics of RISs was developed using Lagrange’s equations (LE) and experimentally validated. A new mathematical model was developed using Gauss’s Principle of Least Constraint (GPLC) and verified by comparing impulse response trajectories of the GPLC model and the LE model in terms of the peak displacements and accelerations of the top platform. Mathematical models for the RIS are tedious to derive because of the non-holonomic rolling constraints imposed on the system. However, using Gauss’s Principle of Least constraint to find the equations of motion removes some of the obscurity and yields a system that can be easily extended. Though the GPLC model requires more state variables, the equations of motion are far simpler. The non-holonomic constraint is enforced in terms of accelerations and therefore requires additional constraint stabilization methods in order to avoid the possibility that numerical integration methods can cause the system to go unstable. The GPLC model allows the incorporation of more physical aspects related to the RIS, such as contribution of the vertical velocity of the platform to the kinetic energy and the mass of the balls. This mathematical model for the RIS is a tool to predict the motion of the isolation platform. The ability to statistically quantify the expected responses of the RIS is critical in the implementation of earthquake hazard mitigation.

Keywords: earthquake hazard mitigation, earthquake isolation, Gauss’s Principle of Least Constraint, nonlinear dynamics, rolling isolation system

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18996 Implementation of a Photo-Curable 3D Additive Manufacturing Technology with Grey Capability by Using Piezo Ink-jets

Authors: Ming-Jong Tsai, Y. L. Cheng, Y. L. Kuo, S. Y. Hsiao, J. W. Chen, P. H. Liu, D. H. Chen

Abstract:

The 3D printing is a combination of digital technology, material science, intelligent manufacturing and control of opto-mechatronics systems. It is called the third industrial revolution from the view of the Economist Journal. A color 3D printing machine may provide the necessary support for high value-added industrial and commercial design, architectural design, personal boutique, and 3D artist’s creation. The main goal of this paper is to develop photo-curable color 3D manufacturing technology and system implementation. The key technologies include (1) Photo-curable color 3D additive manufacturing processes development and materials research (2) Piezo type ink-jet head control and Opto-mechatronics integration technique of the photo-curable color 3D laminated manufacturing system. The proposed system is integrated with single Piezo type ink-jet head with two individual channels for two primary UV light curable color resins which can provide for future colorful 3D printing solutions. The main research results are 16 grey levels and grey resolution of 75 dpi.

Keywords: 3D printing, additive manufacturing, color, photo-curable, Piezo type ink-jet, UV Resin

Procedia PDF Downloads 553