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Articles 331 - 360 of 27030
Full-Text Articles in Entire DC Network
Wood-Plastic Composites Integration For Triboelectric Nanogenerator Electricity Generation, Hanbyeol Park, Razamala Yashna F. Dimaporo, Sophia Maureen A. Emperado, Anton Jefferson L. Pangilinan, Juan Carlo T. Gumangan
Wood-Plastic Composites Integration For Triboelectric Nanogenerator Electricity Generation, Hanbyeol Park, Razamala Yashna F. Dimaporo, Sophia Maureen A. Emperado, Anton Jefferson L. Pangilinan, Juan Carlo T. Gumangan
Sinaya: A Philippine Journal for Senior High School Teachers and Students
Access to electricity in underdeveloped communities is particularly crucial in improving the living standards of people and alleviating poverty by promoting sustainable development. This study deals with the exploration of incorporating wood-plastic composite (WPC) – specifically wood pulp (W) and high-density polyethylene (H) – into triboelectric nanogenerator (TENG) flooring system to convert mechanical energy to electrical energy, promoting sustainable energy, reducing greenhouse gas emissions, improving the quality of life, and serving as feasible flooring tiles. Two types of TENG tiles were prepared by using different WPC ratios: 30W:70H and 70W:30H. A static bending test was conducted to assess the flexural …
Self-Agency As A Strategy In Emergency Remote Learning Among Filipino Grade 10 Students, John Cris C. Tababa, Paul Andrei C. Apo, Golden Grace R. Gammaru, Audrey S. Manaay, Kathrin Anne N. Nadua, James Fhonzy Angelo S. Fontillo
Self-Agency As A Strategy In Emergency Remote Learning Among Filipino Grade 10 Students, John Cris C. Tababa, Paul Andrei C. Apo, Golden Grace R. Gammaru, Audrey S. Manaay, Kathrin Anne N. Nadua, James Fhonzy Angelo S. Fontillo
Sinaya: A Philippine Journal for Senior High School Teachers and Students
The Coronavirus disease 2019 pandemic significantly influences students' educational attainment as they actively find and rationalize knowledge obtained from emergency remote learning. As a response, the agency or the ability to regulate one’s learning provides the students with the ability to believe in themselves. Still, it also necessitates the deliberate consideration to create a plan of action and modify it as required to achieve one's objectives. This study obtained knowledge from emergency remote learning (ERL) experiences of Filipino Grade 10 Students in their Social Studies class. The researchers employed a phenomenological approach to understand the self-agency practices of Grade 10 …
November 2024 Berkeley Pit Migratory Waterfowl Protection Monthly Report, Mark Thompson, Loren Burmeister
November 2024 Berkeley Pit Migratory Waterfowl Protection Monthly Report, Mark Thompson, Loren Burmeister
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Exploring Student Engagement In A Blended And Gamified Statistics And Probability: Designed With Learning Styles And Player Types, Reymund R. Gonowon
Exploring Student Engagement In A Blended And Gamified Statistics And Probability: Designed With Learning Styles And Player Types, Reymund R. Gonowon
Sinaya: A Philippine Journal for Senior High School Teachers and Students
Educators are called to contribute towards achieving SDG 4: Quality Education. A major determinant in achieving this goal is providing learners with essential skills such as analyzing and interpreting data, making inferences, and driving evidence-based decisions which are the expected competencies in Statistics and Probability (STATPRO), one of the core subjects of the senior high school curriculum in the Philippines. To progress towards SDG 4, achieving the learning competencies of STATPRO is vital, however engaging students in a blended learning environment may be challenging. This study aims to explore the behavioral engagement of students in a gamified STATPRO class through …
Optimal Operation Scheduling Of Integrated Energy System Considering Energy Priority, Dongli Jia, Keyan Liu, Zhaoying Ren, Zezhou Wang, Dongsheng Tang
Optimal Operation Scheduling Of Integrated Energy System Considering Energy Priority, Dongli Jia, Keyan Liu, Zhaoying Ren, Zezhou Wang, Dongsheng Tang
Journal of System Simulation
Abstract: Integrated with the actual situation of power grid and the growth of new energy, a multiobjective model for optimal scheduling of the integrated energy system(IES) is established based on the analysis of the energy-flow relationship of the IES and taking into account the priority of energy utilization and the load demand response in terms of the mismatch between the distributed energy sources and the loads, the net benefit of the unit cost of the IES, and the load response degree. Combined with the equipment and the environmental benefits system, a priority constraint for energy utilization has been established for …
Research On Scheduling Strategies Simulation For Building Air-Conditioning Systems Based On Transfer Imitation Learning, Qiaochu Wang, Yan Ding, Chuanzhi Liang, Haozheng Zhang, Chen Huang
Research On Scheduling Strategies Simulation For Building Air-Conditioning Systems Based On Transfer Imitation Learning, Qiaochu Wang, Yan Ding, Chuanzhi Liang, Haozheng Zhang, Chen Huang
Journal of System Simulation
Abstract: To solve the problem of unstable performance and inefficient training process of low-quality data conditions at the initial stage of online deployment of air conditioner scheduling, we propose a migration-imitation learning-based air conditioning scheduling strategy simulation method. Reinforcement learning methods are used to generate building operation strategies. A standard building simulation model serves as the source domain, upon which migration learning is applied. An imitation learning loss function is incorporated into the intelligent loss function to enhance algorithm performance. The results indicate that, compared with the non-use of migration learning, the proposed method can improve the operational efficiency by …
Behavioral Modeling Of Manned-Unmanned Cooperative Air Combat Based On Improved Abc Algorithm, Peng Wang, Haoyu Liu, Ni Li, Zexi Yu, Shangjie Jia
Behavioral Modeling Of Manned-Unmanned Cooperative Air Combat Based On Improved Abc Algorithm, Peng Wang, Haoyu Liu, Ni Li, Zexi Yu, Shangjie Jia
Journal of System Simulation
Abstract: To solve the problem of difficulty in establishing collaborative behavior models and weak adversarial capabilities in typical MAV/UAV air combat scenarios, a mixed decision based MAV/UAV behavior modeling framework is proposed. Using collaborative rule sets, rule subsets, tactical action sets, and other tools, a hierarchical decision collaborative behavior model supporting five types of collaborative tactics, including grinding tactics and unilateral flanking tactics, is constructed in this framework. a behavior model parameter optimization method based on an improved artificial bee colony (ABC) algorithm is proposed. By using the Mason rotation method to initialize the population, a better initial honey source …
Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Final Bpsou Insufficiently Reclaimed Sites Belle Of Butte (Bres No. 8 & Ur-39) Remedial Action Work Plan (Rawp) Request For Change Ir-2024-Ra-02 (Dated December 19, 2024), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Contents Volume 52 No. 4, ศูนย์นวัตกรรมทางการศึกษา สื่อสิ่งพิมพ์ และสื่อออนไลน์ จุฬาฯ
Contents Volume 52 No. 4, ศูนย์นวัตกรรมทางการศึกษา สื่อสิ่งพิมพ์ และสื่อออนไลน์ จุฬาฯ
Journal of Education Studies
No abstract provided.
Effects Of Active Learning In Physics Experiments On Academic Achievement, Attitudes And Concepts Among Grade-11 Students, Kittikhun Seawsakul
Effects Of Active Learning In Physics Experiments On Academic Achievement, Attitudes And Concepts Among Grade-11 Students, Kittikhun Seawsakul
Journal of Education Studies
One of the problems in learning physics is students’ attitudes. Most students think that physics is difficult to learn and to understand. This causes students' motivation and attitudes of curiosity towards the physics subject to decrease. The objectives of this work were to investigate students' attitudes towards physics and physics concepts, as well as to compare the academic achievement of the sample group before and after studying the lessons based on active learning through physics experiments. The sample group in this study consisted of 31 Grade 11 students, and data collection was conducted over the course of one semester. Data …
Effects Of Organizing Mathematics Learning Activity Using Ill-Structured Problem Solving Process And Scaffolding Strategy On Mathematical Reasoning Ability And Attitude Towards Mathematics Of Ninth Grade Students, Apisara Chanhom, Jongkol Thamsuan
Effects Of Organizing Mathematics Learning Activity Using Ill-Structured Problem Solving Process And Scaffolding Strategy On Mathematical Reasoning Ability And Attitude Towards Mathematics Of Ninth Grade Students, Apisara Chanhom, Jongkol Thamsuan
Journal of Education Studies
The purposes of this research were 1) to compare the mathematical reasoning ability of students before and after engaging in organized mathematics learning activities using an ill-structured problem-solving process combined with scaffolding, and 2) to compare the attitudes towards mathematics of students before and after participating in organized mathematics learning activities using an ill-structured problem solving process combined with scaffolding. The sample group consisted of 30 ninth grade students under the Secondary Educational Service Area Office Bangkok 2, selected through purposive sampling. The tools used for the experiment included mathematics lesson plans using the ill-structured problem-solving process combined with scaffolding. …
Privacy Protection In Machine Learning Via Exploitation Of Constrained Adversarial Evasion, Brian Testa
Privacy Protection In Machine Learning Via Exploitation Of Constrained Adversarial Evasion, Brian Testa
Dissertations - ALL
Deep neural networks are extensively applied to real-world tasks. In many cases, the data feeding these tasks are human generated content, which emphasizes the criticality of privacy and data protection. The diverse modalities of this user data provide fertile ground for 3rd parties to monetize a user’s data. This work considers two such modalities: user speech when interacting with smart speaker voice assistants (VAs) and images shared with online service providers. In these cases, the user would like to support some form of machine learning (ML) inference without allowing others. A user interacting with a smart speaker would like the …
Elementary Science Instruction: A Document Analysis Of Teacher Messaging Across Two Sets Of Curriculum Materials, Jessica Mary Whisher-Hehl
Elementary Science Instruction: A Document Analysis Of Teacher Messaging Across Two Sets Of Curriculum Materials, Jessica Mary Whisher-Hehl
Dissertations - ALL
Elementary teachers are tasked with teaching multiple subjects within an instructional day. One mechanism to support this task is through strong curriculum materials, which lay out a course of instruction aligned with instructional standards. This is helpful when teachers are trying to teach to a new set of standards, such as the Next Generation Science Standards, which require a significant shift in instructional strategies. In cases such as this, educative features embedded in the curriculum materials can assist teachers in making the required shifts in instruction. However, sometimes the instructional time required by curriculum materials, especially in elementary science, is …
Mathematical Multi-Compartment Modeling Of Chronic Lymphocytic Leukemia Cell Kinetics Under Ibrutinib, Melanie Schulz, Sanne Bleser, Manouk Groels, Dragan Bošnački, Jan A Burger, Nicholas Chiorazzi, Carsten Marr
Mathematical Multi-Compartment Modeling Of Chronic Lymphocytic Leukemia Cell Kinetics Under Ibrutinib, Melanie Schulz, Sanne Bleser, Manouk Groels, Dragan Bošnački, Jan A Burger, Nicholas Chiorazzi, Carsten Marr
Faculty, Staff and Student Publications
The Bruton tyrosine kinase inhibitor ibrutinib is an effective treatment for patients with chronic lymphocytic leukemia (CLL). While it rapidly reduces lymph node and spleen size, it initially increases the number of lymphocytes in the blood due to cell redistribution. A previously published mathematical model described and quantified those cell kinetics. Here, we propose an alternative mechanistic model that outperforms the previous model in 26 of 29 patients. Our model introduces constant subcompartments for healthy lymphocytes and benign tissue and treats spleen and lymph nodes as separate compartments. This three-compartment model (comprising blood, spleen, and lymph nodes) performed significantly better …
Harmonic Impedance Modeling And Oscillation Analysis Of Modular Multilevel Converter, Yuhong Wang, Wensheng Chen, Shilin Gao, Jianquan Liao, Yangfan Cheng
Harmonic Impedance Modeling And Oscillation Analysis Of Modular Multilevel Converter, Yuhong Wang, Wensheng Chen, Shilin Gao, Jianquan Liao, Yangfan Cheng
Journal of System Simulation
Abstract: To facilitate rapid analysis of the oscillation stability mechanism in modular multilevel converter-based high voltage direct current (MMC-HVDC) systems and streamline the simulation process for determining MMC impedance characteristics, a simplified mathematical simulation model for MMC closed-loop impedance is developed using the harmonic state space method. This model considers various control strategies and includes both AC-side and DC-side impedance models. By applying a Nyquist criterion-based impedance analysis method, the stability mechanisms on the AC and DC sides of the MMC are examined. In addition, a data-driven oscillation stability analysis method is also proposed, leveraging a global sensitivity algorithm based …
Path Planning Of Desert Robot Based On Deep Reinforcement Learning, Ming Li, Wangzhong Ye, Jiehua Yan
Path Planning Of Desert Robot Based On Deep Reinforcement Learning, Ming Li, Wangzhong Ye, Jiehua Yan
Journal of System Simulation
Abstract: Due to the complexity and variability of the desert environment, the key to the high-efficient of mobile robot is how to avoid obstacles and plan its path. To solve the problems of poor search efficiency and slow convergence of deep reinforcement learning algorithm in complex environment, an improved deep reinforcement learning path planning algorithm is proposed. The exploration factor is improved and dynamically adjusted according to the convergence degree of the algorithm, so that the exploration factor dynamically decreases with the increase of the understanding degree of the agent to the environment, thus speeding up the convergence speed of …
Development Of Computational Imaging Pipelines To Advance Quantitative Co-Clinical Imaging And Pathology, Kaushik Dutta
Development Of Computational Imaging Pipelines To Advance Quantitative Co-Clinical Imaging And Pathology, Kaushik Dutta
McKelvey School of Engineering Graduate Student Theses & Dissertations
Deep learning driven computational methods have profoundly impacted medical imaging by advancing feature extraction, and by establishing a critical foundation for downstream image analysis and interpretation. Co-clinical trials are an emerging area of investigation in which a clinical trial is coupled with a corresponding preclinical study to inform the corresponding clinical trial to enhance translational accuracy and therapeutic development. Within this framework, quantitative imaging and pathology plays a fundamental role in both clinical and preclinical arms of co-clinical trials. Quantitative imaging enables enabling identification and validation of imaging biomarkers which are leveraged to predict therapeutic response, characterize disease phenotypes, and …
Discrete Element Method For Mining Industrial Applications: Solving The Clumping Problem Caused By Bulk Cohesive Particles In An Iron Ore Beneficiation Process, Shuang Liu
McKelvey School of Engineering Graduate Student Theses & Dissertations
The discrete element method (DEM) is a widely used numerical approach for simulating and analyzing the behavior of granular materials in various applications. This research focuses on the iron ore beneficiation process, addressing the clumping issue in cohesive iron ores from existing crushing processes through a novel double-layered disperser design. The significance of this study lies in its potential to enhance the efficiency of the existing crushing phase and improve the linkage to subsequent purification stages that target smaller-sized iron ore pellets, thereby enhancing the overall efficiency of the ore beneficiation process and achieving significant energy savings. This research adopts …
Investigating Catalytic Conversion Of Lignin To Valuable Products, Jialiang Zhang
Investigating Catalytic Conversion Of Lignin To Valuable Products, Jialiang Zhang
McKelvey School of Engineering Graduate Student Theses & Dissertations
Lignin is a complex, random, and heterogeneous biopolymer in lignocellulosic biomass. It has significant potential for conversion into valuable chemicals and fuels. However, its natural recalcitrant structure has made selective depolymerization challenging. This dissertation presents a detailed investigation into the mechanisms of lignin disassembly and structural evolution under various catalytic and solvent conditions. The research spans three key studies. In Chapter 2, operando magic-angle spinning (MAS) solid-state nuclear magnetic resonance (NMR) spectroscopy was employed to study reaction pathways and kinetics of lignin model polymers during catalytic hydrogenolysis. We used a Ni-Al2O3 catalyst in methanol under high temperature and pressure, and …
Multimodal Representation Learning Frameworks For Modeling Progression And Heterogeneity In Alzheimer’S Disease, Sayantan Kumar
Multimodal Representation Learning Frameworks For Modeling Progression And Heterogeneity In Alzheimer’S Disease, Sayantan Kumar
McKelvey School of Engineering Graduate Student Theses & Dissertations
Alzheimer’s Disease (AD) is the leading cause of dementia, characterised by cognitive and functional impairments that disrupt daily activities. Different clinical modalities such as neuroimaging biomarkers, cognitive assessments, fluid biomarkers and genetic data provide unique and complementary information, contributing to a more comprehensive understanding of disease progression and heterogeneity in disease characteristics. With recent advancements in computational capabilities, particularly in deep learning, multimodal representation learning frameworks aim to integrate diverse clinical modalities into a cohesive framework, capturing the most significant patterns within each modality. Existing data-driven multimodal representation learning frameworks in AD research have two major limitations. First, AD progresses …
Integrating Physics And Deep Learning For Transmission-Less Attenuation Compensation In Clinical Spect, Zitong Yu
McKelvey School of Engineering Graduate Student Theses & Dissertations
Attenuation compensation (AC) is beneficial for visual interpretation and serves as a prerequisite for quantification tasks in single-photon emission computed tomography (SPECT) imaging. However, conventional AC methods typically rely on a separate X-ray CT component, leading to multiple challenges. In this context, studies have shown that scatter-window projection data contains information to estimate the attenuation distribution. Furthermore, large amounts of SPECT emission data in both photopeak and scatter-energy windows and corresponding CT scans are available. The ability of deep learning (DL) to model complex relationships by leveraging large datasets motivates its use for transmission-less AC in SPECT. Building upon the …
Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor
Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor
McKelvey School of Engineering Graduate Student Theses & Dissertations
Cyber-physical systems (CPS), including autonomous vehicles, drones, and mobile robots, rely on intricate sensors, actuators, and machine learning algorithms to perceive the physical world and execute actions within their surroundings. In the context of vision-driven CPS, achieving this demands processing a substantial volume of visual data captured by on-board cameras. The data is subsequently channeled through digital processors and harnessed by deep neural networks for tasks such as image classification, object detection, and depth perception. This data-centric, machine-vision-infused CPS fosters intelligent decision-making, thereby enhancing overall system performance. Trustworthiness, encompassing the robustness of the entire machine-vision pipeline, and system-level efficiency are …
Discrete Element Method For Mining Industrial Applications: Solving The Clumping Problem Caused By Bulk Cohesive Particles In An Iron Ore Beneficiation Process, Shuang Liu
McKelvey School of Engineering Graduate Student Theses & Dissertations
The discrete element method (DEM) is a widely used numerical approach for simulating and analyzing the behavior of granular materials in various applications. This research focuses on the iron ore beneficiation process, addressing the clumping issue in cohesive iron ores from existing crushing processes through a novel double-layered disperser design. The significance of this study lies in its potential to enhance the efficiency of the existing crushing phase and improve the linkage to subsequent purification stages that target smaller-sized iron ore pellets, thereby enhancing the overall efficiency of the ore beneficiation process and achieving significant energy savings. This research adopts …
Integrating Physics And Deep Learning For Transmission-Less Attenuation Compensation In Clinical Spect, Zitong Yu
McKelvey School of Engineering Graduate Student Theses & Dissertations
Attenuation compensation (AC) is beneficial for visual interpretation and serves as a prerequisite for quantification tasks in single-photon emission computed tomography (SPECT) imaging. However, conventional AC methods typically rely on a separate X-ray CT component, leading to multiple challenges. In this context, studies have shown that scatter-window projection data contains information to estimate the attenuation distribution. Furthermore, large amounts of SPECT emission data in both photopeak and scatter-energy windows and corresponding CT scans are available. The ability of deep learning (DL) to model complex relationships by leveraging large datasets motivates its use for transmission-less AC in SPECT. Building upon the …
Investigating Catalytic Conversion Of Lignin To Valuable Products, Jialiang Zhang
Investigating Catalytic Conversion Of Lignin To Valuable Products, Jialiang Zhang
McKelvey School of Engineering Graduate Student Theses & Dissertations
Lignin is a complex, random, and heterogeneous biopolymer in lignocellulosic biomass. It has significant potential for conversion into valuable chemicals and fuels. However, its natural recalcitrant structure has made selective depolymerization challenging. This dissertation presents a detailed investigation into the mechanisms of lignin disassembly and structural evolution under various catalytic and solvent conditions. The research spans three key studies. In Chapter 2, operando magic-angle spinning (MAS) solid-state nuclear magnetic resonance (NMR) spectroscopy was employed to study reaction pathways and kinetics of lignin model polymers during catalytic hydrogenolysis. We used a Ni-Al2O3 catalyst in methanol under high temperature and pressure, and …
Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor
Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor
McKelvey School of Engineering Graduate Student Theses & Dissertations
Cyber-physical systems (CPS), including autonomous vehicles, drones, and mobile robots, rely on intricate sensors, actuators, and machine learning algorithms to perceive the physical world and execute actions within their surroundings. In the context of vision-driven CPS, achieving this demands processing a substantial volume of visual data captured by on-board cameras. The data is subsequently channeled through digital processors and harnessed by deep neural networks for tasks such as image classification, object detection, and depth perception. This data-centric, machine-vision-infused CPS fosters intelligent decision-making, thereby enhancing overall system performance. Trustworthiness, encompassing the robustness of the entire machine-vision pipeline, and system-level efficiency are …
A Confidence-Based Knowledge Integration Framework For Cross-Domain Table Question Answering, Yuankai Fan, Tonghui Ren, Can Huang, Beini Zheng, Yinan Jing, Zhenying He, Jinbao Li, Jianxin Li
A Confidence-Based Knowledge Integration Framework For Cross-Domain Table Question Answering, Yuankai Fan, Tonghui Ren, Can Huang, Beini Zheng, Yinan Jing, Zhenying He, Jinbao Li, Jianxin Li
Research outputs 2022 to 2026
Recent advancements in TableQA leverage sequence-to-sequence (Seq2seq) deep learning models to accurately respond to natural language queries. These models achieve this by converting the queries into SQL queries, using information drawn from one or more tables. However, Seq2seq models often produce uncertain (low-confidence) predictions when distributing probability mass across multiple outputs during a decoding step, frequently yielding translation errors. To tackle this problem, we present CKIF, a confidence-based knowledge integration framework that uses a two-stage deep-learning-based ranking technique to mitigate the low-confidence problem commonly associated with Seq2seq models for TableQA. The core idea of CKIF is to introduce a flexible …
Scientifically Improving Human-Nature Relationship In Desertification Areas, Bojie Fu, Yanxu Liu, Shuai Wang, Junfeng Song, Zejiang Li
Scientifically Improving Human-Nature Relationship In Desertification Areas, Bojie Fu, Yanxu Liu, Shuai Wang, Junfeng Song, Zejiang Li
Bulletin of Chinese Academy of Sciences (Chinese Version)
The expansion trend of desertification in China has been fundamentally restrained. In the new era, scientifically improving the relationship between human and nature in desertification areas to promote regional sustainable development has become an important demand for desertification combat in China. We summarize four key challenges to sustainable development in desertification areas, including increasing human demand on water, increasing land use intensity, increasing climatic risk, and insufficient industrial innovation. Based on the theoretical understanding of the coupling relationship between human and nature, the evolution of human-nature relationship in combating desertification can be divided into four stages, namely, extensive land exploitation, …
Action Logic And Agenda Game Of Global Methane Emission Control And China’S Countermeasures, Bo Zhang, Jinling Guo, Bing Zhong, Junlian Gao, Guosheng Zhang, He Liu
Action Logic And Agenda Game Of Global Methane Emission Control And China’S Countermeasures, Bo Zhang, Jinling Guo, Bing Zhong, Junlian Gao, Guosheng Zhang, He Liu
Bulletin of Chinese Academy of Sciences (Chinese Version)
Originated from the global response to climate change, methane emission control has evolved into a focus of international climate negotiations in recent years. At present, the agenda for controlling methane emission in global climate governance is basically taking shape, but in the process of shifting from scientific consensus to political consensus, the content of the topic and the focus of the game continue to evolve. To carry out global action, it is necessary to address issues such as the allocation of responsibilities, international rules, climate investment and financing, and risk prevention, as well as the basic capacity guarantees behind them. …
Architecture And Key Technologies Of New Research Informatization Infrastructure Platform Under The Fifth Research Paradigm, Fangyu Liao, Yang Wang, Rongqiang Cao, Bo Zhang, Zhenyu Li, Huajin Wang, Xin Chen, Dong Li, Yangang Wang, Xin Wei
Architecture And Key Technologies Of New Research Informatization Infrastructure Platform Under The Fifth Research Paradigm, Fangyu Liao, Yang Wang, Rongqiang Cao, Bo Zhang, Zhenyu Li, Huajin Wang, Xin Chen, Dong Li, Yangang Wang, Xin Wei
Bulletin of Chinese Academy of Sciences (Chinese Version)
The basic platform of research informatization is an indispensable pedestal for modern scientific research and an important manifestation of national scientific and technological innovation capability. As the research paradigm continues to evolve, the architecture and technologies of research informatization infrastructure platform are bound to evolve as well. The new research paradigm brings unique demands and challenges to the algorithmic computility, network transmission capacity, and data storage and management. Consequently, it is an urgent requirement for research informatization infrastructure platform to make technological breakthroughs in the areas of intelligent computility, large-scale data storage and high throughput read/write, cross-network software and hardware …