A Review of Approaches to Ensure the Quality of Data Collected on the Internet

Different approaches have been used to detect errors in data collected on the Internet. Some of these existing approaches require prior knowledge of data. Others have to test a large number of parameter values. To address these limitations, two approaches have been recently proposed. In this paper, we review these two approaches

Complexity Analysis of Balloon Drawing for Rooted Trees

In a balloon drawing of a tree, all the children under the same parent are placed on the circumference of the circle centered at their parent, and the radius of the circle centered at each node along any path from the root reflects the number of descendants associated with the node. Among various styles of tree drawings reported in the literature, the balloon drawing enjoys a desirable feature of displaying tree structures in a rather balanced fashion. For each internal node in a balloon drawing, the ray from the node to each of its children divides the wedge accommodating the subtree rooted at the child into two sub-wedges. Depending on whether the two sub-wedge angles are required to be identical or not, a balloon drawing can further be divided into two types: even sub-wedge and uneven sub-wedge types. In the most general case, for any internal node in the tree there are two dimensions of freedom that affect the quality of a balloon drawing: (1) altering the order in which the children of the node appear in the drawing, and (2) for the subtree rooted at each child of the node, flipping the two sub-wedges of the subtree. In this paper, we give a comprehensive complexity analysis for optimizing balloon drawings of rooted trees with respect to angular resolution, aspect ratio and standard deviation of angles under various drawing cases depending on whether the tree is of even or uneven sub-wedge type and whether (1) and (2) above are allowed. It turns out that some are NP-complete while others can be solved in polynomial time. We also derive approximation algorithms for those that are intractable in general

Hafnium oxide-based ferroelectric thin-film transistor with a-InGaZnO channel fabricated at temperatures \u3c= 350°C

HfO2-based ferroelectric materials integrated with oxide-based thin-film transistors have been considered as potential candidates for back-end-of-line compatible ferroelectric field-effect transistors, which can be vertically stacked on silicon CMOS circuits to realize high-density neural network applications. However, the formation of ferroelectric orthorhombic phase in HfO2-based materials usually requires an annealing temperature of 400°C or higher. In this work, ferroelectric thin-film transistors (Fe-TFTs) were developed by monolithically integrating HfZrO2 (HZO) ferroelectric capacitors with amorphous indium-gallium-zinc oxide (a-IGZO) TFTs at a maximum processing temperature of 350°C on a glass substrate. A butterfly-shaped C-V curve was clearly observed in the low-temperature annealed metal-HZO-metal capacitor, indicating the formation of ferroelectricity in the HZO layer, as shown in Fig. 1. The positive and negative coercive voltages were 3 V and -2.4 V, respectively. The dielectric constant was 20.65. The field-effect mobility, threshold voltage, subthreshold swing and on/off current ratio of the a-IGZO TFT extracted from the transfer characteristics shown in Fig. 2 were 6.15 cm2V-1s-1, 1.5 V, 0.1 V/dec and 4.3´107, respectively. Fig. 3 shows the transfer hysteresis curves of the low-temperature Fe-TFTs in a metal-ferroelectric-metal-insulator-semiconductor configuration. The Fe-TFTs exhibited large hysteresis memory windows of 2.8 V and 3.8 V when the area ratios between ferroelectric capacitors and gate insulators (AFE / ADE) were 1/8 and 1/12, respectively. The result shows a great potential for back-end-of-line compatible memory applications. Please click Download on the upper right corner to see the full abstract

Rhythm-Flexible Voice Conversion without Parallel Data Using Cycle-GAN over Phoneme Posteriorgram Sequences

Speaking rate refers to the average number of phonemes within some unit time, while the rhythmic patterns refer to duration distributions for realizations of different phonemes within different phonetic structures. Both are key components of prosody in speech, which is different for different speakers. Models like cycle-consistent adversarial network (Cycle-GAN) and variational auto-encoder (VAE) have been successfully applied to voice conversion tasks without parallel data. However, due to the neural network architectures and feature vectors chosen for these approaches, the length of the predicted utterance has to be fixed to that of the input utterance, which limits the flexibility in mimicking the speaking rates and rhythmic patterns for the target speaker. On the other hand, sequence-to-sequence learning model was used to remove the above length constraint, but parallel training data are needed. In this paper, we propose an approach utilizing sequence-to-sequence model trained with unsupervised Cycle-GAN to perform the transformation between the phoneme posteriorgram sequences for different speakers. In this way, the length constraint mentioned above is removed to offer rhythm-flexible voice conversion without requiring parallel data. Preliminary evaluation on two datasets showed very encouraging results.Comment: 8 pages, 6 figures, Submitted to SLT 201