Search results for: business intelligence and analytics

Authors: Armen Grigoryan, Milena Arakelyan

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The idea of smart logistics is still quite a complicated one. It can be used to market products to a large number of customers or to acquire raw materials of the highest quality at the lowest cost in geographically dispersed areas. The use of smart contracts in logistics and supply chain management has the potential to revolutionize the way that goods are tracked, transported, and managed. Smart contracts are simply computer programs written in one of the blockchain programming languages (Solidity, Rust, Vyper), which are capable of self-execution once the predetermined conditions are met. They can be used to automate and streamline many of the traditional manual processes that are currently used in logistics and supply chain management, including the tracking and movement of goods, the management of inventory, and the facilitation of payments and settlements between different parties in the supply chain. Currently, logistics is a core area for companies which is concerned with transporting products between parties. Still, the problem of this sector is that its scale may lead to detainments and defaults in the delivery of goods, as well as other issues. Moreover, large distributors require a large number of workers to meet all the needs of their stores. All this may contribute to big detainments in order processing and increases the potentiality of losing orders. In an attempt to break this problem, companies have automated all their procedures, contributing to a significant augmentation in the number of businesses and distributors in the logistics sector. Hence, blockchain technology and smart contracted legal agreements seem to be suitable concepts to redesign and optimize collaborative business processes and supply chains. The main purpose of this paper is to examine the scope of blockchain technology and smart contracts in the field of logistics and supply chain management. This study discusses the research question of how and to which extent smart contracts and blockchain technology can facilitate and improve the implementation of collaborative business structures for sustainable entrepreneurial activities in smart supply chains. The intention is to provide a comprehensive overview of the existing research on the use of smart contracts in logistics and supply chain management and to identify any gaps or limitations in the current knowledge on this topic. This review aims to provide a summary and evaluation of the key findings and themes that emerge from the research, as well as to suggest potential directions for future research on the use of smart contracts in logistics and supply chain management.

Keywords: smart contracts, smart logistics, smart supply chain management, blockchain and smart contracts in logistics, smart contracts for controlling supply chain management

Procedia PDF Downloads 80

Authors: Belkacem Selma, Boumediene Selma, Tourkia Guerzou, Abbes Labdelli

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Natural disasters have occurred and will continue to cause human and material damage. Therefore, the idea of "preventing" natural disasters will never be possible. However, their prediction is possible with the advancement of technology. Even if natural disasters are effectively inevitable, their consequences may be partly controlled. The rapid growth and progress of artificial intelligence (AI) had a major impact on the prediction of natural disasters and risk assessment which are necessary for effective disaster reduction. The Earthquakes prediction to prevent the loss of human lives and even property damage is an important factor; that is why it is crucial to develop techniques for predicting this natural disaster. This present study aims to analyze the ability of artificial neural networks (ANNs) to predict earthquakes that occur in a given area. The used data describe the problem of high energy (higher than 10^4J) seismic bumps forecasting in a coal mine using two long walls as an example. For this purpose, seismic bumps data obtained from mines has been analyzed. The results obtained show that the ANN with high accuracy was able to predict earthquake parameters; the classification accuracy through neural networks is more than 94%, and that the models developed are efficient and robust and depend only weakly on the initial database.

Keywords: earthquake prediction, ANN, seismic bumps

Procedia PDF Downloads 116

Authors: Wallapa Boonrod

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Thai National Education Act 1999 required all educational institutions received external quality evaluation at least once every five years. The purpose of this study was to compare the awareness in the code of ethics for nurse educators among nurse educators, professional nurses, and nursing students under The Royal Thai Army Nurse College. The sample consisted of 51 of nurse educators 200 nursing students and 340 professional nurses from Army nursing college and hospital by stratified random sampling techniques. The descriptive statistics indicated that the nurse educators, nursing students and professional nurses had different levels of awareness in the 9 roles of nurse educators: Nurse, Reliable Sacrifice, Intelligence, Giver, Nursing Skills, Teaching Responsibility, Unbiased Care, Tie to Organization, and Role Model. The code of ethics for nurse educators (CENE) measurement models from the awareness of nurse educators, professional nurses, and nursing students were well fitted with the empirical data. The CENE models from them were invariant in forms, but variant in factor loadings. Thai Army nurse educators strive to create a learning environment that nurtures the highest nursing potential and standards in their nursing students.

Keywords: awareness of the code of ethics for nurse educators, nursing college and hospital under The Royal Thai Army, Thai Army nurse educators, professional nurses

Procedia PDF Downloads 440

Authors: Duy Nhat Tran, Van Tien Pham, Quang Trung Trinh, Tien Hai Tran, Van Cong Bui

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In recent years, artificial intelligence and the Internet of Things have experienced significant advancements. Collecting image data and real-time analysis and processing of tasks have become increasingly popular in various aspects of life. Optical scanning devices are widely used to observe and analyze different environments, whether fixed outdoors, mounted on mobile devices, or used in unmanned aerial vehicles. As a result, the interaction between the physical environment and these devices has become more critical in terms of safety. Two commonly used methods for addressing these challenges are active and passive approaches. Each method has its advantages and disadvantages, but combining both methods can lead to higher efficiency. One solution is to utilize direct-drive motors for position control and real-time feedback within the operational range to determine appropriate control parameters with high precision. If the maximum motor torque is smaller than the inertial torque and the rotor reaches the operational limit, the spring system absorbs the impact force. Numerous experiments have been conducted to demonstrate the effectiveness of device protection during operation.

Keywords: optical device, collision safety, collision absorption, precise mechanics

Procedia PDF Downloads 49

Authors: Shian Wan, Yi-Chang Wang, Yu-Chien Lin

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This research discussed the various theories of service design, the importance of service design methodology, and the development of transformative service design framework. In this study, transformative service design is applied while building a new brand community service for women, children and infants retailing business. The goal is to enhance the brand recognition and customer loyalty, effectively increase the brand community engagement by embedding the brand community in social network and ultimately, strengthen the impact and the value of the company brand.

Keywords: service design, transformative service design, brand community, innovation

Procedia PDF Downloads 483

Authors: Alia El Akhrass, Raheed Al Jifri, Sara Babalghoum, Jana Bushnag

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This project delves into exploring the functionalities of Mailchimp, an artificial intelligence application. The objective is to comprehend its operations through the AI tools it offers. To achieve this, a survey was conducted among peers, seeking insights into Mailchimp's functionality, accessibility, efficiency, and overall benefits. The survey aimed to gather valuable feedback for analysis. Subsequently, a thorough analysis of the collected data was performed to identify trends, patterns, and areas of improvement. Visual representations were then crafted to effectively summarize the findings, aiding in conveying the research outcomes clearly. Founded in 2001, Mailchimp initially provided email marketing services but has since expanded into a comprehensive marketing platform. Its focus on simplicity and accessibility has contributed to its success among businesses of all sizes. Alternative platforms such as Constant Contact, AWeber, and GetResponse offer similar services with their own unique strengths. Mailchimp's journey exemplifies the importance of vision and adaptability in the ever-evolving digital marketing landscape. By prioritizing innovation, user-centricity, and customer service, Mailchimp has established itself as a trusted partner in the field of digital marketing, enabling businesses to effectively connect with their customers and achieve their marketing goals.

Keywords: email marketing, ai tool, connect, communicate, generate

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Authors: Justyna Żywiołek, Marek Matulewski

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The article presents the results of a survey conducted among students from various European countries. The aim of the study was to understand how artificial intelligence (AI) affects educational processes in a digital environment. The survey covered a wide range of topics, including students' understanding and use of AI, its impact on motivation and engagement, interaction and support issues, accessibility and equity, and data security and privacy concerns. Most respondents admitted having difficulties comprehending the advanced functions of AI in educational tools. Many students believe that excessive use of AI in education can decrease their motivation for self-study and active participation in classes. Additionally, students reported that interaction with AI-based tools is often less satisfying compared to direct contact with teachers. Furthermore, the survey highlighted inequalities in access to advanced AI tools, which can widen the educational gap between students from different economic backgrounds. Students also expressed concerns about the security and privacy of their personal data collected and processed by AI systems. The findings suggest that while AI has the potential to support digital education, significant challenges need to be addressed to make these tools more effective and acceptable for students. Recommendations include increasing training for students and teachers on using AI, providing more interactive and engaging forms of education, and implementing stricter regulations on data protection.

Keywords: AI, digital education, education tools, motivation and engagement

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Authors: Sara M. Ismael, Ali H. Al-Badi

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The rapid development and growth of technology has changed the method of obtaining information for educators and learners. Technology has created a new world of collaboration and communication among people. Incorporating new technology into the teaching process can enhance learning outcomes. Billions of individuals across the world are now connected together, and are cooperating and contributing their knowledge and intelligence. Time is no longer wasted in waiting until the teacher is ready to share information as learners can go online and get it immediately. The objectives of this paper are to understand the reasons why changes in teaching and learning methods are necessary, to find ways of improving them, and to investigate the challenges that present themselves in the adoption of new ICT tools in higher education institutes. To achieve these objectives two primary research methods were used: questionnaires, which were distributed among students at higher educational institutes and multiple interviews with faculty members (teachers) from different colleges and universities, which were conducted to find out why teaching and learning methodology should change. The findings show that both learners and educators agree that educational technology plays a significant role in enhancing instructors’ teaching style and students’ overall learning experience; however, time constraints, privacy issues, and not being provided with enough up-to-date technology do create some challenges.

Keywords: e-books, educational technology, educators, e-learning, learners, social media, Web 2.0, LMS

Procedia PDF Downloads 259

Authors: Vivek Krishna, Nikhil Jain, A. Mary Posonia A., Albert Mayan J

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Terrorism and insurgency are significant global issues that require constant attention and effort from governments and scientists worldwide. To combat these threats, nations invest billions of dollars in developing new defensive technologies to protect civilians. Breakthroughs in vehicle automation have led to the use of sophisticated machines for many dangerous and critical anti-terrorist activities. Our concept of an "Unmanned Ground Vehicle" can carry out tasks such as border security, surveillance, mine detection, and active combat independently or in tandem with human control. The robot's movement can be wirelessly controlled by a person in a distant location or can travel to a pre-programmed destination autonomously in situations where personal control is not feasible. Our defence system comprises two units: the control unit that regulates mobility and the motion tracking unit. The remote operator robot uses the camera's live visual feed to manually operate both units, and the rover can automatically detect movement. The rover is operated by manpower who controls it using a joystick or mouse, and a wireless modem enables a soldier in a combat zone to control the rover via an additional controller feature.

Keywords: robotics, computer vision, Machine learning, Artificial intelligence, future of AI

Procedia PDF Downloads 106

Authors: Torben Hansen, Lars Gronholdt, Alexander Josiassen, Anne Martensen

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Consumers often exhibit a bias in their knowledge; they often think that they know more or less than they do. The concept of 'knowledge over/underconfidence' (O/U) has in previous studies been used to investigate such knowledge bias. O/U appears as a combination of subjective and objective knowledge. Subjective knowledge relates to consumers’ perception of their knowledge, while objective knowledge relates to consumers’ absolute knowledge measured by objective standards. This separation leads to three scenarios: The consumer can either be knowledge calibrated (subjective and objective knowledge are similar), overconfident (subjective knowledge exceeds objective knowledge) or underconfident (objective knowledge exceeds subjective knowledge). Knowledge O/U is a highly useful concept in understanding consumer choice behavior. For example, knowledge overconfident individuals are likely to exaggerate their ability to make right choices, are more likely to opt out of necessary information search, spend less time to carry out a specific task than less knowledge confident consumers, and are more likely to show high financial trading volumes. Through the use of financial services as a case study, this study contributes to previous research by examining how consumer knowledge O/U affects two types of trust (broad-scope trust and narrow-scope trust) and consumer relationship satisfaction. Trust does not only concern consumer trust in individual companies (i.e., narrow.-scope confidence NST), but also concerns consumer confidence in the broader business context in which consumers plan and implement their behavior (i.e., broad scope trust, BST). NST is defined as "the expectation that the service provider can be relied on to deliver on its promises’, while BST is defined as ‘the expectation that companies within a particular business type can generally be relied on to deliver on their promises.’ This study expands our understanding of the interplay between consumer knowledge bias, consumer trust, and relationship marketing in two main ways: First, it is demonstrated that the more knowledge O/U a consumer becomes, the higher/lower NST and levels of relationship satisfaction will be. Second, it is demonstrated that BST has a negative moderating effect on the relationship between knowledge O/U and satisfaction, such that knowledge O/U has a higher positive/negative effect on relationship satisfaction when BST is low vs. high. The data for this study comprises 756 mutual fund investors. Trust is particularly important in consumers’ mutual fund behavior because mutual funds have important responsibilities in providing financial advice and in managing consumers’ funds.

Keywords: knowledge, cognitive bias, trust, customer-seller relationships, financial services

Procedia PDF Downloads 293

Authors: Lito M. Amit, Venecio U. Ultra, Young-Woong Song

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The business process outsourcing (BPO) in the Philippines is expanding rapidly attracting more than 2% of total employment. Currently, the BPO industry is confronted with several issues pertaining to sustainable productivity such as meeting the staffing gap, high rate of employees’ turnover and workforce retention, and the occupational health and safety (OHS) of call center agents. We conducted a survey of OHS programs and health concerns among call center agents in the Philippines and determined the sociocultural factors that affect the vulnerability of call center agents to occupational health risks and hazards. The majority of the agents affirmed that OHS are implemented and OHS orientation and emergency procedures were conducted at employment initiations, perceived favorable and convenient working environment except for occasional noise disturbances and acoustic shock, visual, and voice fatigues. Male agents can easily adjust to the demands and changes in their work environment and flexible work schedules than female agents. Female agents have a higher tendency to be pressured and humiliated by low work performance, experience a higher incidence of emotional abuse, psychological abuse, and experience more physical stress than male agents. The majority of the call center agents had a night-shift schedule and regardless of other factors, night shift work brings higher stress to agents. While working in a call center, higher incidence of headaches and insomnia, burnout, suppressed anger, anxiety, and depressions were experienced by female, younger (21-25 years old) and those at night shift than their counterpart. Most common musculoskeletal disorders include body pain in the neck, shoulders and back; and hand and wrist disorders and these are commonly experienced by female and younger workers. About 30% experienced symptoms of cardiovascular and gastrointestinal disorders and weakened immune systems. Overall, these findings have shown the variable vulnerability by a different subpopulation of call center agents and are important in the occupational health risk prevention and management towards a sustainable human resource for BPO industry in the Philippines.

Keywords: business process outsourcing industry, health risk of call center agents, socio-cultural determinants, Philippines

Procedia PDF Downloads 485

Authors: Elizabeth F. Rodrigues, Julia da R. Mattos, Naira Q. Leitão, Roberta T. da Cunha

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The business strategy of many companies has two factors in common: the search for the competitive edge and its long term maintenance. The thing that differentiates the companies’ performance in their abilities to set the right strategy, which depends on their capacity to analyze and apply all sort of management support tools. In this context, the sponsorship of events stands out as an important way to increase brand awareness, especially when it is a worldwide event, such as Rio 2016 Olympic and Paralympic Games. This paper will present the case of a car maker company, which chose to invest on sponsorship as a way to reach its goals and grow in the brazilian market.

Keywords: strategy, sponsorship, events, management

Procedia PDF Downloads 482

Authors: Antonios Panagopoulos, Stamoulis Georgios

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Dyslexia's diagnosis is made taking into account reading and writing skills and is carried out by qualified scientific staff. In addition, there are screening tests that are designed to give an indication of possible dyslexic difficulties. Their main advantage is that they create a pleasant environment for the user and reduce the stress that can lead to false results. An online application was created for the first time, as far as authors' knowledge, for screening Dyslexia in Greek high school students named «DyScreTe». Thus, a sample of 240 students between 16 and 18 years old in Greece was taken, of which 120 were diagnosed with dyslexia by an official authority in Greece, and 120 were typically developed. The main hypothesis that was examined is that students who were diagnosed with dyslexia by official authorities in Greece had significantly lower performance in the respective software tests. The results verified the hypothesis we made those children with dyslexia in each test had a lower performance com-pared to the type developed in successful responses, except for the intelligence test. After random sampling, it was shown that the new online application was a useful tool for screening dyslexia. However, computer evaluation cannot replace the diagnosis by a professional expert, but with the results of this application, the interdisciplinary team that deals with the differential diagnosis will create and evaluate, at a later time, the appropriate intervention program.

Keywords: dyslexia, screening tests, deficits, application

Procedia PDF Downloads 72

Authors: Michael Smalenberger

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Intelligent tutoring systems (ITS) are computer-based platforms which can incorporate artificial intelligence to provide step-by-step guidance as students practice problem-solving skills. ITS can replicate the benefits of one-on-one tutoring, foster transactivity in collaborative environments, and lead to substantial learning gains when used to supplement the instruction of a teacher or when used as the sole method of instruction. Developments improving the ease of ITS creation have recently increased their proliferation, leading many K-12 schools and institutions of higher education in the United States to regularly use ITS within classrooms. We investigated how students perceive their experience using an ITS. In this study, 111 undergraduate students used an ITS in a college-level introductory statistics course and were subsequently asked for feedback on their experience. Results show that their perceptions were generally favorable of the ITS, and most would seek to use an ITS both for STEM and non-STEM courses in the future. Along with detailed transaction-level data, this feedback also provides insights on the design of user-friendly interfaces, guidance on accessibility for students with impairments, the sequencing of exercises, students’ expectation of achievement, and comparisons to other tutoring experiences. We discuss how these findings are important for the creation, implementation, and evaluation of ITS as a mode and method of teaching and learning.

Keywords: college statistics course, intelligent tutoring systems, in vivo study, student perceptions of tutoring

Procedia PDF Downloads 93

Authors: Kingsley Oturu, Winifred Ijomah, Wale Coker, Chibueze Achi

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With the impact of BREXIT and the need for cross-border collaboration, this international research investigated the use of a conceptual model for remanufacturing medical equipment (with a focus on anesthetic machines and baby incubators). Early findings of the research suggest that contextual factors need to be taken into consideration, as well as an emphasis on cleaning (e.g., sterilization) during the process of remanufacturing medical equipment. For example, copper tubings may be more important in the remanufacturing of anesthetic equipment in tropical climates than in cold climates.

Keywords: medical equipment remanufacture, sustainability, circular business models, remanufacture process model

Procedia PDF Downloads 161

Authors: Ammara Mehmood, Aneela Zameer, Muhammad Asif Zahoor Raja, Muhammad Faisal Fateh

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In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by defining an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefficient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels.

Keywords: parameter estimation, bio-inspired computing, continuous differential evolution (CDE), periodic signals

Procedia PDF Downloads 291

Authors: Triza Edwar Fawzi Deif

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In the process of urbanization in China, new rural construction is on the ascendant, which is becoming more and more popular. Under the driving effect of rural urbanization, the house pattern and tectonic methods of traditional vernacular houses have shown great differences from the family structure and values of contemporary peasant families. Therefore, it is particularly important to find a prototype, form and strategy to make a balance between the traditional memory and modern functional requirements. In order for research to combine the regional culture with modern life, under the situation of the current batch production of new rural residences, Badie village, in Zhejiang province, is taken as the case. This paper aims to put forward a prototype which can not only meet the demand of modern life but also ensure the continuation of traditional culture and historical context for the new rural dwellings design. This research not only helps to extend the local context in the construction of the new site but also contributes to the fusion of old and new rural dwellings in the old site construction. Through the study and research of this case, the research methodology and results can be drawn as reference for the new rural construction in other areas.

Keywords: steel slag, co-product, primary coating, steel aggregate capital, rural areas, rural planning, rural governance village, design strategy, new rural dwellings, regional context, regional expression

Procedia PDF Downloads 29

Authors: G. T. Aigarinova

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This article considers the legal issues of food security as a major component of national security of the republic. The problem of food security is the top priority of the economic policy strategy of any state, the effectiveness of this solution influences social, political, and ethnic stability in society. Food security and nutrition is everyone’s business. Food security exists when all people, at all times, have physical, social and economic access to sufficient safe and nutritious food that meets their dietary needs and food preferences for an active and healthy life. By analyzing the existing legislation in the area of food security, the author identifies weaknesses and gaps, suggesting ways to improve it.

Keywords: food security, national security, agriculture, public resources, economic security

Procedia PDF Downloads 411

Authors: Seong Jun Yoon, Jasurbek Doliev, Sang Min Oh, Rodi Hartono, Kyoojae Shin

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Electric power steering (EPS), which is commonly used in electric vehicles recently, is an electric-driven steering device for vehicles. Compared to hydraulic systems, EPS offers advantages such as simple system components, easy maintenance, and improved steering performance. However, because the EPS system is a nonlinear model, difficult problems arise in controller design. To address these, various machine learning and artificial intelligence approaches, notably artificial neural networks (ANN), have been applied. ANN can effectively determine relationships between inputs and outputs in a data-driven manner. This research explores two main areas: designing an EPS identifier using an ANN-based backpropagation (BP) algorithm and enhancing the EPS system controller with an ANN-based Levenberg-Marquardt (LM) algorithm. The proposed ANN-based BP algorithm shows superior performance and accuracy compared to linear transfer function estimators, while the LM algorithm offers better input angle reference tracking and faster response times than traditional PID controllers. Overall, the proposed ANN methods demonstrate significant promise in improving EPS system performance.

Keywords: ANN backpropagation modelling, electric power steering, transfer function estimator, electrical vehicle driving system

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Authors: Ishani Maheshika

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The intermediary role performed by freight forwarders in exportation has become significant in fulfilling businesses’ supply chain needs in this dynamic world. Since the success of exporter’s business is at present, highly reliant on supply chain optimization, cost efficiency, profitability, consistent service and responsiveness, the decision of selecting the most beneficial freight forwarder has become crucial for exporters. Although there are similar foreign researches, prior researches covering Sri Lankan setting are not in existence. Moreover, results vary with time, nature of industry and business environment factors. Therefore, a study from the perspective of Sri Lankan exporters was identified as a requisite to be researched. In order to identify and prioritize key factors which have affected the exporter’s decision in selecting freight forwarders in Sri Lankan context, Sri Lankan export industry was stratified into 22 sectors based on commodity using stratified sampling technique. One exporter from each sector was then selected using judgmental sampling to have a sample of 22. Factors which were identified through a pilot survey, was organized under 6 main criteria. A questionnaire was basically developed as pairwise comparisons using 9-point semantic differential scale and comparisons were done within main criteria and subcriteria. After a pre-testing, interviews and e-mail questionnaire survey were conducted. Data were analyzed using Analytic Hierarchy Process to determine priority vectors of criteria. Customer service was found to be the most important main criterion for Sri Lankan exporters. It was followed by reliability and operational efficiency respectively. The criterion of the least importance is company background and reputation. Whereas small sized exporters pay more attention to rate, reliability is the major concern among medium and large scale exporters. Irrespective of seniority of the exporter, reliability is given the prominence. Responsiveness is the most important sub criterion among Sri Lankan exporters. Consistency of judgments with respect to main criteria was verified through consistency ratio, which was less than 10%. Being more competitive, freight forwarders should come up with customized marketing strategies based on each target group’s requirements and expectations in offering services to retain existing exporters and attract new exporters.

Keywords: analytic hierarchy process, freight forwarders, main criteria, Sri Lankan exporters, subcriteria

Procedia PDF Downloads 399

Authors: Lucia Varra, Marzia Timolo

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The interest of scholars towards corporate sustainability has strengthened in recent years in parallel with the growing need to undertake paths of cultural and organizational change, as a way for greater competitiveness and stakeholders’ satisfaction. In fact, studies on the business sustainability, while on the one hand have integrated the three dimensions of sustainability that existed for some time in the economic approaches (economic, environmental and social dimensions), on the other hand did not give rise to an organic construct that puts together the aspects of strategic management with corporate social responsibility and even less with the organizational issues. Therefore some important questions remain open: Which organizational structure and which operational mechanisms are coherent or propitious to a sustainability strategy? Existing studies appear to be fragmented, although some aspects have shared importance: knowledge management, human resource, management, leadership, innovation, etc. The construction of a model of sustainable organization that supports the sustainability strategy no longer seems to be postponed, as is its connection with the main practices of measuring corporate social responsibility performance. The paper aims to identify the organizational characteristics of a sustainable corporate. To this end, from a theoretical point of view the work examines the main existing literary contributions and, from a practical point of view, it presents a business case referring to a service organization that for years has undertaken the sustainability strategy. This paper is divided into two parts: the first part concerns a review of the main articles on the strategic management topic and the main organizational issues raised by the literature, such as knowledge management, leadership, innovation, etc.; later, a modeling of the main variables examined by scholars and an integration of these with the international measurement standards of CSR is proposed. In the second part, using the methodology of the case study company, the hypotheses and the structure of the proposed model that aims to integrate the strategic issues with the organizational aspects and measurement of sustainability performance, are applied to an Italian company, which has some organizational and human resource management interventions are in place to align strategic decisions with the structure and operating mechanisms of the structure. The case presented supports the hypotheses of the model.

Keywords: CSR, strategic management, sustainable leadership, sustainable human resource management, sustainable organization

Procedia PDF Downloads 92

Authors: Mohammad Arabi

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Business Process Reengineering (BPR) is a systematic approach to fundamentally redesign organizational processes to achieve significant improvements in organizational performance. At Fars Regional Electric Company, implementing BPR is deemed essential to increase productivity, reduce costs, and improve service quality. This article examines how BPR can help enhance the performance of Fars Regional Electric Company. The objective of this research is to evaluate and analyze the advancements in process modeling and reengineering at Fars Regional Electric Company and to provide solutions for improving the productivity and efficiency of organizational processes. This study aims to demonstrate how BPR can be used to improve organizational processes and enhance the overall performance of the company. This research employs both qualitative and quantitative research methods and includes interviews with senior managers and experts at Fars Regional Electric Company. The analytical tools include process modeling software such as Bizagi and ARIS, and statistical analysis software such as SPSS and Minitab. Data analysis was conducted using advanced statistical methods. The results indicate that the use of BPR techniques can lead to a significant reduction in process execution time and overall improvement in quality. Implementing BPR at Fars Regional Electric Company has led to increased productivity, reduced costs, and improved overall performance of the company. This study shows that with proper implementation of BPR and the use of modeling tools, the company can achieve significant improvements in its processes. Recommendations: (1) Continuous Training for Staff: Invest in continuous training of staff to enhance their skills and knowledge in BPR. (2) Use of Advanced Technologies: Utilize modeling and analysis software to improve processes. (3) Implementation of Effective Management Systems: Employ knowledge and information management systems to enhance organizational performance. (4) Continuous Monitoring and Review of Processes: Regularly review and revise processes to ensure ongoing improvements. This article highlights the importance of improving organizational processes at Fars Regional Electric Company and recommends that managers and decision-makers at the company seriously consider reengineering processes and utilizing modeling technologies to achieve developmental goals and continuous improvement.

Keywords: business process reengineering, electric company, Fars province, process modeling advancements

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Authors: Musatafa Abbas Abbood Albadr, Masri Ayob, Sabrina Tiun, Fahad Taha Al-Dhief, Mohammad Kamrul Hasan

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Breast Cancer (BC) is considered one of the most frequent reasons of cancer death in women between 40 to 55 ages. The BC is diagnosed by using digital images of the FNA (Fine Needle Aspirate) for both benign and malignant tumors of the breast mass. Therefore, this work proposes the Online Sequential Extreme Learning Machine (OSELM) algorithm for diagnosing BC by using the tumor features of the breast mass. The current work has used the Wisconsin Diagnosis Breast Cancer (WDBC) dataset, which contains 569 samples (i.e., 357 samples for benign class and 212 samples for malignant class). Further, numerous measurements of assessment were used in order to evaluate the proposed OSELM algorithm, such as specificity, precision, F-measure, accuracy, G-mean, MCC, and recall. According to the outcomes of the experiment, the highest performance of the proposed OSELM was accomplished with 97.66% accuracy, 98.39% recall, 95.31% precision, 97.25% specificity, 96.83% F-measure, 95.00% MCC, and 96.84% G-Mean. The proposed OSELM algorithm demonstrates promising results in diagnosing BC. Besides, the performance of the proposed OSELM algorithm was superior to all its comparatives with respect to the rate of classification.

Keywords: breast cancer, machine learning, online sequential extreme learning machine, artificial intelligence

Procedia PDF Downloads 99

Authors: Kritchakhris Na-Wattanaprasert

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The objective of this research is to design and develop a prototype of a key performance indicator system this is suitable for warehouse management in a case study and use requirement. In this study, we design a prototype of key performance indicator system (KPI) for warehouse case study of furniture business by methodology in step of identify scope of the research and study related papers, gather necessary data and users requirement, develop key performance indicator base on balance scorecard, design pro and database for key performance indicator, coding the program and set relationship of database and finally testing and debugging each module. This study use Balance Scorecard (BSC) for selecting and grouping key performance indicator. The system developed by using Microsoft SQL Server 2010 is used to create the system database. In regard to visual-programming language, Microsoft Visual C# 2010 is chosen as the graphic user interface development tool. This system consists of six main menus: menu login, menu main data, menu financial perspective, menu customer perspective, menu internal, and menu learning and growth perspective. Each menu consists of key performance indicator form. Each form contains a data import section, a data input section, a data searches – edit section, and a report section. The system generates outputs in 5 main reports, the KPI detail reports, KPI summary report, KPI graph report, benchmarking summary report and benchmarking graph report. The user will select the condition of the report and period time. As the system has been developed and tested, discovers that it is one of the ways to judging the extent to warehouse objectives had been achieved. Moreover, it encourages the warehouse functional proceed with more efficiency. In order to be useful propose for other industries, can adjust this system appropriately. To increase the usefulness of the key performance indicator system, the recommendations for further development are as follows: -The warehouse should review the target value and set the better suitable target periodically under the situation fluctuated in the future. -The warehouse should review the key performance indicators and set the better suitable key performance indicators periodically under the situation fluctuated in the future for increasing competitiveness and take advantage of new opportunities.

Keywords: key performance indicator, warehouse management, warehouse operation, logistics management

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Authors: Asma Omri, Iheb Sifaoui, Sofiane Sayahi, Hichem Besbes

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Future vehicle systems demand advanced capabilities, notably in-cabin life detection and driver monitoring systems, with a particular emphasis on drowsiness detection. To meet these requirements, several techniques employ artificial intelligence methods based on real-time vital sign measurements. In parallel, Frequency-Modulated Continuous-Wave (FMCW) radar technology has garnered considerable attention in the domains of healthcare and biomedical engineering for non-invasive vital sign monitoring. FMCW radar offers a multitude of advantages, including its non-intrusive nature, continuous monitoring capacity, and its ability to penetrate through clothing. In this paper, we propose a system utilizing the AWR6843AOP radar from Texas Instruments (TI) to extract precise vital sign information. The radar allows us to estimate Ballistocardiogram (BCG) signals, which capture the mechanical movements of the body, particularly the ballistic forces generated by heartbeats and respiration. These signals are rich sources of information about the cardiac cycle, rendering them suitable for heart rate estimation. The process begins with real-time subject positioning, followed by clutter removal, computation of Doppler phase differences, and the use of various filtering methods to accurately capture subtle physiological movements. To address the challenges associated with FMCW radar-based vital sign monitoring, including motion artifacts due to subjects' movement or radar micro-vibrations, Long Short-Term Memory (LSTM) networks are implemented. LSTM's adaptability to different heart rate patterns and ability to handle real-time data make it suitable for continuous monitoring applications. Several crucial steps were taken, including feature extraction (involving amplitude, time intervals, and signal morphology), sequence modeling, heart rate estimation through the analysis of detected cardiac cycles and their temporal relationships, and performance evaluation using metrics such as Root Mean Square Error (RMSE) and correlation with reference heart rate measurements. For dataset construction and LSTM training, a comprehensive data collection system was established, integrating the AWR6843AOP radar, a Heart Rate Belt, and a smart watch for ground truth measurements. Rigorous synchronization of these devices ensured data accuracy. Twenty participants engaged in various scenarios, encompassing indoor and real-world conditions within a moving vehicle equipped with the radar system. Static and dynamic subject’s conditions were considered. The heart rate estimation through LSTM outperforms traditional signal processing techniques that rely on filtering, Fast Fourier Transform (FFT), and thresholding. It delivers an average accuracy of approximately 91% with an RMSE of 1.01 beat per minute (bpm). In conclusion, this paper underscores the promising potential of FMCW radar technology integrated with artificial intelligence algorithms in the context of automotive applications. This innovation not only enhances road safety but also paves the way for its integration into the automotive ecosystem to improve driver well-being and overall vehicular safety.

Keywords: ballistocardiogram, FMCW Radar, vital sign monitoring, LSTM

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Authors: Antonyous Fawzy Boshra Girgis

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Nutrition labels are diet-related health policies. They help individuals improve food-choice decisions and reduce intake of calories and unhealthy food elements, like cholesterol. However, many individuals do not pay attention to nutrition labels or fail to appropriately understand them. According to the literature, thinking and cognitive styles can have significant effects on attention to nutrition labels. According to the author's knowledge, the effect of global/local processing on attention to nutrition labels has not been previously studied. Global/local processing encourages individuals to attend to the whole/specific parts of an object and can have a significant impact on people's visual attention. In this study, this effect was examined with an experimental design using the eye-tracking technique. The research hypothesis was that individuals with local processing would pay more attention to nutrition labels, including nutrition tables and traffic lights. An experiment was designed with two conditions: global and local information processing. Forty participants were randomly assigned to either global or local conditions, and their processing style was manipulated accordingly. Results supported the hypothesis for nutrition tables but not for traffic lights.

Keywords: nutrition, public health, SA Harvest, foodeye-tracking, nutrition labelling, global/local information processing, individual differencesmobile computing, cloud computing, nutrition label use, nutrition management, barcode scanning

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Authors: Mohamed Aljarallah, Mohamed Nurullah, George Saridakis

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This paper aims and objectives are to investigate how the structural change of the financial regulatory bodies affect the financial supervision and how the regulators can design such a structure with taking into account; the Central Bank, the conduct of business and the prudential regulators, it will also consider looking at the structure of the international regulatory bodies and what barriers are found. There will be five questions to be answered; should conduct of business and prudential regulation be separated? Should the financial supervision and financial stability be separated? Should the financial supervision be under the Central Bank? To what extent the politician should intervene in changing the regulatory and supervisory structure? What should be the regulatory and supervisory structure when there is financial conglomerate? Semi structure interview design will be applied. This research sample selection contains a collective of financial regulators and supervisors from the emerged and emerging countries. Moreover, financial regulators and supervisors must be at a senior level at their organisations. Additionally, senior financial regulators and supervisors would come from different authorities and from around the world. For instance, one of the participants comes from the International Bank Settlements, others come from European Central Bank, and an additional one will come from Hong Kong Monetary Authority and others. Such a variety aims to fulfil the aims and objectives of the research and cover the research questions. The analysis process starts with transcription of the interview, using Nvivo software for coding, applying thematic interview to generate the main themes. The major findings of the study are as follow. First, organisational structure changes quite frequently if the mandates are not clear. Second, measuring structural change is difficult, which makes the whole process unclear. Third, effective coordination and communication are what regulators looking for when they change the structure and that requires; openness, trust, and incentive. In addition to that, issues appear during the event of crisis tend to be the reason why the structure change. Also, the development of the market sometime causes a change in the regulatory structure. And, some structural change occurs simply because of the international trend, fashion, or other countries' experiences. Furthermore, when the top management change the structure tends to change. Moreover, the structure change due to the political change, or politicians try to show they are doing something. Finally, fear of being blamed can be a driver of structural change. In conclusion, this research aims to provide an insight from the senior regulators and supervisors from fifty different countries to have a clear understanding of why the regulatory structure keeps changing from time to time through a qualitative approach, namely, semi-structure interview.

Keywords: financial regulation bodies, financial regulatory structure, global financial regulation, financial crisis

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Authors: Patrick Innocenti, Elias Montini, Silvia Menato, Marzio Sorlini

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Documented experiences of industrial symbiosis are always triggered and driven only by economic goals: environmental and (even rarely) social results are sometimes assessed and declared as effects of virtuous behaviours, but are merely casual and un-pursued side externalities. Even worse: all the symbiotic project candidates entailing economic loss for just one of the (also dozen) partners are simply stopped without considering the overall benefit for the whole partnership. The here-presented approach aims at providing methodologies and tools to effectively manage these situations and fostering the implementation of virtuous symbiotic investments in manufacturing aggregations for a more sustainable production.

Keywords: business model, industrial symbiosis, industrial agglomerations, sustainability

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Authors: James Forren

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This research paper details a recent demonstrator project in which digital form found textile structures were built by human craftspersons wearing augmented reality (AR) head-worn displays (HWDs). The project utilized a wet-state natural fiber / cementitious matrix composite to generate minimal bending shapes in tension which, when cured and rotated, performed as minimal-bending compression members. The significance of the project is that it synthesizes computational structural simulations with visually guided handcraft production. Computational and physical form-finding methods with textiles are well characterized in the development of architectural form. One difficulty, however, is physically building computer simulations: often requiring complicated digital fabrication workflows. However, AR HWDs have been used to build a complex digital form from bricks, wood, plastic, and steel without digital fabrication devices. These projects utilize, instead, the tacit knowledge motor schema of the human craftsperson. Computational simulations offer unprecedented speed and performance in solving complex structural problems. Human craftspersons possess highly efficient complex spatial reasoning motor schemas. And textiles offer efficient form-generating possibilities for individual structural members and overall structural forms. This project proposes that the synthesis of these three modalities of structural problem-solving – computational, human, and material - may not only develop efficient structural form but offer further creative potentialities when the respective intelligence of each modality is productively leveraged. The project methodology pertains to its three modalities of production: 1) computational, 2) human, and 3) material. A proprietary three-dimensional graphic statics simulator generated a three-legged arch as a wireframe model. This wireframe was discretized into nine modules, three modules per leg. Each module was modeled as a woven matrix of one-inch diameter chords. And each woven matrix was transmitted to a holographic engine running on HWDs. Craftspersons wearing the HWDs then wove wet cementitious chords within a simple falsework frame to match the minimal bending form displayed in front of them. Once the woven components cured, they were demounted from the frame. The components were then assembled into a full structure using the holographically displayed computational model as a guide. The assembled structure was approximately eighteen feet in diameter and ten feet in height and matched the holographic model to under an inch of tolerance. The construction validated the computational simulation of the minimal bending form as it was dimensionally stable for a ten-day period, after which it was disassembled. The demonstrator illustrated the facility with which computationally derived, a structurally stable form could be achieved by the holographically guided, complex three-dimensional motor schema of the human craftsperson. However, the workflow traveled unidirectionally from computer to human to material: failing to fully leverage the intelligence of each modality. Subsequent research – a workshop testing human interaction with a physics engine simulation of string networks; and research on the use of HWDs to capture hand gestures in weaving seeks to develop further interactivity with rope and chord towards a bi-directional workflow within full-scale building environments.

Keywords: augmented reality, cementitious composites, computational form finding, textile structures

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Authors: Aya Salama

Abstract:

Digital Twin is an emerging research topic that attracted researchers in the last decade. It is used in many fields, such as smart manufacturing and smart healthcare because it saves time and money. It is usually related to other technologies such as Data Mining, Artificial Intelligence, and Machine Learning. However, Human digital twin (HDT), in specific, is still a novel idea that still needs to prove its feasibility. HDT expands the idea of Digital Twin to human beings, which are living beings and different from the inanimate physical entities. The goal of this research was to create a Human digital twin that is responsible for real-time human replies automation by simulating human behavior. For this reason, clustering, supervised classification, topic extraction, and sentiment analysis were studied in this paper. The feasibility of the HDT for personal replies generation on social messaging applications was proved in this work. The overall accuracy of the proposed approach in this paper was 63% which is a very promising result that can open the way for researchers to expand the idea of HDT. This was achieved by using Random Forest for clustering the question data base and matching new questions. K-nearest neighbor was also applied for sentiment analysis.

Keywords: human digital twin, sentiment analysis, topic extraction, supervised machine learning, unsupervised machine learning, classification, clustering

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