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Integrating Structural Information: Comparing Classification-Based and Segmentation-Based Predictors in Bioinformatics (Case Study: Protein-Peptide Region Residue-Level Interaction) Using Structural Information

Integrating Structural Information: Comparing Classification...

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International CSI computer Conference, CSICC

作者： Shima Shafiee Abdolhossein Fathi Faezeh Safari Department of Computer Engineering and Information Technology Razi University Kermanshah Iran Faculty of Eng. Architecture and Info. Tech. School of Electrical Eng. and Computer Science University of Queensland Brisbane QLD Australia

ISBN: (数字)9798331523114

ISBN: (纸本)9798331523121

Understanding the regions where proteins bind to peptides is vital for studying diseases like cancer, as it sheds light on various cellular processes and aids in drug discovery. Although researchers can experimentally investigate protein-peptide interactions at the region level by analyzing the structures of their complexes, only a limited number of these structures are known. Additionally, experiments to determine these interactions can be both costly and time-consuming. Computational methods provide an alternative and complementary approach to experimental techniques. As a result, using computational methods to predict peptide-binding regions can significantly enhance the efficiency and cost-effectiveness of experimental research. To leverage these advantages, this study introduces a new method named Structure-based Prediction of Residue-level Interaction of Peptides (SPRINT-Pep), designed to pinpoint the binding regions between proteins and peptides. This approach leverages two distinct predictive models: a classification-based model combining DeepResNet with a Support Vector Machine (SVM) and a segmentation-based model called DeepU-Net. Our predictions outperform other state-of-the-art methods in terms of F-measures (by at least 23%), precision (by at least 3.7%), and the balance between sensitivity and specificity (by about 7.7%). These findings demonstrate the proficiency of the proposed method.

关键词： Proteins Support vector machines Deep learning Peptides Predictive models Sensitivity and specificity Prediction algorithms Robustness Drug discovery Testing

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A Rapid GBDT-BiLSTM Based Damage Detection Technique in Bridges using Accurate Parameters

A Rapid GBDT-BiLSTM Based Damage Detection Technique in Brid...

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2024 Asian Conference on Intelligent Technologies, ACOIT 2024

作者： Babu, Uppara Raghu Patil, Deepak T. Qasim, Jameela Soni, Mukesh Sharma, Neelam Bhoopathy, V. Srinivasa Ramanujan Institute of Technology Andhra Pradesh Anantapur India Bharati Vidyapeeth College of Architecture University of Mumbai Maharashtra Navi Mumbai India Department of Bridge Engineering School of Civil Engineering Tongji University Shanghai China Department of Research and Development Lovely Professional University Phagwara India Physical Education Department Lovely Professional University Punjab India Department of Computer Science and Engineering Sree Rama Engineering College Tirupathi India

ISBN: (纸本)9798350374933

Conventional methods for diagnosing bridge damage have centred on tracking changes in modal-based Damage Sensitive Features (DSFs), which are strongly related to structural stiffness. Environmental and operational variations, inefficient use of machine learning approaches for damage detection, and an overall reliance on modal-based DSFs are some of the limits and hurdles that the system still faces, despite substantial progress towards practical deployment. According to the proposed method, the initial three steps are data preparation, feature extraction, and model training. In order to identify damage during the preprocessing step, the suggested approach utilises anomaly scores. Features in the time-frequency domain allow for parallel processing of signals in the signal-to-feature extraction pipeline. After the features have been extracted, the data is used to train GBDT-BiLSTM models. The proposed approach achieves better results than the well-known alternatives, GBDT and BiLSTM. © 2024 IEEE.

关键词： Bridges

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Critical assessment of opal mining techniques, tools, market system, environmental impact challenges, and prospects — A systematic review

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Arabian Journal of Geosciences 2025年第6期18卷 1-14页

作者： Adamu, Anteneh Yayeh Eneyew, Demessie Mulu Ejigu, Assamen Ayalew Dubiniewicz, Andrzej Kajetan Endalew, Sisay Awoke Nigussie, Asmare Belay Amognehegn, Asnake Enawgaw School of Civil and Water Resource Engineering & Architecture Kombolcha Institute of Technology Kombolcha Ethiopia Department of Electrical and Computer Engineering Kombolcha Institute of Technology Kombolcha Ethiopia Faculty of Earth Sciences and Spatial Management Nicolaus Copernicus University Torun Poland Department of Chemistry College of Natural Science Wollo University Dessie Ethiopia

The study presents the existing challenges in opal mining in the Delanta area (mining methods, tools, market system, and environmental impact) and provides possible recommendations to overcome these challenges. Literature review, data collection, field survey, and data analysis were used as methods for this study. Environmental impact assessment also applied in the study area. Based on the study, the opal mining system in the Delanta area is performed in traditional ways and this method is not benefiting the local miners as well as the country. In the area, due to roof collapse of mining sites, three to eight artesian small-scale miners are dying each year. Opal quality deterioration (wastes locally called Ajara) because of cracking is the other main challenge in the study area. Moreover, environmental problems such as deforestation, concealed underground channels, landslides, the loss of numerous species’ habitats, annihilation of flora, land degradation, soil erosion and pollution, water pollution, air pollution, downstream sedimentation, and the covering of topsoil on agricultural land, which affects the farming system are the main findings of this study. In the study area, only 3% of the opal is processed, while 97% is rough, and this results in loss of income for the country. Finally, the study indicated the possible solutions in opal exploration and mining methods, as well as market system for the safe and sustainable extraction of Delanta opal resources. The study recommended for future work to design a safe mining method, a ventilation shaft, develop a smartphone app for quality grading and branding for selling, developing a low-cost opal cutting and polishing machine for value addition, and establishing training centers. In addition, the sector in the area also needs solar systems planting for lighting of mining sites, design and development of waste soil removal technology/conveyors and hammers for safe mining, sustainable development and management.

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An Approach for Evaluating the Potential Impact of Anti-Patterns on Microservices Performance

An Approach for Evaluating the Potential Impact of Anti-Patt...

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IEEE International Conference on Software architecture Workshops (ICSAW)

作者： Raghad Matar Jasmin Jahić Department of Architecture-Centric Engineering Fraunhofer Institute for Experimental Software Engineering Kaiserslautern Germany Department of Computer Science and Technology University of Cambridge Cambridge UK

The microservices architectural style has been increasingly adopted in recent years due to its advantageous characteristics. While there exist design patterns for microservices that are theoretically beneficial for ensuring performance (and anti-patterns that should be avoided), they do not always lead to the expected impact. Some designs are solutions for achieving quality properties other than performance, and while they might be categorized as anti-patterns in theory, their influence on system performance can be minimal, depending on the context. Architects find it hard to reason about these trade-offs and the impact that design decisions will have on performance before implementing them. To solve this problem, in this paper, we propose an approach that enables rapid evaluation of high-level architectural models by combining both static and dynamic analysis. The static analysis identifies the design anti-patterns that are known to hinder system performance and guides the architect in reasoning about these design decisions. The approach then generates source code for the system under study based on the architectural design model for a subsequent dynamic analysis to assess whether the statically detected anti-patterns do indeed have a negative effect on the performance of the analyzed system.

关键词： Analytical models Software architecture System performance Source coding Microservice architectures Static analysis Cognition

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Energy-Time Profiling for Machine Learning Methods to EEG Classification 1st

Energy-Time Profiling for Machine Learning Methods to EEG Cl...

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1st International Conference on Bioengineering and Biomedical Signal and Image Processing, BIOMESIP 2021

作者： Gómez-López, Juan Carlos Escobar, Juan José González, Jesús Gil-Montoya, Francisco Ortega, Julio Burmester, Mike Damas, Miguel Department of Computer Architecture and Technology CITIC University of Granada Granada Spain Department of Engineering University of Almería Almería Spain Department of Computer Science Florida State University Tallahassee United States

ISBN: (纸本)9783030881627

The Electroencephalography discipline studies a type of signals called Electroencephalograms (EEGs), which represent the electrical activity of different parts of the brain. EEGs are composed of a massive number of features that could be used to create an intelligent recognition system. Nevertheless, the high number of available features difficult the correct classification of the signals as most of them do not contain relevant information. The use of Feature Selection (FS) techniques allows the reduction of the number of features by extracting a reduced but powerful feature subset. Afterwards, the problem can be addressed by using both the reduced features along with classification methods. In this sense, this work proposes a comparison of five supervised classifiers to solve an Electroencephalography problem in the context of Motor Imagery-based BCI tasks. The predictive models are evaluated in terms of classification rate and performance (execution time and energy consumption), with the idea of determining which alternative offers the best trade-off among all the objectives. © 2021, Springer Nature Switzerland AG.

关键词： Classification (of information)

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Health care data analysis and visualization using interactive data exploration for sportsperson

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Science China(Information Sciences) 2022年第6期65卷 85-97页

作者： Hao LIU Yang ZHANG Ke LIAN Yifei ZHANG Oscar Sanjuán MARTíNEZ Rubén González CRESPO Department of Sport and Exercise Sciences Kunsan National University Department of Naval Architecture and Ocean Engineering Ludong University Computer Science Department School of Engineering and Technology Universidad Internacional de La Rioja

Sports have scored significant attention among the public in this multifaceted world. Diverse training strategies are followed by many athletics and even flexible to adapt comfortable and optimal techniques. This fact has led physicians and educators to encourage remote health surveillance as one of the core strategies in athletic training. The need for innovative data exploration methodologies capable of facing Big Data's influence to make remote monitoring services viable has been raised by the growing ties of networks that deliver high quantities of real-time data. This paper presents an interactive healthcare data exploration and visualization(IHDEV) model to enhance multi-scaling data analysis and visualization in the athletic health vision platform. This paper aims to simplify optimization methods to measure sportsperson muscle tension. This model illustrates a three-layer architecture with a raw data acquisition layer, data analysis layer, and visualization layer. The first layer considers the acquisition of health-related data from the athletes for remote monitoring using IoT and stores it into the cloud. The data analysis layer adapts artificial intelligence(AI) in data mining. The final layer introduces an intelligent interactive data visualization model assisted by a reactive workflow mechanism, enabling analysis and visualization solutions to be composed in a personalized data flow appropriate to the athletic training. This experimental study extended with two healthcare datasets to show the feasibility of IHDEV in promoting healthcare based athletic monitoring and improves the accuracy ratio of 96.7%, prediction ratio of 96.2%, an efficiency ratio of 96.8%, Pearson correlation coefficient of 98.2%, and reduces the error rate of 18.7% compared to other conventional models.

关键词： artificial intelligence health monitoring data visualization data analysis athletics

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IoT Based Systems and Services: Recent Security Concerns and Feasible Solutions

IoT Based Systems and Services: Recent Security Concerns and...

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Humanitarian technology Conference (KHI-HTC), IEEE Karachi Section

作者： Hafiz Muhammad Attaullah Shahzad Memon Ozlem Feyza Erkan Ruba Khawar Department of Computer Science Mohammad Ali Jinnah University Karachi Pakistan Department of Computer Engineering Faculty of Engineering and Architecture Beykoz University Istanbul Türkiye Faculty of Information Sciences and Humanities NED University of Engineering and Technology Karachi Pakistan

The term Internet of Things (IoT) is used to refer as embedded devices or objects with internet access, allowing them to communicate globally, interacting with people and networks. IoT security issues are directly related to the widespread use of its systems. This paper examines the security technologies employed in IoT and their respective features and applications. Additionally, it addresses the various security concerns associated with IoT-based systems and services, highlighting their occurrence within the three-layer framework of IoT. These days, as IoT introduces advanced application architectures that minimizes human intervention by integrating businesses in some way to address digital computer processes by communicating within a given network. Moreover, it will be discussed the key technologies associated with Advanced Encryption Standards (AES) and the changes brought in market value and usage of services that has been taken place b since the IoT incorporated.

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Empower Hub: Sustainable Innovative Navigation and Smart Interior Design

Empower Hub: Sustainable Innovative Navigation and Smart Int...

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International Conference on Sustainable Mobility Applications, Renewables and technology (SMART)

作者： Manoon Nasri Abdalla Mohammed Al Falasi Haythem El-Messiry School of Architecture and Interior Design Canadian university Dubai School of Engineering Applied science and Technology Canadian university Dubai Department of Computer Science Canadian University Dubai

ISBN: (数字)9798331532925

ISBN: (纸本)9798331532932

This paper will conclude the integration between smart interior design and Artificial Intelligence including sustainability within design principles and functions. Presenting “Empower hub” a center that is specifically devoted to people with physical disabilities that concludes AI in the infrastructure. Using sustainable materials and energy-efficient lighting are the objectives. This can include solar power smart systems and adaptive technology, which greatly assist people with various types of impairments, and it is not adequately integrated in many sectors. The design focus is to address the special needs of people with visual, auditory, or mobility impairments, utilize state-of-the-art adaptive technology. Therefore, navigation assistance and motion detection systems are being proposed for the center. The smart prototypes will process data and sensors that will detect movements for smooth access. In addition to proximity sensors that can be vocal to ensure audio assistance. Most of those sensors will be powered by solar energy to ensure the sustainable factor of the project in addition to reducing energy consumption. Overall, the research will conclude the integration of AI and interior design while applying sustainable design principles in interior design with the integration of machine learning to benefit people of determination in order of accessibility and function to allow them to give back to society by giving them easy access to ensure their safety and wellbeing.

关键词： Visualization Renewable energy sources Navigation Prototypes Solar energy Smart systems Motion detection Safety Sustainable development Intelligent sensors

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Calibration and Performance Evaluation of a Superconducting Quantum Processor in an HPC Center

Calibration and Performance Evaluation of a Superconducting ...

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ISC High Performance 2024 Research Paper Proceedings (39th International Conference)

作者： Xiaolong Deng Stefan Pogorzalek Florian Vigneau Ping Yang Martin Schulz Laura Schulz QCT Department Leibniz Supercomputing Centre Garching Germany Technology Department IQM Quantum Computers Munich Germany Chair of Computer Architecture and Parallel Systems Technical University of Munich Munich Germany

As quantum computers mature, they migrate from laboratory environments to HPC centers. This movement enables large-scale deployments, greater access to the technology, and deep integration into HPC in the form of quantum acceleration. In laboratory environments, specialists directly control the systems' environments and operations at any time with hands-on access, while HPC centers require remote and autonomous operations with minimal physical contact. The requirement for automation of the calibration process needed by all current quantum systems relies on maximizing their coherence times and fidelities and, with that, their best performance. It is, therefore, of great significance to establish a standardized and automatic calibration process alongside unified evaluation standards for quantum computing performance to evaluate the success of the calibration and operation of the system. In this work, we characterize our in-house superconducting quantum computer, establish an automatic calibration process, and evaluate its performance through quantum volume and an application-specific algorithm. We also analyze readout errors and improve the readout fidelity, leaning on error mitigation.

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Investigating human-robot cooperation in a hospital environment: Scrutinising visions and actual realisation of mobile robots in service work 21

Investigating human-robot cooperation in a hospital environm...

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2021 ACM Designing Interactive Systems Conference: Nowhere and Everywhere, DIS 2021

作者： Tornbjerg, Kristina Kanstrup, Anne Marie Skov, Mikael B. Rehm, Matthias Department of Planning Aalborg University Denmark Department of Computer Science Aalborg University Denmark Department of Architecture Design and Media Technology Aalborg University Denmark

ISBN: (纸本)9781450384766

This study analysed work activity in a hospital basement where humans and robots interacted and cooperated on logistics tasks. The robots were deployed to automate parts of courier processes and improve the work environment for the hospital's kitchen staff. Human-robot cooperation was studied through ethnographic fieldwork relating to mobile service robots and hospital kitchen staff. The results highlighted problems arising through the assumption that the gplug and play' service robots could effectively automate work tasks. The analysis revealed the complexity of human-robot interaction in dynamic work settings such as hospitals and identified contradictions between the envisioning and realisation of robots at work, as well as the visible and invisible procedures underpinning human-robot cooperation. Consequently, we emphasise the importance of considering robots as agents of change and draw attention to the new work practices that arise when robots assume the roles of workers in dynamic work settings. © 2021 Owner/Author.

关键词： Hospitals

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