Ontology-lexicon-based question answering over linked data

Jabalameli, Mehdi,Nematbakhsh, Mohammadali,Zaeri, Ahmad Electronics and Telecommunications Research Instit 2020 ETRI Journal Vol.42 No.2

Recently, Linked Open Data has become a large set of knowledge bases. Therefore, the need to query Linked Data using question answering (QA) techniques has attracted the attention of many researchers. A QA system translates natural language questions into structured queries, such as SPARQL queries, to be executed over Linked Data. The two main challenges in such systems are lexical and semantic gaps. A lexical gap refers to the difference between the vocabularies used in an input question and those used in the knowledge base. A semantic gap refers to the difference between expressed information needs and the representation of the knowledge base. In this paper, we present a novel method using an ontology lexicon and dependency parse trees to overcome lexical and semantic gaps. The proposed technique is evaluated on the QALD-5 benchmark and exhibits promising results.

Analysis of issues in gate recess etching in the InAlAs/InGaAs HEMT manufacturing process

Byoung-Gue Min,Jong-Min Lee,Hyung Sup Yoon,Woo-Jin Chang,Jong-Yul Park,Dong Min Kang,Sung-Jae Chang,Hyun-Wook Jung Electronics and Telecommunications Research Instit 2023 ETRI Journal Vol.45 No.1

We have developed an InAlAs/InGaAs metamorphic high electron mobility transistor device fabrication process where the gate length can be tuned within the range of 0.13㎛-0.16㎛ to suit the intended application. The core processes are a two-step electron-beam lithography process using a three-layer resist and gate recess etching process using citric acid. An electron-beam lithography process was developed to fabricate a T-shaped gate electrode with a fine gate foot and a relatively large gate head. This was realized through the use of three-layered resist and two-step electron beam exposure and development. Citric acid-based gate recess etching is a wet etching, so it is very important to secure etching uniformity and process reproducibility. The device layout was designed by considering the electrochemical reaction involved in recess etching, and a reproducible gate recess etching process was developed by finding optimized etching conditions. Using the developed gate electrode process technology, we were able to successfully manufacture various monolithic microwave integrated circuits, including low noise amplifiers that can be used in the 28 GHz to 94 GHz frequency range.

Disputes over the Intellectual Property Rights of Telecommunications Standardization

Park, Ki-Shik,Kim, Young-Tae,Sohn, Hong Electronics and Telecommunications Research Instit 1998 ETRI Journal Vol.20 No.1

Both telecommunications standardization activities and an intellectual property rights (IPRs) system are regarded as effective mechanisms for improving social benefits. Because of inherent conflicts that exist between the two, however, serious problems are generated in the international arena where the competition for technology development and markets is becoming increasingly fierce. In this paper, ways of harmonizing the relationship between the two are explored and explained. For this purpose, telecommunications standardization and IPRs protection mechanisms are described, and their positive and negative effects as well as their inter-relationship are also analyzed. In addition, IPR case studies related to international standardization are explained and analyzed. The Current status and problems of IPRs policy of major international standardization organizations are analyzed as well. Finally, based on the results of the analyses, viable policy recommendations and research strategies for more comprehensive study of the above problems are proposed.

No-reference quality assessment of dynamic sports videos based on a spatiotemporal motion model

Kim, Hyoung-Gook,Shin, Seung-Su,Kim, Sang-Wook,Lee, Gi Yong Electronics and Telecommunications Research Instit 2021 ETRI Journal Vol.43 No.3

This paper proposes an approach to improve the performance of no-reference video quality assessment for sports videos with dynamic motion scenes using an efficient spatiotemporal model. In the proposed method, we divide the video sequences into video blocks and apply a 3D shearlet transform that can efficiently extract primary spatiotemporal features to capture dynamic natural motion scene statistics from the incoming video blocks. The concatenation of a deep residual bidirectional gated recurrent neural network and logistic regression is used to learn the spatiotemporal correlation more robustly and predict the perceptual quality score. In addition, conditional video block-wise constraints are incorporated into the objective function to improve quality estimation performance for the entire video. The experimental results show that the proposed method extracts spatiotemporal motion information more effectively and predicts the video quality with higher accuracy than the conventional no-reference video quality assessment methods.

Evaluations of AI-based malicious PowerShell detection with feature optimizations

Song, Jihyeon,Kim, Jungtae,Choi, Sunoh,Kim, Jonghyun,Kim, Ikkyun Electronics and Telecommunications Research Instit 2021 ETRI Journal Vol.43 No.3

Cyberattacks are often difficult to identify with traditional signature-based detection, because attackers continually find ways to bypass the detection methods. Therefore, researchers have introduced artificial intelligence (AI) technology for cybersecurity analysis to detect malicious PowerShell scripts. In this paper, we propose a feature optimization technique for AI-based approaches to enhance the accuracy of malicious PowerShell script detection. We statically analyze the PowerShell script and preprocess it with a method based on the tokens and abstract syntax tree (AST) for feature selection. Here, tokens and AST represent the vocabulary and structure of the PowerShell script, respectively. Performance evaluations with optimized features yield detection rates of 98% in both machine learning (ML) and deep learning (DL) experiments. Among them, the ML model with the 3-gram of selected five tokens and the DL model with experiments based on the AST 3-gram deliver the best performance.

Anomaly detection in particulate matter sensor using hypothesis pruning generative adversarial network

Park, YeongHyeon,Park, Won Seok,Kim, Yeong Beom Electronics and Telecommunications Research Instit 2021 ETRI Journal Vol.43 No.3

The World Health Organization provides guidelines for managing the particulate matter (PM) level because a higher PM level represents a threat to human health. To manage the PM level, a procedure for measuring the PM value is first needed. We use a PM sensor that collects the PM level by laser-based light scattering (LLS) method because it is more cost effective than a beta attenuation monitor-based sensor or tapered element oscillating microbalance-based sensor. However, an LLS-based sensor has a higher probability of malfunctioning than the higher cost sensors. In this paper, we regard the overall malfunctioning, including strange value collection or missing collection data as anomalies, and we aim to detect anomalies for the maintenance of PM measuring sensors. We propose a novel architecture for solving the above aim that we call the hypothesis pruning generative adversarial network (HP-GAN). Through comparative experiments, we achieve AUROC and AUPRC values of 0.948 and 0.967, respectively, in the detection of anomalies in LLS-based PM measuring sensors. We conclude that our HP-GAN is a cutting-edge model for anomaly detection.

Power analysis attack resilient block cipher implementation based on 1-of-4 data encoding

Shanmugham, Shanthi Rekha,Paramasivam, Saravanan Electronics and Telecommunications Research Instit 2021 ETRI Journal Vol.43 No.4

Side-channel attacks pose an inevitable challenge to the implementation of cryptographic algorithms, and it is important to mitigate them. This work identifies a novel data encoding technique based on 1-of-4 codes to resist differential power analysis attacks, which is the most investigated category of side-channel attacks. The four code words of the 1-of-4 codes, namely (0001, 0010, 1000, and 0100), are split into two sets: set-0 and set-1. Using a select signal, the data processed in hardware is switched between the two encoding sets alternately such that the Hamming weight and Hamming distance are equalized. As a case study, the proposed technique is validated for the NIST standard AES-128 cipher. The proposed technique resists differential power analysis performed using statistical methods, namely correlation, mutual information, difference of means, and Welch's t-test based on the Hamming weight and distance models. The experimental results show that the proposed countermeasure has an area overhead of 2.3× with no performance degradation comparatively.

Corrigendum

Hong, Kang Woon,Ryu, Won Electronics and Telecommunications Research Instit 2018 ETRI Journal Vol.37 No.4

Quantum-based exact pattern matching algorithms for biological sequences

Soni, Kapil Kumar,Rasool, Akhtar Electronics and Telecommunications Research Instit 2021 ETRI Journal Vol.43 No.3

In computational biology, desired patterns are searched in large text databases, and an exact match is preferable. Classical benchmark algorithms obtain competent solutions for pattern matching in O (N) time, whereas quantum algorithm design is based on Grover's method, which completes the search in $O(\sqrt{N})$ time. This paper briefly explains existing quantum algorithms and defines their processing limitations. Our initial work overcomes existing algorithmic constraints by proposing the quantum-based combined exact (QBCE) algorithm for the pattern-matching problem to process exact patterns. Next, quantum random access memory (QRAM) processing is discussed, and based on it, we propose the QRAM processing-based exact (QPBE) pattern-matching algorithm. We show that to find all t occurrences of a pattern, the best case time complexities of the QBCE and QPBE algorithms are $O(\sqrt{t})$ and $O(\sqrt{N})$, and the exceptional worst case is bounded by O (t) and O (N). Thus, the proposed quantum algorithms achieve computational speedup. Our work is proved mathematically and validated with simulation, and complexity analysis demonstrates that our quantum algorithms are better than existing pattern-matching methods.

Real-time implementation of distributed beamforming for simultaneous wireless information and power transfer in interference channels

Hong, Yong-Gi,Hwang, SeongJun,Seo, Jiho,Lee, Jonghyeok,Park, Jaehyun Electronics and Telecommunications Research Instit 2021 ETRI Journal Vol.43 No.3

In this paper, we propose one-bit feedback-based distributed beamforming (DBF) techniques for simultaneous wireless information and power transfer in interference channels where the information transfer and power transfer networks coexist in the same frequency spectrum band. In a power transfer network, multiple distributed energy transmission nodes transmit their energy signals to a single energy receiving node capable of harvesting wireless radio frequency energy. Here, by considering the Internet-of-Things sensor network, the energy harvesting/information decoding receivers (ERx/IRx) can report their status (which may include the received signal strength, interference, and channel state information) through one-bit feedback channels. To maximize the amount of energy transferred to the ERx and simultaneously minimize the interference to the IRx, we developed a DBF technique based on one-bit feedback from the ERx/IRx without sharing the information among distributed transmit nodes. Finally, the proposed DBF algorithm in the interference channel is verified through the simulations and also implemented in real time by using GNU radio and universal software radio peripheral.