In submitting conference proceedings to <i>Engineering Proceedings</i>, the volume editors of the proceedings would like to certify to the publisher that all papers published in this volume have been subjected to peer review by the designated expert referees and were administered by the volume editors following the policies announced on the conference website [...]
Precise stock price forecasting is essential for informed decision-making in financial markets. This study examines the combination of large language models (LLMs) with data augmentation approaches, utilizing improvements in cognitive computing to enhance stock price prediction. Traditional methods rely on structured data and basic time-series analysis. However, new research shows that deep learning and transformer-based architectures can effectively process unstructured financial data, such as news articles and social media sentiment. This study employs models, such as RNN, mBERT, RoBERTa, and GPT-4 based architectures, to illustrate the efficacy of our suggested method in forecasting stock movements. The research employs data augmentation techniques, including synthetic data creation using Generative Pre-trained Transformers, to rectify imbalances in training datasets. We assess metrics like accuracy, F1-score, recall, and precision to verify the models’ performance. We also investigate the influence of preprocessing methods like text normalization and feature engineering. Extensive tests show that transformer models are much better at predicting how stock prices will move than traditional methods. For example, the GPT-4 based model got an F1 score of 0.92 and an accuracy of 0.919, which shows that LLMs have a lot of potential in financial applications.
Truss-braced wings (TBWs) feature higher aspect ratios with a lighter weight and lower bending moment than conventional wings. These wings show significant potential for performance improvements in terms of fuel efficiency. However, additional configurations of these wings also present nonlinear problems and challenges in aeroelastic designs. This paper investigates the static response of a TBW with a high aspect ratio, specifically focusing on the impact of the spanwise joint location on aeroelastic characteristics. The TBW is modeled by nonlinear beam elements and the unsteady vortex-lattice method (UVLM). The results show that the bending deformation is effectively reduced by the truss member and the deformation is impacted by the location of the spanwise joint connected to the main body.
Nouhaila Farajy, Ahmed Remaida, Benyoussef Abdellaoui
et al.
This study, based on a 25-year dataset (2000–2025) collected from the Scopus database, provides a comprehensive bibliometric analysis of the intellectual structure of research on emotion recognition, prediction, and skills. Using bibliographic coupling as the primary method, the analysis examines the titles, abstracts, keywords, frameworks, and review literature, presenting the most significant articles in this area, along with the headings of 202 relevant papers. The study investigates the temporal distribution of research outputs, focusing particularly on trends from the last decade. To visualize the scientific landscape, the study uses VOSviewer to map co-authorship, keyword co-occurrence, and citation networks. The analysis highlights the most prolific journals, influential authors, dominant subject areas, and frequently used keywords. Additionally, it identifies the algorithms used for emotion recognition in predicting soft skills, along with the objectives of the studies, as well as the data and results involved. The study also identifies the leading countries and educational institutions contributing to this research domain. The findings offer a detailed overview of the field’s development and intellectual trends, providing insights and recommendations for future research directions. This research also helps to understand how emotion recognition can contribute to human development across various domains, as discussed in this article.
Amani S. Aljohi, Sara S. Alzaabi, Rahma S. Almahri
et al.
This work sheds light on the effectiveness of digital kiosks in targeting specific audiences in contrast to centrally managed mobile phone applications. To this end, we have conducted a case study where a digital kiosk was developed to support the academic activities of the computer science department. Our results show that the students continue to use the mobile phone application. However, the digital kiosk added the following main benefits to the service: Firstly, being in a physical location and thanks to their larger screens, digital kiosks are ‘eye-catching’ devices, which makes them ideal for advertising products/services or communicating relevant information. Secondly, they are brilliant points of attraction. By seeing other people standing in front of any of them, members of the target audience are encouraged to imitate them, even if they did not have the intention to do so. Thirdly, even if the services are available from a mobile phone application, some people do not wish to create an account, download and install the application on their devices, and/or give permission to it, which can potentially invade their privacy and security. Lastly, and equally important, digital kiosks are human-centered technologies that can be more appealing to people who seek social interactions. With this, we conclude that digital kiosks cannot replace mobile phone applications. Rather, they are further technologies that enhance self-service overall.
This paper presents the design and development of a proof of concept (PoC) open-source data logger system for wireless data acquisition via Wi-Fi aimed at bench testing and fault detection in combustion and electric engines. The system integrates multiple sensors, including accelerometers, microphones, thermocouples, and gas sensors, to monitor critical parameters, such as vibration, sound, temperature, and CO<sub>2</sub> levels. These measurements are crucial for detecting anomalies in engine performance, such as ignition and combustion faults. For combustion engines, temperature sensors detect operational anomalies, including diesel engines operating beyond the normal range of 80 °C to 95 °C and gasoline engines between 90 °C and 110 °C. These readings help identify failures in cooling systems, thermostat valves, or potential coolant leaks. Acoustic sensors identify abnormal noises indicative of issues such as belt misalignment, valve knocking, timing irregularities, or loose parts. Vibration sensors detect displacement issues caused by engine mount failures, cracks in the engine block, or defects in pistons and valves. These sensors can work synergistically with acoustic sensors to enhance fault detection. Additionally, CO<sub>2</sub> and organic compound sensors monitor fuel combustion efficiency and detect failures in the exhaust system. For electric motors, temperature sensors help identify anomalies, such as overloads, bearing problems, or excessive shaft load. Acoustic sensors diagnose coil issues, phase imbalances, bearing defects, and faults in chain or belt systems. Vibration sensors detect shaft and bearing problems, inadequate motor mounting, or overload conditions. The collected data are processed and analyzed to improve engine performance, contributing to reduced greenhouse gas (GHG) emissions and enhanced energy efficiency. This PoC system leverages open-source technology to provide a cost-effective and versatile solution for both research and practical applications. Initial laboratory tests validate its feasibility for real-time data acquisition and highlight its potential for creating datasets to support advanced diagnostic algorithms. Future work will focus on enhancing telemetry capabilities, improving Wi-Fi and cloud integration, and developing machine learning-based diagnostic methodologies for combustion and electric engines.
Engineering machinery, tools, and implements, Technological innovations. Automation
The paper discusses the role of social marketing in preventing health-related harmful habits such as tobacco consumption and smoking. These habits are the causes of deadly diseases such as lung cancer, tuberculosis, and other chronic infections which are detrimental to life of the people. Children fall prey to the wrong habits in the wrong company and become tobacco addicts. So many cases of teen drug addicts are reported in a large number. They have a lack of conscience at a tender age and negligence of their counselling and awareness increases the number of smokers, drunkards, and drug addicts. Once they are afflicted with the diseases they must run for medicines and treatment. Therefore, it should be prevented before suffering as the saying goes, “Prevention is better than cure “. They are unaware that they are prevented not only by clinical treatment and medicines but also by social awareness and education. Social mobilization of the people through awareness programs, education, camps, campaigns, etc. is known as social marketing. The significance of social marketing is its effects on the prevention of physically detrimental habits in the youth which contributed a lot to the reduction of cases of diseases. The role of government programs, educational and medical institutions, social workers, and NGOs is worth applauding in India which undertake and complete projects, organize awareness camps, and educate parents and youths to save themselves from the consumption of harmful substances. It has also produced good output in India that the cases of smoking and drug addiction have reduced to support the country’s development as India is advancing towards becoming the third largest economy and a developed country by 2030 and 2047 respectively.
В машиностроении одними из наиболее перспективных являются аддитивные технологии (АТ) выращивания изделий из металлов и сплавов. Они находят все более широкое применение в производстве изделий в различных отраслях машиностроения. Термин «выращивание» связан с постепенным послойным характером изготовления сложного изделия на основе его компьютерной 3D-модели. Проволочные АТ экономически более выгодные в связи с более высокой производительности процесса и, на порядок более низкой стоимости проволоки по сравнению с порошками для популярных технологий SLM и LMD. Кроме того, современной промышленностью освоен выпуск проволоки из широкой номенклатуры материалов, среди которых: алюминий, низколегированные стали, нержавеющие стали, титановые, никелевые сплавы. Недостатком проволочных АТ является более грубая поверхность выращенных изделий. В статье приведены результаты проектирования и применения многофункционального оборудования для совместного использования аддитивных и субтрактивных технологий.
Engineering machinery, tools, and implements, Motor vehicles. Aeronautics. Astronautics
The geometry of truss structure is expressed in terms of its nodal positions; that is, the nodal positions vector is the fundamental design variable for the optimal geometry design of a truss. In order to solve an optimal design problem, there are various approaches that uses differentiation of the objective function in terms of the design variable, such as the steepest descent method and the gradient projection method. Many of the objective functions of structural optimal design problems are formulated in terms of the stiffness matrix; the gradient or differentiation approach requires differentiation of the stiffness matrix in terms of the nodal positions vector. It is, however, not impossible but still impractical in many cases since we have to deal with the third-order differential coefficient tensor. In this paper, we deal with the differentiation of the product of the stiffness matrix and a vector in terms of the nodal positions vector. We develop a formulation in general form that can be applied to trusses of any configuration. Examples of optimal geometry designs of 2D and 3D trusses are demonstrated.
Mechanical engineering and machinery, Engineering machinery, tools, and implements
The ever-growing global population, combined with the industrial revolution and increased consumerism, has led to an exponential surge in waste generation. The implementation of integrated solid waste management (ISWM) is crucial for addressing the challenges posed by increasing waste generation and limited landfill space. Remote sensing (RS) and Geographic Information Systems (GIS) have emerged as powerful tools to support ISWM strategies through their diverse applications. This short review explores the novel applications of RS and GIS in ISWM and highlights their potential for enhancing waste management practices. RS techniques, such as satellite imagery and aerial photography, enable the accurate mapping and monitoring of waste generation, disposal sites, and recycling facilities. GIS facilitates spatial analysis and decision-making, allowing for optimized waste collection routes, landfill site selection, and the identification of suitable locations for waste-to-energy projects. Furthermore, RS and GIS provide valuable insights into waste composition analysis, landfill stability assessment, and environmental impact evaluation. This review underscores the importance of leveraging RS and GIS technologies to improve waste management practices and offers valuable recommendations for future research in this field.
Microplate-based methods are commonly used to conduct spectrophotometric-based assays on large batches of sample extracts as they allow much greater throughput compared to traditional benchtop methods. However, many reported methods have not undergone a thorough method development/optimisation process; thus, the significance of maintaining certain parameters and procedures is often unknown. This study investigated the importance of plate shaking prior to the absorbance measurement step in two common assays: total phenolic content (TPC) measured using the Folin–Ciocalteu method, and total antioxidant activity measured using the Ferric Reducing Antioxidant Power (FRAP) method. A comparison was conducted on 36 methanol extracts of chickpea (<i>Cicer arietinum</i>) kernel, which had TPCs ranging from 43 to 111 mg GAEs (gallic acid equivalents)/L and FRAP values ranging from 25 to 67 mg TE (Trolox equivalents)/L. The absorbance of the samples was measured before and after the plate was shaken (300 s); each sample was analysed in duplicate. For the TPC, the unshaken and shaken absorbance values showed a high correlation with one another (R<sup>2</sup> = 0.990); however, a paired samples <i>t</i>-test demonstrated a significant increase in absorbance after shaking (<i>p</i> < 0.001; mean increase of 10.6%). Similarly, the unshaken and shaken absorbance values for FRAP showed a strong correlation (R<sup>2</sup> = 0.973), but again the shaken absorbance values were significantly higher (<i>p</i> < 0.001, mean increase of 12.1%). This demonstrates the importance of plate shaking for ensuring the complete reaction of the well contents prior to measuring their absorbance values. Furthermore, it highlights the need to closely follow the specified procedure when attempting to replicate or set up a microplate-based spectrophotometric method from the literature.
Prathvi Shenoy, Joslin D’Souza, Mahadev Rao
et al.
The study of a drug’s absorption, distribution, metabolization, and excretion by the body is known as pharmacokinetics (PK). In pharmacokinetics, the two-compartment model is used to understand the distribution and elimination of drugs. The two-compartment model represents the body as two distinct compartments: the central compartment (such as the blood) and the peripheral compartment (such as tissues). This work aims to enhance the understanding of drug kinetics inside the human body by comparing different mathematical models. The important focus of this study is to compare the distribution patterns of the drugs methadone, buprenorphine, tramadol, and tapentadol when administered intravenously using a two-compartment model. To mathematically describe the distribution of drugs in the body, a system of nonlinear ordinary differential equations is employed. These equations capture the dynamics of drug concentration in the different compartments over time. The roots are obtained by solving this system of equations using numeric analysis techniques. The study determines the duration of the drugs to attain the minimum effective concentration in the blood by analyzing the obtained results. Furthermore, the study also determines the time it takes for these drugs to be eliminated from the body. This data is significant for understanding the drug’s clearance rate and its potential duration of action. By comparing the distribution patterns and elimination rates of methadone, buprenorphine, tramadol, and tapentadol, the study provides insights into the differences between these drugs in terms of their pharmacokinetic properties. Healthcare professionals can utilize this information to optimize drug therapy, ensuring that the drugs are administered in accurate amounts and at precise intervals to target the desired therapeutic effect. Overall, this study provides a comprehensive analysis of drug kinetics, aiding in a better understanding of drug behavior within the human body and facilitating informed decision making in clinical settings.
This study investigates the thermal insulation and moisture management of three types of mountaneering boots and simulated hiking activities under controlled environmental conditions with two elite athletes. Temperature and humidity were determined with six wireless probes placed on the most exposed parts of the foot (hallux, middle toe, little toe, dorsum, ankle and sole). Thermal images were taken to record the thermal insulation of each sample. Methodologically, the study aims to simulate every movement and activity of alpinism in order to realistically evaluate the conditions of use of this kind of footwear (also taking into account the lacing pressure exerted on the foot). Based on the results obtained, in a further step it will be possible to define the best solution in terms of combination of materials by creating a comfort scale for hiking boots.
Textile bleaching, dyeing, printing, etc., Engineering machinery, tools, and implements
Community water fluoridation (CWF) adjusts fluoride levels in public water supplies to prevent tooth decay and promote dental health, irrespective of socioeconomic status or dental care access. Regular sampling by community water systems (CWS) ensures compliance with regulations and standards. The Centers for Disease Control and Prevention (CDC) provide biennial reports for health statistics surveillance by monitoring CWF status in US water systems. It is important to note that specific policies and practices related to CWF can vary between countries. Therefore, this research applies the spectral clustering method to group and analyze the reception of fluorinated water by CWS between populations in US states. The data from the National Water Fluoridation Statistics (2016–2018–2020) reported by the CDC have been considered. The spectral clustering approach identified five clusters of US states, which represent the different percentages of the population served by CWS receiving fluorinated water. Among the results, one cluster has the lowest value of the percentage (33.3%), and it includes Hawaii, New Jersey, Oregon, Idaho, Montana, Louisiana, New Hampshire, Alaska, and Utah. Conversely, the cluster of states including Ohio, Indiana, Maryland, South Dakota, Georgia, Virginia, North Dakota, Illinois, Minnesota, Kentucky, and the District of Columbia had the highest percentage (96.1%). These findings reveal relevant variations in the implementation of CWF across different US states, with some states having a notably lower percentage of their population receiving fluorinated water than others. This could inform policy and public health efforts to improve access to fluoridated water and enhance dental health outcomes in areas with lower coverage.
Agus Kurniawan, Bayu Prabandono, Dicky Bondan Wirawan
et al.
During the Covid-19 pandemic, the need for food was one of the problems faced by the government. The government urges the public to do independent food planting using polybag planting media as one solution to overcome this problem. However, single-use polybags can increase the amount of plastic waste, which is still unresolved. This study aims to design the value of the knockdown polybag product and gain strength from the knockdown product design. Knockdown Polybag product design using the VDI 2222 method (Verein Deutscher Ingenieure / German Engineers Association). This method helps facilitate designing products and learning for beginners and can optimize the productivity of designers to find the most optimal and efficient problems. After determining the method used, the next step is planning, conceptualizing, designing, and completing knockdown polybag products. The result of the design concept from the VDI 2222 method is an alternative overall function (AFK) 2 which has a square cross-section, is cones-shaped to facilitate plant transfer applications on agricultural land, and uses a hook locking model, which is flexible, and easy to assemble and disassemble. The product design of knockdown polybags has been obtained to meet the needs according to those on the market. Therefore, knockdown polybags can be produced and used to make planting more accessible and reduce costs for farmers.
Heat sealing is a packaging technique by means of welding of seal materials with heating and compression, and is widely used for hermetic seal of foods and medical supplies. However, a defect of the heat sealing, for example a “pinhole”, caused by small wrinkle on the sealing film or jamming by contaminants occasionally arises. In order to enhance the reliability of heat seal products, this study proposes a nondestructive technique to detect such a small defect in the heat seal by utilizing coincidence effect of airborne ultrasound. In the proposed method, a bending wave with sufficient amplitude is excited by the coincidence effect, and this bending wave appears as a traveling wave on the heat seal. This traveling wave is sensitive to the defect in heat seal and shows apparent phase lags compared with defectless heat seal. Therefore, defect in the heat seal is detectable by observation of the phase lags in the traveling wave. Arrangement of ultrasound transmitter and receiver is important for the proposed technique in order to observe the phase lags efficiently. Traveling wave plays an important role to detect the defect in heat seal, so that the airborne ultrasound inspection without the coincidence effect is unavailable because the traveling wave is not generated. Validity of the proposed technique is demonstrated through experiments and numerical simulations.
Mechanical engineering and machinery, Engineering machinery, tools, and implements
In recent decades, new optimization algorithms have attracted much attention from researchers in both gradientand evolution-based optimal methods. Many strategy techniques are employed to enhance the effectiveness of optimal methods. One of the newest techniques is opposition-based learning (OBL), which shows more power in enhancing various optimization methods. This research presents a new edition of the Differential Evolution (DE) algorithm in which the OBL technique is applied to investigate the opposite point of each candidate of self-adaptive control parameters. In comparison with conventional optimal methods, the proposed method is used to solve benchmark-test optimal problems and applied to real optimizations. Simulation results show the effectiveness and improvement compared with some reference methodologies in terms of the convergence speed and stability of optimal results.
Engineering machinery, tools, and implements, Mechanical engineering and machinery