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Book ; Online: Waveform Design for 5G and beyond Systems

Choi, Kwonhue

2022

Keywords	Technology: general issues ; History of engineering & technology ; Energy industries & utilities ; multicarrier modulation ; prototype filter design ; frequency sampling methods ; windowing based methods ; optimization based methods ; V2X ; LDS-F-OFDM ; LDS-UFMC ; EVA channel model ; multi-input-multi-output (MIMO) ; space time block coding ; physical layer security (PLS) ; secrecy capacity ; 5G waveform ; SC-FDMA ; FBMC ; Low PAPR FBMC (LP-FBMC) ; access timing offset ; carrier frequency offset ; high-power amplifier (HPA) nonlinearity ; software defined radio (SDR) device ; uplink indoor channel ; out-of-band (OOB) emission ; space time codes ; differential space time modulation ; differential detection ; pair-wise detection ; maximum likelihood detection ; n/a
Language	0\|e
Size	1 electronic resource (102 pages)
Publisher	MDPI - Multidisciplinary Digital Publishing Institute
Publishing place	Basel
Document type	Book ; Online
Note	English ; Open Access
HBZ-ID	HT021608882
ISBN	9783036531748 ; 3036531742
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Article ; Online: Block Partitioning Information-Based CNN Post-Filtering for EVC Baseline Profile.

Choi, Kiho

Sensors (Basel, Switzerland)

2024 Volume 24, Issue 4

Abstract: The need for efficient video coding technology is more important than ever in the current scenario where video applications are increasing worldwide, and Internet of Things (IoT) devices are becoming widespread. In this context, it is necessary to ... ...

Abstract	The need for efficient video coding technology is more important than ever in the current scenario where video applications are increasing worldwide, and Internet of Things (IoT) devices are becoming widespread. In this context, it is necessary to carefully review the recently completed MPEG-5 Essential Video Coding (EVC) standard because the EVC Baseline profile is customized to meet the specific requirements needed to process IoT video data in terms of low complexity. Nevertheless, the EVC Baseline profile has a notable disadvantage. Since it is a codec composed only of simple tools developed over 20 years, it tends to represent numerous coding artifacts. In particular, the presence of blocking artifacts at the block boundary is regarded as a critical issue that must be addressed. To address this, this paper proposes a post-filter using a block partitioning information-based Convolutional Neural Network (CNN). The proposed method in the experimental results objectively shows an approximately 0.57 dB for All-Intra (AI) and 0.37 dB for Low-Delay (LD) improvements in each configuration by the proposed method when compared to the pre-post-filter video, and the enhanced PSNR results in an overall bitrate reduction of 11.62% for AI and 10.91% for LD in the Luma and Chroma components, respectively. Due to the huge improvement in the PSNR, the proposed method significantly improved the visual quality subjectively, particularly in blocking artifacts at the coding block boundary.
Language	English
Publishing date	2024-02-19
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s24041336
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Structure-property Relationships Reported for the New Drugs Approved in 2023.

Choi, Kihang

Mini reviews in medicinal chemistry

2024

Abstract: Drug-like properties play pivotal roles in drug adsorption, distribution, metabolism, excretion, and toxicity. Therefore, efficiently optimizing these properties is essential for the successful development of novel therapeutics. Understanding the ... ...

Abstract	Drug-like properties play pivotal roles in drug adsorption, distribution, metabolism, excretion, and toxicity. Therefore, efficiently optimizing these properties is essential for the successful development of novel therapeutics. Understanding the structure-property relationships of clinically approved drugs can provide valuable insights for drug design and optimization strategies. Among the new drugs approved in 2023, which include 31 small-molecule drugs in the US, the structure-property relationships of nine drugs were compiled from the medicinal chemistry literature, in which detailed information on pharmacokinetic and/or physicochemical properties was reported not only for the final drug but also for its key analogs generated during drug development. The structure-property relationships of nine newly approved drugs are summarized, including three kinase inhibitors and three G-protein-coupled receptor antagonists. Several optimization strategies, such as bioisosteric replacement and steric handle installation, have successfully produced clinical candidates with enhanced physicochemical and pharmacokinetic properties. The summarized structure-property relationships demonstrate how appropriate structural modifications can effectively improve overall drug-like properties. The ongoing exploration of structure- property relationships of clinically approved drugs is expected to offer valuable guidance for developing future drugs.
Language	English
Publishing date	2024-04-25
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2104081-3
ISSN	1875-5607 ; 1389-5575
ISSN (online)	1875-5607
ISSN	1389-5575
DOI	10.2174/0113895575308674240415074629
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: A review of the Bayesian approach with the MCMC and the HMC as a competitor of classical likelihood statistics for pharmacometricians.

Choi, Kyungmee

Translational and clinical pharmacology

2023 Volume 31, Issue 2, Page(s) 69–84

Abstract: This article reviews the Bayesian inference with the Monte Carlo Markov Chain (MCMC) and the Hamiltonian Monte Carlo (HMC) samplers as a competitor of the classical likelihood statistical inference for pharmacometricians. The MCMC and the HMC samplers ... ...

Abstract	This article reviews the Bayesian inference with the Monte Carlo Markov Chain (MCMC) and the Hamiltonian Monte Carlo (HMC) samplers as a competitor of the classical likelihood statistical inference for pharmacometricians. The MCMC and the HMC samplers have greatly contributed to realization of the Bayesian methods with minimal requirement of mathematical theory. They do not require any closed form of the posterior density nor linear approximation of complex nonlinear models in high dimension even with non-conjugate priors. The HMC even weakens the dependency of the chain and improves computational efficiency. Pharmacometrics is one of great beneficiaries since they use complex multivariate multilevel nonlinear mixed effects models based on the restricted maximum likelihood estimation. Comprehension of the Bayesian approach will help pharmacometricians to access the data analysis more conveniently.
Language	English
Publishing date	2023-06-26
Publishing country	Korea (South)
Document type	Journal Article ; Review
ZDB-ID	2861878-6
ISSN	2383-5427 ; 2289-0882
ISSN (online)	2383-5427
ISSN	2289-0882
DOI	10.12793/tcp.2023.31.e9
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Structure-property Relationships Reported for the New Drugs Approved in 2022.

Choi, Kihang

Mini reviews in medicinal chemistry

2023 Volume 24, Issue 3, Page(s) 330–340

Abstract: Background: The structure-property relationship illustrates how modifying the chemical structure of a pharmaceutical compound influences its absorption, distribution, metabolism, excretion, and other related properties. Understanding structure-property ... ...

Abstract	Background: The structure-property relationship illustrates how modifying the chemical structure of a pharmaceutical compound influences its absorption, distribution, metabolism, excretion, and other related properties. Understanding structure-property relationships of clinically approved drugs could provide useful information for drug design and optimization strategies. Method: Among new drugs approved around the world in 2022, including 37 in the US, structure- property relationships of seven drugs were compiled from medicinal chemistry literature, in which detailed pharmacokinetic and/or physicochemical properties were disclosed not only for the final drug but also for its key analogues generated during drug development. Results: The discovery campaigns for these seven drugs demonstrate extensive design and optimization efforts to identify suitable candidates for clinical development. Several strategies have been successfully employed, such as attaching a solubilizing group, bioisosteric replacement, and deuterium incorporation, resulting in new compounds with enhanced physicochemical and pharmacokinetic properties. Conclusion: The structure-property relationships hereby summarized illustrate how proper structural modifications could successfully improve the overall drug-like properties. The structure-property relationships of clinically approved drugs are expected to continue to provide valuable references and guides for the development of future drugs.
MeSH term(s)	Drug Design ; Chemistry, Pharmaceutical ; Pharmaceutical Preparations
Chemical Substances	Pharmaceutical Preparations
Language	English
Publishing date	2023-05-19
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2104081-3
ISSN	1875-5607 ; 1389-5575
ISSN (online)	1875-5607
ISSN	1389-5575
DOI	10.2174/1389557523666230519162803
Database	MEDical Literature Analysis and Retrieval System OnLINE

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ab Jg. 2022: Lesesaal (EG)

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Article ; Online: The Structure-property Relationships of Clinically Approved Protease Inhibitors.

Choi, Kihang

Current medicinal chemistry

2023 Volume 31, Issue 12, Page(s) 1441–1463

Abstract: Background: Proteases play important roles in the regulation of many physiological processes, and protease inhibitors have become one of the important drug classes. Especially because the development of protease inhibitors often starts from a substrate- ...

Abstract	Background: Proteases play important roles in the regulation of many physiological processes, and protease inhibitors have become one of the important drug classes. Especially because the development of protease inhibitors often starts from a substrate- based peptidomimetic strategy, many of the initial lead compounds suffer from pharmacokinetic liabilities. Objective: To reduce drug attrition rates, drug metabolism and pharmacokinetics studies are fully integrated into modern drug discovery research, and the structure-property relationship illustrates how the modification of the chemical structure influences the pharmacokinetic and toxicological properties of drug compounds. Understanding the structure- property relationships of clinically approved protease inhibitor drugs and their analogues could provide useful information on the lead-to-candidate optimization strategies. Methods: About 70 inhibitors against human or pathogenic viral proteases have been approved until the end of 2021. In this review, 17 inhibitors are chosen for the structure- property relationship analysis because detailed pharmacological and/or physicochemical data have been disclosed in the medicinal chemistry literature for these inhibitors and their close analogues. Results: The compiled data are analyzed primarily focusing on the pharmacokinetic or toxicological deficiencies found in lead compounds and the structural modification strategies used to generate candidate compounds. Conclusion: The structure-property relationships hereby summarized how the overall druglike properties could be successfully improved by modifying the structure of protease inhibitors. These specific examples are expected to serve as useful references and guidance for developing new protease inhibitor drugs in the future.
MeSH term(s)	Humans ; Peptide Hydrolases ; Protease Inhibitors/pharmacology ; Protease Inhibitors/chemistry
Chemical Substances	Peptide Hydrolases (EC 3.4.-) ; Protease Inhibitors
Language	English
Publishing date	2023-04-05
Publishing country	United Arab Emirates
Document type	Review ; Journal Article
ZDB-ID	1319315-6
ISSN	1875-533X ; 0929-8673
ISSN (online)	1875-533X
ISSN	0929-8673
DOI	10.2174/0929867330666230409232655
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Laparoscopic management of a gastric liposarcoma with malignant transformation from a gastric lipoma: A rare case report.

Choi, KyeongWoon

International journal of surgery case reports

2023 Volume 113, Page(s) 109039

Abstract: Introduction and importance: Liposarcoma is one of the most common mesenchymal neoplasms in adults. Among liposarcomas, gastrointestinal tract involvement is uncommon, and liposarcoma of the stomach is a particularly rare entity, In addition, few cases ... ...

Abstract	Introduction and importance: Liposarcoma is one of the most common mesenchymal neoplasms in adults. Among liposarcomas, gastrointestinal tract involvement is uncommon, and liposarcoma of the stomach is a particularly rare entity, In addition, few cases of gastric liposarcoma with malignant transformation from benign gastric lipoma have been reported. Presentation of case: Here we present the case of a 62-year-old male patient who was diagnosed with gastric liposarcoma and managed with laparoscopic surgical resection. He was first diagnosed with subepithelial lipoma of the stomach 4 years ago and was under observation, but underwent laparoscopic distal gastrectomy due to malignant transformation of gastric lipoma. He has been following up for 1 year after surgery, and there are no recurrence or other complications to date. Clinical discussion: This patient was initially diagnosed with gastric lipoma and was surgically resected after 4 years of observation to show malignant transformation. To the best of our knowledge, this case represents the first report of gastric lipoma demonstrating malignant transformation into gastric liposarcoma. Conclusion: Gastric lipoma can be transformed into gastric liposarcoma, so if the size is large or the rate of size change is fast, surgical resection is recommended in the early state, and en-bloc resection including node dissection and reconstruction are desirable during surgery.
Language	English
Publishing date	2023-11-21
Publishing country	Netherlands
Document type	Case Reports
ISSN	2210-2612
ISSN	2210-2612
DOI	10.1016/j.ijscr.2023.109039
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A Comparative Study between Image- and Projection-Domain Self-Supervised Learning for Ultra Low-Dose CBCT.

Choi, Kihwan

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

2022 Volume 2022, Page(s) 2076–2079

Abstract: We compare image domain and projection domain denoising approaches with self-supervised learning for ultra low-dose cone-beam CT (CBCT), where number of detected x-ray photons is significantly low. For image-domain self-supervised denoising, we first ... ...

Abstract	We compare image domain and projection domain denoising approaches with self-supervised learning for ultra low-dose cone-beam CT (CBCT), where number of detected x-ray photons is significantly low. For image-domain self-supervised denoising, we first reconstruct CBCT images with the standard filtered backprojection. For model training, we use blind-spot filtering to partially blind images and recover the blind spots. For projection-domain self-supervised denoising, we regard the post-log projections as training examples of convolutional neural network. From experimental results with various low-dose CBCT settings, the projection-domain denoiser outperforms the image-domain denoiser both in image quality and accuracy for ultra low-dose CBCT.
MeSH term(s)	Cone-Beam Computed Tomography/methods ; Image Processing, Computer-Assisted/methods ; Phantoms, Imaging ; Spiral Cone-Beam Computed Tomography ; Supervised Machine Learning
Language	English
Publishing date	2022-09-10
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	2694-0604
ISSN (online)	2694-0604
DOI	10.1109/EMBC48229.2022.9871947
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A Study on Fast and Low-Complexity Algorithms for Versatile Video Coding.

Choi, Kiho

Sensors (Basel, Switzerland)

2022 Volume 22, Issue 22

Abstract: Versatile Video Coding (VVC)/H.266, completed in 2020, provides half the bitrate of the previous video coding standard (i.e., High-Efficiency Video Coding (HEVC)/H.265) while maintaining the same visual quality. The primary goal of VVC/H.266 is to ... ...

Abstract	Versatile Video Coding (VVC)/H.266, completed in 2020, provides half the bitrate of the previous video coding standard (i.e., High-Efficiency Video Coding (HEVC)/H.265) while maintaining the same visual quality. The primary goal of VVC/H.266 is to achieve a compression capability that is noticeably better than that of HEVC/H.265, as well as the functionality to support a variety of applications with a single profile. Although VVC/H.266 has improved its coding performance by incorporating new advanced technologies with flexible partitioning, the increased encoding complexity has become a challenging issue in practical market usage. To address the complexity issue of VVC/H.266, significant efforts have been expended to develop practical methods for reducing the encoding and decoding processes of VVC/H.266. In this study, we provide an overview of the VVC/H.266 standard, and compared with previous video coding standards, examine a key challenge to VVC/H.266 coding. Furthermore, we survey and present recent technical advances in fast and low-complexity VVC/H.266, focusing on key technical areas.
Language	English
Publishing date	2022-11-20
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s22228990
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The Structure-property Relationships of Clinically Approved Protein Kinase Inhibitors.

Choi, Kihang

Current medicinal chemistry

2022 Volume 30, Issue 22, Page(s) 2518–2541

Abstract: Background: Protein kinase inhibitors have become one of the most successful classes of small-molecule drugs during the last decades. In modern drug discovery, considering 'drug-like' physicochemical and pharmacokinetic properties as early as possible ... ...

Abstract	Background: Protein kinase inhibitors have become one of the most successful classes of small-molecule drugs during the last decades. In modern drug discovery, considering 'drug-like' physicochemical and pharmacokinetic properties as early as possible in drug design is widely acknowledged as an important strategy to reduce drug attrition rates. Methods: In this review, clinically approved 25 protein kinase inhibitors and their key analogues reported in medicinal chemistry literature were compared for their biological, physicochemical, and pharmacokinetic properties. Although there is no common trajectory to follow through complex drug discovery campaigns, knowledge of the structure- activity relationship obtained from the successful lead optimization studies might be extended to other drug design efforts. Results: Among more than 70 protein kinase inhibitors clinically approved around the world, the structure-activity relationships of 25 inhibitors and their key analogues are compiled from medicinal chemistry literature, in which detailed results from the 'lead-tocandidate' stage are available with associated property data. For the other inhibitors, such information has not been disclosed in the literature, or the available data is limited and not sufficient to provide clear structural analysis. Conclusion: The structure-property relationships summarized for 25 inhibitors and their analogues illustrate general guidelines for lead optimization and candidate selection, and this information could be extended for better property-based drug design in the future.
MeSH term(s)	Humans ; Protein Kinase Inhibitors/pharmacology ; Protein Kinase Inhibitors/chemistry ; Drug Design ; Drug Discovery/methods ; Structure-Activity Relationship ; Chemistry, Pharmaceutical
Chemical Substances	Protein Kinase Inhibitors
Language	English
Publishing date	2022-10-06
Publishing country	United Arab Emirates
Document type	Review ; Journal Article
ZDB-ID	1319315-6
ISSN	1875-533X ; 0929-8673
ISSN (online)	1875-533X
ISSN	0929-8673
DOI	10.2174/0929867329666220822123552
Database	MEDical Literature Analysis and Retrieval System OnLINE

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ab Jg. 2022: Lesesaal (EG)

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