The growing problem of water scarcity is made worse by the unchecked use of fossil fuels for irrigation water-table pumping, which contributes to both environmental degradation and global warming. An burgeoning popula...
详细信息
In this work, we study the quantum confinement (QC) effect on the Schottky barrier height (ΦSB) of various metals on atomically thin In2O3 channels for the first time. A positive-to-negative ΦSB conversion is experi...
详细信息
In this paper, a distributed optimal power flow (OPF) for the AC/DC hybrid grid, composed of the AC grid, renewable energy system (RES), and voltage source converter (VSC)-based multi-terminal DC (MTDC) grid, is prese...
详细信息
We construct a spectral-distinctive photodetector based on p-AlGaN/n-Si nanowires modified with carbon layer, where the carbon layer effectively regulates the surface band bending of the nanowires, further successfull...
详细信息
Machine learning (ML) has since been a powerful tool in advancing the modeling of many wireless communication systems, e.g., cellular networks, WiFi, vehicular networks, and space-air-ground networks. The benefits of ...
详细信息
This work is a full research-to-practice paper that describes a predictive method to improve the prediction of student test scores. Predicting student test scores is difficult. However, doing so can improve education ...
详细信息
ISBN:
(纸本)9798350351507
This work is a full research-to-practice paper that describes a predictive method to improve the prediction of student test scores. Predicting student test scores is difficult. However, doing so can improve education greatly by improving advising, scheduling, tutoring assignment and other educational processes. This research extends previous research by using a domain space reduction technique to improve accuracy. Factor Analysis is used to reduce the number of domain attributes for improving the accuracy of a Neural Network to predict student test scores. In this research datasets for Mathematics and Language of high school student test scores were used. Test scores were predicted using a Neural Network computing the Mean Absolute Error as a measurement of accuracy. The datasets have 30 domain attributes each. Factor Analysis was used to reduce the domain size from between 1 to 29, each time using it to train the Neural Network. Because the Mean Absolute Error may vary depending upon which records in the dataset are used for training versus testing, 50 trials of each dataset size were executed producing an Average Mean Absolute Error for each domain size. A statistical test was used to show statistical significance between the Neural Network without Factor Analysis and the Neural Network with varying domain sizes using Factor Analysis. Results were very promising and correspond to previous research that used Principal Component Analysis. Numerous domain sizes had significantly better Average Mean Absolute Errors than the accuracy of the Neural Network without Factor Analysis. This research shows that reducing the domain size using Factor Analysis can greatly improve the accuracy of Neural Networks when predicting student test scores. The best improvements occurred when domain sizes were very small ranging from 2 to 6. Domain reduction techniques, such as Factor Analysis, have been shown to improve predictive models for student test score prediction. Future research
In Wireless Sensor Networks (WSNs), ensuring the real-time and reliable collection of state information is crucial for maintaining the efficient operation of the network. To ensure freshness of information in delay-se...
详细信息
This paper deals with the problem of constrained bilinear control of a parabolic trough solar collector (PTSC) in the infinite-dimensional setting. The PTSC is modeled by a 1st-order hyperbolic PDE, and the objective ...
详细信息
Long Range Wide Area Network (LoRaWAN) is a wireless communication protocol used in open Radio Frequency (RF) communication links. However, this openness also makes LoRaWAN vulnerable to Denial of Service (DoS) attack...
详细信息
Edge computing offers a groundbreaking architecture for supplying computing, storage, and networking resources to propel the Internet of Things forward. By situating them at the network's edge, this model makes co...
详细信息
暂无评论