Innovative Components Research Articles

"CARBGAME" (CARd & Board GAmes in Medical Education) as an innovative gamification tool for learning clinical enzymology in biochemistry for first year medical students.

Gamification is emerging as an active learning innovation in medical education to enhance student engagement and promote life-long learning in a unique and collaborative environment. Clinical enzymology in biochemistry is one of the core topics in the medical curriculum. However, students face challenges in comprehension and retention of information. Hence, CARd & Board GAmes in Medical Education (CARBGAME)was introduced and evaluated for its effectiveness in enhancing learning, application, and retention of knowledge in clinical enzymology via gamification context. This mixed-method study involved 150 first-year undergraduate medical students. Before the game, students completed a pre-test in clinical enzymology. Later they were divided into 25 small groups to compete in the board game designed for enzymology in biochemistry. The students took turns throwing the dice and answering the questions on the game board to continue moving forward. The first team to reach 100 and solve the case-based question was deemed the winner. Following the board game, the students took up the post-test to compare the educational impact of the innovation. Also, the subsequent internal assessment scores were compared with previous batch who were not implemented with this intervention. Then students evaluated the effectiveness of CARBGAME-Clinical Enzymology using a 32-item questionnaire on 5-point Likert scale. The feedback obtained on a 10-point rating scale and for qualitative analysis, students' and faculty perceptions were recorded in small groups. CARBGAME received overwhelmingly positive feedback from both students and faculty. It was perceived well by students for being fun, relevant, consistent, motivating, collaborative, and promoting experiential learning. The game's low-stakes approach, effective feedback, and sense of accomplishment were highly appreciated, making it a valuable tool for education. A significant improvement in knowledge was recorded, from a mean score of 8.37 ± 1.126 on a 20-point scoring scale before the game to 16.53 ± 1.219 after with a p-value of 0.0001. The comparison of the internal assessment scores between the intervention and non-intervention group of students also showed a significant improvement among those implemented with CARBGAME (p < 0.0001). The CARBGAME innovation has achieved the intended outcome of promoting active learning and enhanced performance in clinical enzymology. Highly positive responses from faculty and students also indicate the exigent need to introduce innovative components like games into curricula to achieve student engagement and promote a meaningful learning experience.

Ensuring the economic development of the Samara region on the basis of increasing the level of innovation activity and competitiveness of the industrial complex

The article proposes a model for ensuring the competitiveness of an enterprise based on the integration of an innovative component into its activities for each level of its competitiveness. Key factors have been identified that ensure the success of applying innovations in the region, obtaining government support, developing a research base and creating a favorable innovation environment. The need for active implementation of innovations in the regional economy is emphasized, and the role played by innovative technologies in gaining competitive advantages for industrial enterprises is noted. A system of competitive advantages is shown, in which, at each level, the competitiveness of an enterprise is formed in a certain area of ??its functioning. In accordance with statistical data, an analysis of the innovation policy of the Samara region in the field of innovation activity was carried out, on the basis of which conclusions were drawn and recommendations were made.

Instructor led rotational model: An innovative approach to social work practicums in hospital environments

With the saturation of student practicum placements requests in urban centres, job vacancies, budgetary restraints, and social workers’ intensive workloads, field education coordination teams are increasingly challenged to find social workers who are able to supervise student practicums and secure educational partnerships with organizations willing to support their staff in doing so. This is especially true in hospital settings, where social workers are still feeling the effects of the Coronavirus (COVID-19) pandemic in their daily work lives. Hospital practicums are highly sought out by social work students and yet there are few practicum opportunities for students compared to the demand. Social workers are employed in various practice settings, including hospital social work. As social workers are Canada's largest group of mental health professionals within the hospital system, having robust and sustainable practicum opportunities is critical to the training and development of future social workers. To address these ongoing challenges in social work field education, the University of Calgary, MacEwan University, and Alberta Health Services worked together to develop and pilot a new practicum model at the Bachelor of Social Work level. This practicum model, titled the ‘Instructor Led Rotational Model’, was implemented as a pilot project during the winter 2023 semester. This article provides an overview of this initiative, including a description of innovative practice education components and discussion of the challenges in field education that the model aims to address. Considerations for revisions and future offerings of the instructor led practicum model are also identified.

(Invited) Looking Beyond the Stack: A Systems Engineering Approach to Optimize Stack and System Design of Electrolysers

In the coming decade green hydrogen production is expected to grow at an unparalleled rate. Much of the international focus is currently on the Gigawatt scale plants, with regular announcement of new projects. From a European perspective, the rapid scale-up is necessary to reduce the reliance on fossil fuels and achieve CO₂ reduction targets. Importing green hydrogen or derivatives such as ammonia from regions where renewable electricity cost are low, is key driver for investments for the energy intensive industry, especially in the North Western part of Europe. This will require hydrogen production on a very large-scale. In contrast to the differentiation on application level, a one-size fits all approach for stack manufacturing appears to be attractive, with a high degree of standardisation and volume of production.However, as the case for the Netherlands illustrates, there are more drivers for green hydrogen production, such as addressing (regional) grid congestion, improving the business case for offshore wind farm developments, and providing green energy to small and medium enterprises. For all these use cases the requirements for the electrolyser system differ. Aspects such as the variability of the energy supply, capacity factors, logistics for operation and maintenance, available footprint, are application specific. Therefore, electrolyser system designs may need to be optimized for different markets and applications.At TNO we focus on the development, integration and validation of novel materials and innovative cell components for the different generations of electrolyser technology, both for low temperature (liquid alkaline, PEM, AEM) and high temperature electrolysers. To understand and assess the requirements for future generations of electrolyser technology, a systems engineering approach is developed together with the industrial partners. This allows to translate the requirements from the application, to the system and stack design, down to the requirements on a cell and component level.Results will be presented from several studies carried out by TNO and industrial partners in the field of low temperature electrolyser systems to understand: How to optimize a stack design for a specific application. Should an electrolyser be designed to maximize flexible operation and achieve a broad operating range? Or will a high efficiency be the most important target? And how application specific is such an optimisation.How to bring down the cost of the total system. What impact do the design choices for the electrolyser stack have on the complexity of the system around the electrolyser, the balance-of-plant? What can we learn from this for the future stack requirements?How different operating strategies impact a certain design. Which stack requirements change in large multi-stack systems powered by renewable electricity supply? Can different strategies improve overall system performance and bring down the overall cost of hydrogen production?How can the desired safety level be achieved against the lowest cost by optimizing component and stack design? As both the electrolyser technology and the value chains become more mature, a systems engineering approach will be indispensable, bringing together the requirements of the different levels: from application, electrolyser system and stack design, down to the performance of individual components.

Piezoresistive modeling of orthotropic 3D-printing composite line extrusions with non-affine reorientation of fibers

This work introduces a micromechanical semi-analytical model to estimate piezoresistive constants in 3D-printable short-fiber composites, extending the Mori–Tanaka scheme with two innovative components. Firstly, the model incorporates non-affine reorientation of fibers, controlled by a parameter η, which significantly impacts texture coefficients. This parameter introduces an additional layer of complexity, modifying texture coefficients beyond traditional affine fiber reorientations. Observational data illustrate a linear relationship between piezoresistivities and η, leading to the development of a statistical model that calculates η based on the fiber aspect ratio. Secondly, the model accounts for preferential fiber orientation in the undeformed state, resulting in an orthotropic material model. This anisotropy is quantified using an Orientation Distribution Function (ODF) derived from X-ray scans, which is parameterized to maintain symmetry across three orthogonal planes. Initial investigations indicate that the inherent anisotropy introduced by the printing process substantially affects the initial resistivity of 3D-printed composites. Utilizing a Gaussian transversely isotropic model, we find that neglecting this anisotropy could lead to significant errors in understanding and predicting piezoresistive behavior. The model’s incorporation into advanced nanocomposite frameworks offers preliminary reconciliation with experimental data. Additionally, our results emphasize the necessity to refine wavy fiber models by incorporating non-affine rotations, particularly crucial for fibers with small aspect ratios, thereby enhancing predictive accuracy. The findings lay a robust foundation for future research, emphasizing the need for comprehensive experimental validation and setting the stage for nuanced applications in piezoresistive composite materials.

MOVEMENT-CONTROLLED STREET LIGHTING SYSTEM WITH MINIMAL POWER CONSUMPTION

Energy consumption in the public lighting system represents the largest part of the energy usage of a community, while the maintenance and operation of the system are a considerable expense for every city. This paper focuses on products and innovative components for street lighting, proposing a consumption-reducing solution based on an intelligent system for remote measurements and control with dimming technologies for high-intensity discharge (HID) lamps. The results indicate that considerable energy savings are achieved and the service life of the lamps is extended. A movement-controlled street light system is controlled according to the specific mode. The modes are controlled by two sensors, which are the light-dependent resistor (LDR) and the infrared (IR) sensor. This system can automatically turn on and off the lights according to traffic flow. It operates at night, and the focus is only on the one-way road at a junction. The street light will be on when there is at least one road user; otherwise, it will turn off. This design can save a great deal of energy compared to conventional street lights that keep a light throughout the night. Moreover, the maintenance cost can be reduced, and the lifespan of the system will increase. As a result, the system has been successfully designed and implemented as a model system.

The Role of Smart Materials, Sustainable Engineering Practices, and IoT Integration in Advancing Engineering Solutions

This study explores the role of smart materials, sustainable engineering practices, and Internet of Things (IoT) integration in advancing modern engineering solutions. The primary objective is to qualitatively analyze the literature on how these innovative components contribute to the development of efficient, sustainable, and intelligent engineering systems. The research employs a qualitative literature review methodology, examining a broad range of academic articles, technical reports, and case studies related to smart materials, sustainable engineering, and IoT applications. The literature review methodology involves systematically collecting and analyzing relevant scholarly sources to identify key trends and insights. The study categorizes the literature into major themes, such as the properties and applications of smart materials, the principles and benefits of sustainable engineering, and the impact of IoT integration on engineering processes. By synthesizing findings from diverse sources, the research provides a comprehensive overview of the advancements and challenges associated with these technologies. The findings reveal that smart materials, such as shape-memory alloys, piezoelectric materials, and self-healing composites, offer significant potential for enhancing the functionality and durability of engineering systems. Sustainable engineering practices, including the use of renewable materials and energy-efficient designs, are critical for reducing environmental impact and promoting long-term sustainability. IoT integration enables real-time monitoring, data-driven decision-making, and improved system efficiency, thus transforming traditional engineering approaches.

Innovation in the esports servicescape: a media business research agenda

ABSTRACT Esports represent an increasingly influential and innovative component of the global media business landscape. The ever-evolving ecosystem of dynamic new media is driven by a heterogeneous array of stakeholders that co-create value in online and offline spaces, often described as servicescapes, where innovations are increasingly influential in diverse areas including entrepreneurial business models, media, sports, entertainment, culture, and consumer engagement. In this research, a semi-systematic literature review was undertaken focused on the intersection of the esports ecosystem, servicescapes and innovations. Four clear directions for future research, with questions specific to esports, servicescapes and media were identified. Scholars can utilise these findings to enhance understanding of innovation from the servicescape perspective, with relevance for scholars engaged in business, marketing, and media.

Turbofan Performance Estimation Using Neural Network Component Maps and Genetic Algorithm-Least Squares Solvers

Computational models of turbofans that are oriented to assist the design and testing of innovative components are of fundamental importance in order to reduce their environmental impact. In this paper, we present an effective method for developing numerical turbofan models that allows reliable steady-state turbofan performance calculations. The main difference between the proposed method and those used in various commercial algorithms, such as GasTurb, GSP 12 and NPSS, is the use of neural networks as a multidimensional interpolation method for rotational component maps instead of classical β parameter. An additional aspect of fundamental importance lies in the simplicity of implementing this method in Matlab and the high degree of customization of the turbofan components without performing any manipulation of variables for the purpose of reducing the dimensionality of the problem, which would normally lead to a high condition number of the Jacobian matrix associated with the nonlinear turbofan system (and, thus, to significant error). In the proposed methodology, the component behavior can be modeled by analytical relationships and through the use of neural networks trained from component bench test data or data obtained from CFD simulations. Generalization of rotational component maps by feedforward neural networks leads to an average interpolation error up to around 1%, for all variables. The resulting nonlinear system is solved by a combined genetic algorithm and least squares algorithm approach, instead of the standard Newton’s method. The turbofan numerical model turns out to be convergent, and results suggest that the trend in overall turbofan performance, as flight conditions change, is in agreement with the outputs of the GSP 12 software.

Fabrication and control architecture of novel hybrid metal additive manufacturing incremental forming technology

Hybrid manufacturing processes redefine production dynamics by harnessing the synergistic interplay between process mechanisms, energy sources, and tools to impact manufacturing quality, productivity, and sustainability significantly. Accordingly, this article focuses on hybrid additive manufacturing incremental forming, where additive manufacturing and incremental forming are integrated in a unified setup, driven by a single power source. This integration opens avenues for innovative component and production design, capitalizing on the strengths of both methods while mitigating drawbacks. The fabrication of the hybrid additive manufacturing incremental forming setup involves crucial components like a hybrid extrusion forming unit, supporting plates, hopper-barrel assembly, band heaters, solenoid setup, and a comprehensive control architecture. Addressing challenges, particularly overheating in the hopper, and feeding zone, ensures effective material transformation with the hybrid extrusion forming unit. The subsequent section provides analytical analysis and validation of the hybrid extrusion unit. This technology enhances the entire process and addresses issues related to metal additive manufacturing, such as porosity and material shrinkage. The maximum tensile force sustained in hybrid additive manufacturing incremental forming before fracture demonstrates a notable enhancement of about 20% from 670 N in additive manufacturing to 805 N in hybrid additive manufacturing incremental forming. It also removes micro-cracks, and voids, and improves the inter-layer bonding, as observed through scanning electron microscopy. The results highlight hybrid additive manufacturing incremental forming's superior enhancement of mechanical properties and surface quality compared to traditional additive manufacturing approaches.

Regulating the thermophysical properties of rare earth cerates through high entropy design and substitute

Cerate ceramics are considered promising candidates for the new generation of thermal barrier coatings. However, in the middle temperature area (473–673 K), the CTE mismatch due to the thermal contraction often results in coating failure. The aim of this work is to develop an innovative component regulation method that significantly reduces the thermal conductivity and alleviates the thermal contraction. Cerates exhibit a low thermal diffusion coefficient, primarily attributed to the impact of extrinsic phonon scattering mechanisms. Our comprehensive analysis encompassed various factors such as point defects, the degree of size and mass disorder, grain interfaces, and lattice distortion. By employing high entropy design and doping strategies, we have successfully alleviated the thermal contraction phenomenon in cerates, while maintaining their high CTE. Furthermore, an in-depth investigation of the valence states of elements and lattice energy was conducted to elucidate the thermal contraction mechanism of cerates in the middle temperature area.

Innovación organizacional en la estrategia de internacionalización en pymes vitivinícolas: El caso chileno

This investigation aims to determine the components of the organizational innovation in Chilean bottled wine SMEs, to strengthen the internationalization strategy in global markets, concerning the leading countries with international recognition. These results should help enhance competitiveness in cosmopolitan markets with wine tradition. In operational terms, it includes five stages: data collection from wine SMEs, instrument design (questionnaire), application of this instrument in companies through personalized field work, processing, analysis, and systematization of the collected data through office automation instruments—mainly the SPSS statistical program for a validation—and delivery of these results to each of the participant companies. As one of the primary outcomes, wine SMEs are gaining legitimacy through organization innovation as a corporate strategy to have opportunities to stay in national and international markets.

MambaReID: Exploiting Vision Mamba for Multi-Modal Object Re-Identification.

Multi-modal object re-identification (ReID) is a challenging task that seeks to identify objects across different image modalities by leveraging their complementary information. Traditional CNN-based methods are constrained by limited receptive fields, whereas Transformer-based approaches are hindered by high computational demands and a lack of convolutional biases. To overcome these limitations, we propose a novel fusion framework named MambaReID, integrating the strengths of both architectures with the effective VMamba. Specifically, our MambaReID consists of three components: Three-Stage VMamba (TSV), Dense Mamba (DM), and Consistent VMamba Fusion (CVF). TSV efficiently captures global context information and local details with low computational complexity. DM enhances feature discriminability by fully integrating inter-modality information with shallow and deep features through dense connections. Additionally, with well-aligned multi-modal images, CVF provides more granular modal aggregation, thereby improving feature robustness. The MambaReID framework, with its innovative components, not only achieves superior performance in multi-modal object ReID tasks, but also does so with fewer parameters and lower computational costs. Our proposed MambaReID's effectiveness is validated by extensive experiments conducted on three multi-modal object ReID benchmarks.

Sustainable Cultivation of Discipline Competition Programs for Innovation and Entrepreneurship Education: An Example of the Food Science and Engineering Major

Cultivating innovative and entrepreneurial talents has become the responsibility and mission of higher education. It reflects the effectiveness of education in terms of teaching quality, scientific prowess, and social service. Discipline competitions played a significant role in fostering innovation and entrepreneurship ability, serving as a crucial component of innovation and entrepreneurship education in colleges. This study used the food science and engineering major as an example to address the gap between theoretical knowledge teaching and the actual production process. It aimed to improve the poor performance of innovative practices by establishing a sustainable cultivation model for discipline competition programs. There needs to be an investigation into the conduct of disciplinary competitions and the students’ participation in them. Then, a model comprising a “theory + experiment + practice” course to guide students in participating in competitions should be formed. A rational and sustainable innovation team and a collaborative innovation platform for school–enterprise integration needs to be built. In order to achieve sustainable development education and cultivate applied talents who can solve complex problems in food engineering, the sustainable cultivation model was established. This work could serve as a reference for developing professional discipline competitions and fostering innovative and entrepreneurial talents for sustainable development.

Ontological model of structure and parameters of components in high-tech product modernization projects

The subject of the article is models representing the structure and parameters of components in high-tech products based on the analysis of technical documentation in modernization projects. The purpose of the proposed research is to enhance the quality of modernization processes of high-tech products by forming an ontological model of the product with innovative components, considering the diversity of information support. The article addresses the following tasks: studying the main methods and technologies of system representation of complex product structure; forming a model of structural-functional decomposition of a high-tech product, creating an ontological model of the structure and parameters of a high-tech product based on technical documentation. The following methods are applied: systemic approach, methods of functional-structural decomposition, set theory, ontology construction methods, semantic models. The following results were obtained: The main methods of system representation of complex product structure were investigated, based on the following principles: decomposition of complex product architecture, layering of complex product representation, multivariate synthesis of component architecture. The main directions and advantages of using 3D technologies for solving design tasks in modernization projects of high-tech product components are considered. The decomposition of a high-tech product into component parts and partial parameters is proposed, taking into account functional, structural, and parametric characteristics. An ontological model of the structure and parameters of a high-tech product is formed based on a set of technical documentation and considering additional heterogeneous sources of information. Innovative elements are identified, the description of which may be fuzzy. Conclusions. The proposed ontological model can serve as a basis for finding similar solutions regarding the design of innovative components in the precedent database, which is properly structured. In the absence of similar design solutions, innovative component design can be carried out using 3D technologies based on supplementing fuzzy information in the semantic model.

오차수정모형을 이용한 금융발전의 영향요인 분석

This study empirically analyzed the effected determinants of global innovation, economic freedom, and GDP on financial development. An analysis was conducted by the OLS error correction model using panel data(N=224) from 2011 to 2019 of 28 countries. The results showed that economic freedom was the most influential factor in global financial development, and that global innovation and GDP also had a positive impact. Among components of economic freedom, property rights, money soundness, and market openness were found to have a positive impact on financial development, while regulations and government size were found to have a negative impact on financial development. And among components of global innovation, market sophistication, human capital research, infrastructure, knowledge and technology outputs, and business sophistication had an impact on financial development, but institutions and creative outputs did not appear to have an effect. This results has an academic importance of showing that economic freedom and innovation is more important factors than GDP for global financial development. Thus it is assumed that an advanced free-market economy system with a fair legal framework and a constant innovation is important for financial development in global environment where neo-protectionism is spreading.

Technological innovation and its role in promoting the competitive advantage of the industrial enterprises

Purpose. This study aims to identify the role of technological innovation in promoting the competitive advantage of industrial enterprises by examining the case of the Bioscan Pharmaceutical Industry Corporation in the State of Setif, Algeria. Results. This study explores the importance of both product innovation and the creation of productive processes in improving the competitive advantage of the pharmaceutical industry in the State of Setif, while also identifying the most influential dimension in supporting the competitive advantage of the studied enterprise. The results indicate that technological innovation has a positive impact on upgrading the competitive advantage of the Bioscan Pharmaceutical Industry Corporation in the state of Setif. It is concluded that the mechanisms used by the firm to develop its technological innovation through product creation and the establishment of production processes have contributed in a very positive and effective way to improving its competitive advantage. Scientific novelty. The current study presents its novelty by focusing on technological innovation in industrial enterprises within the pharmaceutical industry. Previous studies on this subject have primarily examined industrial enterprises in other sectors such as the electrical and household equipment industry and heavy industries. Additionally, this study comprehensively reviews all theoretical concepts related to technological innovation and competitive advantage, thereby contributing to strengthening the theoretical understanding of enterprise workers. Practical value. The practical value of the study lies in highlighting the role and importance of analysing the views and responses of pharmaceutical industry workers regarding the optimal use of technological innovation components as the primary component of industrial enterprises. This effective asset contributes to lower production costs and improves product quality, positively influencing the current and future objectives of the enterprise.

Economic evolution of Durres University: A historical perspective from 1803 to 2030

The purpose of this study was to examine the history of the development of Alexander Moisiu University of Durres to form recommendations for its future development. It also remained important to form advices in the context of the future development of universities to ensure the improvement of the entire field of education. The main methods that were used in the framework of the study were analysis, forecasting, and comparison. The paper considered the features of the development of the city of Durres, its role for the country, and the main areas of activity. Subsequently, the history of the main local Alexander Moisiu University, which was founded in 2006, was evaluated. It was concluded that, despite significant successes, there are still difficulties and problems in its development. In this regard, actions were proposed (from the standpoint of the university’s management staff) to improve the quality of the university’s development in the future. Special attention was paid to components of innovation, digitalisation, and sustainable development. The conclusions showed that close cooperation between the municipality and the university will lead to mutually beneficial consequences, which is why representatives of both sides should be interested in this. The conclusions generated within the framework of the study can be used both to develop the future strategy of Alexander Moisiu University and to form a state strategy in the field of education in general

Devising a methodological approach to identifying the economic potential of production costs for eco-innovative products

The object of this study is the production costs of ecologically oriented innovative products. The problem under consideration was to improve the efficiency of cost management for the production of eco-innovative products by improving the methodical approach to identifying reserves for their reduction in order to ensure competitive advantages and strengthen the economic and environmental security of the enterprise. The devised methodological approach is based on a systematic analysis using economic and mathematical methods. It provides for the establishment of the dependence of costs per dollar of eco-innovative products on factors related to the economic potential of the enterprise, and the search for reserves for reducing costs for the production of eco-innovative products. The analysis technology was substantiated and modeling of costs per dollar of eco-innovative products of the enterprise was carried out using the principal component analysis. A distinctive feature of the built model was the consideration of the influence of micro-level factors, risk management, and the innovative component of the enterprise's economic potential. The resulting model is significant and reliable since the variation of costs per dollar of innovative products depends on the change in the principal components under investigation by 85 %. Within the framework of the devised methodical approach, a technology for calculating reserves for reducing production costs of enterprises producing eco-innovative products has been proposed. It was established that the potential of reducing costs per dollar of eco-innovative products for the totality of the investigated enterprises is on average 5.4 cents per dollar of costs. The area of practical use of the devised methodical approach is the process of minimizing and optimizing costs per hryvnia of eco-innovative products

Semantic attention-based heterogeneous feature aggregation network for image fusion

Infrared and visible image fusion aims to generate a comprehensive image that retains both salient targets of the infrared image and texture details of the visible image. However, existing methods overlook the differences in attention to semantic information among different fused images. To address this issue, we propose a semantic attention-based heterogeneous feature aggregation network for image fusion. The key component of our network is the semantic attention-based fusion module, which leverages the weights derived from semantic feature maps to dynamically adjust the significance of various semantic objects within the fusion feature maps. By using semantic weights as guidance, our fusion process concentrates on regions with crucial semantics, resulting in a more focused fusion that preserves rich semantic information. Moreover, we propose an innovative component called the attentive dense block. This block effectively filters out irrelevant features during extraction, accentuates essential features to their maximum potential, and enhances the visual quality of the fused images. Importantly, our network demonstrates strong generalization capabilities. Extensive experiments validate the superiority of our proposed network over current state-of-the-art techniques in terms of both visual appeal and semantics-driven evaluation.