Evaluation of accuracies of genomic predictions for body conformation traits in Korean Holstein

하쿠에엠디아지줄,Alam Mohammad Zahangir,이크발아시프,이윤미,Dang Chang Gwon,김종주 아세아·태평양축산학회 2024 Animal Bioscience Vol.37 No.4

Objective: This study aimed to assess the genetic parameters and accuracy of genomic predictions for twenty-four linear body conformation traits and overall conformation scores in Korean Holstein dairy cows. Methods: A dataset of 2,206 Korean Holsteins was collected, and genotyping was performed using the Illumina Bovine 50K single nucleotide polymorphism (SNP) chip. The traits investigated included body traits (stature, height at front end, chest width, body depth, angularity, body condition score, and locomotion), rump traits (rump angle, rump width, and loin strength), feet and leg traits (rear leg set, rear leg rear view, foot angle, heel depth, and bone quality), udder traits (udder depth, udder texture, udder support, fore udder attachment, front teat placement, front teat length, rear udder height, rear udder width, and rear teat placement), and overall conformation score. Accuracy of genomic predictions was assessed using the single-trait animal model genomic best linear unbiased prediction method implemented in the ASReml-SA v4.2 software. Results: Heritability estimates ranged from 0.10 to 0.50 for body traits, 0.21 to 0.35 for rump traits, 0.13 to 0.29 for feet and leg traits, and 0.05 to 0.46 for udder traits. Rump traits exhibited the highest average heritability (0.29), while feet and leg traits had the lowest estimates (0.21). Accuracy of genomic predictions varied among the twenty-four linear body conformation traits, ranging from 0.26 to 0.49. The heritability and prediction accuracy of genomic estimated breeding value (GEBV) for the overall conformation score were 0.45 and 0.46, respectively. The GEBVs for body conformation traits in Korean Holstein cows had low accuracy, falling below the 50% threshold. Conclusion: The limited response to selection for body conformation traits in Korean Holsteins may be attributed to both the low heritability of these traits and the lower accuracy estimates for GEBVs. Further research is needed to enhance the accuracy of GEBVs and improve the selection response for these traits.

MECHA: 다중스레드 및 효율적인 암호화 하드웨어 액세스

프라타마데리 ( Pratama Derry ),락스모노아구스마하르디카아리 ( Laksmono Agus Mahardika Ari ),이크발무함마드 ( Iqbal Muhammad ),김호원 ( Howon Kim ) 한국정보처리학회 2023 한국정보처리학회 학술대회논문집 Vol.30 No.1

메시지 전달 기법을 이용한 개념도 구축 시스템의 설계 및 구현

이크발 카심,이동호,정진우,허지욱 한국정보과학회 2013 데이타베이스 연구 Vol.29 No.1

Concept map is a graphical tool that is widely used for organizing and representing knowledge and shows the relationships among related concepts. Automatic concept map construction from text documents requires methods for extracting concepts and relationships (taxonomic and non-taxonomic). Even though a lot of studies have been conducted to automatically construct a concept map, they still have some limitations such as a resolution of anaphora problem and defining relationships to form propositions. In this paper, we propose a clustering-based approach for constructing a concept map from text documents. First, relevant concepts are extracted using typed dependency linguistic patterns. Anaphoric resolution for pronouns is then introduced to map the pronouns with candidate terms. Second, extracted concepts are clustered using affinity propagation algorithm. Finally, relationships are assigned between the extracted concepts in each cluster. Our empirical results show that the constructed concept maps conform to the outputs generated manually by domain experts. Furthermore, domain experts verified that the constructed concept maps are in accordance with their knowledge. 개념도는 지식체계를 조직화하고 표현하기 위해 사용되는 도구로서 서로 관련이 있는 개념들 간의 관계성을 나타내게 된다. 텍스트 문서로부터 개념도를 자동으로 추출하는 과정은 개념과 개념들 간의 분류적/비분류적 관계를 추출하는과정을 필요로 한다. 개념도의 자동 구축과 관련하여 많은 연구들이 진행되고 있지만, 대명사의 대용 해소 문제, 개념간 관련성에 대한 방향성 할당 문제 등 여전히 많은 개선점들이 필요한 실정이다. 본 논문에서는 텍스트 문서로부터 개념도를 자동으로 구축하기 위한 클러스터링 기반의 기법을 제안한다. 제안하는 시스템의 흐름은 다음과 같다. 먼저, 의존문법 규칙을 이용하여 도메인 개념들을 추출하고 대명사에 대한 대용 해소 문제를 해결하기 위한 방법을 적용함으로써문서 내 대명사들을 추출된 개념들과 연결한다. 그 후, 친근도 전파 알고리즘을 활용하여 추출된 도메인 개념들에 대한클러스터링을 수행한다. 마지막으로, 구축 된 각각의 클러스터내의 개념들간의 관련성을 할당함으로써 개념도를 구축한다. 정보 시스템 도메인 문서들에 대하여 제안하는 기법에 의하여 구축된 개념도와 해당 도메인의 전문가에 의하여 구축된 개념도간의 비교를 통하여 성능 평가를 수행하였다. 실험 결과를 통해, 본 논문에서 제안하는 기법은 도메인 전문가들에 의하여 수동으로 구축된 개념도와 유사한 수준의 개념도를 구축할 수 있음을 보였다.

Enhanced Belief Propagation Polar Decoder for Finite Lengths

이크발 샤질,최광석,Iqbal, Shajeel,Choi, Goangseog Korea Society of Digital Industry and Information 2015 디지털산업정보학회논문지 Vol.11 No.3

In this paper, we discuss the belief propagation decoding algorithm for polar codes. The performance of Polar codes for shorter lengths is not satisfactory. Motivated by this, we propose a novel technique to improve its performance at short lengths. We showed that the probability of messages passed along the factor graph of polar codes, can be increased by multiplying the current message of nodes with their previous message. This is like a feedback path in which the present signal is updated by multiplying with its previous signal. Thus the experimental results show that performance of belief propagation polar decoder can be improved using this proposed technique. Simulation results in binary-input additive white Gaussian noise channel (BI-AWGNC) show that the proposed belief propagation polar decoder can provide significant gain of 2 dB over the original belief propagation polar decoder with code rate 0.5 and code length 128 at the bit error rate (BER) of $10^{-4}$.

폐수의 막 전기 화학적 산화와 수소연료발생

타히르 이크발,추광호 한국막학회 2016 한국막학회 총회 및 학술발표회 Vol.2016 No.11

Membrane based water and wastewater treatment becomes more and more popular; however, membrane fouling is still a critical obstacle for its extensive use. Most of the membranes being used are polymeric and have limitations in physical, chemical, and thermal stability, even though various novel materials were introduced. In this study, metal membranes were fabricated to solve those weak points of polymeric membranes. We evaluated the physical properties of a metal membrane, such as pore size distribution, surface morphology, and water flux, and finally used the membrane for electrochemical oxidation of municipal wastewater with simultaneous hydrogen fuel generation. The metal membrane removed 50-70% of the feed organic matter by electrochemical oxidation; 10-30 % removal by electrochemical oxidation plus 40% by membrane rejection.

(PIM-co-Ellagic Acid)-기반의 이산화탄소 분리막의 개발

호세인 이크발,허스너 아스몰,김동영,김태현 한국막학회 2020 멤브레인 Vol.30 No.6

(PIM-1)과 ellagic acid로 만든 랜덤형 공중합체가 간단한 방법으로 합성되었으며, 이산화탄소 분리막에 대한 적용 가능성에 대해서 연구하였다. 이 공중합체의 경우 PIM (polymers with intrinsic microporosity) 고분자의 미세 기공 구조에 기 인한 높은 기체 투과도와 평면 구조와 친수성을 갖는 ellagic acid에 기인한 높은 이산화탄소에 대한 선택성에 의해 우수한 이 산화탄소 기체 분리 성능을 나타내었다. 즉, 이산화탄소에 대한 투과도 4516 Barrer와 CO2/N2 (> 23~26) 및 CO2/CH4 (> 18~19)의 높은 선택성으로 두 쌍의 가스 혼합물에 대해 Robeson 상한(2008)을 초과한 결과를 나타내었다. 이와 같이 PIM-1 에 평면구조를 갖는 ellagic acid을 혼입하면 PIM-1의 꼬인 구조를 방해하여 기체 투과성을 향상 시킬 뿐만 아니라 공중합체 의 강성과 극성이 증가하여 N2 및 CH4에 대한 CO2의 선택성을 증가시키는 결과를 확인하였다. Random copolymers made of both ‘polymer of intrinsic microporosity (PIM-1)’ and Ellagic acid were prepared for the first time by a facile one-step polycondensation reaction. By combining the highly porous and contorted structure of PIM (polymers with intrinsic microporosity) and flat-type hydrophilic ellagic acid, the membranes obtained from these random copolymers [(PIM-co-EA)-x] showed high CO2 permeability (> 4516 Barrer) with high CO2/N2 (> 23~26) and CO2/CH4 (> 18~19) selectivity, that surpassed the Robeson upper bound (2008) for both pairs of the gas mixture. Incorporation of flat-type ellagic acid into the PIM-1 not only enhances the gas permeability by disturbing the kinked structure of PIM-1 but also increases the selectivity of CO2 over N2 and CH4, due to an increase of rigidity and polarity in the resultant copolymer membranes.

Automatic Acquisition of Domain Concepts for Ontology Learning using Affinity Propagation

Iqbal Qasim(이크발 카심),Jin-Woo Jeong(정진우),Dong-Ho Lee(이동호) 한국정보과학회 2011 한국정보과학회 학술발표논문집 Vol.38 No.1C

One important issue in semantic web is identification and selection of domain concepts for domain ontology learning when several hundreds or even thousands of terms are extracted and available from relevant text documents shared among the members of a domain. We present a novel domain concept acquisition and selection approach for ontology learning that uses affinity propagation algorithm, which takes as input semantic and structural similarity between pairs of extracted terms called data points. Real-valued messages are passed between data points (terms) until high quality set of exemplars (concepts) and cluster iteratively emerges. All exemplars will be considered as domain concepts for learning domain ontologies. Our empirical results show that our approach achieves high precision and recall in selection of domain concepts using less number of iterations.

A Survey on the Utilization of OTFS Modulation in LEO Satellite Communication

Usman Iqbal(우스만 이크발),Haejoon Jung(정해준),Hyundong Shin(신현동) 한국통신학회 2023 한국통신학회 학술대회논문집 Vol.2023 No.6

Performance Comparison of Positioning Techniques in Body Area Network (BAN)

Asif iqbal(아시프 이크발),Kim jeonghoon(김정훈),Kwak kyungsup(곽경섭) 한국통신학회 2010 한국통신학회 학술대회논문집 Vol.2010 No.6

Unveiling the Unseen: A Review on current trends in Open-World Object Detection

MUHAMMAD ALI IQBAL(이크발 무하마드 알리),Soo Kyun Kim(김수균) 한국컴퓨터정보학회 2024 한국컴퓨터정보학회 학술발표논문집 Vol.32 No.1