Jaeyong Chung

Increasingly, the sophistication of modern computer-gaming systems is becoming comparable to that of immersive, virtual reality (VR) environments, and the popular VR research topic of “presence” is now being explored in the context of computer games. The explosion of popularity of networked gameplay and the movement of computing infrastructure on to the Internet and the cloud mean that technical anomalies such as network latency, dropouts, and so on, may increasingly disrupt players' experience

Deep learning using deep neural networks is taking machine intelligence to the next level in computer vision, speech recognition, natural language processing, etc. Brain-like hardware platforms for the brain-inspired computational models are being studied, but none of such platforms deals with the huge size of practical deep neural networks. This paper presents two techniques, factorization and pruning, that not only compress the models but also maintain the form of the models for the execution

In the face of large-scale process variations, statistical timing methodology has advanced significantly over the last few years, and statistical path selection takes advantage of it in at-speed testing. In deterministic path selection, the separation of path selection and test generation is known to require time consuming iteration between the two processes. This paper shows that in statistical path selection, this is not only the case, but also the quality of results can be severely degraded e

One of the obstacles to the use of VR is the expensive, intrusive, cumbersome and brittle nature of the sensors required to detect user's intent. While optical tracking has been regarded as one solution to this problem, the problems of establishing marker correspondence and resolving their occlusions remain. One solution is to simply add hardware, making the tracking system too expensive for general usage, while another, to track human body parts, suffers from the inability to track point featur

Antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleoprotein (NP) were purified from pig serum through two steps: (1) isolation of anti-NP IgG antibodies using magnetic beads with immobilized human SARS CoV-2 NP and (2) fi ltration of anti-spike protein (SP) IgG antibodies using magnetic beads with immobilized human SARS-CoV SP. The enhanced specificity of the purified antibodies to the NP of SARS-CoV-2 was demonstrated using an immunoassay with anti-NP IgG antib

Breaks in presence (BIP) are those moments during virtual environment (VE) exposure in which participants become aware of their real world setting and their sense of presence in the VE becomes disrupted. In this study, we investigate participants' experience when they encounter technical anomalies during game play. We induced four technical anomalies and compared the BIP responses of a navigation mode game to that of a combat mode game. In our analysis, we applied a linear mixed model (LMM) and

Several endemic corona viruses (eCoVs) have been reported to be the most common etiologic agents for the seasonal common cold and also cause pneumonia. These eCoVs share extensive sequence homology with SARS-CoV-2, and immune responses to eCoVs can cross-react with SARS-CoV-2 antigens. Based on such cross-reactivity of antigens among eCoVs, the IgG antibodies against the spike protein (SP) of severe acute respiratory syndrome coronavirus (SARS-CoV) were isolated from pig serum using magnetic bea

Circuit timing is becoming more and more uncertain under greater process variation as technology scales. Given the fault probability of each timing path and their statistical correlation from a statistical timing framework, the path selection problem for delay faults has a nature similar to the problem of designing a portfolio of stocks or assets or determining the size of bets in gambling to minimize risk. This observation allows us to develop a very different path selection approach from the c

Deep neural networks have been demonstrated impressive results in various cognitive tasks such as object detection and image classification. In order to execute large networks, Von Neumann computers store the large number of weight parameters in external memories, and processing elements are timed-shared, which leads to power-hungry I/O operations and processing bottlenecks. This paper describes a neuromorphic computing system that is designed from the ground up for the energy-efficient evaluati

This paper presents a method to compute criticality probabilities of paths in parameterized statistical static timing analysis. We partition the set of all the paths into several groups and formulate the path criticality into a joint probability of inequalities. Before evaluating the joint probability directly, we simplify the inequalities through algebraic elimination, handling topological correlation. Our proposed method uses conditional probabilities to obtain the joint probability, and stati

Systolic arrays are the primary part of modern deep learning accelerators and are being used widely in real-life applications such as self-driving cars. This paper presents a novel factored systolic array, where the carry propagation adder for accumulation and the rounding logic are extracted out from each processing element, which reduces the area, power and delay of the processing elements substantially. The factoring is performed in the column-wise manner and the cost of the factored logic, p

This paper presents a built-in self repair analyzer with the optimal repair rate for memory arrays with redundancy. The proposed method requires only a single test, even in the worst case. By performing the must-repair analysis on the fly during the test, it selectively stores fault addresses, and the final analysis to find a solution is performed on the stored fault addresses. To enumerate all possible solutions, existing techniques use depth first search using a stack and a finite-state machin

Fv-antibodies against the nucleocapsid protein (NP) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were screened from an Fv-antibody library, and a one-step immunoassay was performed to detect SARS-CoV-2 using real viral samples. The Fv-antibody library was prepared using site-directed mutagenesis of the CDR3 region, which was composed of 11 amino acids. To screen the target Escherichia coli from the Fv-antibody library, the expressed probes [N-terminal domain (NTD) labeled with