Several approaches have been presented, which aim to extract models from natural language specifications. These approaches have inherent weaknesses for they assume an initial problem understanding that is perfect, and...
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Predicting water quality is essential to preserving human health and environmental sustain ability. Traditional water quality assessment methods often face scalability and real-time monitoring limitations. With accura...
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ISBN:
(数字)9798331527549
ISBN:
(纸本)9798331527556
Predicting water quality is essential to preserving human health and environmental sustain ability. Traditional water quality assessment methods often face scalability and real-time monitoring limitations. With accuracies of 62%, 72 %, 83 %, 69%, 63 %, 66%, 71 %, 63 %, and 64%, respectively, the current techniques utilized were Logistic Regression, Decision Trees, Random Forest Regressor, Extreme Gradient Boosting, Naive Bayes, K-nearest neighbors, Support Vector Machine, AdaBoost, and Bagging [9]. This study addresses these challenges by leveraging Adaptive Synthetic Sampling (ADASYN) to balance the dataset and evaluating model performance on datasets of 5,000 and 10,000 entries per class. A robust dataset obtained from Kaggle was used, with five models - Long Short-Term Memory (LSTM), Feed Forward Neural Network (FFNN), Categorical Boosting (CatBoost), Extreme Gradient Boosting (XGBoost), and Random Forest - evaluated and compared. The proposed methods demonstrate significant improvements in accuracy, with XGBoost achieving the highest accuracy of 95.53%, followed by Random Forest at 93.98%. This work underscores the importance of advanced machine learning techniques in addressing the limitations of traditional methods, enhancing accuracy, scalability, and adaptability in water quality prediction. These findings contribute to advancing environmental monitoring and management practices with reliable, data-driven insights.
The quality of trajectory data plays a crucial role in the investigation of microscopic traffic flow. However, the challenge of effectively and automatically eliminating false positive collisions from the measured dat...
The quality of trajectory data plays a crucial role in the investigation of microscopic traffic flow. However, the challenge of effectively and automatically eliminating false positive collisions from the measured data still remains an unsolved problem. Firstly, this paper formulates the problem of reconstructing multi-vehicle trajectories as a nonconvex quadratic constraint quadratic programming (QCQP) problem. Subsequently, it derives the equivalent semidefinite programming (SDP) problem and develops a semidefinite relaxation technique to e·fficiently obtain the global minimum of the relaxed problem. We then apply a randomization method to obtain a feasible near-optimal solution to the original problem. The proposed approach is validated through experiments conducted on the NGSIM I–80 camera 6 lane 5 data, and the results of these experiments demonstrate that the unreasonable vehicle dynamics are removed and the platoon inconsistency decreased from 0.622% to 0.268% in the experimental data.
Automated driving systems can be helpful in a wide range of societal challenges, e.g., mobility-on-demand and transportation logistics for last-mile delivery, by aiding the vehicle driver or taking over the responsibi...
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Optical parametric oscillators (OPOs) emit narrow-linewidth light that is widely tunable in wavelength. In particular in the mid infrared, they are of prime interest because a single device can cover the entire wavele...
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Educational operating systems are crucial for facilitating learning in the digital age, as they exist at the intersection of technology and education. While their technical role is well understood, improving their edu...
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ISBN:
(数字)9798331540388
ISBN:
(纸本)9798331540395
Educational operating systems are crucial for facilitating learning in the digital age, as they exist at the intersection of technology and education. While their technical role is well understood, improving their educational value requires enhancing traditional approaches. This paper explores ways to enrich educational operating systems not just through technological advancement, but also by integrating pedagogical principles. In an ever-changing world, the need for an adaptive and responsive educational operating system to meet diverse student needs is crucial. Through case studies, we analyze how design, interactivity, and accessibility can transform these systems into effective and appealing learning environments. We propose a series of recommendations for the future development of educational operating systems, focusing on enhancing the learning experience and promoting student autonomy, thereby offering a fresh perspective on how technology and education can blend harmoniously and efficiently.
Adiabatic frequency conversion (AFC) in microresonators is independent of the intensity of laser light, and it is free from phase matching restrictions. It even allows for changing the frequency of single photons. The...
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Along the process of engineering a safety-critical system, software engineers produce various artifacts, ranging from requirements and change requests to source code and test cases. In order to aid the development of ...
Along the process of engineering a safety-critical system, software engineers produce various artifacts, ranging from requirements and change requests to source code and test cases. In order to aid the development of the system and to adhere to the complex safety regulations and standards in place, engineers are often required to maintain bidirectional and consistent traceability between the produced artifacts. However, such artifacts are rarely maintained in one single tool. Because of that, the cross-tool bidirectional traces have to frequently be manually maintained, which can easily become a very time-consuming or infeasible task. Through interviews and observations at our industry partners in regulated domains, we observed that a number of different strategies are used to deal with this challenge. The use of naming conventions, querying, or URL links is observed in the industry. However, they have their shortcomings and hinder engineers from realizing the full potential that traceability can offer. Knowing the challenges in the industry, we explored existing literature. A range of approaches in the literature aims at dealing with traceability, but often they are context-specific and not easily transferable into practice. Given this gap between the state-of-the-art and industry needs, we performed interviews with our industry partners and analyzed tertiary studies from the literature to obtain a better understanding of what traceability properties are needed to unleash the potential of traces. We identified properties that represent the shared challenges between the related work and the industry requirements: discoverability, type checks, flexibility, navigability, and extensibility. While each property is addressed by a subset of the available solutions, we propose a novel traceability approach to support all of them in a single tool.
In the field of industry 4.0 and smart factories of the future, dynamic teams of robots will play an important role in the manufacturing of custom-tailored products with small lot sizes. Especially the planning for su...
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For various automated palletizing tasks, the detection of packaging units is a crucial step preceding the actual handling of the packaging units by an industrial robot. We propose an approach to this challenging probl...
For various automated palletizing tasks, the detection of packaging units is a crucial step preceding the actual handling of the packaging units by an industrial robot. We propose an approach to this challenging problem that is fully trained on synthetically generated data and can be robustly applied to arbitrary real world packaging units without further training or setup effort. The proposed approach is able to handle sparse and low quality sensor data, can exploit prior knowledge if available and generalizes well to a wide range of products and application scenarios. To demonstrate the practical use of our approach, we conduct an extensive evaluation on real-world data with a wide range of different retail products. Further, we integrated our approach in a lab demonstrator and a commercial solution will be marketed through an industrial partner.
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