Efficient Access Research Articles

Evaluating Budget Functions for Effective Revenue and Expenditure Planning in Hulu River South District

The public sector budget has a function as a local financial management planning tool. BPKPD district of Hulu River South is an institution that carries out the duties of the local government in the planning of the regional budget. This study is aimed at finding out the application of budget functions as a tool for planning income and expenditure in the BPKPD district of Hulu River South. This study uses a method of quantitative research using a descriptive approach. The study uses three types of measurement analysis to find out the use of budget function as a planning tool, namely, the process of budgeting, the level of effectiveness of budget income, and the degree of efficiency as well as deviations in budget expenditures. The income budget effectiveness rate for 2022 reached 118.60% (more than 100%) with the category of highly effective, coming from three types of regional income. First, Regional Real Income with an efficiency ratio of 87.51% belongs to the effective category. Second, Transfer income with an effectiveness rate of 119.82% belonging to the highly efficient category. The calculation of the expenditure efficiency ratio showed less efficient access, with a ratio of 93.06%. Operations purchases obtained a rate of 75.92% in the efficient category. Capital purchases gained access to efficiency ratios of 91.41%, including the less effective category. Unexpected expenditures reached the rate of efficiency of 17.92%, in the highly efficient categories. Lastly, the transfer spending sector has an efficiency rate of 99.81% in the less efficient category. Secondly, the calculation of the variance analysis in the regional spending sector shows that the entire account in the local spending area has more variance. No spending account has a budget deficit as a result of the realization or achievement of greater income than estimated. The deviation that occurs on the entire account of the shopping sector is favorable.

The Role of Artificial Intelligence in Creation of Future Education: Possibilities and Challenges

Artificial intelligence has significant potentials in revolutionizing education by enhancing teaching methods, personalizing learning experiences, and improving educational outcomes. The aim of the research is to specify the role of AI in creation of future education and to outline the potentials and challenges artificial intelligence can bring within the educational process. To answer the research questions the case study on the role of AI in the creation of future education was conducted. The methods included structured interviews among institutions administrators, faculty members, students, and AI developers; survey among students and faculty to collect quantitative data on their use of and attitudes towards AI technologies; classroom observations. Over 50 recent scientific works were selected to evaluate the role of artificial intelligence in education and to conduct the comparative educational analysis. The research was conducted among 56 participants, in particularly 9 institutions administrators, 19 faculty members, 24 students, and 4 artificial intelligence developers. The results showed that artificial intelligence integrated in the educational process are used to design simulation-based activities, organize personalized learning, form specific skills among students, and automate the administrative process. artificial intelligence leads to enhancement of learning outcomes among students, increased efficiency, and greater accessibility of education, during war in particularly when the educational process can be disrupted. Using artificial intelligence in education presents several challenges that need to be addressed for its effective implementation. Also, it was found that efficient using artificial intelligence tools within the educational process will lead to the creation of positive artificial intelligence based learning landscape at the institutions of higher education which is characterized by efficiency, interactivity, inclusivity, innovation, and accessibility. The results of research can be implied by educational institutions to improve the educational process and by EdTech companies to develop educational tools and platforms.

Local large language models for privacy-preserving accelerated review of historic echocardiogram reports.

The study developed framework that leverages an open-source Large Language Model (LLM) to enable clinicians to ask plain-language questions about a patient's entire echocardiogram report history. This approach is intended to streamline the extraction of clinical insights from multiple echocardiogram reports, particularly in patients with complex cardiac diseases, thereby enhancing both patient care and research efficiency. Data from over 10 years were collected, comprising echocardiogram reports from patients with more than 10 echocardiograms on file at the Mount Sinai Health System. These reports were converted into a single document per patient for analysis, broken down into snippets and relevant snippets were retrieved using text similarity measures. The LLaMA-2 70B model was employed for analyzing the text using a specially crafted prompt. The model's performance was evaluated against ground-truth answers created by faculty cardiologists. The study analyzed 432 reports from 37 patients for a total of 100 question-answer pairs. The LLM correctly answered 90% questions, with accuracies of 83% for temporality, 93% for severity assessment, 84% for intervention identification, and 100% for diagnosis retrieval. Errors mainly stemmed from the LLM's inherent limitations, such as misinterpreting numbers or hallucinations. The study demonstrates the feasibility and effectiveness of using a local, open-source LLM for querying and interpreting echocardiogram report data. This approach offers a significant improvement over traditional keyword-based searches, enabling more contextually relevant and semantically accurate responses; in turn showing promise in enhancing clinical decision-making and research by facilitating more efficient access to complex patient data.

Efficient access control scheme for heterogeneous signcryption based on blockchain in VANETs

Efficient access control scheme for heterogeneous signcryption based on blockchain in VANETs

Agriculture eCommerce Website with ML Chatbot

The project aims to develop an innovative Agriculture eCommerce platform integrated with a Machine Learning (ML) chatbot to revolutionize the agricultural industry's online marketplace. The proposed system addresses the growing need for efficient access to agricultural products and services while enhancing user engagement through intelligent conversational interfaces. The Agriculture eCommerce site serves as a digital marketplace where farmers, agricultural professionals, and enthusiasts can browse, purchase, and interact with a wide range of agricultural products, equipment, and services. Leveraging ML algorithms, the platform's chatbot offers intuitive conversational interactions, allowing users to inquire about products, receive recommendations, and troubleshoot queries effectively. Through this project, B.Tech students will gain valuable experience in developing a comprehensive eCommerce solution integrated with cutting-edge ML technology. Additionally, the project holds the potential to make a significant impact on the agricultural sector by fostering digital transformation and facilitating access to agricultural resources. Keywords: - Agricultural industry, eCommerce, Machine Learning, Digital experience, User-friendly platform, Chatbot, Farming community.

Design, synthesis, and biological evaluation of novel 2,3-Di-O-Aryl/Alkyl sulfonate derivatives of l-ascorbic acid: Efficient access to novel anticancer agents via in vitro screening, tubulin polymerization inhibition, molecular docking study and ADME predictions

A series of novel l-ascorbic acid derivatives bearing aryl and alkyl sulfonate substituents were synthesized and characterized. In vitro anticancer evaluation against MCF-7 (breast) and A-549 (lung) cancer cell lines revealed potent activity for most of the compounds, with 2b being equipotent to the standard drug colchicine against MCF-7 (IC50 = 0.04 μM). Notably, compound 2b displayed 89-fold selectivity for MCF-7 breast cancer over MCF-10A normal breast cells. Derivatives with two sulfonate groups (2a-g, 3a-g) exhibited superior potency over those with one sulfonate (4a-c,5g, 6b). Compounds 2b and 2c potently inhibited tubulin polymerization in A-549 cancer cells (73.12 % and 62.09 % inhibition, respectively), substantiating their anticancer potential through microtubule disruption. Molecular docking studies showed higher binding scores and affinities for these compounds at the colchicine-binding site of α, β-tubulin compared to colchicine itself. In-silico ADMET predictions indicated favourable drug-like properties, with 2b exhibiting the highest binding affinity. These sulfonate derivatives of l-ascorbic acid represents promising lead scaffolds for anticancer drug development.

Understanding the Role of Digital Identity: A Conceptual Framework and Proposed Methodology for Measuring Malaysia's National Digital Identity Initiative

Malaysia is in the process of developing a National Digital Identity (NDI) system to provide citizens and residents with secure and efficient access to digital services. However, the success of the initiative depends on public awareness, perception and acceptance of the system. This paper proposes a preliminary framework for measuring public awareness, perception and acceptance of the NDI initiative in Malaysia. The framework was developed based on an extensive literature review and includes several important variables, including public awareness, perception and acceptance, as well as perceived usefulness, perceived ease of use, user experience, social influence and facilitating conditions. The proposed research design is based on a quantitative methodology using a questionnaire to collect data from a diverse sample of respondents. The proposed framework and methodology are a valuable contribution to the literature on the NDI initiative and can provide a foundation for future empirical research in this area. By using a rigorous research design, this study can provide valuable insights into the public's attitudes and perceptions towards this initiative, which can inform policy decisions and contribute to the successful implementation of the NDI initiative in Malaysia. The study contributes to the ongoing discussions on digital identity (DI) and provides valuable insights for policy makers, practitioners and researchers seeking to promote the adoption of DI systems in Malaysia and beyond.

P097 Launching the Juvenile Idiopathic Arthritis VIP Research Panel - an innovative and unique way to engage with the Juvenile Idiopathic Arthritis community

Abstract Background/Aims The volume of survey-based research targeting families affected by Juvenile Idiopathic Arthritis (JIA) has been increasing, leading to respondent fatigue, reduced response rates, repetitive data collection, and consequential reduced robustness of data. In addition, poor quality surveys with no anticipated research outcomes of benefit to the community have further added to the burden on families. There is also increased interest in recruiting patient representatives to help shape and steer research through appropriate Patient and Public Engagement and Involvement (PPIE), but without a robust structure in place the numbers of families involved has been small and their representativeness questioned. This project improves research quality, accessibility for researchers to access motivated survey respondents, reduces the burden on participants, and provides a central solution for accessing JIA research participants. Methods Juvenile Arthritis Research is a charity in the UK, with considerable experience of developing research projects and engaging in PPIE activities, and a highly-engaged network of families affected by JIA. The charity launched the JIA VIP Research Panel in September 2023, inviting members of their network to join. Participants give fully informed consent upon sign-up, and provide demographic details. These are held securely and anonymously. New research, developed in-house or with academic, clinical or industry partners, is shared with the JIA VIP Research Panel. Participants are invited to complete surveys, knowing they have been quality assured and verified, and without the need to re-submit the same demographic data repeatedly over time. The Panel is also available for PPIE activities, with researchers able to access members of the Panel based on diagnosis, demographic or other criteria. Results Within 3 days of launch, over 100 families joined the JIA VIP Research Panel, with a representative spread of participants; recruitment is an ongoing and continuous process. Conclusion The JIA VIP Research Panel (www.jarproject.org/vip) is an innovative resource enabling faster, more flexible, and more efficient access to families with JIA in the UK both for survey-based research and involvement in PPIE. The Panel has begun to improve the quality of research, building upon previous success and continuing to develop high levels of engagement with participants. Disclosure R.P. Beesley: None. R.M. Beesley: None.

Palladium-Catalyzed Carbohalogenation of Olefins with Alkynyl Oxime Ethers: Rapid Access to Chlorine-Containing Isoxazoles.

A palladium-catalyzed carbohalogenation of olefins with alkynyl oxime ethers has been described, which provides efficient and practical access to various chlorine-containing isoxazoles. This method exhibits excellent regioselectivity, good functional group compatibility, and mild reaction conditions. The mechanistic studies suggest that the reaction proceeds via a stabilized π-benzyl palladium intermediate, which is essential for the formation of C(sp3)-Cl bonds.

The Impact of Digital Marketing and Innovation on Marketing Performance is Influenced through the Development of a Competitive Advantage

Objective: The aim of this research is to explain how Micro Small Medium Enterprises (MSMEs) implement digital marketing and innovation, achieve competitive advantage, and improve marketing performance. The study also examines how digital marketing and innovation influence marketing performance through competitive advantage. This study centers on detailing and examining these aspects, involving an investigation carried out on small-scale food and beverage entrepreneurs in Bekasi, Indonesia. Theoretical Framework: Este estudo está fundamentado na Teoria da Visão Baseada em Recursos. Ele enfatiza a importância das capacidades dinâmicas, que são a habilidade de uma empresa ajustar seus recursos e capacidades para se manter competitiva em condições de mercado em constante mudança. As organizações podem manter sua vantagem competitiva e alcançar sucesso a longo prazo ao adaptar-se continuamente e introduzir novas ideias. Method: This study utilizes quantitative methodologies. 100 food and beverage micro business owners were surveyed using the simple random sampling method. The PLS technique is utilized in the data analysis process. Results and Discussion: The findings indicate that competitive advantage is positively impacted by digital marketing and innovation. Digital marketing also has a beneficial impact on marketing effectiveness. Competitive advantage plays a role in connecting digital marketing with marketing performance, as well as linking innovation with competitive advantage. Innovation does not impact marketing performance. Research Implications: Entrepreneurs must integrate digital marketing to enhance marketing effectiveness and incorporate digital marketing and innovation to boost competitive edge. It is necessary to engage in constant communication with customers using online platforms, ensure fast and efficient access to information, keep product content up-to-date and in line with current trends, deliver products as scheduled, and provide frequent updates on product availability in the market. They must also implement modifications in their business operations to effectively and efficiently meet the demands and desires of their customers. Originality/Value: This research adds to the existing body of research by validating that digital marketing can enhance marketing effectiveness both directly and through competitive advantage. Innovation does not have a direct impact on marketing performance. In order to enhance the marketing performance of food and beverage MSMEs, innovation must serve as a competitive edge. The MSME owners can be motivated by the research results to adopt digital marketing and innovation, leading to a competitive edge for their products. This will help enhance their marketing performance and ensure long-term sustainability.

Rancang Bangun Sistem Informasi Manajemen Asset Berbasis Web Dengan Metode Waterfall

This research is an effort to design and build a web-based Asset Management Information System (SIMA) by applying the Waterfall Method. SIMA is an important component in managing an organization's assets, including the efficient procurement, maintenance and monitoring of assets. The Waterfall method was chosen because it has a systematic and structured approach, starting from the needs analysis stage to the implementation and system maintenance stages. The aim of this research is to optimize the asset management process by integrating web technology so that it can provide real-time and efficient access to information. This is expected to have a positive impact on more effective and measurable asset management in various industrial sectors. This research will focus on the key steps in developing a web-based SIMA using the Waterfall Method. The first stage is requirements analysis, where the functional and non-functional requirements of SIMA will be identified in detail. Next, system design will be carried out based on the results of the analysis, including designing the user interface and database structure. The implementation phase will change the system design into program codes that can run, followed by the testing phase to ensure the quality and performance of the system. Finally, the system will be fully implemented and maintained according to needs and changes that occur. Thus, it is hoped that this research can make a significant contribution in increasing the efficiency and effectiveness of asset management through the use of appropriate and structured information technology..

An Optimized Data Storage in A Secure Cloud-Edge Collaboration A Fault Tolerance Approach

The rise of edge smart IoT devices has led to the development of edge storage systems (ESS) for efficient access to massive edge data. ESS can reduce the load on cloud centers and improve user experience. However, ESS still faces challenges in improving fault tolerance and efficiency. Thus, there is a need for a secure and efficient fault-tolerant storage scheme. Existing schemes have drawbacks like high edge storage overhead, difficulty in protecting edge data privacy, and low data writing performance. To address these issues, we propose a Hierarchical Cloud-Edge Collaborative Fault-Tolerant Storage (HCEFT) model. This model aims to enhance system robustness, reduce edge storage overhead, and ensure edge data privacy. We also introduce an optimization method for data writing in HCEFT, called ECWSS (Erasure Code data Writing method based on Steiner tree and SDN). This method improves the trade-off between data writing time and traffic consumption. Our scheme improves data robustness, availability, and security. Additionally, the writing optimization method reduces data write time by 13%-67% and network traffic consumption by 20%-62%, enhancing network load balance performance.

Landscape of Digital Technologies Used in the National Health Service in England: Content Analysis.

In England, digital technologies are exploited to transform the way health and social care is provided and encompass a wide range of hardware devices and software that are used in all aspects of health care. However, little is known about the extent to which health care providers differ in digital health technology capabilities and how this relates to geographical and regional differences in health care capacities and resources. This paper aims to identify the set of digital technologies that have been deployed by the National Health Services clinical commissioning groups (NHS CCGs) in England. In doing this, we respond to calls to shed light on the internal dynamics and variation in the form of digital capability in England in terms of health service regional differences and health diversity, equity, and inclusion. We collected 135 annual reports that belong to 106 NHS CCGs in England, comprising more than 18,000 pages in total, released from 2020 to 2021. Using this data set, we identified 2163 pages related to digital technologies and labeled them using content analysis. We follow the construct taxonomy used by digital options theory, a theory from the management information systems field analyzing organizational resource investment choices, in classifying observed technologies according to digital themes-inherent design patterns that we identified and explained. We then used a hierarchical clustering method to extract groups of NHS CCGs that implement similar technology themes. We found 31 technologies from the reports and grouped them into 9 digital themes. The 9 themes were further assigned to 1 of the 3 constructs of digital options theory, the identification of patients' requirements (we identified information portals [76/106], digital health engagement [67/106], and digital inclusion support [45/106]), the development of new work patterns (we identified telehealth [87/106], telemedicine [35/106], and care home technologies [40/106]), the realization of improvements in efficiency and public accessibility (we identified online booking [26/106], online triage [104/106], and digital mental health services [74/106]). The 3 clusters of CCGs are identified based on the 8 themes (Hopkins=0.9914, silhouette=0.186), namely (1) digitally disengaged, (2) digitally engaged, and (3) digital torchbearer. Our findings show prominent digital themes within each construct group, namely information portals, telehealth, and online triage, covering people's fundamental health information needs. Almost half of CCGs fell into the digitally disengaged group, and all London CCGs (5/106) belonged to this group. We propose that practitioners should offer specialized assistance to regions with limited digital engagement, emphasizing digital health literacy, inclusion support, and ongoing evaluation, rather than concentrating solely on technical advancements.

Efficient access to triphenylene derivatives via carbamate-directed bay-region selective arylation of biphenol derivatives and Scholl cyclization

A novel method for carbamate-directed meta-C-H bond arylation of biphenyl derivatives employing diaryliodonium salts as the arylation agents was explored. Consequently, the Scholl reaction was utilized to cyclize the product, yielding 21 varieties of multifunctional triphenylene derivatives. The maximum yield achieved through this two-step process was 94 %, offering an efficient synthesis route for the production of multi-substituted triphenylene derivatives.

Identity in the Digital Age: An Investigation of Malaysian Perspectives on Technology and Privacy

Malaysia is in the process of developing a new identity system to provide citizens and residents with secure and efficient access to digital services. This study aimed to determine the responsiveness of the Malaysian population to new technologies and evaluate their opinions on managing their identity online. The study employed a quantitative research design and collected data through an online questionnaire. A total of 1,014 participants from Malaysia, aged 18 years and above, were included in the study, and the data were analysed using cross-tabulation analysis. The theoretical framework of the study was based on the technology acceptance model, the risk and negative consequences theory of individuals' perceptions, and the organizational trustworthiness theory. The results showed that various demographic characteristics influence individuals' attitudes towards technology adoption and online identity management. Gender, age, ethnicity/race, work status, employment sector, level of education, place of living, household income level, and residence state were all significantly associated with early adoption of emerging technologies, trying out new technologies, and enjoyment of trying out new technologies. Certain demographic factors may also have an impact on people's preferences for specific identity management tools. The study also found significant relationships between various demographic factors and trust levels when it comes to personal data. The study findings have implications for policymakers and practitioners involved in promoting the adoption of new technologies and the management of online identities. The study's findings may assist policymakers in implementing better measures for protecting Malaysians' online identity and privacy. Additionally, the results could also inform future research investigating technology adoption and acceptance among Malaysians.

Research Review on Multi-Port Energy Routers Adapted to Renewable Energy Access

With the continuous development of renewable energy technologies, both domestically and internationally, the focus of energy research has gradually shifted towards renewable energy directions such as distributed photovoltaics and wind power. The penetration rate of renewable energy generation is constantly increasing, at the same time, the elements in the grid are becoming increasingly complex, and large-scale energy storage, as well as a variety of electricity loads such as electric vehicle charging piles and data centers are gradually appearing. Therefore, traditional distribution methods of the power grid are difficult to ensure the stable operation of the power system and cannot achieve efficient integration of renewable energy. Consequently, some scholars have proposed the concept of an energy internet. Compared to traditional power grids, the energy internet employs more comprehensive power electronics and communication technologies, enabling the interconnection of various new and traditional energy sources, and effectively integrating renewable energy. As the core device in the energy internet, the energy router plays a role in energy transformation and distribution, facilitating multi-information interconnection and multi-energy exchange within the energy internet. At the level of distribution network, the energy router can realize the efficient access of various forms of energy and the flexible control and management, which is of great significance for the optimal operation of distribution network. Against this backdrop, this paper reviews the development and current research status of energy routers, systematically analyzes the typical topologies and related control technologies of multi-port energy routers and summarizes and forecasts key issues and future development trends, aiming to provide thoughts and reference for subsequent related research.

Benchmarking Large Language Models for Code Generation

As the landscape of software development continues to evolve, the need for efficient and innovative coding practices becomes increasingly apparent. This research endeavors to explore the effectiveness of Large Language Models (LLMs) in code generation, focusing on benchmarking their performance across various coding tasks. Leveraging advanced Natural Language Processing (NLP) techniques and deep learning architectures, our study investigates how LLMs, such as the codellama-13b-instruct.Q5_K_S.gguf engine, interpret and generate code from natural language instructions. With an emphasis on accuracy, efficiency, and user accessibility, our research seeks to shed light on the capabilities of LLMs in bridging the gap between human language and executable code. By evaluating factors such as model architecture, training data quality, and task complexity, we aim to provide insights into the potential of LLMs for revolutionizing the coding experience. Through meticulous benchmarking and analysis, this study aims to contribute to the advancement of LLM development and its applications in code generation, paving the way for more efficient and inclusive coding practices in the future.

The challenges of sustainable energy transition: A focus on renewable energy

Energy is both a fundamental necessity and a driving force behind human activities. Throughout history, energy consumption has steadily risen, evolving from basic needs like food and fire for early humans to complex industrial and technological requirements today. Transitioning to a sustainable energy system requires a policy framework that empowers developing nations to promote green industries, diversify their sectors, and accelerate growth while addressing climate change and related challenges. In response to the urgent need for a global transition towards sustainable energy sources, this research explores the pivotal roles of technology, research, and policy in advancing renewable energy solutions. Motivated by the growing environmental challenges associated with conventional energy sources, the primary goal of this study is to shed light on the multifaceted strategies that facilitate the widespread adoption of renewable energy and contribute to mitigating climate change. Through an extensive analysis of renewable energy technologies, research contributions, and policy frameworks, this research uncovers critical insights. Our findings reveal how technological innovations have revolutionized renewable energy sources, making them more efficient, affordable, and scalable. Furthermore, research efforts have identified new opportunities and addressed technical challenges, while also assessing the environmental and societal impacts of renewable energy adoption. Crucially, this study underscores the indispensable role of policy in driving renewable energy transitions. Governments worldwide play a pivotal role in incentivizing renewable energy development through financial incentives, regulatory mandates, and research and development support. Moreover, these policies aim to promote energy efficiency, conservation, and equitable access to sustainable solutions. The results of this research emphasize that the transition to renewable energy is not only a viable solution to climate change but also an opportunity to create green jobs, enhance energy security, and reduce greenhouse gas emissions. The potential for a sustainable future powered by renewable energy is within reach, and this study serves as a guidepost for realizing this transformative vision.

D 2 Comp: Efficient Offload of LSM-tree Compaction with Data Processing Units on Disaggregated Storage

LSM-based key-value stores suffer from sub-optimal performance due to their slow and heavy background compactions. The compaction brings severe CPU and network overhead on high-speed disaggregated storage. This paper further reveals that data-intensive compression in compaction consumes a significant portion of CPU power. Moreover, the multi-threaded compactions cause substantial CPU contention and network traffic during high-load periods. Based on the above observations, we propose fine-grained dynamical compaction offloading by leveraging the modern Data Processing Unit (DPU) to alleviate the CPU and network overhead. To achieve this, we first customized a file system to enable efficient data access for DPU. We then leverage the Arm cores on the DPU to meet the burst CPU and network requirements to reduce resource contention and data movement. We further employ dedicated hardware-based accelerators on the DPU to speed up the compression in compactions. We integrate our DPU-offloaded compaction with RocksDB and evaluate it with NVIDIA’s latest Bluefield-2 DPU on a real system. The evaluation shows that the DPU is an effective solution to solve the CPU bottleneck and reduce data traffic of compaction. The results show that compaction performance is accelerated by 2.86 to 4.03 times, system write and read throughput is improved by up to 3.2 times and 1.4 times respectively, and host CPU contention and network traffic are effectively reduced compared to the fine-tuned CPU-only baseline.

Genetically optimized TD3 algorithm for efficient access control in the internet of vehicles

Genetically optimized TD3 algorithm for efficient access control in the internet of vehicles