Browse Items (11810 total)
Sort by:
-
Designing a Precision Seed Sowing Machine for Enhanced Crop Productivity
A seed sowing machine is a valuable agricultural device that facilitates the precise and efficient sowing of seeds in fields. When designing and optimizing such a machine, several crucial factors need consideration including seed size, seed rate, soil type, and field conditions. The primary objective is to achieve uniform seed distribution and optimal seed-to-soil contact, which can be accomplished by incorporating a seed metering mechanism to control the seed rate accurately. Versatility is another important aspect of the machine's design, as it should be able to handle different seed sizes, types, soil conditions, and field variations. To achieve this, utilizing advanced technologies such as sensors, automation, and precision farming techniques can significantly enhance the machine's performance and efficiency while also reducing costs and minimizing environmental impact. The optimization of a seed sowing machine plays a crucial role in ensuring successful crop production. By implementing cutting-edge technologies and precision farming techniques, farmers can increase their yields and decrease the amount of seed and fertilizer needed for a specific area. Ultimately, this leads to improved productivity, increased profitability, and a more sustainable approach to agriculture. 2024 E3S Web of Conferences -
Designing an artificial intelligence-enabled large language model for financial decisions
Purpose: Artificial intelligence (AI) has profoundly reshaped financial decision-making, introducing a paradigm shift in how institutions and individuals navigate the complex finance landscape. The study evaluates the significant impact of integrating advanced AI and large language models (LLMs) in financial decision analytics. Design/methodology/approach: The study offers FinSageNet, a novel framework designed and tested to harness the potential of LLMs in financial decisions. The framework excels in handling and analyzing large volumes of numerical and textual data through advanced data mining techniques. Findings: FinSageNet demonstrates exceptional text summarization capabilities, outperforming models like FLAN and GPT-3.5 in Rouge score metrics. The proposed model has shown more accuracy than generic models. Originality/value: The study emphasizes the significance of consistently updating models and adopting a comprehensive approach to integrating AI into financial decisions. This study improves our understanding of how artificial intelligence transforms financial analytics and decision-making processes. 2025, Emerald Publishing Limited. -
Designing an efficient and scalable relational database schema: Principles of design for data modeling
Relational databases are a critical component of modern software applications, providing a reliable and scalable method for storing and managing data. A well-designed database schema can enhance the performance and flexibility of applications, making them more efficient and easier to maintain. Data modeling is an essential process in designing a database schema, and it involves identifying and organizing data entities, attributes, and relationships. In this chapter, the authors discuss the principles of designing an efficient and scalable relational database schema, with a focus on data modeling techniques. They explore the critical aspects of normalization, data types, relationships, indexes, and denormalization, as well as techniques for optimizing database queries and managing scalability challenges. The principles discussed in this chapter can be applied to various database management systems and can be useful for designing a schema that meets the demands of modern data-intensive applications. 2023, IGI Global. All rights reserved. -
Designing and delivery of e-service quality of mobile banking /
Patent Number: 202231004591, Applicant: Tapan Kumar Shadilya.
The present disclosure is method for the enhancing quality for mobile banking service. In an aspect, the specification describes a method for transmitting data between smartphone or any other mobile device and a server. The method includes running a mobile application on the smartphone or any other mobile device. The mobile application has plurality of features. -
Designing Artificial Intelligence-Enabled Training Approaches and Models for Physical Disabilities Individuals
The focus of this research is on investigating AI-based strategies and models that can be used to develop workforce training systems specifically for individuals with physical disabilities. The goal is to leverage the advancements in artificial intelligence (AI) and its potential impact on workplace learning and development. There is an increasing demand for utilizing AI capabilities to design comprehensive training programs that are both inclusive and effective for people who face physical challenges. The research will examine effective strategies, real-life examples, and current AI-based training platforms for people with physical disabilities. Additionally, it aims to tackle the obstacles and ethical matters linked to incorporating AI in workforce training. These concerns include mitigating biases, ensuring accessibility, and safeguarding privacy. The outcomes of this study will assist in creating progressive approaches and frameworks driven by AI that can empower individuals with physical disabilities by improving their employability prospects while simultaneously fostering inclusivity within workforce training. The chapter will also explore the integration of AI-powered solutions in training programs for physically challenged individuals. By utilizing AI technologies like personalized learning algorithms, predictive analytics, and adaptive content delivery systems, training can be customized to cater to the unique requirements and learning needs of everyone. The implementation of AI has the potential to automate processes, analyze data effectively, and generate personalized learning pathways for improved accessibility. 2024 selection and editorial matter, Alex Khang; individual chapters, the contributors. -
Designing Bifunctional Electrocatalysts Based on Complex Cobalt-Sulfo-Boride Compound for High-Current-Density Alkaline Water Electrolysis
In the quest to harness renewable energy sources for green hydrogen production, alkaline water electrolysis has emerged as a pivotal technology. Enhancing the reaction rates of overall water electrolysis and streamlining electrode manufacturing necessitate the development of bifunctional and cost-effective electrocatalysts. With this aim, a complex compound electrocatalyst in the form of cobalt-sulfo-boride (Co-S-B) was fabricated using a simple chemical reduction method and tested for overall alkaline water electrolysis. A nanocrystalline form of Co-S-B displayed a combination of porous and nanoflake-like morphology with a high surface area. In comparison to Co-B and Co-S, the Co-S-B electrocatalyst exhibits better bifunctional characteristics requiring lower overpotentials of 144 mV for hydrogen evolution reaction and 280 mV for oxygen evolution reaction to achieve 10 mA/cm2 in an alkaline electrolyte. The improved Co-S-B performance is attributed to the synergistic effect of sulfur and boron on cobalt, which was experimentally confirmed through various material characterization tools. Tafel slope, electrochemical surface area, turnover frequency, and charge transfer resistance further endorse the active nature of the Co-S-B electrocatalyst. The robustness of the developed electrocatalyst was validated through a 50 h chronoamperometric stability test, along with a recyclability test involving 10,000 cycles of linear sweep voltammetry. Furthermore, Co-S-B was tested in an alkaline zero-gap water electrolyzer, reaching 1 A/cm2 at 2.06 V and 60 C. The significant activity and stability demonstrated by the cobalt-sulfo-boride compound render it as a promising and cost-effective electrode material for commercial alkaline water electrolyzers. 2024 The Authors. Published by American Chemical Society. -
Designing Biomass Rice Husk Silica as an Efficient Catalyst for the Synthesis of Biofuel Additive n-Butyl Levulinate
The conversion of lignocellulosic biomass levulinic acid to biorefinery platform organic component n-butyl levulinate is done by an eco-friendly process. The catalyst used for this reaction was prepared by an innovative strategy of impregnating CeO2 and Sm2O3 on silica derived from rice husk, biomass of low economic value, using different methods. The impregnation of ceria and samaria into the silica framework led to a change in the textural properties which was confirmed by various spectroscopic methods. A comprehensive study of the influence of reaction parameters on the esterification of levulinic acid with n-butanol revealed the optimum conditions for maximum yield and selectivity. In the solvent-free condition, the reaction achieved 94.9% conversion of levulinic acid and 97.2% selectivity of n-butyl levulinate within a duration of 1.5h. The regenerated catalysts were stable and efficient up to four cycles. [Figure not available: see fulltext.]. 2020, Springer Science+Business Media, LLC, part of Springer Nature. -
Designing coordinatively unsaturated metal sites in bimetallic organic frameworks for oxygen evolution reaction
Metal organic frameworks (MOFs) are developing as promising catalysts for oxygen evolution reactions. A bimetallic electrocatalyst MOF using Ni and Cu as metal sources and 1,4-benzene dicarboxylic acid as a linker has been synthesized and evaluated for oxygen evolution reaction. Compared to monometallic MOFs, bimetallic MOFs participate more actively in electrocatalysis due to the higher abundance of active sites, local crystallinity, and lower long-range disorder. When utilized as oxygen evolution catalysts, NiCu MOFs have a low overpotential of 340 mV at 10 mA/cm2 and a low Tafel slope of 65 mV/dec. The study paves the way for the development of highly efficient catalysts for water splitting applications. 2023 Elsevier Ltd -
Designing of a Free-Standing Flexible Symmetric Electrode Material for Capacitive Deionization and Solid-State Supercapacitors
In this work, a highly efficient free-standing flexible electrode material for capacitive deionization and supercapacitors was reported. The reported porous carbon shows a high surface area of 2070.4 m2 g-1 with a pore volume of 0.8208 cm3 g-1. The material exhibited a high specific capacitance of 357 F g-1 at 1 A g-1 in a two-electrode symmetric setup. A solid-state supercapacitor device has been fabricated with a total cell capacitance of 152.5 F g-1 at 1 A g-1 in a solid PVA/H2SO4 gel electrolyte with an energy density of 21.18 W h kg-1 at a 501.63 W kg-1power density. A long-run stability test was carried out up to 15,000 cycles at 5 A g-1 that showed capacitance retention of 99% with ?100% Coulombic efficiency. Furthermore, the electrosorption experiment was conducted by a flow-through test by coating on commercially available cellulose thread that was employed, which shows electrosorption ability up to 16.5 mg g-1 at 1.2 V in a 500 mg L-1 NaCl solution. Complete experiments were conducted with a proper procedure, provided by scientific approaches with analytical data. Thus, the reported electrode material showed bifunctional application for energy storage and environmental remediation. 2023 American Chemical Society. -
Designing social learning analytics for collaborative learning using virtual reality, life skill, and STEM approach
This chapter explores the design of social learning analytics for collaborative learning, incorporating virtual reality, life skills, and a STEM approach. Researchers employ social learning analytics, an emerging field that combines social network analysis and learning analytics, to gain insights into collaborative learning environments. The chapter emphasizes integrating virtual reality, life skills, and STEM in social learning analytics, covering data collection methods, data analysis techniques, and pedagogical applications. It also explores key considerations for designing social learning analytics in collaborative learning, encompassing the development of tools and assessment strategies. Finally, the chapter looks ahead to future directions and prospects for social learning analytics in collaborative learning. 2024, IGI Global. All rights reserved. -
Desiri Naturals: sustainable agriculture and eco-friendly business
Learning outcomes: After completion of the case study, the students will be able to critically analyze the business model of Desiri Naturals, analyze the pricing strategy of Desiri Naturals, examine the importance of experiential marketing in the success of an environment-friendly business, identify the challenges faced by new entrepreneurs and evaluate the sustainability practices of Desiri Naturals. Case overview/synopsis: This case study discusses the business model of an environmentally friendly business. The challenges and obstacles faced by entrepreneurs are illustrated in this case. The entrepreneurs vision to provide chemical-free food is highlighted and their business operations as a means to fulfill this vision are explained. Desiri used an age-old bull-driven method of oil extraction (Ghana). Challenges in pricing due to the availability of low-priced mass-produced edible oil using the solvent extraction process are presented in this case. The entrepreneurs faced the pricing dilemma at the inception of the business, as oil produced using the natural cold pressing method cost three times the selling pricing of solvent-extracted oil. Innovative methods of experiential marketing such as Ghana tourism are explained in this case. This case study also explains the sustainable and natural farming techniques propagated through its network of farmers. This case study provides insights into the scalability of this model and the scope for employment generation in rural India. The environmentally friendly practices followed by Desiri, such as the use of glass bottles and reusable steel containers for packaging oil are emphasized. Finally, this case presents the marketing and operational challenges faced by entrepreneurs in their quest to expand their operations. Complexity academic level: This case study can be used by postgraduate and undergraduate students studying marketing, entrepreneurship, sustainability and operations management courses in commerce and business management streams. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS8: Marketing. 2024, Emerald Publishing Limited. -
Desk organizer /
Patent Number: 350152-001, Applicant: Vaibhav Tripathi. -
Desk organizer /
Patent Number: 350152-001, Applicant: Vaibhav Tripathi. -
Desk organizer /
Patent Number: 350152-001, Applicant: Vaibhav Tripathi. -
Desk organizer /
Patent Number: 350152-001, Applicant: Vaibhav Tripathi. -
Despeckling of Ultra sound Images using spatial filters - A Fusion Approach
Ultra sound images are normally affected by speckle noise which is typically multiplicative in nature. This study proposes different fusion based despeckling methods for ultra sound images. The output of existing spatial domain despeckling methods viz. Lee filter, Bayesian Non Local Means (BNLM) filter and Frost filter are fused pairwise. Fusion is implemented in two steps, first an inter-scale stationary wavelet coefficient fusion followed by an intra-scale wavelet coefficient fusion. Analysis of these projected despeckling strategies are conducted using metrics like Peak Signal to Noise Ratio (PSNR), Equivalent Number of Looks (ENL), Structural Similarity Index (SSIM) and Universal Image Quality Index (UIQI). The results show that the performance of fusion based methods is better than the respective individual filters for despeckling ultra sound images. 2019 IEEE. -
-
Destination governance and a strategic approach to crisis management in tourism /
Journal Of Investment And Management, Vol.5, Issue 1, pp.1-5, ISSN: 2328-7721 (Online), 2328-7713 (Print). -
Destination image and perceived meaningfulness for visitor loyalty: A strategic positioning of Indian destinations
The purpose of this study is to empirically test and validate a multi-dimensional structure of In-loco Destination Image and perceived meaningfulness using an integrated model of visitor loyalty. The model was tested using data collected from responses of foreign tourists visiting India (n = 246). The results identified six dimensions of In-loco Destination Image: Amenities, Attractions, Leisure, Culture, Support Systems, and Hospitality. In addition, the investigation observes that of the identified dimensions of perceived meaningfulness, the spiritual and societal dimensions contribute more to perceived meaningfulness than the physical well-being aspect. Further, the exploration estimated the theoretical framework developed using structural equation modelling and established the mediating role of perceived meaningfulness in developing visitor loyalty from In-loco Destination Image. The studys observations helped identify three positioning approaches, namely objective, subjective, and combined, offering suggestions to destination marketers to effectively reposition Indian destinations. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Destination Resilience and Smart Tourism Ecosystem : A Destination Management Framework for Competitiveness
Over the past many decades, the travel and tourism industry has been at the forefront of adapting to new changes and accepting the latest technologies. Today's travelers are sophisticated and knowledgeable, as they have all the information available to them easily, which contributes to fast and quick decision making. The world is gradually changing into a much more intelligent and advanced platform that makes it possible to employ techniques like augmented reality, virtual reality, and artificial intelligence. This has proven to be very successful in a variety of fields, including education, healthcare, marketing, and communication. The current study focuses on incorporating smart tourism strategies to build a sustainable ecosystem at destinations, which enhances the competitiveness of the destination and makes it easier for value co- creation among the different stakeholders. Research suggests that although industry-led and government-initiated projects seem to prioritize the use of smart applications in destinations in theory, practical implementation appears to lag behind. Less research has been done in India on gamification, smart wearable technology at travel destinations, and the practical application of AR and VR tools. The study revolves around the South Indian State of Kerala, which has been a pioneer in tourism promotion in the country. In addition to proposing a framework for destination management and tourism competitiveness with smart tourism applications, this study aims to investigate the practical implications of smart tourism tools and technologies at destinations. To shed more light on the findings, a mixed methodology approach is used to analyze the data using a mix of quantitative and qualitative methods. The study's conclusions have significant ramifications for destination management, strategic planning, and the application of smart technologies at travel locations.