Dual Objective Research Articles

Research on similarity bias in dual objective visual search based on nuclear power human-machine interface icons

Using icons from nuclear power interface as the research object, this study explored how icon similarity affected the performance of dual objective visual search. Firstly, the process of generating similarity bias was described from the perspective of human cognitive processing. The feature attributes of nuclear power icons were extracted, and then associated and mapped with similarity bias attributes. Secondly, a total of 16 instruction icons, device icons, and component icons were selected to propose icon coding logic for different similarity dimensions, and similarity experimental materials were designed. Finally, a dual objective search experiment with a 4 × 4 matrix was conducted to explore the impact of graph similarity on search performance and to determine the priority of perceptual similarity, semantic similarity, and memory similarity. High-level (H) similarity between the two targets resulted in superior visual search performance (p = 0.01 between the response times of similarity high and medium/low). Improving experiential familiarity enhanced search performance in cases of low-level (L) (p = 0.021) and medium-level (M) (p ≤ 0.009) icon similarity, but had no significant impact on search performance in cases of high-level (H) similarity (p ≥ 0.269). Compared to semantic similarity, enhancing perceptual similarity was more likely to improve search performance(p = 0.024).

A strategic and social analytics model for sustainable packaging in the cosmetic industry

Every day, we use cosmetic products that are not only focused on beauty but also with everything related to personal care and hygiene. The impact that these products have on sustainability cannot be overlooked. Many cosmetics contain unsustainable ingredients that can cause environmental damage and loss of biodiversity. In addition, fossil-based packaging contributes greatly to environmental pollution and increases waste in the absence of a circular supply chain. This work has a dual objective. The first is to provide a strategic analysis based on a multi-criteria approach to evaluate the most sustainable alternatives to traditional packaging that manufacturers could adopt based on the opinions of experts from different categories of stakeholders. In this study, the multi-criteria approach was employed, as it has been widely recognized in the literature for its effectiveness in evaluating and comparing alternatives across multiple, often conflicting criteria. The second is to provide a social analysis to assess consumers’ views, habits, preferences, and willingness to pay toward sustainable packaging. The results show divergence among experts who prefer refillable packaging while consumers prefer recyclable packaging. In contrast, a convergence in selling price and production costs is verified, highlighting the strategic importance of the economic dimension is for sustainable packaging, and the willingness to pay for sustainable packaging is about twice that of traditional packaging. The implications of this work suggest that circular supply chains covering the entire life cycle of products, based on a pragmatic approach, can drive the convergence of consumption and production patterns toward sustainable development.

Integrating Forest Ecosystem Services into Health Strategies to Improve Human Well-Being

As the largest terrestrial ecosystem covering extensive expanses of the Earth’s surface, forests offer crucial health benefits to humans, both directly and indirectly. Presently, health services derived from forest resources have presented significant opportunities for enhancing human well-being. Nonetheless, the absence of a comprehensive understanding regarding the mechanisms by which forests impact human health jeopardizes the potential gains in health. Regrettably, there remains a dearth of scholarly work elucidating these pathways. This paper aims to furnish a thorough examination of how forests influence human health. We initiate by formulating a conceptual framework upon which we delineate the various pathways through which forests impact human health. These encompass the provisioning of resources, preventive services, and forest therapies. Concurrently, we outline the moderating influence of social, economic, and individual characteristics as mediators within this pathway. These characteristics are classified into two overarching dimensions: accessibility and behavioral choices, which notably affect marginalized demographics such as those with lower socioeconomic status, women, the elderly, individuals with disabilities, and children in developing nations. Consequently, we build upon these foundational insights to propose six strategies aimed at perpetuating the positive impact of forests on human health in the foreseeable future. In the future, the development of forest management policies, the assessment of long-term health benefits, social practices, and international cooperation must be considered holistically to attain the dual objective of sustainable forest management and the advancement of human well-being.

Streamlining Complex Intervention Evaluation Through Participatory Systems Mapping and Contribution Analysis: A Comprehensive Framework for Actionable Complexity Evaluation

The use of complexity-based evaluation methods remains relatively underexplored in the field of evaluation. While increasingly employed to assess complex interventions, Contribution Analysis (CA) continues to suffer from a lack of operationalization. In this article, we propose enhancing the implementation of CA by leveraging Participatory Systems Mapping as a tool to delineate and scrutinize contribution narratives. The research has a dual objective. It aims to experiment with the recently introduced Participatory Systems Mapping method in the field of evaluation while providing a tool for examining contribution narratives. The combination of CA and Participatory Systems Mapping was tested by evaluating a youth employability project. This approach enabled a collaborative and in-depth examination of impact stories and alternative explanations. It proved valuable not only in managing the complexity of the intervention but also in strengthening the implementation of CA.

Security Protection of Video-GIS Data Based on Data Encryption and Digital Watermarking

Abstract. Video-GIS data, a novel generation of multimedia produced through the integration of geographic videos and GIS, has evolved into an innovative form of geospatial data representation. As a kind of digital products, Video-GIS data is vulnerable to unauthorized replication, dissemination, and usage. The potential for large-scale leakage of sensitive or confidential information, including commercial, political, military, and personal privacy data, poses a significant threat to the rights of data producers and may even compromise national security. Given this context, the primary concern is ensuring the security protection of video data in an open and shared data environment. To address this issue, we propose a novel scheme for the security protection of Video-GIS data in this paper, which collaboratively utilizes digital watermarking and data encryption. In the proposed scheme, Video-GIS data is divided into two categories, i.e., general and confidential, based on the presence or absence of sensitive information within the image frames. Appropriate security measures were meticulously designed for each data type to ensure effective prevention and control. Experimental results indicate that this watermarking algorithm exerts minimal influence on the quality of the Video-GIS data, while simultaneously maintaining optimal invisibility and robustness. The employed audio denoising method is characterized by its low complexity, simplicity, and feasibility, thereby ensuring the security of audio signal storage and transmission. This approach effectively realizes the dual protection objective for Video-GIS data, audio, and video.

Echoes of Speculation Underway in Relations Between the Occident and China

In a previous article I talked about speculative waves in sequence that have hit the global economy since the 2000s in a world struggling with deflation. Well, this wave of speculation has not stopped but today it seems to concern the transfer of industrial plants from the West to China. A process that was born with the good intentions of transferring industrial activities to developing countries with the dual objective. Give a boost to the economy in developing areas and at the same time reduce the management costs of large multinationals' plants. A process therefore that was born with a positive sign in the intent to help a coordinated development of the territories and a reduction in the costs of industrial products. Meanwhile, the objective of coordinating the development of the territories and continents has not been achieved and on the contrary the process has led to an almost exclusive delocalization of industrial production from the West to China. The excess of industrial localization has exacerbated the concentration of unassimilable waste with a worsening of the disease of the planet struggling with atmospheric overheating. The process, therefore, has been slowed down but not stopped for natural reasons. On the other hand, the acceleration of the development of the Chinese economy has also marked a halt coinciding with the spread of the global epidemic. After about fifty years of accelerated economic growth, the Chinese community has sensed the change in the country's economic prospects and has pulled the brakes on both consumption and investments, marking the end of the accelerated race on the road to development. The picture of the speculative evolution of industrial delocalization processes sees together the interest of mega companies in reducing management costs which is congenial to the increase in the financial values of companies that increase on the Western stock exchanges. In other words, delocalization helps reduce management costs and at the same time seems to support ultra increasing financial values. In short, it plays into the hands of speculation which is certainly not the interest of global social and economic development which instead requires coordination of the territories on the road to development. With the further dilemma that the fate of the global economy may be in the hands of the Boards of Directors of mega companies and not of states and communities.​

Multi-Objetive Dispatching in Multi-Area Power Systems Using the Fuzzy Satisficing Method

The traditional mathematical models for solving the economic dispatch problem at the generation level primarily focus on minimizing overall operational costs while ensuring demand is met across various periods. However, contemporary power systems integrate a diverse mix of generators from both conventional and renewable energy sources, contributing to economically efficient energy production and playing a pivotal role in reducing greenhouse gas emissions. As the complexity of power systems increases, the scope of economic dispatch must expand to address demand across multiple regions, incorporating a range of objective functions that optimize energy resource utilization, reduce costs, and achieve superior economic and technical outcomes. This paper, therefore, proposes an advanced optimization model designed to determine the hourly power output of various generation units distributed across multiple areas within the power system. The model satisfies the dual objective functions and adheres to stringent technical constraints, effectively framing the problem as a nonlinear programming challenge. Furthermore, an in-depth analysis of the resulting and exchanged energy quantities demonstrates that the model guarantees the hourly demand. Significantly, the system’s efficiency can be further enhanced by increasing the capacity of the interconnection links between areas, thereby generating additional savings that can be reinvested into expanding the links’ capacity. Moreover, the multi-objective model excels not only in meeting the proposed objective functions but also in optimizing energy exchange across the system. This optimization is applicable to various types of energy, including thermal and renewable sources, even those characterized by uncertainty in their primary resources. The model’s ability to effectively manage such uncertainties underscores its robustness, instilling confidence in its applicability and reliability across diverse energy scenarios. This adaptability makes the model a significant contribution to the field, offering a sophisticated tool for optimizing multi-area power systems in a way that balances economic, technical, and environmental considerations.

CONTROL OF SHROUD LEAKAGE LOSS AND WINDAGE TORQUE IN A LOW-PRESSURE TURBINE STAGE

Abstract As new aeroengine architectures move to larger diameter fans and rotors, the associated increase in weight will need to be counterbalanced by lighter, more compact, and more efficient low-pressure turbines (LPT). Efficiency gains in LPTs can be achieved by reducing the losses associated with the shroud leakage flows. Flow control studies on the topic have traditionally focused on reducing the mixing loss, which constitutes a considerable proportion of the total loss. Nonetheless, increasing engine speeds are driving additional gains obtained by also targeting the reduction of windage losses. Developing a flow control solution with the dual objective of reducing over-tip cavity mixing and windage losses has not previously been attempted. This is a challenge due to conflicting flow control requirements and geometric constraints. Reducing windage loss generally requires increasing the swirl-ratio of the leakage flow, while reducing mixing loss requires reducing this ratio to match that of the main gas path. The current work proposes a novel flow control solution to successfully achieve this purpose through the emerging technology of additive manufacturing. The successful flow control concept was developed through numerical simulation, printed using an additive manufacturing process, and validated in a purpose-built rig. Experiments and computations were consistent with a cumulative reduction in cavity windage of 16%. The FCC is estimated to increase the mechanical efficiency of the turbine stage in isolation by 1%.

Green Innovation and firm Performance: An Empirical Study of China's Power Industry

With China’s goal of achieving "carbon peak and neutrality”, green innovation has become an inevitable choice to accomplish the dual objective of ecological protection and economic growth. The objective of this study is to examine whether green innovation can contribute to enhancing firm performance. Specifically, this study empirically investigates the relationship between green innovation and firm performance by analyzing a sample of listed firms in China's A-share power industry from 2009 to 2022. By using panel fixed effect regression, this study found that green innovation markedly and positively enhances the firm's current performance. Furthermore, this paper tested the effect of green innovation on the firm's future performance, which is positive and greater than the effect on the current performance. Through data support spanning 14 years, this study verifies the theoretical hypothesis that green innovation can substantially enhance firm performance in the power industry. This not only deepens the understanding of how green innovation affects firm performance but also offers empirical evidence to support the further implementation and advancement of green innovation within the power industry. This study only uses a sample of a single industry, so the conclusions of this study do not have explanatory power for firms in other industries.

Decoding Urban Intelligence: Clustering and Feature Importance in Smart Cities

The rapid urbanization trend underscores the need for effective management of city resources and services, making the concept of smart cities increasingly important. This study leverages the IMD Smart City Index (SCI) dataset to analyze and rank smart cities worldwide. Our research has a dual objective: first, we aim to apply a set of unsupervised learning models to cluster cities based on their smartness indices. Second, we aim to employ supervised learning models such as random forest, support vector machines (SVMs), and others to determine the importance of various features that contribute to a city’s smartness. Our findings reveal that while smart living was the most critical factor, with an importance of 0.259014. Smart mobility and smart environment also played significant roles, with the importance of 0.170147 and 0.163159, respectively, in determining a city’s smartness. While the clustering provides insights into the similarities and groupings among cities, the feature importance analysis elucidates the critical factors that drive these classifications. The integration of these two approaches aims to demonstrate that understanding the similarities between smart cities is of limited utility without a clear comprehension of the importance of the underlying features. This holistic approach provides a comprehensive understanding of what makes a city ’smart’ and offers a robust framework for policymakers to enhance urban living standards.

Construction site environmental pollution management - initiatives, innovation and research

The management of pollution, and in particular of the impact of noise and vibrations, is very important for construction activities, even more so when it comes to urban construction sites. Indeed, some operations have very significant emissive potential and it is appropriate, for the proper conduct of the activities, to adopt a certain strategy in order to control the impacts and thus ensure good acceptance of the construction by the neighborhood. Environmental monitoring is the key to achieving this dual objective: prevent pollution and communicate. This paper presents our innovative approach to localize, identify and report noise pollution on construction sites for efficient noise mitigation. More precisely, usage of acoustic high resolution beamforming is discussed to both identify predominant sources and estimate reliably their contribution to overall noise pollution captured at a given reference point by à Class I metrological device. By combining the easy-to-deploy ATD directional acoustic sensor with its 10cm aperture microphone array, with video recording for event confirmation and labelling on the highly responsive Cadence interface, we show how we can solve complex use cases for a wide range of users, from site managers to acoustic experts.

Exploring the Impact of Heat Treatment on Residual Stress, Microstructure, and Mechanical Behavior of Laser Powder Bed Fusion Additively Manufactured Ti-6Al-2Sn-4Zr-2Mo Alloy

In the field of additive manufacturing (AM), a promising alloy that is gaining attention is the near-α Ti-6Al-2Sn-4Zr-2Mo (Ti6242) alloy. This alloy is known for its remarkable resistance to creep and corrosion at elevated temperatures. However, the production of Ti6242 components via Laser-based AM technologies faced with several challenges, such as the formation of residual stress in the as-built state that originates from the nature of these processes. Therefore, this study has a dual objective: first, to evaluate the microstructure and residual stresses in the as-built Ti6242 produced through laser powder bed fusion. Secondly, to investigate the impact of a promising post heat treatment on mitigating residual stresses, inducing alterations in the microhardness of the Ti6242 alloy and its ductility, phase transformations and microstructure evolution. The as-built specimen exhibited a significant residual stress of 1357 MPa, which was caused by the pronounced temperature gradients experienced during the fabrication process. It is interesting to note that this promising post heat treatment was highly effective in eliminating 99% of the residual stress. After heat treatment, the amount of α' present in the as-built specimen decreased. This resulted in the activation of diffusion of elements such as molybdenum, causing a proportion of the α' to decompose into the more ductile α+β structure. Additionally, it is revealed that the microstructural changes and relieved stresses from the heat treatment process caused a lower microhardness and a higher ductility under compressive loading, as the elongation and toughness reached 20.5% and 23.255 kJ/mm3 in the heat-treated samples, respectively. The outcomes of this work facilitate the use of this alloy in the production of complex shape components through laser-based AM technologies.

Exploring strong controlled partial metric type spaces: Analysis of fixed points and theoretical contributions

This study involves the generalization of partial metric spaces and strong controlled metric type spaces through the introduction of the notion of strong controlled partial metric type spaces. This research pursues a dual objective: firstly, to scrutinize fixed points related to contractions of the Kannan type within the framework of strong controlled partial metric type spaces, encompassing both linear and nonlinear contractions; secondly, to furnish illustrative examples and applications that underscore the consequential implications of our theoretical contributions.

Dual objective nonlinear PD sliding mode control based on a reference model for an active suspension system

Dual objective nonlinear PD sliding mode control based on a reference model for an active suspension system

Integrating machine learning and parametric design for energy-efficient building cladding systems in arid climates: Sport hall in Kerman

Climate change, driven by fossil fuel dependence, presents a significant challenge for the construction industry, particularly in energy-intensive regions like arid climates. This research investigates the potential of integrating machine learning and parametric optimization to enhance the energy efficiency of spatial structure domes in such environments. Focusing on a sports pavilion in Kerman, Iran, the study examines the crucial role of cladding systems in building energy performance. Employing a rigorous four-phase methodology, the research optimizes dome cladding materials for hot, dry climates using a dual objective function: energy cost and material cost. The process involves a comprehensive literature review, data-driven material selection, advanced energy simulations, and optimization analysis. Parametric modeling tools (Rhino, Grasshopper, Honeybee) facilitate the comparative analysis of various cladding systems. Multivariate Polynomial Regression (MPR) enables predictive modeling of energy consumption and material costs, streamlining the design process for architects. The optimized solution is a hybrid cladding model composed of 10 % polycarbonate and 90 % aluminum. Analysis reveals that the hybrid system offers superior energy optimization compared to pure aluminum (4.58 %) and polycarbonate (5.70 %). While polycarbonate has a lower initial material cost, the hybrid system achieves a balance between material expenditure and long-term energy efficiency. This highlights the importance of considering life-cycle costs when evaluating building envelope materials. This research advances a framework that leverages machine learning and parametric design for building envelope optimization. This framework empowers architects and engineers to create energy-efficient structures within arid environments, promoting a more sustainable built environment.

The emotions lived in mathematics classes and their reflection outside the school context: A case study of Manuel

Based on the theory of the Cognitive Structure of the Emotions (OCC), this article has a dual objective: 1) to document negative attitudes toward mathematics generated during the academic formation of Manuel, an adult who ended his school education 15 years before this investigation and today is a professional voice-over actor; and 2) to analyze the reflection of those attitudes in the emotions that emerged during the process of solving mathematical problems related to his work. Manuel was chosen from among ten voice-over professionals who, before the study began, manifested a strong aversion toward mathematics. Manuel was interviewed twice: once before, and then after solving the mathematical problems posed. Results indicate that his negative attitude toward mathematics was reflected in the emotions — frustration, fear, anger, and nervousness — he experienced while solving the problems.

A review on carbonaceous materials for fuel cell technologies: An advanced approach

AbstractIn the context of sustainable development environment‐friendly approaches, technologies have gained momentum with dual objective of achieving technological advancements and innovations through green energy source. One such approach is fuel cells which have been identified as a potential source for the production of electric power from chemical fuels. Fuel cell has become popular as they represent environmentally friendly method to generate power. The trucking industry and fleet transit networks have shown the potential of the hydrogen fuel cell despite many obstacles, such as material composition, storage, and distribution, because it can be used and moved securely, leading to a significant reduction in CO2 and particulate pollution. Proton exchange membrane fuel cells (PEMFC) are the subject of intense research in environmental friendly power transformation and storing tools as a consequence of environmental friendliness, minimal emissions, and great effectiveness. Fuel cell transportation is successful with oxygen reduction process (ORR). Graphite, a highly organized type of carbon, serves as the standard due to its durability and accessibility. This article focuses on the evolution of electrodes as well as electrolytic materials or fluid materials for various kinds of fuel cells and also explains the uses, difficulties, advancements, etc. pertaining to electrodes and fluids of diverse types of fuel cells.

The Financial Feasibility of Investing in a Sustainability Index in India

ESG is at the center of dialogue for investments, corporate governance and management. It used as an acronym for ‘Environmental, Social and Governance’ factors. The rapid rise of ESG has led to the prominence of socially responsible investing and has created a dual objective for investor’s capital. Researchers have previously studied the volatility of sustainable investments and whether SRI affects portfolio performance. Analyzing the financial feasibility of investing in a sustainability index was done by utilizing the historical data of returns on BSE ESG Index, NIFTY 500 Index and the BSE ESG 100 Index from October 2017 to April 2024. S&P BSE 100 ESG Index was used as a proxy for a sustainability index and the S&P BSE 100 Index was the index used to proxy traditional investments. This study has utilized financial ratios along with EGARCH and Granger causality test to understand the risk-reward characteristics of sustainable investments and compare them with traditional investments to understand whether it is financially viable to be a sustainably responsible investor. T test was conducted to identify whether is a significant difference between the returns of the sustainability index and its parent index. Results suggest that the sustainability index has a lower risk-adjusted return than traditional investments however, there is not a significant difference between the returns of the sustainability index and its parent index. There is a presence of strong persistent volatility in the sustainability index and negative shocks have a greater impact on the volatility of the index. Data also suggests a bi-directional relationship between the S&P 500 ESG Index and India’s sustainability index. The study recommends investors to consider the cost associated with investing in sustainability themed instruments while also taking into considerations the factors which are responsible for volatility of sustainable investments as well as the asymmetrical impact of negative shocks on returns.

Management of typical and atypical metastatic lung carcinoids: present and future perspectives.

Lung carcinoids are rare tumors representing 1-2% of all invasive lung malignancies. They include typical and atypical carcinoids, whose distinction is made based on the mitotic index and presence or absence of necrosis. The 10-year overall survival for stage IV typical carcinoid is 47% and 18% for atypical carcinoid, reflecting the indolent growth of these tumors. There are limited approved treatment options for them and most of the evidence comes from retrospective analyses, single-arm trials, subgroup analysis of phase II/III trials for metastatic neuroendocrine tumors and extrapolation of data from phase III trials for gastroenteropancreatic neuroendocrine tumors. Management of metastatic lung carcinoids requires a multidisciplinary standardized approach in specialized centers. Treatment should have a dual objective, control of tumor growth and control of symptoms related to hypersecretion syndromes, aiming to improve quality of life and survival. In the continuum of treatment disease, locoregional treatment options need to be considered in parallel with systemic treatments. In this paper, we review the present treatment options and their rational and we give an insight into future alternatives.

Resilient multi-objective mission planning for UAV formation: A unified framework integrating task pre- and re-assignment

Combat effectiveness of unmanned aerial vehicle (UAV) formations can be severely affected by the mission execution reliability. During the practical execution phase, there are inevitable risks where UAVs being destroyed or targets failed to be executed. To improve the mission reliability, a resilient mission planning framework integrates task pre- and re-assignment modules is developed in this paper. In the task pre-assignment phase, to guarantee the mission reliability, probability constraints regarding the minimum mission success rate are imposed to establish a multi-objective optimization model. And an improved genetic algorithm with the multi-population mechanism and specifically designed evolutionary operators is used for efficient solution. As in the task-reassignment phase, possible trigger events are first analyzed. A real-time contract net protocol-based algorithm is then proposed to address the corresponding emergency scenario. And the dual objective used in the former phase is adapted into a single objective to keep a consistent combat intention. Three cases of different scales demonstrate that the two modules cooperate well with each other. On the one hand, the pre-assignment module can generate high-reliability mission schedules as an elaborate mathematical model is introduced. On the other hand, the re-assignment module can efficiently respond to various emergencies and adjust the original schedule within a millisecond. The corresponding animation is accessible at bilibili.com/video/BV12t421w7EE for better illustration.