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2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)最新文献

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Driving Sustainability using Big Data Analytics 利用大数据分析推动可持续发展
Dhriti Ashtekar T, Nishit Khamesra, M. S. Bhargavi
With the explosion of data in the digital age, Big Data Analytics (BDA) has been embraced as a powerful technology for businesses to gain insights and make data-driven decisions. Its impact is evident across various industries, from fast-food chains utilizing it for personalized marketing to healthcare institutions employing it for improved patient care. This research explores the burgeoning field of BDA concerning sustainability by employing case studies to illuminate the powerful ways BDA empowers companies to move towards sustainability, aiming to demonstrate its transformative potential in achieving environmental and social goals. A humongous amount of data is generated, estimated at 2.5 quintillion bytes daily, which provides a fertile ground for BDA applications. Harnessing this data will help companies gain valuable insights into their environmental footprint, optimize resource utilization, and frame ingenious solutions for sustainability challenges. As a case study, we will be delving into Allbirds, a company that has sustainability as a core concept, that has identified pivotal areas for enhancement and incorporated data-driven solutions to optimize resource utilization and minimize the environmental impact to cope with issues such as climate changes and global warming. As another case study, we will explore Siemens which demonstrates the transformative power of big data in achieving broader environmental and social goals using their MindSphere platform.
随着数字时代数据的爆炸式增长,大数据分析(BDA)已成为企业获得洞察力和做出数据驱动决策的强大技术。它对各行各业的影响显而易见,从快餐连锁店利用它进行个性化营销,到医疗机构利用它改善病人护理。本研究通过案例研究,探讨了有关可持续发展的新兴 BDA 领域,阐明了 BDA 赋予公司实现可持续发展的强大方法,旨在展示其在实现环境和社会目标方面的变革潜力。据估计,每天产生的数据量高达 2.5 万亿字节,这为 BDA 应用提供了肥沃的土壤。利用这些数据将有助于企业深入了解其环境足迹,优化资源利用,并为应对可持续发展挑战制定巧妙的解决方案。作为一个案例研究,我们将对 Allbirds 公司进行深入研究,该公司以可持续发展为核心理念,确定了需要改进的关键领域,并采用数据驱动的解决方案来优化资源利用,最大限度地减少对环境的影响,以应对气候变化和全球变暖等问题。作为另一个案例研究,我们将探讨西门子公司,该公司利用其 MindSphere 平台展示了大数据在实现更广泛的环境和社会目标方面的变革力量。
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引用次数: 0
Analysis of User Satisfaction with Battery Electric Vehicles: Toward Green Transportation in Jakarta 电池电动汽车用户满意度分析:雅加达的绿色交通
Aldi Damora Siregar, Fitria Indah Astari, Nabilla Farah Raissa Maharani, Ardhy Lazuardy, R. Nurcahyo, M. Habiburrahman
Due to the action taken to combat climate change, the world is on its time to transition vehicles to battery-electric vehicles. This research examines the satisfaction levels among DKI Jakarta residents using Battery Electric Vehicles (BEVs). Through a comprehensive analysis, this study aims to identify critical factors resulting in three factors with the highest total user satisfaction scale, including government policy, environmental sustainability, and recommendations. There were also three factors with the lowest entire scale, including charging location, brand, and the price of the BEVs. Using survey data and statistical methods, the weighted average total user satisfaction level was found to be 4.38, indicating that overall, electric car users are delighted with the performance of electric cars. The findings contribute valuable insights for policymakers, urban planners, and industry stakeholders, offering a nuanced understanding of the dynamics shaping satisfaction with BEVs in the context of DKI Jakarta.
由于应对气候变化的行动,世界正处于向电池电动汽车过渡的时期。本研究对雅加达 DKI 区居民使用电池电动汽车(BEV)的满意度进行了调查。通过综合分析,本研究旨在找出关键因素,从而得出用户满意度最高的三个因素,包括政府政策、环境可持续性和建议。此外,还有三个因素的总体满意度最低,包括充电地点、品牌和 BEV 的价格。通过调查数据和统计方法,加权平均用户总满意度为 4.38,表明电动汽车用户总体上对电动汽车的性能感到满意。研究结果为政策制定者、城市规划者和行业利益相关者提供了有价值的见解,使他们对雅加达DKI地区电动汽车满意度的动态变化有了细致入微的了解。
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引用次数: 0
The Challenges of The Artificial Intelligence of Law in The Context of Technological Development 技术发展背景下法律人工智能的挑战
Mahmoud Khalifa, Mahmoud Sabry
Intelligent intelligence is the most exciting technological development of our modern age. In the area of legal practice, artificial intelligence has played a prominent role in demonstrating a proactive perception and conclusion of the outcome of judicial proceedings with precision, comprehensiveness, and maximum speed. It helps to inform and inform lawyers about the development and definition of litigation strategies. The study highlights the advantages and disadvantages of artificial intelligence in the legal field and has produced several important findings. One of these results is the need to balance humans and robots so that artificial intelligence does not replace the human mind because of the progress and evolution of algorithms. However, the legal community must effectively exploit the capabilities of artificial intelligence and view it as a complementary tool to the human mind by establishing an appropriate legal framework governing its use and defining the legal responsibility for that innovative technology. In this way, we will be able to make the most of artificial intelligence in the administration of justice and the improvement of the justice system.
智能化是当代最激动人心的技术发展。在法律实践领域,人工智能发挥了突出的作用,展现了对司法程序结果的主动感知和结论的准确性、全面性和最大速度。它有助于让律师了解和掌握诉讼策略的制定和定义。这项研究强调了人工智能在法律领域的优势和劣势,并得出了几项重要结论。其中一项成果是需要平衡人类与机器人之间的关系,使人工智能不会因为算法的进步和演化而取代人类思维。然而,法律界必须有效利用人工智能的能力,将其视为人类思维的补充工具,建立适当的法律框架来规范人工智能的使用,并界定这一创新技术的法律责任。这样,我们就能在司法管理和改进司法系统方面最大限度地利用人工智能。
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引用次数: 0
Integrated Transfer Learning and Nature-Inspired Optimization for Enhanced Feature Extraction in Diabetic Retinopathy Image Analysis 在糖尿病视网膜病变图像分析中整合迁移学习和自然启发优化技术以增强特征提取能力
R. Tiwari, Anurag Kumar
This research aims to detect diabetic retinopathy using optimized features extracted from deep learning model. Initially, several deep learning architectures are trained using retinal image dataset and the best model is determined. Regarding transfer learning approaches for diabetic retinopathy patients, SqueezeNet seems to be the best model. The proposed model in this research relies on a two-stage optimization process to enhance the features extracted by SqueezeNet. Deep features obtained by SqueezeNet are optimized using Particle Swarm Optimization (PSO) and the Crow Search Algorithm (CSA). Merging the results of the two optimization methods with a value-maximizing solution is essential for producing an accurate and resilient feature vector. The proposed hybrid model employs a variety of machine-learning algorithms to classify diabetic retinopathy and non-diabetic retinopathy cases. The experimental findings indicate that the suggested method is effective with correct classification accuracy of 96.8%.
这项研究旨在利用从深度学习模型中提取的优化特征检测糖尿病视网膜病变。最初,使用视网膜图像数据集训练了几种深度学习架构,并确定了最佳模型。关于糖尿病视网膜病变患者的转移学习方法,SqueezeNet 似乎是最佳模型。本研究提出的模型依靠两阶段优化过程来增强 SqueezeNet 提取的特征。使用粒子群优化算法(PSO)和乌鸦搜索算法(CSA)对 SqueezeNet 提取的深度特征进行优化。将这两种优化方法的结果与价值最大化解决方案合并,对于生成准确而有弹性的特征向量至关重要。所提出的混合模型采用多种机器学习算法对糖尿病视网膜病变和非糖尿病视网膜病变病例进行分类。实验结果表明,所建议的方法非常有效,正确分类准确率达到 96.8%。
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引用次数: 0
An IoT Based Smart Hydroponics – Plant Automation BOT 基于物联网的智能水培 - 植物自动化 BOT
Pravalika Reddy, Mohammed Sohel, Santosh Madeva Naik
Traditional Agriculture is unpredictable and very desirable. The sector has many problems like limited resources, financing, labour and land. With these problems, it becomes harder to get high yields. This is the present case in India, where the condition of farming is much better in developed western countries but even they are subjected to similar problems. Over the years, there is a need for increased output from agriculture to meet the needs of the population. Luckily, there have been alternative ways to traditional agriculture. One such different method is Hydroponics. Over the years, Hydroponics is a type of method of growing plants on less land and with fewer resources. Present hydroponics farms require some human interactions. We propose an automation solution for these Hydroponics systems. This method of farming reuses the majority of water and so saves around 90% of the water. Adding automation into the picture can help scale farms without worrying about the workforce and additionally data received.
传统农业是不可预测的,也是非常理想的。该行业存在许多问题,如资源、资金、劳动力和土地有限。有了这些问题,获得高产就变得更加困难。印度目前的情况就是如此,西方发达国家的农业条件要好得多,但即使是这些国家也面临着类似的问题。多年来,人们需要提高农业产量以满足人口需求。幸运的是,已经有了替代传统农业的方法。其中一种不同的方法就是水耕法。多年来,水培法是一种在较少土地和资源上种植植物的方法。目前的水培农场需要一些人工互动。我们为这些水培系统提出了一种自动化解决方案。这种耕作方法可以重复利用大部分水,因此可以节约大约 90% 的水。加入自动化技术可以帮助扩大农场规模,而无需担心劳动力问题和额外的数据接收问题。
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引用次数: 0
Reconfigurable Intelligent Reflecting Surfaces Enabled Spectrum Access for Beyond 5G Networks 可重构的智能反射面实现了超越 5G 网络的频谱接入
Raymond Sabogu-Sumah, K. A. Opare, J. Gadze, Edmund Y. Fianko, Timothy Ashong
This paper studies the use of Reconfigurable Intelligent Surfaces (RIS) to enable coexistence between Primary and Secondary Spectrum Users. While RIS tech-nology is widely used to improve user throughput or extend coverage to cell edge devices, this study deviates from the conventional use scenario. We model the propagation channel of the users of a Beyond 5G (BSG) cellular networks taking note of the direct path and reflected paths facilitated by the RIS. Simulation results show that the use of the RIS improves the user capacity while reflecting the signals from the direction of the primary users which enables the B5G system to use the primary user's spectrum without harm-fully interfering with it. Further, it is shown that indoor cellular deployment ensures maximum and/or complete protection of the primary spectrum user whereas outdoor deployment requires extra protection mechanisms such as longer separation distances, power control schemes.
本文研究了利用可重构智能表面(RIS)实现主频谱用户和辅助频谱用户共存的问题。虽然 RIS 技术被广泛用于提高用户吞吐量或扩大小区边缘设备的覆盖范围,但本研究偏离了传统的使用场景。我们对 Beyond 5G (BSG) 蜂窝网络用户的传播信道进行建模,同时考虑到 RIS 所提供的直接路径和反射路径。仿真结果表明,RIS 的使用提高了用户容量,同时反射了来自主用户方向的信号,使 B5G 系统能够使用主用户的频谱,而不会对其造成有害干扰。此外,研究还表明,室内蜂窝部署可确保最大和/或完全保护主频谱用户,而室外部署则需要额外的保护机制,如更长的分离距离和功率控制方案。
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引用次数: 0
An Integrated Task-Technology Fit and Technology Acceptance Model Theories of Massive Online Open Courses Applications: An Empirical Study of Students in Indonesia 大规模在线开放课程应用的任务-技术契合和技术接受模型综合理论:印度尼西亚学生的实证研究
L. Wijaya, Apata Stella Bolanle, Kin Meng Cheng, Kah Choon Ng, Vional Vional, J. W. Wahono
The objective of this research is to propose a comprehensive model that combines the technology acceptance model (TAM) and the task fit technology (TTF) model, with the aim of investigating the intention to continue using MOOCs of the behaviors associated with this context can be achieved by utilizing a research methodology that integrates the TAM for adoption and the TTF model for utility. The total sample of 326 MOOC app users was analyzed using the PLS-SEM method with SmartPLS. Attitude towards MOOCs is crucial for their desired use. Predicting the intention to continue using MOOC applications involves various factors, including the perceived ease of use, perceived usefulness, and the fit between the task and the technology. All of the hypotheses were confirmed by the findings. The study results suggest that the perception of ease of use is strongly shaped by the fit between the task and the technology, closely followed by the perception of usefulness. Therefore, if a MOOC application is considered suitable, users will continue to use it, thereby enhancing the sustainability of the business. Lastly, the theoretical and practical consequences are brought forth and deliberated upon, and recommendations for forthcoming investigations are proffered.
本研究的目的是提出一个结合了技术接受模型(TAM)和任务适合技术模型(TTF)的综合模型,旨在通过采用综合了技术接受模型(TAM)和任务适合技术模型(TTF)的研究方法,调查继续使用 MOOCs 的相关行为意向。本研究使用 SmartPLS 的 PLS-SEM 方法对 326 名 MOOC 应用程序用户进行了分析。对 MOOCs 的态度对其预期使用至关重要。预测继续使用 MOOC 应用程序的意愿涉及多个因素,包括感知易用性、感知有用性以及任务与技术之间的契合度。研究结果证实了所有假设。研究结果表明,任务与技术之间的契合度极大地影响了易用感,其次是有用感。因此,如果 MOOC 应用程序被认为是合适的,用户就会继续使用,从而提高业务的可持续性。最后,提出并讨论了理论和实践后果,并对今后的研究提出了建议。
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引用次数: 0
Potential of Harnessing Green Electricity Using Photovoltaic Modules on Pitched Rooftop Using DC-DC Boost Converter 利用直流-直流升压转换器在斜屋顶上使用光伏组件获取绿色电力的潜力
M. N. Mamat, S. Kaharuddin, M.N. Abdullah, D. Ishak
This paper explores the potential of harnessing renewable energy through the use of photovoltaic modules installed on pitched terrace roofs in Malaysia, employing the eco-roof concept. Utilising typical climate data from Malaysia, the study investigates a system designed to charge a 339 V based battery storage system to estimate electricity generation and potential cost savings for residential homes. The series configuration of the PV rooftop connected to the boost converter charging circuit demonstrates favourable output characteristics and is deemed suitable for the charging application. A case study involving 150 houses per residential area reveals that the ratio of households contributing to and benefiting from electricity consumption and savings is 15:1. In summary, for every 15 houses charged to the designated battery system, one house can access the stored energy for daily use.
本文采用生态屋顶概念,探讨了通过在马来西亚斜面露台屋顶上安装光伏组件来利用可再生能源的潜力。研究利用马来西亚的典型气候数据,调查了一个旨在为 339 V 电池储能系统充电的系统,以估算发电量和为住宅节省成本的潜力。光伏屋顶与升压转换器充电电路的串联配置显示出良好的输出特性,被认为适合充电应用。一项涉及每个住宅区 150 栋房屋的案例研究显示,家庭在用电和节电方面的贡献和受益比例为 15:1。总之,每 15 户家庭向指定的电池系统充电,就有一户家庭可以将储存的电能用于日常使用。
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引用次数: 0
Antecedents of Individuals' Switching Intention to Adopt Sharia Compliance in Fintech Transactions among Generation Y: A Case of Thai Southern Borders Provinces Y 世代中个人在金融科技交易中采用符合伊斯兰教法的转换意向的前因:泰国南部边境省份案例
A. Hassama, Mohamed Soliman, Tawat Noipom
Muslims are increasingly concerned about Sharia compliance (SC) in Fintech (Financial technology) transactions. Because non-Sharia compliance might engender distrust and prevent many Muslims from using Fintech. No comprehensive Sharia compliance standard for financial systems exists. Thus, a comprehensive Sharia compliance standard for Fintech systems is needed. This study examines the factors that lead Generation Y (Gen Y) Muslims to adopt Sharia compliance in Fintech transactions by combining the technology acceptance model (TAM) and push-pull-mooring (PPM) framework. Google Forms will be used to collect data for a quantitative research study using a self-administered questionnaire. For this purpose, we will engage a two-staged partial least square structural equation model (PLS-SEM) and artificial neural network (ANN) model, combining a linear PLS model with compensation and a nonlinear ANN model without compensation.
穆斯林越来越关注金融科技(Fintech)交易中的伊斯兰教法合规性(SC)问题。因为不遵守伊斯兰教法可能会引起不信任,并阻止许多穆斯林使用金融科技。目前还没有针对金融系统的全面伊斯兰教法合规标准。因此,需要为金融科技系统制定全面的伊斯兰教法合规标准。本研究通过结合技术接受模型(TAM)和推拉式营销(PPM)框架,研究了导致 Y 世代(Gen Y)穆斯林在金融科技交易中采用伊斯兰教法合规性的因素。我们将使用谷歌表格,通过自填问卷的方式收集数据,进行定量研究。为此,我们将采用两阶段偏最小二乘法结构方程模型(PLS-SEM)和人工神经网络(ANN)模型,结合有补偿的线性 PLS 模型和无补偿的非线性 ANN 模型。
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引用次数: 0
The Impact of Generative Artificial Intelligence on Organizational Innovation Performance: Roles of AI Generated Content Quality, AI Experience, and AI Usage Environment 生成式人工智能对组织创新绩效的影响:人工智能生成内容质量、人工智能体验和人工智能使用环境的作用
Haonan Xu, Ruoxuan Xu, Hongyu Lin, Xiaojuan He
With the progress of artificial intelligence (AI), generative AI has emerged as a novel catalyst for driving innovation within enterprises. This study, rooted in behavior activation theory, endeavors to examine the impact of generative AI on enterprise innovation. A conceptual model is formulated to elucidate the relationship between generative AI and enterprise innovation. Utilizing structural equation modeling to scrutinize this model, the findings reveal substantial positive effects: AI generated content quality significantly influences the activation of enterprise innovation behavior (ß = 0.37, t-value = 7.64, p < 0.01), AI experience has a notable positive impact on innovation behavior activation (ß = 0.19, t-value = 3.47, p < 0.01), and a supportive AI usage environment significantly influences the activation of enterprise innovation behavior (ß= 0.46, t-value = 10.48, p <0.01). Furthermore, innovation behavior activation makes a significant contribution to enterprise innovation performance (ß = 0.65, t-value = 18.23, p < 0.01).
随着人工智能(AI)的发展,生成式人工智能已成为推动企业创新的新型催化剂。本研究以行为激活理论为基础,试图探讨生成式人工智能对企业创新的影响。本研究建立了一个概念模型,以阐明生成性人工智能与企业创新之间的关系。利用结构方程模型对该模型进行仔细研究,研究结果显示了实质性的积极影响:人工智能生成内容的质量明显影响企业创新行为的激活(ß=0.37,t值=7.64,p<0.01),人工智能经验对创新行为激活有明显的积极影响(ß=0.19,t值=3.47,p<0.01),支持性人工智能使用环境明显影响企业创新行为的激活(ß=0.46,t值=10.48,p<0.01)。此外,创新行为激活对企业创新绩效也有重要贡献(ß= 0.65,t 值= 18.23,p <0.01)。
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引用次数: 0
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2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)
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