Cost Considerations Research Articles

Effects of Artificial Sugar Supplementation on the Composition and Nutritional Potency of Honey from Apis cerana.

In the global apiculture industry, reward feeding and supplementary feeding are essential for maintaining bee colonies. Beekeepers provide artificial supplements to their colonies, typically in the form of either a honey-water solution or sugar syrup. Owing to cost considerations associated with beekeeping, most beekeepers opt for sugar syrup. However, the effects of different types of artificial sugar supplements on bee colonies and their subsequent impact on honey composition remain unclear. To address this gap, this study compared the chemical composition, antioxidant capacity, and nutritional potency of three types of honey: honey derived from colonies fed sugar syrup (sugar-based product, SP) or a honey-water solution (honey-sourced honey, HH) and naturally sourced honey (flower-sourced honey, FH), which served as the control. The results revealed that FH outperformed HH and SP in terms of total acidity, sugar content, total protein content, and antioxidant capacity, and HH outperformed SP. Regarding nutritional efficacy, including the lifespan and learning and memory capabilities of worker bees, FH exhibited the best outcomes, with no significant differences observed between HH and SP. This study underscores the importance of sugar source selection in influencing honey quality and emphasizes the potential consequences of substituting honey with sugar syrup in traditional apiculture practices.

Cost-effective data classification storage through text seasonal features

Data classification storage has emerged as an effective strategy, harnessing the diverse performance attributes of storage devices and orchestrating a harmonious equilibrium between energy consumption, cost considerations, and user accessibility. As research on emerging storage media (e.g. Non-Volatile Memory (NVM)) delves deeper, in scenarios characterized by dynamically evolving storage demands, conventional paradigms of rigid classification strategy and Solid-State Drive (SSD) and Hard Disk Drive (HDD) storage architectures fall short of addressing such complex situations. In this paper, we propose an effective data classification storage method using text seasonal features based on the traditional access frequency analysis strategy. First, to procure richer semantic information, we employ external knowledge actualizing the short-text feature expansion. Then, we leverage the ensemble learning stacking method optimized models to improve the accuracy of data classification based on seasonal features. Additionally, following the seasonal feature, we further classify the data into hot, warm, and cold and place them separately on the NVM, SSD, and HDD, which conserves storage energy consumption and operational costs while ensuring the quality of user access. The experimental results demonstrate that data classification accuracy can reach more than 95.10%, and the energy consumption and operating cost can be reduced by more than 30.22% and 8.73%, respectively.

Scalable business models for startups in renewable energy: Strategies for using GIS technology to enhance SME scaling

The renewable energy sector has witnessed remarkable growth in recent years, driven by global efforts to mitigate climate change and transition towards sustainable energy sources. Startups play a crucial role in this transition, often pioneering innovative solutions and technologies. However, for these startups to thrive and contribute significantly to the renewable energy landscape, scalable business models are essential. This abstract explores strategies for leveraging Geographic Information System (GIS) technology to enhance scalability in small and medium-sized enterprise (SME) startups operating in the renewable energy sector. GIS technology offers a powerful framework for analyzing and visualizing spatial data, providing valuable insights into site selection, resource assessment, and infrastructure planning. By integrating GIS into their business models, startups can optimize operations, reduce costs, and accelerate growth. This review discusses various strategies for utilizing GIS technology, including market analysis, site suitability assessment, supply chain optimization, and infrastructure planning. Drawing on case studies and industry examples, this review highlights the effectiveness of GIS in enhancing scalability for renewable energy startups. It also addresses the challenges and limitations associated with GIS implementation, such as technical complexities, data accessibility, and cost considerations. Furthermore, this review discusses emerging trends in GIS technology and their potential impact on the renewable energy sector, offering insights into future opportunities for startups. In conclusion, this review emphasizes the importance of GIS technology in facilitating scalable business models for renewable energy startups. By harnessing the power of GIS, SMEs can unlock new growth opportunities, drive innovation, and contribute significantly to the transition towards a sustainable energy future. Keywords: Scalable Business Models, Startups, Renewable Energy, GIS Technology, SME Scaling.

Sustainable architecture: Envisioning self-sustaining buildings for the future

Sustainable Architecture: Envisioning Self-Sustaining Buildings for the Future explores the imperative for sustainable design practices in the construction industry. With global environmental challenges becoming increasingly urgent, the need for buildings that are not just energy-efficient but also self-sustaining is paramount. This report delves into the principles, technologies, and design strategies that can transform traditional buildings into sustainable structures that reduce environmental impact and enhance quality of life. The report begins by highlighting the pressing need for sustainable architecture, emphasizing the role of buildings in contributing to carbon emissions, resource depletion, and environmental degradation. It then outlines key principles of sustainable architecture, including energy efficiency, water conservation, waste reduction, and the use of environmentally friendly materials. A major focus of the report is on innovative technologies and design strategies that can be employed to create self-sustaining buildings. These include passive design strategies such as orientation, shading, and natural ventilation, as well as active technologies like solar panels, rainwater harvesting systems, and green roofs. Case studies of successful sustainable buildings from around the world illustrate the practical application of these principles and technologies. Finally, the report discusses the challenges and barriers to implementing sustainable architecture, such as cost considerations, lack of awareness, and regulatory hurdles. It concludes with a call to action for stakeholders in the construction industry to embrace sustainable practices and work towards creating a built environment that is not just sustainable but regenerative, contributing positively to the planet and its inhabitants. "Sustainable Architecture: Envisioning Self-Sustaining Buildings for the Future" provides a comprehensive overview of the principles, technologies, and design strategies that can drive the transition towards a more sustainable built environment. It serves as a valuable resource for architects, designers, policymakers, and anyone interested in creating a more sustainable future. Keywords: Sustainability, Building, Future, Architecture.

Analysis of Deep Peak Shaving Methods for Thermal Power Generation Units Based on the Improved Energy Consumption Framework

Because thermal power producing units account for a large portion of the world's energy consumption, their energy consumption is a major concern. Reducing energy consumption and raising the overall efficiency of thermal power production units has become more and more important in recent years. Reducing energy consumption during peak hours is known as bottomless peak shaving, and it is one way to accomplish this. An enhanced framework for energy consumption is presented in this study to assess and examine deep peak shaving techniques for thermal power plants. The framework takes into consideration the various factors that affect energy consumption, such as fuel type, plant size, and external conditions. It also considers the different aspects of peak shaving, such as intensity and duration. Through the use of this framework, various deep peak shaving methods, such as thermal storage systems, load shifting, and demand response, are evaluated. The effectiveness of these methods is assessed based on their impact on energy consumption, cost, and environmental considerations. The framework also takes into account how feasible and useful it would be to apply these techniques in various kinds of thermal power generating units. The analysis's findings demonstrate that deep peak shaving techniques can dramatically lower energy use during peak hours, which can save money and possibly have positive effects on the environment. The best approach would rely on the unique qualities of every thermal power generating unit.

Cost identification in health professions education: A scoping review.

Resource scarcity in health professions education (HPE) demands rigorous consideration of costs. Yet, thus far, we have been unable to completely and consistently identify the costs of HPE. To address this knowledge gap and enable use of economic evidence in decision making, a detailed overview of all existing costs and approaches to cost identification in HPE is needed. This review summarises the diversity of costs, cost perspectives and cost identification methods used in economic research of HPE to answer the following questions: which educational topics, costs, cost perspectives and cost identification methods are being investigated in HPE literature? This investigation followed the Joanna Briggs Institute guidelines for scoping reviews. PubMed, ERIC, CINAHL and PsycINFO were iteratively searched for English language publications between 2012 and 2022 that reported costs of HPE. Data was extracted for study characteristics, educational context and economic methodology. A total of 136 articles of original research on the costs of educating all major licence healthcare professionals were included. A diffuse interest in costs is reflected in publications from 93 distinct journals and by the diversity of educational topics and cost types explored. However, the majority of investigations failed to define the cost perspective (86, 63%) and cost identification methods (117, 86%) and did not demonstrate common reporting structure or cost terminology, all of which contribute to persistent inconsistencies in cost identification. The source of disharmonious cost identification in HPE is fuelled by diverse interests and divergent concepts of costs and costing methodology. Left in its current state, disharmonious cost identification will continue to limit transparency, comparison and synthesis of evidence, hamper objectivity in implementation and policy decisions and impede the efficient and sustainable allocation of resources. A research agenda must be developed, prioritised, and validated by the broader community to develop a theoretical framework for HPE cost research, define stakeholders, elicit values and preferences and chart a path toward harmonised costing.

Digital public opinion and moratorium policy of Indonesia on Malaysia's maid online system to recruit Indonesian domestic workers

ABSTRACT Since Malaysian authorities developed the Maid Online System (MOS) to recruit foreign domestic workers remotely, including Indonesian workers, the government of Indonesia has enacted a moratorium policy. The system allows Malaysian employers to have low-cost overseas workers. Nevertheless, it offends the bilateral agreement signed in the Memoranda of Understanding between Indonesia and Malaysia. Within the system, the sending countries like Indonesia cannot appropriately protect the workers who utilize MOS independently. In contrast, the host countries dominate the process from pre-departure to arrival. Without proper protection from the country of origin, the workers are more likely to become victims of human trafficking and slavery. This study investigates the positive support of online Indonesian public opinion for Indonesia's moratorium policy concerning Malaysia's Maid Online System (MOS) to recruit foreign domestic workers, including Indonesians. The paper focuses on secondary data from YouTube, Instagram, and online news. The data analysis of this paper utilizes netnography to elaborate on domestic politics in which public opinion (comments on YouTube, Instagram, and online news) strongly supports Indonesia's moratorium policy. Considering Putnam's two-level game theory, this article argues that netizens support Indonesia's moratorium policy because of cost and benefits considerations, rivalry among states, and meritocratic authorities.

Public Health Interventions in the Emergency Department: A Framework for Evaluation.

Emergency departments (ED) in the United States serve a dual role in public health: a portal of entry to the health system and a safety net for the community at large. Public health officials often target the ED for public health interventions due to the perception that it is uniquely able to reach underserved populations. However, under time and resource constraints, emergency physicians and public health officials must make calculated decisions in choosing which interventions in their local context could provide maximal impact to achieve public health benefit. We identify how decisions regarding public health interventions are affected by considerations of cost, time, and available personnel, and further consider the role of local community needs, health department goals, and political environment. We describe a sample of ED-based public health interventions and demonstrate how to use a proposed framework to assess interventions. We posit a series of questions and variables to consider: local disease prevalence; ability of the ED to perform the intervention; relative efficacy of the ED vs community partnerships as the primary intervention location; and expected outcomes. In using this framework, clinicians should be empowered to improve the public health in their communities.

A Wrist-Worn Internet of Things Sensor Node for Wearable Equivalent Daylight Illuminance Monitoring.

Light exposure is a vital regulator of physiology and behavior in humans. However, monitoring of light exposure is not included in current wearable Internet of Things (IoT) devices, and only recently have international standards defined [Formula: see text] -optic equivalent daylight illuminance (EDI) measures for how the eye responds to light. This article reports a wearable light sensor node that can be incorporated into the IoT to provide monitoring of EDI exposure in real-world settings. We present the system design, electronic performance testing, and accuracy of EDI measurements when compared to a calibrated spectral source. This includes consideration of the directional response of the sensor, and a comparison of performance when placed on different parts of the body, and a demonstration of practical use over 7 days. Our device operates for 3.5 days between charges, with a sampling period of 30 s. It has 10 channels of measurement, over the range 415-910 nm, balancing accuracy and cost considerations. Measured [Formula: see text]-opic EDI results for 13 devices show a mean absolute error of less than 0.07 log lx, and a minimum between device correlation of 0.99. These findings demonstrate that accurate light sensing is feasible, including at wrist worn locations. We provide an experimental platform for use in future investigations in real-world light exposure monitoring and IoT-based lighting control.

Supply and demand behaviors in the Chinese emission allowances pledge credit market under different value type: An evolutionary game analysis

Chinese Emission Allowances (CEAs) pledge credit provides a new way for banks to reduce green credit risks and for low-carbon enterprises to improve the credit availability. However, insufficient supply and demand is the main dilemma of CEAs pledge credit in China. One of the reasons for this dilemma may be the neglect of the forward value of CEAs in value assessment. This research explores the decision-making behavior of the supply and demand subjects in the CEAs pledge credit market under different value types of CEAs. First, the improved B–S options pricing model with consideration of transaction costs is used in the construction of the payoff matrix to measure the option value of CEAs. The new matrix aims to place both the option value (corresponding to forward value) and the market value (corresponding to spot value) in the CEAs pledge value evaluation framework. Then, based on the new matrix, an evolutionary game model between key emission enterprises (KEEs) and commercial banks (CBs) is built to dynamically analyze the equilibrium state of supply and demand as well as the strategic interaction of participants in CEAs pledge credit market. Finally, numerical simulations demonstrate the driving factors of supply and demand for CEAs pledge credit. The research results show that compared to market value, the option value of CEAs is more conducive to stimulating the supply and demand of CEA pledge credit; and the shorter the remaining valid period of CEAs, the higher the participation enthusiasm of supply and demand parties. Furthermore, reducing low-carbon technology risks and increasing the carbon emissions trading prices at the end of pledge period can significantly improve the supply and demand of CEAs pledge credit, but the loan and deposit interest rates of CEAs pledge credit are ineffective.

Asian Advantage: Leveraging Logistics for Peak Performance in Efficiency, Effectiveness, Cost, Quality, and Differentiation

The significance of logistics administration in the contemporary, fast-paced business environment has significantly transformed the way organizations operate. This study investigates the interconnected impacts of logistics efficacy, efficiency, cost, quality, and differentiation on the performance of businesses. An in-depth analysis is employed to examine the effect of various logistics management facets on the financial and operational outcomes of a business. Efficient logistics assesses the functionality of supply chains through the optimization of resources and the refining of processes, whereas successful logistics evaluates the ability to promptly and precisely fulfill consumer demands. Through the consideration of both direct and indirect costs, logistics cost analysis assesses the financial impact of logistics operations. Logistics quality examines the reliability, security, and precision of logistical processes, whereas logistics differentiation explores the ways in which unique logistical strategies set an organization apart from its competitors. The objective of this study is to examine the intricate relationships among various performance metrics and these logistics variables. To achieve this, empirical research and statistical modeling are utilized. With the intention that they will assist managers in making more informed decisions and guide businesses toward enhancing their logistics management procedures so that they may flourish in a dynamic marketplace. In order to thrive in the contemporary global marketplace, businesses must recognize the criticality of logistics in shaping organizational results and devise strategies to capitalize on the synergies that exist between these components.

AIRLINE PRICING: HOW AIRLINES USE PRICING STRATGEIES

Airline pricing strategies play a pivotal role in the aviation industry's revenue management. This abstract explores the intricate mechanisms behind airline pricing, delving into the fundamental principles, factors, and techniques utilized by airlines to set fares. Drawing from a combination of academic research, industry reports, and real-world examples, this abstract provides a concise overview of the dynamic landscape of airline pricing. The abstract begins by elucidating the core objectives of airline pricing strategies, emphasizing the dual goals of maximizing revenue and optimizing capacity utilization. It then delineates the key determinants that shape pricing decisions, including demand forecasting, market segmentation, competition analysis, cost considerations, and consumer behavior. Furthermore, the abstract elucidates various pricing tactics employed by airlines, such as dynamic pricing, yield management, fare differentiation, and ancillary revenue generation. It examines how advanced analytics and revenue management systems enable airlines to dynamically adjust fares in response to fluctuating demand patterns, market conditions, and competitor actions. Moreover, the abstract explores the role of distribution channels in airline pricing, highlighting the importance of direct bookings, online travel agencies (OTAs), global distribution systems (GDS), and partnerships with intermediaries. It also discusses the emergence of personalized pricing strategies, leveraging big data analytics and machine learning algorithms to tailor fares based on individual preferences and purchasing behavior. Additionally, the abstract touches upon the regulatory frameworks and ethical considerations surrounding airline pricing practices, including transparency, fairness, and consumer protection. It underscores the need for airlines to strike a balance between revenue optimization and customer satisfaction, fostering trust and loyalty among passengers. In conclusion, this abstract offer valuable insights into the complex ecosystem of airline pricing strategies, shedding light on the multifaceted interplay between market dynamics, technological advancements, and business objectives. By understanding the underlying principles and tactics of airline pricing, stakeholders can navigate the competitive landscape more effectively, driving sustainable growth and profitability in the aviation industry.

Fusing LSTM neural network and expanded disturbance Kalman filter for estimating external disturbing forces of ball screw drives

Monitoring external disturbing forces is of great significance for improving the control performance and interaction safety of ball screw drives. In consideration of the low cost in long-term use and the non-invasiveness to work space, estimating external disturbing forces using motor torque and motion states has been viewed as the solution that has great potential to be applied in real industry. However, the existing methods cannot efficiently establish accurate estimation models in a low-cost and general manner (i.e., not depend on specific work scenarios). To overcome this challenge, a novel hybrid-driven method that fuses Long Short-Term Memory (LSTM) Neural Network (NN) and Expanded Disturbance Kalman Filter (EDKF) is proposed. The motion state of the worktable is decoupled as the linear superposition of the outputs of two independent dynamic models, i.e., Ideal Dynamic Model (IDM) and Disturbance Dynamic Model (DDM). IDM predicts the motion state that is only driven by the motor torque, is modeled as an LSTM NN and trained by self-excitation experiments. DDM is equivalent to the disturbance transfer function and easily identified by impact tests. The motion state only driven by external disturbing forces is calculated by the predicted result of IDM and the monitored actual motion state, and then external disturbing forces are estimated by a DDM-based EDKF. The verifications in simulation and real environments both show that by the proposed method, accurate estimation models of external disturbing forces can be efficiently established through self-excitation experiments and impact tests.

Cash holdings decision‐making in Spanish family firms: Exploring the impact of heterogeneity

AbstractCash holding decision‐making is one of the main corporate challenges for family firms (FFs), with significant consequences for their growth and survival. It is closely connected to key financial decisions such as financing, investments, and dividends. The motivations behind adjusting cash holdings vary, encompassing precautionary, risk avoidance, opportunity cost considerations, and the spending hypothesis. In our study, we aim to integrate specific motivations for cash holding decisions that stem from the influence of family dynamics within these businesses since FFs have unique characteristics, which affect their financial choices. Therefore, we analyze the impact of family involvement in management and the generational stage of FFs on their level of cash holdings. The results of the partial least squares–structural equation modeling, which was estimated on a sample of 7269 unlisted Spanish FFs, show that the higher the level of family involvement in management, as well as the higher the generational stage, the higher the level of cash holdings, with this having a positive effect on the firm's performance. In addition, we find that the positive relationship between family involvement in management and the level of cash holdings is strengthened by family ownership and weakened by family governance. These findings are relevant for a better understanding of the complexity of cash holding decision‐making in FFs and have practical implications not only for the FFs themselves but also for the entities related to them due to the important links between a firm's liquidity and its risk of default and performance.

The Relationship between Pre-Estimation and Cost Management in Industrial Construction Projects

Industrial construction projects are the foundation of organizing industrial production, requiring both quality assurance and cost considerations. Pre-estimation of project costs and cost management are essential means and methods for project cost management. Strengthening the pre-estimation management of construction project costs can effectively control project costs and quality, save funds, and provide data support for management decisions. This article first briefly introduces the concepts of pre-estimation and cost management in engineering costs, focusing on the relationship between pre-estimation and cost management in industrial construction projects. It then proposes countermeasures from the aspects of enhancing the scientificity and accuracy of pre-estimation compilation and strengthening fine management on the construction site, aiming to provide some reference for the industry.

Comparing Oral Vs. Vaginal Antifungal Treatment for Vulvovaginal Candidiasis

Background: Vulvovaginal candidiasis remains a pervasive gynecological concern, affecting a significant portion of women at least once in their lifetime. With the myriad of antifungal treatments available, the choice between oral and intravaginal therapies continues to challenge clinicians and patients alike, underscored by considerations of efficacy, side effects, and patient compliance. Objective: This study aimed to compare the efficacy, side effects, and acceptability of oral fluconazole and intravaginal clotrimazole for treating vulvovaginal candidiasis in a population of married women aged 16 to 50 years. Methods: Conducted as an interventional, experimental study at Pulse Medical Complex, Lahore, over six months from June 2023 to December 2023, 100 participants were randomly allocated to receive either a single dose of 150 mg oral fluconazole or 500 mg of clotrimazole administered as a vaginal pessary or 1% cream for three consecutive days. Data on demographic features, drug side effects, patient compliance, and cost-effectiveness were meticulously collected and analyzed using SPSS version 10.0. Results: Fluconazole demonstrated a higher cure rate with 84% of patients symptom-free within an average of 5 days, compared to 86% for clotrimazole over an average of 8.5 days. Side effects were more common and varied with fluconazole, yet 96% of patients expressed a preference for this treatment due to its convenience and faster symptom resolution. Clotrimazole users reported a 74% preference rate, primarily due to cost considerations. Conclusion: The study reaffirms the superior efficacy and patient acceptability of oral fluconazole over intravaginal clotrimazole for the treatment of uncomplicated vulvovaginal candidiasis, advocating for a patient-centered approach in the selection of antifungal therapy.

Feasibility of high temperature superconducting cables for energy harvesting in large space-based solar power satellite applications: Electromagnetic, thermal and cost considerations

The aim of this paper is to present feasibility of application of High Temperature Superconducting (HTS) cables for Space-Based Solar Power (SBSP) application. SBSP is a promising technology that can deliver an infinite amount of clean and eco-friendly energy to the Earth. To deliver the harvested solar energy to the power systems on Earth, efficient energy transmission is critically important. To address the challenges of conventional transmission means, an ideal solution would be using HTS cables. In this research, the design procedure of a Direct Current (DC) HTS cable considering electromagnetic, thermal, and cost constraints is presented. The study considered a 2 MW bipolar DC HTS cable in five operational temperatures: 20 K, 30 K, 50 K, 65 K, and 77 K. The results were showed that the cost and weight of the designed HTS cables were increased by operational temperature increase. However, the cooling cost of HTS cable in higher temperatures, was less than lower temperatures. Also, the total efficiency of the HTS cable and cooling system were increased, when operational temperatures were changed from 20 K to 77 K, from 99.70% to 99.97%, respectively.

Evaluation of KIAA1549::BRAF fusions and clinicopathological insights of pilocytic astrocytomas

BackgroundPilocytic astrocytoma (PAs) represents a significant portion of childhood primary brain tumors, with distinct histological and radiological features. The prevalence of KIAA1549::BRAF fusion in PAs has been well-established, this study aims to assess the prevalence of KIAA1549::BRAF fusions and explore their associations with tumor characteristics, radiological findings, and patient outcomes in PAs. MethodsHistologically confirmed cases of PAs from a 5-year period were included in the study. Demographic, histopathological, and radiological data were collected, and immunohistochemistry was performed to characterize tumor markers. FISH and qRT-PCR assays were employed to detect KIAA1549::BRAF fusions. Statistical analyses were conducted to examine associations between fusion status and various other parameters. ResultsHistological analysis revealed no significant differences in tumor features based on fusion status. However, younger age groups showed higher fusion prevalence. Radiologically, fusion-positive cases were distributed across different tumor subtypes SE, CWE and NCWE. Survival analysis did not demonstrate a significant impact of fusion status on overall survival, however most cases with recurrence and death harboured KIAA1549::BRAF fusion. Of 200 PAs, KIAA1549::BRAF fusions were detected in 64 % and 74 % of cases via qRT-PCR and FISH, respectively. Concordance between the two platforms was substantial (86 %). ConclusionKIAA1549::BRAF fusions are prevalent in PAs and can be reliably detected using both FISH and qRT-PCR assays. Cost considerations suggest qRT-PCR as a more economical option for fusion detection in routine clinical practice.

Emerging Technologies for Automation in Environmental Sensing: Review

This article explores the impact of automation on environmental sensing, focusing on advanced technologies that revolutionize data collection analysis and monitoring. The International Union of Pure and Applied Chemistry (IUPAC) defines automation as integrating hardware and software components into modern analytical systems. Advancements in electronics, computer science, and robotics drive the evolution of automated sensing systems, overcoming traditional limitations in manual data collection. Environmental sensor networks (ESNs) address challenges in weather constraints and cost considerations, providing high-quality time-series data, although issues in interoperability, calibration, communication, and longevity persist. Unmanned Aerial Systems (UASs), particularly unmanned aerial vehicles (UAVs), play an important role in environmental monitoring due to their versatility and cost-effectiveness. Despite challenges in regulatory compliance and technical limitations, UAVs offer detailed spatial and temporal information. Pollution monitoring faces challenges related to high costs and maintenance requirements, prompting the exploration of cost-efficient alternatives. Smart agriculture encounters hurdle in data integration, interoperability, device durability in adverse weather conditions, and cybersecurity threats, necessitating privacy-preserving techniques and federated learning approaches. Financial barriers, including hardware costs and ongoing maintenance, impede the widespread adoption of smart technology in agriculture. Integrating robotics, notably underwater vehicles, proves indispensable in various environmental monitoring applications, providing accurate data in challenging conditions. This review details the significant role of transfer learning and edge computing, which are integral components of robotics and wireless monitoring frameworks. These advancements aid in overcoming challenges in environmental sensing, underscoring the ongoing necessity for research and innovation to enhance monitoring solutions. Some state-of-the-art frameworks and datasets are analyzed to provide a comprehensive review on the basic steps involved in the automation of environmental sensing applications.

Comparative study of Ti-6.5Al-2Zr-1Mo-1V (TA15) alloy fabricated by selective laser melting and laser metal deposition

In the present study, Ti-6.5Al-2Zr-1Mo-1V (TA15) alloy, one of the widely used near-α titanium alloys in the field of aeronautical and astronautical, was fabricated by two lasers additive manufacturing technologies, namely selective laser melting (SLM) and laser metal deposition (LMD). Microstructure, mechanical property, productivity, and forming cost of fabricated TA15 samples by these two processes were compared systematically. The results showed that the microstructure of the SLM-ed and LMD-ed samples exhibited differences in terms of crystallographic orientations, grain boundaries, and grain sizes, which was mainly attributed to the distinct thermal histories associated with each process. Such differences resulted in the LMD-ed sample presenting anisotropy, lower tensile strength, and higher elongation compared to the SLM-ed sample. Cost analysis indicated that the forming cost per unit volume of the LMD-ed sample was about half that of the SLM-ed sample. This difference was primally due to the higher productivity of the LMD process (226.1 cm3/h) compared to the SLM process (8.8 cm3/h), as well as the lower power cost of the powder materials (60 vs. 100 $/kg). Furthermore, the forming maximum volume of the LMD process (∼30.38 m3) was about 28 times than that of the SLM process (∼1.08 m3). In conclusion, this study provides a detailed comparison between SLM-ed and LMD-ed TA15 samples. The findings can act as a reference for selecting optimized fabrication methods for practical industrial applications, taking into consideration specific mechanical properties, forming size, and cost requirements.