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Big Life-Science: Study Of Omics From Microscopic To Mesoscopic Scales, Jiarui Wu May 2024

Big Life-Science: Study Of Omics From Microscopic To Mesoscopic Scales, Jiarui Wu

Bulletin of Chinese Academy of Sciences (Chinese Version)

The human genome project at the turn of the century opened a new era of life science research and formed various omics characterized by holistic high-throughput research. The initial omics research was mainly carried out at the molecular level, such as genomics, transcriptomics, proteomics, etc., showing a new paradigm of data-driven research. With the development of research technologies, the omics research has risen to the mesoscopic level, the representative is the “Human Cell Atlas” project launched in 2017. At present, researchers have been able to carry out omics research at the level of tissues, organs, and even individuals, and resulted …

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Progress And Challenges Of Sustainable Development Goals (Sdgs) In The World And In China, Bojie Fu, Junze Zhang May 2024

Progress And Challenges Of Sustainable Development Goals (Sdgs) In The World And In China, Bojie Fu, Junze Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Achieving the 17 Sustainable Development Goals (SDGs) adopted by United Nations is a critical task for countries around the world from 2016 to 2030. Yet, recent assessments indicate that progress on half of the SDGs has stagnated or even regressed, and that most goals are unlikely to be met by 2030. This study reviews the progress globally and in China towards achieving the 17 SDGs, and summarizes five key challenges that are impinging their realization: 1) the data gaps and insufficient monitoring capacity, 2) the high complexity of interlinkages among the SDGs, 3) the influence of regional disparities and negative …

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New Frontier In Race For Deep Space Exploration: Lunar Water Resources, Yong Wei, Honglei Lin, Fei He, Hui Zhang May 2024

New Frontier In Race For Deep Space Exploration: Lunar Water Resources, Yong Wei, Honglei Lin, Fei He, Hui Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Deep space exploration has become the commanding heights of science and technology competition. Since the beginning of the 21st century, China has successfully completed the lunar exploration missions of “orbiting, landing, and returning” in just twenty years, and upgraded to a new roadmap of “survey, construction, and utilization”. Meanwhile, lunar exploration worldwide has shown a trend towards normalization and commercialization. The research on lunar water resources has sparked widespread interest and intense competition among countries and space agencies, marking a new focus in human’s deep space exploration. The exploration of lunar water can help reveal crucial processes in the formation …

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Multiple Input System Of Disruptive Technologies, Mimi Zhan, Xianke Peng, Xiaoyang Cao, Xiaomian Hu May 2024

Multiple Input System Of Disruptive Technologies, Mimi Zhan, Xianke Peng, Xiaoyang Cao, Xiaomian Hu

Bulletin of Chinese Academy of Sciences (Chinese Version)

As the great power to drive human society’s development and the industrial transformation, disruptive technologies have attracted the attention of countries around the world. The major economies worldwide have made relevant strategic plans to develop disruptive technologies for preempting the zenith of technological innovation. As the effective approach to gather various resources, the multiple input system of disruptive technologies has become a place of strategic importance and related studies have also been paid more and more attention. The multiple input system of disruptive technologies is investigated firstly from the perspective of innovation mechanism in this study. Based on the innovation …

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Advances In Data-Driven Life Sciences Research, Haiping Jiang, Chunchun Gao, Wenhao Liu, Yungui Yang, Xin Li May 2024

Advances In Data-Driven Life Sciences Research, Haiping Jiang, Chunchun Gao, Wenhao Liu, Yungui Yang, Xin Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

The field of life sciences is rapidly evolving, driven by advancements in experimental techniques and vast biological big data which gradually arise and play an increasingly important role in life science research. First of all, biological big data has diversity and complexity, including genomic data, epigenomic data, proteomic data and other types. These data provide researchers with more comprehensive information and help reveal the laws behind life phenomena. Second, new data-driven developments and applications in life sciences cover many fields such as gene editing, precision medicine, drug development, etc., providing unprecedented possibilities for human health and quality of life. However, …

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Deep Clustering Of Tabular Data By Weighted Gaussian Distribution Learning, Shourav B. Rabbani, Ivan V. Medri, Manar D. Samad May 2024

Deep Clustering Of Tabular Data By Weighted Gaussian Distribution Learning, Shourav B. Rabbani, Ivan V. Medri, Manar D. Samad

Computer Science Faculty Research

Deep learning methods are primarily proposed for supervised learning of images or text with limited applications to clustering problems. In contrast, tabular data with heterogeneous features pose unique challenges in representation learning, where deep learning has yet to replace traditional machine learning. This paper addresses these challenges in developing one of the first deep clustering methods for tabular data: Gaussian Cluster Embedding in Autoencoder Latent Space (G-CEALS). G-CEALS is an unsupervised deep clustering framework for learning the parameters of multivariate Gaussian cluster distributions by iteratively updating individual cluster weights. The G-CEALS method presents average rank orderings of 2.9(1.7) and 2.8(1.7) …

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Perspective—Surface-Display Techniques In Electrochemical Biosensor Designs For Health Monitoring, Courtney J. Weber, Megan D. Whisonant, Olivia M. Clay, Olja Simoska May 2024

Perspective—Surface-Display Techniques In Electrochemical Biosensor Designs For Health Monitoring, Courtney J. Weber, Megan D. Whisonant, Olivia M. Clay, Olja Simoska

Faculty Publications

Enzymatic and microbial electrochemical biosensors integrate enzymes and microorganisms as biological recognition elements into the sensor design and functionality. Enzyme-based sensors offer high sensitivity and selectivity for target analyte detection. However, these have limited stability necessary for continuous analyte monitoring. Contrarily, microbe-based electrochemical sensors provide a means for continuous analyte sensing but are associated with challenges related to analyte selectivity in complex samples. To address these limitations, surface-display methods, which bind enzymes to microbial surfaces, enhance biosensor selectivity and sensitivity. This perspective outlines the application of surface-display techniques, offering a promising avenue for health monitoring.

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Chm110 Principles Of Chemistry Lecture Slides, Leah S. Cohen May 2024

Chm110 Principles Of Chemistry Lecture Slides, Leah S. Cohen

Open Educational Resources

These modified slides contain information from the first ten chapters from the General, Organic, and Biochemistry: connecting Chemistry to Your Life textbook by Blei & Odian.

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Unveiling Anomalies: A Survey On Xai-Based Anomaly Detection For Iot, Esin Eren, Feyza Yildirim Okay, Suat Özdemi̇r May 2024

Unveiling Anomalies: A Survey On Xai-Based Anomaly Detection For Iot, Esin Eren, Feyza Yildirim Okay, Suat Özdemi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, the rapid growth of the Internet of Things (IoT) has raised concerns about the security and reliability of IoT systems. Anomaly detection is vital for recognizing potential risks and ensuring the optimal functionality of IoT networks. However, traditional anomaly detection methods often lack transparency and interpretability, hindering the understanding of their decisions. As a solution, Explainable Artificial Intelligence (XAI) techniques have emerged to provide human-understandable explanations for the decisions made by anomaly detection models. In this study, we present a comprehensive survey of XAI-based anomaly detection methods for IoT. We review and analyze various XAI techniques, including …

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Text-To-Sql: A Methodical Review Of Challenges And Models, Ali Buğra Kanburoğlu, Faik Boray Tek May 2024

Text-To-Sql: A Methodical Review Of Challenges And Models, Ali Buğra Kanburoğlu, Faik Boray Tek

Turkish Journal of Electrical Engineering and Computer Sciences

This survey focuses on Text-to-SQL, automated translation of natural language queries into SQL queries. Initially, we describe the problem and its main challenges. Then, by following the PRISMA systematic review methodology, we survey the existing Text-to-SQL review papers in the literature. We apply the same method to extract proposed Text-to-SQL models and classify them with respect to used evaluation metrics and benchmarks. We highlight the accuracies achieved by various models on Text-to-SQL datasets and discuss execution-guided evaluation strategies. We present insights into model training times and implementations of different models. We also explore the availability of Text-to-SQL datasets in non-English …

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Security Fusion Method Of Physical Fitness Training Data Based On The Internet Of Things, Bin Zhou May 2024

Security Fusion Method Of Physical Fitness Training Data Based On The Internet Of Things, Bin Zhou

Turkish Journal of Electrical Engineering and Computer Sciences

Physical fitness training, an important way to improve physical fitness, is the basic guarantee for forming combat effectiveness. At present, the evaluation types of physical fitness training are mostly conducted manually. It has problems such as low efficiency, high consumption of human and material resources, and subjective factors affecting the evaluation results. ”Internet+” has greatly expanded the traditional network from the perspective of technological convergence and network coverage objects. It has expedited and promoted the rapid development of Internet of Things (IoT) technology and its applications. The IoT with many sensor nodes shows the characteristics of acquisition information redundancy, node …

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Dpafy-Gcaps: Denoising Patch-And-Amplify Gabor Capsule Network For The Recognition Of Gastrointestinal Diseases, Henrietta Adjei Pokuaa, Adeboya Felix Adekoya, Benjamin Asubam Weyori, Owusu Nyarko-Boateng May 2024

Dpafy-Gcaps: Denoising Patch-And-Amplify Gabor Capsule Network For The Recognition Of Gastrointestinal Diseases, Henrietta Adjei Pokuaa, Adeboya Felix Adekoya, Benjamin Asubam Weyori, Owusu Nyarko-Boateng

Turkish Journal of Electrical Engineering and Computer Sciences

Deep learning (DL) models have performed tremendously well in image classification. This good performance can be attributed to the availability of massive data in most domains. However, some domains are known to have few datasets, especially the health sector. This makes it difficult to develop domain-specific high-performing DL algorithms for these fields. The field of health is critical and requires accurate detection of diseases. In the United States Gastrointestinal diseases are prevalent and affect 60 to 70 million people. Ulcerative colitis, polyps, and esophagitis are some gastrointestinal diseases. Colorectal polyps is the third most diagnosed malignancy in the world. This …

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Joint Control Of A Flying Robot And A Ground Vehicle Using Leader-Follower Paradigm, Ayşen Süheyla Bağbaşi, Ali Emre Turgut, Kutluk Bilge Arikan May 2024

Joint Control Of A Flying Robot And A Ground Vehicle Using Leader-Follower Paradigm, Ayşen Süheyla Bağbaşi, Ali Emre Turgut, Kutluk Bilge Arikan

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a novel control framework for the collaboration of an aerial robot and a ground vehicle that is connected via a taut tether is proposed. The framework is based on a leader-follower paradigm. The leader follows a desired trajectory while the motion of the follower is controlled by an admittance controller using an extended state observer to estimate the tether force. Additionally, a velocity estimator is also incorporated to accurately assess the leader’s velocity. An essential feature of our system is its adaptability, enabling role switching between the robots when needed. Furthermore, the synchronization performance of the robots …

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Stereo-Image-Based Ground-Line Prediction And Obstacle Detection, Emre Güngör, Ahmet Özmen May 2024

Stereo-Image-Based Ground-Line Prediction And Obstacle Detection, Emre Güngör, Ahmet Özmen

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, vision systems have become essential in the development of advanced driver assistance systems or autonomous vehicles. Although deep learning methods have been the center of focus in recent years to develop fast and reliable obstacle detection solutions, they face difficulties in complex and unknown environments where objects of varying types and shapes are present. In this study, a novel non-AI approach is presented for finding the ground-line and detecting the obstacles in roads using v-disparity data. The main motivation behind the study is that the ground-line estimation errors cause greater deviations at the output. Hence, a novel …

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Practical Demonstration And Novel Optimization Control For A Smart Soft Open Point To Maximize The Synergy Between The Dc Metro Line And The Lv Distribution Grid, Tamer Kamel, Mansoureh Zangiabadi, Hongzhi Dong, Zhongbei Tian, Neal Wade, Volker Pickert, Pietro Tricoli May 2024

Practical Demonstration And Novel Optimization Control For A Smart Soft Open Point To Maximize The Synergy Between The Dc Metro Line And The Lv Distribution Grid, Tamer Kamel, Mansoureh Zangiabadi, Hongzhi Dong, Zhongbei Tian, Neal Wade, Volker Pickert, Pietro Tricoli

School of Engineering, Computing and Mathematics

The steady increment in electrical loads often requires expensive and disruptive upgrading of the electrical power supply infrastructure. This can be avoided by synergizing the DC railway networks with local AC grids using soft-open points to transfer the available regenerative braking energy of the trains to the nearby local grid. Besides, a battery energy storage system is integrated into the soft-open point to match the braking events with the grid load power. So that the new developed system effectively decouples both the rail and grid networks. This paper presents a practical study for such novel rail+grid energy management strategy. A …

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High Heat Flux Dissipation Techniques Using Enhancement Structures And Subcooled Boiling Chamber For High Performance Computing Applications, Maharshi Y. Shukla May 2024

High Heat Flux Dissipation Techniques Using Enhancement Structures And Subcooled Boiling Chamber For High Performance Computing Applications, Maharshi Y. Shukla

Theses

With a rising need for high-performance computing in data centers, enhanced heat dissipation from microprocessors becomes critical for maintaining their surface temperature in a compact setting. While air cooling has been sufficient until now, liquid cooling proves to be superior in its heat dissipation capabilities. The present work investigates enhancing liquid cooling with boiling and enhanced boiling structures in a novel subcooled boiling chamber. The single-phase forced convection heat transfer is first studied by enhancing the heat transfer performance (CHF and HTC) by more than 50 % with the injection of air bubbles at the heater surface. A self-sustaining method …

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Deep Learning-Based Breast Cancer Diagnosis With Multiview Of Mammography Screening To Reduce False Positive Recall Rate, Meryem Altın Karagöz, Özkan Ufuk Nalbantoğlu, Derviş Karaboğa, Bahriye Akay, Alper Baştürk, Halil Ulutabanca, Serap Doğan, Damla Coşkun, Osman Demi̇r May 2024

Deep Learning-Based Breast Cancer Diagnosis With Multiview Of Mammography Screening To Reduce False Positive Recall Rate, Meryem Altın Karagöz, Özkan Ufuk Nalbantoğlu, Derviş Karaboğa, Bahriye Akay, Alper Baştürk, Halil Ulutabanca, Serap Doğan, Damla Coşkun, Osman Demi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

Breast cancer is the most prevalent and crucial cancer type that should be diagnosed early to reduce mortality. Therefore, mammography is essential for early diagnosis owing to high-resolution imaging and appropriate visualization. However, the major problem of mammography screening is the high false positive recall rate for breast cancer diagnosis. High false positive recall rates psychologically affect patients, leading to anxiety, depression, and stress. Moreover, false positive recalls increase costs and create an unnecessary expert workload. Thus, this study proposes a deep learning based breast cancer diagnosis model to reduce false positive and false negative rates. The proposed model has …

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05.20.2024 Orsp Connect, Liz Williamson May 2024

05.20.2024 Orsp Connect, Liz Williamson

ORED Newsletter

NIH RPPR Update (Research Performance Progress Report)

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The Effects Of Classroom Integration On Children With Autism Spectrum Disorder, Makena Johnson May 2024

The Effects Of Classroom Integration On Children With Autism Spectrum Disorder, Makena Johnson

Undergraduate Honors Theses

Inclusion refers to the practice of fully educating students with special learning and/or behavioral needs within the traditional classroom. Such students participate in age-appropriate classes for the entirety of the school day, integrating them into the general school program with the intent to foster successful academic and social outcomes. Because inclusion is often driven by the desire to promote social integration, disorders that involve social dysfunction may be associated with additional challenges that hamper any potential inclusive benefits. Autism spectrum disorder (ASD) is one such candidate. This literature review aims to integrate research exploring the impact of separating or including …

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A Computational Framework For Consciousness: Integrating Quantum Mechanics And Integrated Information Theory, Allie Ellis May 2024

A Computational Framework For Consciousness: Integrating Quantum Mechanics And Integrated Information Theory, Allie Ellis

Undergraduate Honors Theses

Integrated Information Theory (IIT) provides a rigorous mathematical framework for consciousness, defining it by a system’s intrinsic causal power, quantified by the integrated information (Φ). A central obstacle to testing IIT is the prohibitive computational complexity of calculating Φ, which scales exponentially with system size. This work investigates whether efficient computational techniques from quantum information theory, specifically tensor network contractions, can be adapted to approximate key structural properties of IIT without directly computing the full Φ. We developed a classical model of 8-node networks with binary states, characterized by their Transition Probability Matrices (TPMs). For these systems, we constructed corresponding …

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Employing Digital Pcr For Enhanced Detection Of Perinatal Toxoplasma Gondii Infection: A Cross-Sectional Surveillance And Maternal-Infant Outcomes Study In El Salvador, Mary K. Lynn, Marvin Stanley Rodriguez Aquino, Pamela Michelle Cornejo Rivas, Xiomara Miranda, David F. Torres-Romero, Hanson Cowan, Madeleine M. Meyer, Willber D. Castro-Godoy, Mufaro Kanyangarara Ph.D., Stella Coker Watson Self Ph.D., Ms, Berry A. Campbell, Melissa Nolan Ph.D., Mph May 2024

Employing Digital Pcr For Enhanced Detection Of Perinatal Toxoplasma Gondii Infection: A Cross-Sectional Surveillance And Maternal-Infant Outcomes Study In El Salvador, Mary K. Lynn, Marvin Stanley Rodriguez Aquino, Pamela Michelle Cornejo Rivas, Xiomara Miranda, David F. Torres-Romero, Hanson Cowan, Madeleine M. Meyer, Willber D. Castro-Godoy, Mufaro Kanyangarara Ph.D., Stella Coker Watson Self Ph.D., Ms, Berry A. Campbell, Melissa Nolan Ph.D., Mph

Faculty Publications

Toxoplasma gondii is a parasitic infection that can be transmitted in utero, resulting in fetal chorioretinitis and other long-term neurological outcomes. If diagnosed early, pregnancy-safe chemotherapeutics can prevent vertical transmission. Unfortunately, diagnosis of acute, primary infection among pregnant women remains neglected, particularly in low-and-middle-income countries. Clinically actionable diagnosis is complex due to the commonality of infection during childhood and early adulthood which spawn long-last antibody titers and historically unreliable direct molecular diagnostics. The current study employed a cross-sectional T. gondii perinatal surveillance study using digital PCR, a next generation molecular diagnostic platform, and a maternal-fetal outcomes survey to ascertain …

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Comparative Analysis Of Water-Induced Response In 3d-Printed Scf/Abs Composites Under Controlled Diffusion, Samiul Alam, Md Tareq Hassan, Joshua Merrell, Juhyeong Lee May 2024

Comparative Analysis Of Water-Induced Response In 3d-Printed Scf/Abs Composites Under Controlled Diffusion, Samiul Alam, Md Tareq Hassan, Joshua Merrell, Juhyeong Lee

Mechanical and Aerospace Engineering Faculty Publications

Additive manufacturing (AM) or 3D printing of fiber-reinforced composites (FRCs) has garnered significant interests for its versatility in creating intricate parts and rapid prototyping due to cost-effectiveness. Although short fiber-reinforced thermoplastic composites are challenging to manufacture, their mechanical properties are enhanced. However, void formation during printing is a key issue, impacting mechanical properties and facilitating water ingress, affecting long-term durability. This work studies water diffusion characteristics and the associated hydro-aging of 3Dprinted short carbon fiber (SCF)/acrylonitrile butadiene styrene (ABS) composites with controlled water diffusion. Effects of material type (ABS and SCF/ABS), 3D printing path (horizontal and vertical filament orientation), and …

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Signer-Independent Sign Language Recognition With Feature Disentanglement, İnci̇ Meli̇ha Baytaş, İpek Erdoğan May 2024

Signer-Independent Sign Language Recognition With Feature Disentanglement, İnci̇ Meli̇ha Baytaş, İpek Erdoğan

Turkish Journal of Electrical Engineering and Computer Sciences

Learning a robust and invariant representation of various unwanted factors in sign language recognition (SLR) applications is essential. One of the factors that might degrade the sign recognition performance is the lack of signer diversity in the training datasets, causing a dependence on the singer’s identity during representation learning. Consequently, capturing signer-specific features hinders the generalizability of SLR systems. This study proposes a feature disentanglement framework comprising a convolutional neural network (CNN) and a long short-term memory (LSTM) network based on adversarial training to learn a signer-independent sign language representation that might enhance the recognition of signs. We aim to …

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Machine Learning For Intrusion Detection: A Reproducible Baseline Is All You Need, Salma A. Walli, Karam Sallam May 2024

Machine Learning For Intrusion Detection: A Reproducible Baseline Is All You Need, Salma A. Walli, Karam Sallam

Sustainable Machine Intelligence Journal

Ensuring Responsible AI practices is paramount in the advancement of systems founded upon machine learning (ML) principles, particularly in sensitive domains like intrusion detection within cybersecurity. A fundamental aspect of Responsible AI is reproducibility, which guarantees the reliability and transparency of research outcomes. In this paper, we address the critical challenge of establishing reproducible for intrusion detection utilizing ML techniques. Leveraging the NSL-KDD dataset and the Edge-IIoTset, we carry out extensive experiments to evaluate the efficacy of our approach. Our study prioritizes meticulous experiment design and careful implementation setups, aligning with the principles of Responsible AI. Through rigorous experimentation and …

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Ri2ap: Robust And Interpretable 2d Anomaly Prediction In Assembly Pipelines, Chathurangi Shyalika, Kaushik Roy, Renjith Prasad, Fadi El Kalach, Yuxin Zi, Priya Mittal, Vignesh Narayanan, Ramy Harik, Amit Sheth May 2024

Ri2ap: Robust And Interpretable 2d Anomaly Prediction In Assembly Pipelines, Chathurangi Shyalika, Kaushik Roy, Renjith Prasad, Fadi El Kalach, Yuxin Zi, Priya Mittal, Vignesh Narayanan, Ramy Harik, Amit Sheth

Publications

Predicting anomalies in manufacturing assembly lines is crucial for reducing time and labor costs and improving processes. For instance, in rocket assembly, premature part failures can lead to significant financial losses and labor inefficiencies. With the abundance of sensor data in the Industry 4.0 era, machine learning (ML) offers potential for early anomaly detection. However, current ML methods for anomaly prediction have limitations, with F1 measure scores of only 50% and 66% for prediction and detection, respectively. This is due to challenges like the rarity of anomalous events, scarcity of high-fidelity simulation data (actual data are expensive), and the complex …

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Illinois State University Graduate Course Catalog, 2024-2025, Illinois State University May 2024

Illinois State University Graduate Course Catalog, 2024-2025, Illinois State University

Course Catalogs

Illinois State University Graduate Course Catalog, 2024-2025. Effective May 20, 2024.

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Illinois State University Undergraduate Course Catalog, 2024-2025, Illinois State University May 2024

Illinois State University Undergraduate Course Catalog, 2024-2025, Illinois State University

Course Catalogs

Illinois State University Undergraduate Course Catalog, 2024-2025. Effective May 20, 2024.

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Living On The Outskirts Of Things: Women And Nonbinary People Of Color With Cognitive Disabilities Describe Their Employment Experiences, Laura Spura Rodriguez May 2024

Living On The Outskirts Of Things: Women And Nonbinary People Of Color With Cognitive Disabilities Describe Their Employment Experiences, Laura Spura Rodriguez

Dissertations and Theses

This study examines the experiences of discrimination and the strategies used to navigate employment for women of color and nonbinary people of color (POC) with cognitive disabilities (CD) through their own narratives. Using Dis/ability Critical Race Theory and an interpretive description methodology, this study engaged 10 women of color and/or nonbinary POC with CD in semi-structured interviews in order to answer the following research questions: 1) What stories do women of color and nonbinary POC with CD tell about their experiences seeking employment? 2) What are the narratives of women and nonbinary POC with CD about their experiences of racism, …

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Brain Science And Brain-Inspired Intelligence In Intelligent Era, Xu Zhang May 2024

Brain Science And Brain-Inspired Intelligence In Intelligent Era, Xu Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

With intelligence technology as the core technology and intelligent computing power as the productive force, the intelligent era has once again pushed brain science to the forefront of world science and technology. Brain science is the science that studies the nature and rule of cognition and intelligence of human, animal, and machine. A comprehensive analysis of the structure and functional connection rule of the nervous system will eventually draw the functional connectivity map of the brain. In the past decade, neuroscience research has been committed to systematically analyzing the types of neurons and neural structural connections of the nervous system, …

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Some Reflections On Developing Trend Of Gravimetry In China, Heping Sun May 2024

Some Reflections On Developing Trend Of Gravimetry In China, Heping Sun

Bulletin of Chinese Academy of Sciences (Chinese Version)

With the development of modern science and technology, gravimetry is growing vigorously and is increasingly becoming an interdisciplinary subject that is closely related to many others such as geology, fundamental physics, geodynamics, hydrology, oceanography, and astronomy. It is now a key subject in giving service to demands in national strategy and fundamental researches in geoscience such as fiducial surveying and mapping, resource exploration, military security, and hazard monitoring. Therefore, owning the core gravimetric techniques is one of the pivots which reflect national core competitiveness. This study first briefly overviews the history and actuality of the growth of gravimetry subject in …

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