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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Kuo Guo Yifan Li Hao Chen Hong-Bin Shen Yang Yang Department of Computer Science and Engineering Shanghai Jiao Tong University and Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Computational Biology Department School of Computer Science Carnegie Mellon University Pittsburgh PA USA

Isoforms refer to different mRNA molecules transcribed from the same gene, which can be translated into proteins with varying structures and functions. Predicting the functions of isoforms is an essential topic in bioinformatics as it can provide valuable insights into the intricate mechanisms of gene regulation and biological processes. Conventionally, gene function labels are standardized in Gene Ontology (GO) terms. However, traditional methods for predicting isoform function are largely limited by the absence of isoform-specific labels, sparse annotations, and the vast number of GO terms. To address these issues, we propose HANIso, a deep learning-based method for isoform function prediction. HANIso leverages a pretrained protein language model to extract features from protein sequences. It also integrates heterogeneous information, such as isoform sequence features, GO annotations, and isoform interaction data, using a Heterogeneous Graph Attention Network (HAN). This allows the model to learn the importance of different sources of information and their semantic relationships through the attention mechanism. Our method can predict function labels at both the gene level and isoform level. We conduct experiments on two species datasets, and the results demonstrate that our method outperforms existing methods on both AUROC and AUPRC. HANIso has the potential to overcome the limitations of traditional methods and provide a more accurate and comprehensive understanding of isoform function.

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Aligning Learning Materials and Assessment with Course Learning Outcomes in MOOCs Using Data Mining Techniques 8th

Aligning Learning Materials and Assessment with Course Learn...

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8th International Workshop on Combinations of Intelligent Methods and Applications, CIMA 2018 held in conjunction with the 30th IEEE International Conference on Tools with Artificial Intelligence, IEEE ICTAI 2018

作者： Ewais, Ahmed Awad, Mohammed Hadia, Khetam Department of Computer Science Arab American University Jenin Palestine Department of Computer System Engineering Arab American University Jenin Palestine Laboratory Department of Computer Science Vrije Universiteit Brussel Brussels Belgium

ISBN: (纸本)9789811519178

Massive open online courses (MOOCs) are considered as a new trend in the domain of e-learning. They provide a platform for supporting learners from different places and at any time with highly scalable and interesting learning experience. As a result, this led to continuous increase in the rate of learners with different knowledge, background, and skills. Therefore, supporting learners with adapted courses’ materials and assessments based on learning outcomes is considered as a crucial concept for enhancing MOOCs. This paper presents a framework for delivering learning materials and generating assessments based on intended learning outcomes (ILOs) using both support vector machine (SVM) and fuzzy logic algorithm. The SVM is mainly used to classify learning materials according to learning outcomes. On the other hand, the fuzzy logic algorithm is mainly used to generate examinations and quizzes automatically based on learners’ achievements and scores. Accordingly, the proposed framework can be used to enable learners to achieve learning outcomes by following adapted learning materials and automatically generated examinations. To validate the proposed framework, a prototype was developed and evaluated. The results of classifying both learning materials and assessment show interesting results. For instance, the results of classification process for learning materials were related to a number of factors such as accuracy rate for SVM classifier which was 71.5%, the weighted average for TP rate = 0.715, FN rate = 0.285, FP rate = 0.028, TN rate = 0.972, precision = 0.738, recall = 0.715, F-measure = 0.678, and finally ROC area = 0.939. In addition, fuzzy logic technique provided promising results to deliver examinations with a difficulty levels that are compatible with the current level of the learner depending on his grade point average (GPA). © 2020, Springer Nature Singapore Pte Ltd.

关键词： Support vector machines

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LidarGait: Benchmarking 3D Gait Recognition with Point Clouds

arXiv

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arXiv 2022年

作者： Shen, Chuanfu Fan, Chao Wu, Wei Wang, Rui Huang, George Q. Yu, Shiqi Department of Industrial and Manufacturing Systems Engineering The University of Hong Kong Hong Kong Department of Computer Science and Engineering Southern University of Science and Technology China Research Institute of Trustworthy Autonomous System Southern University of Science and Technology China Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hong Kong

Video-based gait recognition has achieved impressive results in constrained scenarios. However, visual cameras neglect human 3D structure information, which limits the feasibility of gait recognition in the 3D wild world. Instead of extracting gait features from images, this work explores precise 3D gait features from point clouds and proposes a simple yet efficient 3D gait recognition framework, termed LidarGait. Our proposed approach projects sparse point clouds into depth maps to learn the representations with 3D geometry information, which outperforms existing point-wise and camera-based methods by a significant margin. Due to the lack of point cloud datasets, we build the first large-scale LiDAR-based gait recognition dataset, SUSTech1K, collected by a LiDAR sensor and an RGB camera. The dataset contains 25,239 sequences from 1,050 subjects and covers many variations, including visibility, views, occlusions, clothing, carrying, and scenes. Extensive experiments show that (1) 3D structure information serves as a significant feature for gait recognition. (2) LidarGait outperforms existing point-based and silhouette-based methods by a significant margin, while it also offers stable cross-view results. (3) The LiDAR sensor is superior to the RGB camera for gait recognition in the outdoor environment. The source code and dataset have been made available at https://***. Copyright © 2022, The Authors. All rights reserved.

关键词： Cameras

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Students' Capability in Bridging the Entrepreneurial and Innovation Chasm 12

Students' Capability in Bridging the Entrepreneurial and Inn...

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12th IEEE International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2021

作者： Malele, Vusumuzi Letsoalo, Manthiba Elizabeth Mafu, Mhlambululi Tshwane University of Technology Departments of Information Technology and Computer System Engineering Pretoria South Africa University of Limpopo Mathematics Science and Technology Education Mankweng South Africa Botswana International University of Science and Technology Department of Physics and Astronomy Palapye Botswana

ISBN: (纸本)9780738144627

Practical entrepreneurship and innovation are essential for economic growth, individual growth, job creation, and increased social progress. Contrary, to more experienced entrepreneurs or innovators, young and ill-experienced 20-somethings entrepreneurs or innovators have time and access to technological resources to be active within the Innovation Value Chain. They have the potential to build incredibly successful business ventures. This paper adopts a pragmatic approach to explore and contribute to the discussion of addressing entrepreneurial and innovation chasm. Specifically, it demonstrates whether young people or students in their 20-something years of age are opportunity-oriented, proactive, and capable of innovating and establishing new ventures. Also, we examine if young people or students have a general understanding of the intellectual property system or, more specifically, a patent system. This study reveals that some of the most successful entrepreneurs and innovators started their businesses at a younger or at 20-something age group. Based on the importance of protecting the intellectual property emanating from entrepreneurial activities, this study indicates that most students who participated in the survey have a general understanding of the patent concept and have positive attitudes (i.e. belief and interest in establishing and managing a business of their own) towards entrepreneurship and innovation. This work's findings further demonstrate that young and ill-experienced individuals can establish new business ventures, thus bridging the entrepreneurial and innovation chasm. Bearing in mind that most students in this study are at universities, we provide recommendations, including future work on how technology-based universities could bridge the innovation chasm. © 2021 IEEE.

关键词： Students

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Improving the Performance of Perovskite Solar Cells by Forming a Matrix of Microlenses in Ito Electrode Using Single Laser Pulses

SSRN

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SSRN 2024年

作者： Augustowski, Dariusz Pawlowska, Agnieszka Izabela Kwaśnicki, Pawel Rysz, Jakub Research & Development Centre for Photovoltaics ML System S.A. Zaczernie 190G Zaczernie36-062 Poland Department of Advanced Materials Engineering Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University Lojasiewicza 11 Cracow30-348 Poland

Perovskite-based photovoltaics is progressing towards commercial application, but still requires improvement in both efficiency and durability. In this paper, we present results on enhancing the performance of perovskite solar cells by introducing laser-induced texturizing at the ITO electrode, which could be easily up-scaled and applied to large area devices. Single pulses of the fibre laser were used to ablate the ITO and create a matrix of microlenses. Their role was to increase the diffusive transmittance of the patterned electrode and the light harvesting within the device. In addition, texturizing expands its active surface, which also has a beneficial effect on the performance of perovskite solar cells. According to data obtained, active layers (PEDOT:PSS, CH3NH3PbI3-xClx perovskite and PC70BM) did not fully fill the hollows, but formed continuous layers along the substrate topography. As a result, the power conversion efficiency increased from 8.2 to 11.0% for reference and patterned devices, respectively. © 2024, The Authors. All rights reserved.

关键词： Solar energy

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VulPin: Finer-Grained Slicing for Pinpointing Vulnerability in Binary Programs 23

VulPin: Finer-Grained Slicing for Pinpointing Vulnerability ...

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Proceedings of the 2023 7th International Conference on computer science and Artificial Intelligence

作者： Abdulrahman Hamman Adama Chukkol Senlin Luo Haruna Yunusa Abdulganiyu Abdu Yusuf Abulfatahi Mohammed Information and Electronics Department of Information and Electronics. Beijing Institute of Technology Beijing China China Information and Electronics Information System and Security & Countermeasures Experimental Center Beijing Institute of Technology Beijing China China Automation Science and Electrical Engineering School of Automation Science and Electrical Engineering Beihang University Beijing China China Computer Science School of Computer Science and Technology Beijing Institute of Technology Beijing China China Information Technology School of Management and Information Technology Modibbo Adama University Yola Nigeria Nigeria

ISBN: (纸本)9798400708688

Identifying vulnerabilities in binary code with precision is a critical area of study in the field of software security. Most existing techniques fail to pinpoint the vulnerability's exact location, due to the extensive labelled data requirement and lack of targeted approach to improve on the problematic code. In this paper, we introduce VulPin, a system specifically designed to pinpoint vulnerabilities in binary code. This framework uses a hierarchical attention network that analyze program slices along with a vulnerability position matrix. Experimental outcomes indicate that our framework not only outperforms existing approaches but also pinpoints vulnerabilities more rapidly with a high Accuracy and a very low rate of false positives.

关键词： Binary codes KEYWORDS Program slice Neural networks Vulnerability detection Vulnerability pinpoint

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Microcomb based silicon photonics data link with 100Gbps/Lane PAM4 transmission

Microcomb based silicon photonics data link with 100Gbps/Lan...

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CLEO: science and Innovations, S and I 2022

作者： Shu, Haowen Shen, Bitao Chang, Lin Tao, Yuansheng Xie, Weiqiang Jin, Ming Netherton, Andrew Zhang, Xuguang Qin, Jun Chen, Ruixuan Yu, Shaohua Wang, Xingjun Bowers, John E. State Key Laboratory of Advanced Optical Communications System and Networks Peking University Beijing100871 China Department of Electrical and Computer Engineering University of California Santa BarbaraCA93106 United States Peng Cheng Laboratory Shenzhen518055 China Frontiers Science Center for Nano-optoelectronics Peking University Beijing100871 China

We achieve 100 Gbps/Lane PAM4 transmission by employing an AlGaAsOI microcomb source and silicon modulators. With 20 parallel wavelength channels utilized at C-band, an aggregate data rate of 2 Tbit/s is achieved. ... 详细信息

ISBN: (纸本)9781557528209

关键词： Gallium compounds

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Meet-in-the-Middle Statistical Fault Analysis of the PRESENT lightweight Cryptosystem

Meet-in-the-Middle Statistical Fault Analysis of the PRESENT...

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作者： Li, Wei Zhu, Xiao-Ming Gu, Da-Wu Li, Jia-Yao Cai, Tian-Pei School of Computer Science and Technology Donghua University Shanghai201620 China Department of Computer and Science and Engineering Shanghai Jiao Tong University Shanghai200240 China Shanghai Key Laboratory of Scalable Computing and System Shanghai200240 China Shanghai Key Laboratory of Integrate Administration Technologies for Information Security Shanghai200240 China

The lightweight block cipher PRESENT was presented at the International Conference on Cryptographic Hardware and Embedded systems (CHES) in 2007, and it has become a standard of ISO/IEC-29192-2 for lightweight cryptosystems since 2012. Within the environment of the Internet of Things, this cipher is applicable to Radio Frequency Identification, network sensors, and smart cards. Its secret key can be either 80 or 128 bits long, while the block is 128 bits long. Since the publication of the PRESENT, numerous forms of cryptanalysis have been developed in order to evaluate its level of security. Some examples of these attacks include the differential attack, the linear attack, the integral attack, the algebraic attack, the fault attack, the side-cube attack, and the Biclique attack. All of these cryptanalyses are on the basis of the assumption that an attack using a chosen plaintext or an attack using a known plaintext would occur. In order to carry out a chosen-plaintext attack, an attacker must have the ciphertexts along with the plaintexts that go along with them, whereas a known-plaintext attack requires a significant quantity of plaintexts and ciphertexts. The ciphertext-only attack is distinct from the chosen-plaintext attack and the known-plaintext attack, which require the ciphertext only in order to be successful. In this sense, the ciphertext-only attack is relevant in a range of scenarios. There is no research that has been released yet regarding PRESENT'S resilience to the ciphertext-only attack. This study presents a novel meet-in-the-middle statistical fault analysis using the approach of statistical analysis and meet-in-the-middle attack of PRESENT. This analysis is able to decrypt the 80-bit and 128-bit secret keys of PRESENT with a series of new distinguishers that include the Pearson correlation coefficient-Hamming weight, the Kullback Leibler divergence- Hamming weight, and the Jaccard similarity coefficient-Hamming weight-maximum likelihood estimatio

关键词： Side channel attack

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Query-guided Prototype Evolution Network for Few-Shot Segmentation

arXiv

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arXiv 2024年

作者： Cong, Runmin Xiong, Hang Chen, Jinpeng Zhang, Wei Huang, Qingming Zhao, Yao Institute of Information Science Beijing Jiaotong University Beijing100044 China School of Control Science and Engineering Shandong University Jinan250061 China Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan250061 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China Department of Computer Science City University of Hong Kong Hong Kong School of Computer Science and Technology University of Chinese Academy of Sciences Beijing101408 China

Previous Few-Shot Segmentation (FSS) approaches exclusively utilize support features for prototype generation, neglecting the specific requirements of the query. To address this, we present the Query-guided Prototype Evolution Network (QPENet), a new method that integrates query features into the generation process of foreground and background prototypes, thereby yielding customized prototypes attuned to specific queries. The evolution of the foreground prototype is accomplished through a support-query-support iterative process involving two new modules: Pseudo-prototype Generation (PPG) and Dual Prototype Evolution (DPE). The PPG module employs support features to create an initial prototype for the preliminary segmentation of the query image, resulting in a pseudo-prototype reflecting the unique needs of the current query. Subsequently, the DPE module performs reverse segmentation on support images using this pseudo-prototype, leading to the generation of evolved prototypes, which can be considered as custom solutions. As for the background prototype, the evolution begins with a global background prototype that represents the generalized features of all training images. We also design a Global Background Cleansing (GBC) module to eliminate potential adverse components mirroring the characteristics of the current foreground class. Experimental results on the PASCAL-5i and COCO-20i datasets attest to the substantial enhancements achieved by QPENet over prevailing state-of-the-art techniques, underscoring the validity of our ideas. © 2024, CC BY-NC-SA.

关键词： Semantic Segmentation

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Low-Latency, Predictable, and High-Precision Networking for Cooperative Vehicle Infrastructure system

SSRN

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SSRN 2022年

作者： Lin, Chi Wu Yu, Chang Wang, Ning Institute of Intelligent System School of Software Dalian University of Technology Dalian China Department of Computer Science and Information Engineering Chung Hua University Hsinchu Taiwan Computer Science & Research Rowan University GlassboroNJ United States

Traditionally, infrastructural architects and road design have independently analyzed respective subsystems' needs in customary transportation. The two's inability to cooperate has culminated in possible safety issues, lousy road congestion, and unnecessary resource utilization. Moreover, challenges concerning sensor arrangement, data collecting, wireless communications, multi-source data fusion, analytical methodologies, and the development of decision-making processes might occur when cooperative vehicle infrastructure systems are used. In recent decades, Cooperative vehicle infrastructure systems(CVIS) have been suggested to assure intelligent transportation's effectiveness, effectiveness, and durability by integrating cars and infrastructures. A cooperative vehicle infrastructure system represents a novel business structure linked to businesses like autos, semiconductors, relevant information, and road infrastructure. Informatics, machine intelligence, telecommunications, data fusion, and intelligent monitoring are all included in this domain. Recent generations of networking technologies are pushing the boundaries of what became achievable utilizing cooperative vehicle infrastructure systems. Especially cooperative vehicle infrastructure systems, such instance, factory automation, Mixed Reality, and Touchscreen Network need ultra-low delay evaluated in single-digit milliseconds and cannot accept any fluctuation. Higher financial literacy requires an increased cloudification of application scenarios that require precise service level requirements for cooperative vehicle infrastructure systems. Almost all of those apps are mission-critical and therefore can risk perhaps a data packet being interrupted. Consequently, emerging applications need network infrastructure capable of delivering high-precision and predictable levels of service and accompanying assurances bordering on predictability. Cooperative vehicle infrastructure systems will require reassessing the f

关键词： Autonomous vehicles

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