Digital marketing is an integral part of the process of digital business transformation. It incorporates new marketing techniques that are based on information and communication technologies. For this reason, its application in practice is a prerequisite for the successful development of the business in the contemporary market conditions. The object of this paper is the digital marketing and the subject is the digital marketing advantages and disadvantages. The first purpose of this paper is to systemize the various terms for digital marketing used in the specialized literature and the Internet and to show the differences between them. The second is to present the characteristics of the main advantages and disadvantages of digital marketing. Knowing them in depth, companies will be able to develop effective digital marketing strategies that have high potential to achieve company goals and at the same time are suitable to their profile. Thereby, they will be able to determine to what extent and which tools of the whole digital marketing palette are best suited to their marketing activities.
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S S Veleva and A I Tsvetanova 2020 IOP Conf. Ser.: Mater. Sci. Eng. 940 012065
S Anu Mary Ealia and M P Saravanakumar 2017 IOP Conf. Ser.: Mater. Sci. Eng. 263 032019
As per ISO and ASTM standards, nanoparticles are particles of sizes ranging from 1 to 100nm with one or more dimensions. The nanoparticles are generally classified into the organic, inorganic and carbon based particles in nanometric scale that has improved properties compared to larger sizes of respective materials. The nanoparticles show enhanced properties such as high reactivity, strength, surface area, sensitivity, stability, etc. because of their small size. The nanoparticles are synthesised by various methods for research and commercial uses that are classified into three main types namely physical, chemical and mechanical processes that has seen a vast improvement over time. This paper presents a review on nanoparticles, their types, properties, synthesis methods and its applications in the field of environment.
Harshit Jindal et al 2021 IOP Conf. Ser.: Mater. Sci. Eng. 1022 012072
Day by day the cases of heart diseases are increasing at a rapid rate and it's very Important and concerning to predict any such diseases beforehand. This diagnosis is a difficult task i.e. it should be performed precisely and efficiently. The research paper mainly focuses on which patient is more likely to have a heart disease based on various medical attributes. We prepared a heart disease prediction system to predict whether the patient is likely to be diagnosed with a heart disease or not using the medical history of the patient. We used different algorithms of machine learning such as logistic regression and KNN to predict and classify the patient with heart disease. A quite Helpful approach was used to regulate how the model can be used to improve the accuracy of prediction of Heart Attack in any individual. The strength of the proposed model was quiet satisfying and was able to predict evidence of having a heart disease in a particular individual by using KNN and Logistic Regression which showed a good accuracy in comparison to the previously used classifier such as naive bayes etc. So a quiet significant amount of pressure has been lift off by using the given model in finding the probability of the classifier to correctly and accurately identify the heart disease. The Given heart disease prediction system enhances medical care and reduces the cost. This project gives us significant knowledge that can help us predict the patients with heart disease It is implemented on the.pynb format.
Z Khanam et al 2021 IOP Conf. Ser.: Mater. Sci. Eng. 1099 012040
The fake news on social media and various other media is wide spreading and is a matter of serious concern due to its ability to cause a lot of social and national damage with destructive impacts. A lot of research is already focused on detecting it. This paper makes an analysis of the research related to fake news detection and explores the traditional machine learning models to choose the best, in order to create a model of a product with supervised machine learning algorithm, that can classify fake news as true or false, by using tools like python scikit-learn, NLP for textual analysis. This process will result in feature extraction and vectorization; we propose using Python scikit-learn library to perform tokenization and feature extraction of text data, because this library contains useful tools like Count Vectorizer and Tiff Vectorizer. Then, we will perform feature selection methods, to experiment and choose the best fit features to obtain the highest precision, according to confusion matrix results.
N R E Lim et al 2021 IOP Conf. Ser.: Mater. Sci. Eng. 1109 012031
Groundbreaking advancements have driven significant industries to adopt and take advantage of the key technologies in order to thrive in these adjustments coming from the Fourth Industrial Revolution (FIRe). However, with the threat of the Coronavirus disease 2019 (COVID-19) causing catastrophic setback to the society and economy, scientific endeavors have shifted towards finding a solution to this pandemic. It is high time to evaluate how the current technology from the FIRe can help a country, such as the Philippines, survive such outbreaks and unforeseen circumstances. Advancements in the field of nanotechnology aim to develop smaller and inexpensive testers, and overall newer and more effective medical solutions. However, the extent on how these technologies can be realized depends on the interplay between the country's policies, and the strong link between industry and academe. This paper raises policy recommendations from synthesizing the trends in nanotechnology and forecasting how it develops so as the country can readily adapt. Moreover, this paper identifies the barriers and constraints, as well as the factors necessary for the technology adoption in the country.
Edreis Edreis and A Petrov 2020 IOP Conf. Ser.: Mater. Sci. Eng. 963 012027
Annotation The heat exchanger as the main element in various types of energy complex is widely studied in technological and production processes. Heat exchangers are classified according to their application. Therefore, in this article we will consider the main types of heat exchange equipment, the choice of a specific type, depending on temperature, flow, pressure drop, and so on. The paper also provides a brief description of software for calculating, modeling and designing CFD, the advantages of each of the methods used to study heat transfer and its efficiency.
S.J Niranjana et al 2018 IOP Conf. Ser.: Mater. Sci. Eng. 376 012135
In this project we are designing a pressure vessel using ASME section VIII and Division 2, designing a closed container to find the required thickness of the shell, head, nozzle and leg support. Uniform thickness assigned to the entire vessel, Modelling of the pressure vessel is carried out using Pro-e 2.0; meshing is carried out using Hypermesh 6.1. Here we used 2D Quad element for the meshing, Analysis is carried out using ANSYS Software 11 for two different cases, working pressure and Maximum operating pressure, fatigue analysis is carried out, and the result is 106. Finally, theoretical validation is carried out for the entire model, And the results are within the limit.
S Y Chia and M W Lim 2022 IOP Conf. Ser.: Mater. Sci. Eng. 1257 012001
Relative humidity of ambient air is a critical parameter for crop production as it influences the water balance and photosynthesis process in the plants. A comprehensive review on leafy, fruiting, flowering plants and grains were conducted to determine the effects of varying humidity levels on plant growth. Data from published works concluded that the plant growth improved with increasing humidity, as higher humidity conditions help to keep the stomata open to maintain the photosynthesis process and minimize evaporation process of the plants. By using regression analysis, it is forecasted that the increase in the air relative humidity by 10% would increase the leaf length, width and aerial dry weight for Lactuca Sativa by 10±3%, 2±5% and 28±3% respectively. The data trend suggests that the optimal relative humidity that could improve plant growth is 85±2%, as low humidity below optimum level will increase stomatal resistance, which leads to a reduction of carbon dioxide uptake and photosynthesis rate. Inversely, relative humidity above the optimal levels will adversely reduce the transpiration rate, which negatively affects the plant growth and leaf development due to impaired nutrient assimilation. The outcome of this study provides an insight for the development of plant growth forecasting model.
Zuraina Ali 2020 IOP Conf. Ser.: Mater. Sci. Eng. 769 012043
The uses of Artificial Intelligence (AI) seems to be relevant in many fields nowadays due to its ability in providing a simulation of human intelligence processes that are handled by machines; in particular computer systems. This paper concerns with reviewing the uses of AI in language teaching and learning. In particular, it reviews the research on the uses of AI in its application in the learning and teaching of language. Qualitative research method; specifically content analysis, is employed as the technique to review the articles that are obtained from relevant databases. Findings from the study reveal that there are four (4) themes emerge in the uses of AI in relation to teaching and learning a language. The uses of AI for pedagogy, therefore, prove that its uses eases language teaching and learning.
Prakash Agrawal and Rakesh Narain 2018 IOP Conf. Ser.: Mater. Sci. Eng. 455 012074
Many global supply chains are unequipped to cope with the world we are entering. For that reason, supply chain managers need to shift their attention from cutting costs to enabling new processes, and make corporations more connected and agile to create value across the enterprise. New digital technologies that are emerging everyday are on their way to disrupt nearly all the areas of traditional business processes. The key business priority of almost every industry will find itself in the centre of this upcoming digital era. The process of digitization affects almost everything in today's organizations, including supply chain management and puts huge pressure on organizations to change. Hence it is crucial for managers to understand the implication of digitization on their organization and employees. Current scenario emphasises on the importance of management of people and organization issues in digital transformations. The effect of digitization includes varied impacts on economy as a whole; create tremendous opportunities and challenges for businesses. In the current world of globalization digitization is not a choice but an imperative for all businesses across all industries. Manufacturing processes and work, business model, products and services are the main targets of digitization. The digital transformation enablers and framework discussed in this study-comprised of six techniques of Big data, Cloud services, Unique identification and display innovation, Robotics, Sensors and geolocation, and nanotech and 3D printing-can serve as enablers of digitization.
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N. Bonora et al 2024 IOP Conf. Ser.: Mater. Sci. Eng. 1306 011001
The Italian Association for Stress Analysis (AIAS) was founded in 1971 by researchers from academia, research centers and industry. AIAS was intended as a community where to discuss, to share and to develop scientific knowledge related to all technical aspects of stress analysis. In the years, from an initial focus on experimental techniques, AIAS contributed considerably to the development of modern numerical methods and computational techniques for the mechanical engineering design. In 2015, AIAS turned in the Italian Scientific Society of Mechanical Engineering Design.
Today, AIAS is an institutional partner that supports the instances from academia in subject area of the mechanical engineering design. Every year, AIAS organizes a technical conference offering the possibility to present research updates, share new ideas and foster collaborations. The AIAS conference has become a fundamental event for all those interested in current developments in mechanical engineering design and stress analysis, where to meet researchers, testing equipment and software developers.
The 52nd AIAS Conference edition was held in Genoa, Italy. The response of researchers and students has been outstanding: over 200 oral contributions have been presented during the three days of the conference, with four parallel sessions. In addition to the thematic sessions on AIAS traditional subjects, special sessions on additive manufacturing, energy methods for structural analysis, circular design in mechanical engineering, mechanical behavior under extreme conditions, have been successfully organized with the contribution of the AIAS technical committees.
Among all contributions presented at the conference, 44 have been selected to be published after peer review, in this volume. This was made possible thanks to the active participation of all AIAS members, to the work of the AIAS Scientific Committee panel (Profs Umberto Galietti, AIAS Scientific Coordinator, Gabriele Arcidiacono AIAS Scientific coordinator for external relationships, Enrico Armentani, Davide Castagnetti, Virgilio Fontanari and Aurelio Somá) and Conference Papers Reviewers. Their outstanding contribution is gratefully acknowledged.
Disclaimer
AIAS2023 Conference was held in presence on Sept. 6-9, 2023. Presentations were arranged on four parallel sessions with a time slot of 15 min assigned to each presenter. Approximately 280 participants attended the conference during the three days event. All sessions have been continuously monitored by the organizers to provide technical support. The conference ran smoothly, and participants feedback was very positive.
2024 IOP Conf. Ser.: Mater. Sci. Eng. 1306 011002
All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.
• Type of peer review: Single Anonymous
• Conference submission management system: Morressier
• Number of submissions received: 44
• Number of submissions sent for review: 44
• Number of submissions accepted: 44
• Acceptance Rate (Submissions Accepted / Submissions Received × 100): 100
• Average number of reviews per paper: 2.090909090909091
• Total number of reviewers involved: 36
• Contact person for queries:
Name: Giovanni Meneghetti
Email: giovanni.meneghetti@unipd.it
Affiliation: Universita degli Studi di Padova - Universita degli Studi di Padova Scuola di Ingegneria
G Loi et al 2024 IOP Conf. Ser.: Mater. Sci. Eng. 1306 012001
The dissipative properties of road pavements may have beneficial effects to reduce vehicle vibrations, traffic noise, vehicles-structure dynamic interaction, and degradation of pavement materials. Assessing the dissipative capacity and the damping properties of road pavements is, therefore, of critical importance. Such assessment has been mainly conducted in recent years by laboratory-scale dynamic experiments, while little effort has been devoted to in-situ tests. The latter are, in fact, cumbersome for practical reasons and typically require a more advanced data analysis when highly coupled modes of vibration are involved. Due to the heterogeneity of the road structure, classical methods are not capable of accurately estimating the road damping properties. The present study proposes an alternative experimental approach based on recording signals from accelerometers embedded in the road, which is impacted by an instrumented hammer. The data are analyzed both in the frequency and in the time domains through the combined use of stabilization diagrams and energy decay tools. Multi-mode fitting algorithms are employed to construct stabilization diagrams for the identification of resonance frequencies, while energy decay curves allow for a robust evaluation of the damping values at the identified frequencies. The effectiveness of the approach was assessed on an asphalt road structure.
Luca Chiappelloni et al 2024 IOP Conf. Ser.: Mater. Sci. Eng. 1306 012002
During a seismic event, fluid storage tanks are subject to sloshing phenomena; their effect on the structural components of the tanks is one of the main aspects to be considered during the design. The movement in successive modal forms of the roof-fluid system determined by the earthquake can cause severe damage to both the containment shell and the floating roof. The fluid-structure interaction imposes extremely complex out-of-plane deformation fields, mainly in the presence of floating roofs with lower flexible resistance. Such deformations can cause severe structural damage and subsequent catastrophic events such as those experienced in the past in Japan and Turkey. In fact, recently recorded earthquakes in Japan and Turkey, characterized by oscillation periods between 3 and 8 sec (long-period ground motion), compatible with the natural first and second slosh frequencies of the fluid-structure system, led to conspicuous problems of instability failure with the consequent sinking of the floating roof. These events dictated a new starting point for the research into the seismic behaviour of roof-fluid-tank systems.
F. Cianetti et al 2024 IOP Conf. Ser.: Mater. Sci. Eng. 1306 012003
The evaluation of fatigue damage of structural components within dynamic systems subjected to random loads is typically addressed using multibody models wherein one or more components are modeled as flexible using the modal approach. While incorporating flexible elements allows for consideration of their influence on the overall dynamic behavior of the system, certain components are intentionally designed to function as rigid bodies. Consequently, in this case the incorporation of flexible elements within multibody models merely leads to complex and time-consuming analysis. Hence, it would be more pragmatic to realize rigid body multibody models, with components characterized solely by their inertial properties, and subsequently extract the dynamic forces applied to the components to be verified. The assessment of stress can then be carried out by exploiting the principle of superposition of effects in the time domain. In this context, the objective of the present study is to develop this methodology in the frequency domain. This approach not only capitalizes on the simplicity of rigid multibody models but also harnesses the computational capabilities of the frequency-domain method for evaluating fatigue damage in components subjected to random loading conditions. This work, therefore, provides a rapid, effective, and robust method for verifying and designing rigid mechanical components integrated into dynamic systems subjected to random loads.