One of the biggest concerns voiced by families about child-centered robots in homes is privacy. My work uses co-design to better understand how youth, their family, and their clinicians formalize a youth's right t...
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Morphing attacks are based on the technique of digitally fusing two (or more) face images into one, with the final visage resembling the contributing faces. Morphed images not only pose a challenge to Face-Recognition...
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Morphing attacks are based on the technique of digitally fusing two (or more) face images into one, with the final visage resembling the contributing faces. Morphed images not only pose a challenge to Face-Recognition Systems (FRS) but also challenge experienced human observers due to high quality, postprocessing eliminating any visible artifacts, and further the printing and scanning process. Few studies have concentrated on examining how human observers can recognize morphing attacks, even as several publications have examined the susceptibility of automated FRS to morphing attacks and offered morphing attack detection (MAD) approaches. MAD approaches base their decisions either on a single image with no reference to compare against (Single-Image MAD (S-MAD)) or using a reference image (Differential MAD (D-MAD)). One prevalent misconception is that an examiner's or observer's capacity for facial morph detection depends on their subject expertise, experience, and familiarity with the issue. No works have reported the specific results of observers who regularly verify identity (ID) documents for their jobs. As human observers are involved in checking ID documents having facial images, a lapse in their competence can result in significant societal challenges. To assess the observers' proficiency, this research first builds a new benchmark database of realistic morphing attacks from 48 different subjects, resulting in 400 morphed images. Unlike the previous works, we also capture images from Automated Border Control (ABC) gates to mimic realistic border-crossing scenarios in the D-MAD setting with 400 probe images, to study the ability of human observers to detect morphed images. A new dataset of 180 morphing images is also produced to research human capacity in the S-MAD environment. In addition to creating a new evaluation platform to conduct S-MAD and D-MAD analysis, the study employs 469 observers for D-MAD and 410 observers for S-MAD who are primarily governmenta
The fusion of technology and culinary exploration has allowed for the emergence of advanced online customer service systems. We developed a novel approach to enhance the dining experience. We used a Cuisine Image Reco...
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This empirical study involved volunteers who played a game featuring NPCs specially developed for the research. The research investigated the influence and behaviour of NPC appearance on some factors regarding the pla...
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Blockchain, Metaverse & NFT are technologies that were booming during the Pandemic. As a derivative product of blockchain, the Non-Fungible Token (NFT) is one of the technologies that has attracted the most intere...
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When processing datasets in diabetes classification, common problems included a large number of missing values, outliers, and dataset imbalance. To deal with those issues, this study analyzed 18 studies on diabetes cl...
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When processing datasets in diabetes classification, common problems included a large number of missing values, outliers, and dataset imbalance. To deal with those issues, this study analyzed 18 studies on diabetes classification with machine learning algorithms over the past 5 years. This revealed the important role of data pre-processing in creating effective classification models, as it was found that by using different data pre-processing techniques, the same model can provide different performance. The study identified K-Nearest Neighbor (KNN) and support vector machine (SVM) as superior methods for filling in missing values, achieving an accuracy of 98.49% and 94.89%, respectively. These approaches outperformed traditional methods such as median or mean replacement. However, the challenge of imbalanced data sets remains in all studies reviewed. The common evaluation metrics used to evaluate the created models in previous studies included accuracy, precision, specificity, sensitivity/recall, and F1 Score. Overall, this review showed that the role of data pre-processing is no less important than algorithm selection to improve the performance of machine learning models in diabetes classification.
Numerous beverages available in Indonesia belong to the category of harmful drinks, which contributes to the country's high diabetes rate. As a result of the rising prevalence of diabetes among the population in I...
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The background of this research is the condition of the covid-19 pandemic which has an impact on online ticket sales. Meanwhile, when future of covid-19 pandemic is starting to become clearer, we are going to have a l...
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It has been an open question in deep learning if fault-tolerant computation is possible: can arbitrarily reliable computation be achieved using only unreliable neurons? In the grid cells of the mammalian cortex, analo...
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It has been an open question in deep learning if fault-tolerant computation is possible: can arbitrarily reliable computation be achieved using only unreliable neurons? In the grid cells of the mammalian cortex, analog error correction codes have been observed to protect states against neural spiking noise, but their role in information processing is unclear. Here, we use these biological error correction codes to develop a universal fault-tolerant neural network that achieves reliable computation if the faultiness of each neuron lies below a sharp threshold; remarkably, we find that noisy biological neurons fall below this threshold. The discovery of a phase transition from faulty to fault-tolerant neural computation suggests a mechanism for reliable computation in the cortex and opens a path towards understanding noisy analog systems relevant to artificial intelligence and neuromorphic computing.
When making a new microprocessor (MPU), the instruction set architecture is considered. It is also necessary to design how to work the instructions in hardware circuits of the MPU. As a solution to these, we previousl...
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