Abstract: Digital transformation is about identifying the necessary changes of the entire business model, rethinking how to transform the traditional operations into digital ones that can create better value to its customers. Efforts are common across industries, but they often fail due to a lack of understanding of the factors required to focus on and change to be able to embark in digital transformation successfully. Further research is required to bridge the knowledge gap between academia and industry to support companies starting their digital transformation journey. To date there is no consensus on digital transformation key success factors. Therefore, the aim of this paper is to identify the success factors in digital transformation journey, throughout conducting a systematic literature review of 134 peer-reviewed articles to get better insights regarding the research progress in this field. After completing the systematic literature review it will be followed by Delphi study to get experts consensus on the most significant factors affecting digital transformation implementation. The findings indicate that organizations undergoing digital transformation should focus mainly on (1) well managed digital transformation activities; (2) digital business strategy; (3) supportive culture; (4) top management support; (5) organizational change capabilities.
Abstract: This research aimed at developing a web-based mobile system and figuring out a better understanding of how could “web-based mobile system supports farmers in Kebbi State”. Thus, by finding out the answers to the research questions, a conceptual framework of the entire system was implemented using Unified Modelling Language (UML). The work involved a review of existing research on web-based mobile technology for farmers in some countries and other geographical areas within Nigeria. This research explored how farmers in Northern Nigeria, especially in Kebbi state, make use of the web-based mobile system for agribusiness. Also, the benefits of using web-based mobile systems and the challenges farmers face using such systems were examined. Considering the dynamic nature of theory of information and communication technology; this research employed survey and focus group discussion (FGD) methods. Stratified, random, purposive, and convenience sampling techniques were adopted to select the sample. A questionnaire and FGD guide were used to collect data. The survey finds that most of the Kebbi state farms use their alternative medium to get relevant information for their agribusiness. Also, the research reveals that using a web-based mobile system can benefit farmers significantly. Finally, the study has successfully developed and implemented the proposed system using mobile technology in addition to the framework design.
Abstract: This work describes a system that uses electromyography (EMG) signals obtained from muscle sensors and an Artificial Neural Network (ANN) for signal classification and pattern recognition that is used to control a small unmanned aerial vehicle using specific arm movements. The main objective of this endeavor is the development of an intelligent interface that allows the user to control the flight of a drone beyond direct manual control. The sensor used were the MyoWare Muscle sensor which contains two EMG electrodes used to collect signals from the posterior (extensor) and anterior (flexor) forearm, and the bicep. The collection of the raw signals from each sensor was performed using an Arduino Uno. Data processing algorithms were developed with the purpose of classifying the signals generated by the arm’s muscles when performing specific movements, namely: flexing, resting, and motion of the arm. With these arm motions roll control of the drone was achieved. MATLAB software was utilized to condition the signals and prepare them for the classification. To generate the input vector for the ANN and perform the classification, the root mean square and the standard deviation were processed for the signals from each electrode. The neuromuscular information was trained using an ANN with a single 10 neurons hidden layer to categorize the four targets. The result of the classification shows that an accuracy of 97.5% was obtained. Afterwards, classification results are used to generate the appropriate control signals from the computer to the drone through a Wi-Fi network connection. These procedures were successfully tested, where the drone responded successfully in real time to the commanded inputs.
Abstract: As more parts of the power grid become connected to the internet, the risk of cyberattacks increases. To identify the cybersecurity threats and subsequently reduce vulnerabilities, the common practice is to carry out a cybersecurity risk assessment. For safety classified systems and products, there is also a need for safety risk assessments in addition to the cybersecurity risk assessment to identify and reduce safety risks. These two risk assessments are usually done separately, but since cybersecurity and functional safety are often related, a more comprehensive method covering both aspects is needed. Some work addressing this has been done for specific domains like the automotive domain, but more general methods suitable for, e.g., Intelligent Distributed Grids, are still missing. One such method from the automotive domain is the Security-Aware Hazard Analysis and Risk Assessment (SAHARA) method that combines safety and cybersecurity risk assessments. This paper presents an approach where the SAHARA method has been modified to be more suitable for larger distributed systems. The adapted SAHARA method has a more general risk assessment approach than the original SAHARA. The proposed method has been successfully applied on two use cases of an intelligent distributed grid.
Abstract: This paper is a result of implemented research on proposed introduced methodology for nautical ports capacity planning by introducing a multi-criteria approach of defined criteria in the Adriatic Sea region. The purpose was analyzing the determinants - characteristics of infrastructure and services of nautical ports capacity allocated, especially nowadays due to COVID-19 pandemic, as crucial for successful operation of nautical ports. Giving the importance of the defined priorities for short-term and long-term planning is essential not only in terms of the development of nautical tourism, but also in terms of developing the maritime system, but unfortunately this is not always carried out. Evaluation of the use of resources should follow from a detailed analysis of all aspects of resources bearing in mind that nautical tourism used resources in a sustainable manner and generates effects in the tourism and maritime sectors. Consequently, identified multiplier effect of nautical tourism, which should be defined and quantified in detail, should be one of the major competitive products on the Croatian Adriatic and the Mediterranean. Research of nautical tourism is necessary to quantify the effects and required planning system development. In the future, the greatest threat to long-term sustainable development of nautical tourism can be its further uncontrolled or unlimited and undirected development, especially under pressure markedly higher demand than supply for new moorings in the Mediterranean. Results of this implemented research are applicable to nautical ports management and decision makers of maritime transport system development. This paper will present implemented research and obtained result - developed methodology for nautical port capacity planning - Port Capacity Planning Multi-criteria decision-making. A proposed methodological approach of multi-criteria capacity planning includes four criteria (spatial - transport, cost - infrastructure, ecological and organizational criteria, and additional services). The importance of the criteria and sub-criteria is evaluated and carried out the basis for a sensitivity analysis of the importance of the criteria and sub-criteria. Based on the analysis of the identified and quantified importance of certain criteria and sub-criteria as well as sensitivity analysis and analysis of changes of the quantified importance scientific and applicable results will be presented. These obtained results have practical applicability by management of nautical ports in the planning of increasing capacity and further development and for the adaptation of existing nautical ports. The obtained research is applicable and replicable in other seas and results are especially important and useful in this COVID-19 pandemic challenging maritime development framework.
Abstract: Bone Scaffolds are fundamental architecture or a support structure that allows the regeneration of lost or damaged tissues and they are developed as a crucial tool in biomedical engineering. The structure of bone scaffolds plays an important role in treating bone defects. The shape of the bone scaffold performs a vital role, specifically pore size and shape, which help understand the behavior and strength of the scaffold. In this article, first, fundamental aspects of bone scaffold design are established. Second, the behavior of each architecture of the bone scaffold with biomaterials is discussed. Finally, for each structure, the stress analysis was carried out. This study aimed to design a porous and mechanically strong bone regeneration scaffold that can be successfully manufactured. Four porous architectures of the bone scaffold were designed using Rhinoceros solid modelling software. The structure model consisted of repeatable unit cells arranged in layers to fill the chosen scaffold volume. The mechanical behavior of used biocompatible material is studied with the help of ANSYS 19.2 software. It is also playing significant role to predict the strength of defined structures or 3 dimensional models.
Abstract: Purpose: The aim of this research is to explore and discuss innovation-workspaces, and how the design of the workspace has the potential to boost the work process and encourage employees’ satisfaction, leading to inventive and creative results. Background: The relationship between the workers and the work environment has a strong potential to enhance work outcomes when optimized for work goals. Innovation-work environment can benefit employees’ satisfaction, health, and performance. To understand this complex relationship, this research explores innovation-work environments. Methods: A review of 26 peer-reviewed articles, seven books, and 23 companies’ websites was conducted; in addition, five case studies were analyzed to deduce appropriate examples for the study. Results: The research found all successful five innovation environments focused on two aspects: first, workers’ satisfaction and comfort, which includes a focus on physical, functional, and psychological comfort; second aspect, all five centers were diverse work environments that addressed workers’ needs, design for individuals and teamwork, design for workers’ freedom, and design for increasing interaction. Conclusion: understanding individuals' needs and creating work environments that enhance interaction between workers and with the space are key aspects of successful innovation-work environments.
Abstract: A business decision to move to the cloud brings fundamental changes in how an organization develops and delivers its Information Technology solutions. The accelerated pace of digital transformation across businesses and government agencies increases the reliance on cloud-based services. Collecting, managing, and retaining large amounts of data in cloud environments make information security and data privacy protection essential. It becomes even more important to understand what key factors drive successful cloud adoption following the commencement of the Privacy Amendment Notifiable Data Breaches (NDB) Act 2017 in Australia as the regulatory changes impact many organizations and industries. This quantitative correlational research investigated the governance, risk management, and compliance factors contributing to cloud security success. The factors influence the adoption of cloud computing within an organizational context after the commencement of the NDB scheme. The results and findings demonstrated that corporate information security policies, data storage location, management understanding of data governance responsibilities, and regular compliance assessments are the factors influencing cloud computing adoption. The research has implications for organizations, future researchers, practitioners, policymakers, and cloud computing providers to meet the rapidly changing regulatory and compliance requirements.
Abstract: The death of a sibling in childhood leads to significant impacts on both personal and family development of the surviving siblings, however, both short-term and long-term effects of sibling loss in Chinese societies such as Hong Kong have been inadequately documented in the literature. This paper explores the experience of encountering siblings’ death during childhood with the use of semi-structured interviews. Through thematic analysis, the author explores the impacts on surviving siblings’ emotions, coping styles, struggles and challenges and personal development. Furthermore, the influences on family dynamics are explored thoroughly, including the changes in family atmosphere, family roles, family relationship, family communication and parenting styles. More importantly, the author identifies (i) existing continuing bonds; (ii) crying; (iii) adequate social support; (iv) hiding own emotions as a gesture of protecting parents as the crucial elements pertinent to surviving siblings’ successful adaptation in the face of sibling loss. In addition, “child-centered” and “family-centered” service implications of families with a sibling's death in a Chinese context are discussed.
Abstract: Si-based double-junction tandem solar cells have become a popular research topic because of the advantages of low manufacturing cost and high energy conversion efficiency. However, there is no set of calculations to select the appropriate top cell materials. Therefore, this paper will propose a simple but practical selection method. First of all, we calculate the S-Q limit and explain the reasons for developing tandem solar cells. Secondly, we calculate the theoretical energy conversion efficiency of the double-junction tandem solar cells while combining the commercial monocrystalline Si and materials' practical efficiency to consider the actual situation. Finally, we conservatively conclude that if considering 75% performance of the theoretical energy conversion efficiency of the top cell, the suitable bandgap energy range will fall between 1.38 eV to 2.5 eV. Besides, we also briefly describe some improvements of several proper materials, CZTS, CdSe, Cu2O, ZnTe, and CdS, hoping that future research can select and manufacture high-efficiency Si-based tandem solar cells based on this paper successfully. Most importantly, our calculation method is not limited to silicon solely. If other materials’ performances match or surpass silicon's ability in the future, researchers can also apply this set of deduction processes.
Abstract: In higher education, a great degree of importance is placed on the internationalisation of the student experience. This is seen as a valuable contributor to elements such as building confidence, broadening knowledge, creating networks, and connections and enhancing employability for current students who will become the next generation of managers in technology and business. The COVID-19 pandemic has affected all areas of people’s lives. The limitations of travel coupled with the fears and concerns generated by the health risks have dramatically reduced the opportunity for students to engage with this agenda. Institutions of higher education have been required to rethink fundamental aspects of their business model from recruitment and enrolment, through learning approaches, assessment methods and the pathway to employment. This paper presents a case study which focuses on student mobility and how the physical experience of being in another country either to study, to work, to volunteer or to gain cultural and social enhancement has of necessity been replaced by alternative approaches. It considers trans-national education as an alternative to physical study overseas, virtual mobility and internships as an alternative to international work experience and adopting collaborative on-line projects as an alternative to in-person encounters. The paper concludes that although these elements have been adopted to address the current situation, the lessons learnt and the feedback gained suggests that they have contributed successfully in new and sometimes unexpected ways, and that they will persist beyond the present to become part of the "new normal" for the future. That being the case, senior leaders of institutions of higher education will be required to revisit their international plans and to rewrite their international strategies to take account of and build upon these changes.
Abstract: This paper presents the results of the study on the estimation of fly ash, slag and cement contents in blended and composite cements by selective dissolution method. Types of cement samples investigated include Ordinary Portland Cement (OPC) with fly ash as performance improver, OPC with slag as performance improver, Portland Pozzolana Cement (PPC), Portland Slag Cement (PSC) and composite cement confirming to respective Indian Standards. Slag and OPC contents in PSC were estimated by selectively dissolving OPC in stage 1 and selectively dissolving slag in stage 2. In the case of composite cement sample, the percentage of cement, slag and fly ash were estimated systematically by selective dissolution of cement, slag and fly ash in three stages. In the first stage, cement is dissolved and separated by leaving the residue of slag and fly ash, designated as R1. The second stage involves gravimetric estimation of fractions of OPC, residue and selective dissolution of fly ash and slag contents. Fly ash content, R2 was estimated through gravimetric analysis. Thereafter, the difference between the R1 and R2 is considered as slag content. The obtained results of cement, fly ash and slag using selective dissolution method showed 10% of standard deviation with the corresponding percentage of respective constituents. The results suggest that this selective dissolution method can be successfully used for estimation of OPC and Supplementary Cementitious material (SCM) contents in different types of cements.
Abstract: Entrepreneurship is an essential source of economic growth and a prominent factor influencing socio-economic development. Entrepreneurship education educates and enhances entrepreneurial activity. This study aims to understand current trends in entrepreneurship education and evaluate the effectiveness of diverse entrepreneurship education programs. An increasing number of universities offer entrepreneurship education courses to create and successfully continue entrepreneurial ventures. Despite the prevalence of entrepreneurship education, research studies lack inconsistency about the effectiveness of entrepreneurship education to promote and develop entrepreneurship. Strategies to develop entrepreneurial attitudes and intentions among individuals are hindered by a lack of understanding of entrepreneurs' educational purposes, components, methodology, and resources required. Lack of adequate entrepreneurship education has been linked with low self-efficacy and lack of entrepreneurial intent. Moreover, in the age of digitisation and during the COVID-19 pandemic, digital learning platforms (e.g. online entrepreneurship education courses and programs) and other digital tools (e.g. digital game-based entrepreneurship education) have become more relevant to entrepreneurship education. This paper contributes to the continuation of academic literature in entrepreneurship education by evaluating and assessing current trends in entrepreneurship education programs, leading to better understanding to reduce gaps between entrepreneurial development requirements and higher education institutions.
Abstract: In recent years, a nondestructive elemental analysis method based on muonic X-ray measurements has been developed and applied for various samples. Muonic X-rays are emitted after the formation of a muonic atom, which occurs when a negatively charged muon is captured in a muon atomic orbit around the nucleus. Because muonic X-rays have a higher energy than electronic X-rays due to the muon mass, they can be measured without being absorbed by a material. Thus, estimating the two-dimensional (2D) elemental distribution of a sample became possible using an X-ray imaging detector. In this work, we report a non-destructive imaging experiment using muonic X-rays at Japan Proton Accelerator Research Complex. The irradiated target consisted of a polypropylene material, and a double-sided silicon strip detector, which was developed as an imaging detector for astronomical obervation, was employed. A peak corresponding to muonic X-rays from the carbon atoms in the target was clearly observed in the energy spectrum at an energy of 14 keV, and 2D visualizations were successfully reconstructed to reveal the projection image from the target. This result demonstrates the potential of the nondestructive elemental imaging method that is based on muonic X-ray measurement. To obtain a higher position resolution for imaging a smaller target, a new detector system will be developed to improve the statistical analysis in further research.
Abstract: One of the most common fields of natural language processing (NLP) is sentimental analysis. The inferred feeling in the text can be successfully mined for various events using sentiment analysis. Twitter is viewed as a reliable data point for sentimental analytics studies since people are using social media to receive and exchange different types of data on a broad scale during the COVID-19 epidemic. The processing of such data may aid in making critical decisions on how to keep the situation under control. The aim of this research is to look at how sentimental states differed in a single geographic region during the lockdown at two different times.1162 tweets were analyzed related to the COVID-19 pandemic lockdown using keywords hashtags (lockdown, COVID-19) for the first sample tweets were from March 23, 2020, until April 23, 2020, and the second sample for the following year was from March 1, 2021, until April 4, 2021. Natural language processing (NLP), which is a form of Artificial intelligent was used for this research to calculate the sentiment value of all of the tweets by using AFINN Lexicon sentiment analysis method. The findings revealed that the sentimental condition in both different times during the region's lockdown was positive in the samples of this study, which are unique to the specific geographical area of New Zealand. This research suggests applied machine learning sentimental method such as Crystal Feel and extended the size of the sample tweet by using multiple tweets over a longer period of time.
Abstract: In March 2020, in Spain, a sanitary and unexpected crisis caused by COVID-19 was declared. All of a sudden, all degrees, classes and evaluation tests and projects had to be transformed into online activities. However, the chaotic situation generated by a complex operation like that, executed without any well-established procedure, led to very different experiences and, finally, results. In this paper, we are describing three experiences in two different Universities in Madrid. On the one hand, the Technical University of Madrid, a public university with little experience in online education was considered. On the other hand, Alfonso X el Sabio University, a private university with more than five years of experience in online teaching was involved. All analyzed subjects were related to computer engineering. Professors and students answered a survey and personal interviews were also carried out. Besides, the professors’ workload and the students’ academic results were also compared. From the comparative analysis of all these experiences, we are extracting the most successful strategies, methodologies, and activities. The recommendations in this paper will be useful for courses during the next months when the sanitary situation is still affecting an educational organization. While, at the same time, they will be considered as input for the upcoming digitalization process of higher education.
Abstract: Developing new medicine and health solutions and improving patient health currently rely on the successful execution of clinical trials, which generate relevant safety and efficacy data. For their success, recruitment and retention of participants are some of the most challenging aspects of protocol adherence. Main barriers include: i) lack of awareness of clinical trials; ii) long distance from the clinical site; iii) the burden on participants, including the duration and number of clinical visits, and iv) high dropout rate. Most of these aspects could be addressed with a new paradigm, namely the Remote Decentralized Clinical Trials (RDCTs). Furthermore, the COVID-19 pandemic has highlighted additional advantages and challenges for RDCTs in practice, allowing participants to join trials from home and not depending on site visits, etc. Nevertheless, RDCTs should follow the process and the quality assurance of conventional clinical trials, which involve several processes. For each part of the trial, the Building Blocks, existing software and technologies were assessed through a systematic search. The technology needed to perform RDCTs is widely available and validated but is yet segmented and developed in silos, as different software solutions address different parts of the trial and at various levels. The current paper is analyzing the availability of technology to perform RDCTs, identifying gaps and providing an overview of Basic Building Blocks and functionalities that need to be covered to support the described processes.
Abstract: Marine shipping has now become one of the major worldwide contributors to pollution and greenhouse gas emissions. Hybrid ships technology based on multiple energy sources has taken a great scope of research to get rid of ship emissions and cut down fuel expenses. Insufficiency between power generated and the demand load to withstand the transient behavior on ships during severe climate conditions will lead to a blackout. Thus, an efficient energy management system (EMS) is a mandatory scope for achieving higher system efficiency while enhancing the lifetime of the onboard storage systems is another salient EMS scope. Considering energy storage system conditions, both the battery state of charge (SOC) and temperature represent important parameters to prevent any malfunction of the storage system that eventually degrades the whole system. In this paper, a two battery packs ratio fuzzy logic control model is proposed. The overall aim is to control the charging/discharging current while including both the battery SOC and temperature in the energy management system. The full designs of the proposed controllers are described and simulated using Matlab. The results prove the successfulness of the proposed controller in stabilizing the system voltage during both loading and unloading while keeping the energy storage system in a healthy condition.
Abstract: One of the most relevant phenomena in manufacturing is the residual stress state development through the manufacturing chain. In most cases, the residual stresses have their origin in the heterogenous plastification produced by the processes. Although a few manufacturing processes have been successfully approached by numerical modeling, there is still lack of understanding on how these processes' interactions will affect the final stress state. The objective of this work is to analyze the effect of the grinding procedure on the residual stress state generated by a quasi-static indentation. The model consists in a simplified approach of shot peening, modeling four cases with variations in indenter size and force. This model was validated through topography, measured by optical 3D focus-variation. The indentation model configured with two loads was then exposed to two grinding procedures and the result was analyzed. It was observed that the grinding procedure will have a significant effect on the stress state.
Abstract: Detrimental effects of lunar dust on space hardware, spacesuits, and astronauts’ health have been already identified during Apollo missions. Developing effective dust mitigation technologies is critically important for successful space exploration and related missions in NASA applications. In this study, an electrostatic cleaning system (ECS) integrated with a negatively ionized Thunderon brush was developed to mitigate small-sized lunar dust particles with diameters ranging from 0.04 µm to 35 µm, and the mean and median size of 7 µm and 5 µm, respectively. It was found that the frequency pulses of the negative ion generator caused particles to stick to the Thunderon bristles and repel between the pulses. The brush was used manually to ensure that particles were removed from areas where the ECS failed to mitigate the lunar simulant. The acquired data demonstrated that the developed system removed over 91-96% of the lunar dust particles. The present study was performed as a proof-of-concept to enhance the cleaning performance of ECSs by integrating a brushing process. Suggestions were made to further improve the performance of the developed technology through future research.