Computer Sciences Commons^™

From Chip Design To Chip Learning, Yunji Chen, Zidong Du, Qi Guo, Wei Li, Yijun Tan

Bulletin of Chinese Academy of Sciences (Chinese Version)

Chip is the foundation of the modern information society. As the world is entering a new era of human-cyber-physical ternary computing, with diverse intelligent applications over trillions of devices, chip with specialized architecture will be heavily demanded in both numbers and types. However, chip design is very costly, which usually requires a long design cycle, complicated process, and high professional developers. Hence, there is a large gap between the need of tremendous chips and the high cost of chip design in the new era. This study proposes Chip Learning, a learning-based method to perform the entire chip design, including logic …

Ubiquitous Operating System: Toward The Blue Ocean Of Human-Cyber-Physical Ternary Ubiquitous Computing Mei, Hong Mei, Donggang Cao, Tao Xie

Bulletin of Chinese Academy of Sciences (Chinese Version)

In response to the new patterns and scenarios of future human-cyber-physical ternary ubiquitous computing, a new kind of operating system named Ubiquitous Operating System (UOS) is emerging and under exploration for further development. The human-cyberphysical ternary ubiquitous computing has many new features, such as open and dynamic environment, diverse requirements, and complex application scenarios. New ubiquitous applications pose special demands on ubiquitous sensing and connection, lightweight computing and artificial intelligence, dynamic adaptation, feedback and control, natural human-computer-interaction, etc. To support these new requirements, a software definition mechanism is in need to flexibly control hardware, data resources, platforms, and applications. This …

Thoughts On Innovation Of Future Network Architecture, Yunjie Liu, Tao Huang, Shou Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Currently, network technology is deeply integrated with the physical world. Traditional network architectures cannot support the differentiated, customizable, and deterministic needs of industrial Internet and other services. Exploring new network architecture and core technology has officially become the strategic commanding heights of the global Internet competition. To this end, the paper reviews the evolution and trends of the network, analyzes how to achieve high-performance, low-cost, intelligent network development strategies for establishing an autonomous and controllable future network. Two conclusions are drawn as follows. (1) Through the exploration of network construction in recent decades, integration, openness, intelligence, customization and integration of …

Improving Cyberspace Security Situation From Perspective Of “Talent, Finance And Infrastructure”, Binxing Fang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Cyberspace security has been an important part in ensuring economic development and supporting the progress of modern science and technology. As more and more applications are relying on information technology (IT), it becomes very important to improve the security situation of cyberspace. How to take effective measures to practically improve the cyberspace security situation has become the core problem disscussed in this paper. This paper addresses it from the perspectives of "talent, finance and infrastructure". First, on the premise of insufficient supply of cyberspace security talents, this paper proposes to establish the ability certification of talents transferred from other IT …

Thinking On New System For Big Data Technology, Xueqi Chegn, Shenghua Liu, Ruqing Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

In recent years, there are such significant improvements on the performance and efficiency of big data technology and system. As it is widely applied in various fields, big data has empowered industrial intelligence, and is the key step into the intelligent stage of information society. Therefore, we are facing greater challenges nowadays, such as the paradox of data flooding and high-value data lacking, the complexity and uncertainty of big data analysis, and the difficulty to balance the data on sharing and circulation, and trustworthiness and security. Moreover, these challenges will not only promote the innovation and change of big data …

A Surrogate Assisted Quantum-Behaved Algorithm For Well Placement Optimization, Jahedul Islam, Amril Nazir, Moinul Hossain, Hitmi Khalifa Alhitmi, Muhammad Ashad Kabir, Abdul-Halim Jallad

All Works

The oil and gas industry faces difficulties in optimizing well placement problems. These problems are multimodal, non-convex, and discontinuous in nature. Various traditional and non-traditional optimization algorithms have been developed to resolve these difficulties. Nevertheless, these techniques remain trapped in local optima and provide inconsistent performance for different reservoirs. This study thereby presents a Surrogate Assisted Quantum-behaved Algorithm to obtain a better solution for the well placement optimization problem. The proposed approach utilizes different metaheuristic optimization techniques such as the Quantum-inspired Particle Swarm Optimization and the Quantum-behaved Bat Algorithm in different implementation phases. Two complex reservoirs are used to investigate …

A Systematic Literature Review On Spam Content Detection And Classification, Sanaa Kaddoura, Ganesh Chandrasekaran, Daniela Elena Popescu, Jude Hemanth Duraisamy

All Works

The presence of spam content in social media is tremendously increasing, and therefore the detection of spam has become vital. The spam contents increase as people extensively use social media, i.e ., Facebook, Twitter, YouTube, and E-mail. The time spent by people using social media is overgrowing, especially in the time of the pandemic. Users get a lot of text messages through social media, and they cannot recognize the spam content in these messages. Spam messages contain malicious links, apps, fake accounts, fake news, reviews, rumors, etc. To improve social media security, the detection and control of spam text are …

Current Trends In Blockchain Implementations On The Paradigm Of Public Key Infrastructure: A Survey, Daniel Maldonado-Ruiz, Jenny Torres, Nour El Madhoun, Mohamad Badra

All Works

Since the emergence of the Bitcoin cryptocurrency, the blockchain technology has become the new Internet tool with which researchers claim to be able to solve any existing online problem. From immutable log ledger applications to authorisation systems applications, the current technological consensus implies that most of Internet problems could be effectively solved by deploying some form of blockchain environment. Regardless this ‘consensus’, there are decentralised Internet-based applications on which blockchain technology can actually solve several problems and improve the functionality of these applications. The development of these new blockchain-based solutions is grouped into a new paradigm called Blockchain 3.0 and …

Application Of Gravity Data For Hydrocarbon Exploration Using Machine Learning Assisted Workflow, Oluwafemi Temidayo Alaofin

LSU Master's Theses

Gravity survey has played an essential role in many geoscience fields ever since it was conducted, especially as an early screening tool for subsurface hydrocarbon exploration. With continued improvement in data processing techniques and gravity survey accuracy, in-depth gravity anomaly studies, such as characterization of Bouguer and isostatic residual anomalies, have the potential to delineate prolific regional structures and hydrocarbon basins. In this study, we focus on developing a cost-effective, quick, and computationally efficient screening tool for hydrocarbon exploration using gravity data employing machine learning techniques. Since land-based gravity surveys are often expensive and difficult to obtain in remote places, …

Transformers In Vision: A Survey, Salman Khan, Muzammal Naseer, Munawar Hayat, Syed Waqas Zamir, Fahad Shahbaz Khan, Mubarak Shah

Computer Vision Faculty Publications

Astounding results from Transformer models on natural language tasks have intrigued the vision community to study their application to computer vision problems. Among their salient benefits, Transformers enable modeling long dependencies between input sequence elements and support parallel processing of sequence as compared to recurrent networks e.g., Long short-term memory (LSTM). Different from convolutional networks, Transformers require minimal inductive biases for their design and are naturally suited as set-functions. Furthermore, the straightforward design of Transformers allows processing multiple modalities (e.g., images, videos, text and speech) using similar processing blocks and demonstrates excellent scalability to very large capacity networks and huge …

On The Horizon: Nanosatellite Constellations Will Revolutionize The Internet Of Things (Iot), Diane Janosek

Seattle Journal of Technology, Environmental, & Innovation Law

The Internet of Things has experienced exponential growth and use across the globe with 25.1 billion devices currently in use. Until recently, the functionality of the IoT was dependent on secure data flow between internet terrestrial stations and the IoT devices. Now, a new alternative path of data flow is on the horizon.

IoT device manufacturers are now looking to outer space nanosatellite constellations to connect to a different type of internet. This new internet is no longer terrestrial with fiber cables six feet underground but now looking up, literally, 200 to 300 miles above the earth, to communicate, connect …

Me2b Alliance Validation Testing Report: Consumer Perception Of Legal Policies In Digital Technology, Noreen Y. Whysel, Karina Alexanyan, Shaun Spaulting, Julia Little

Publications and Research

Our relationship with technology involves legal agreements that we either review or enter into when using a technology, namely privacy policies and terms of service or terms of use (“TOS/TOU”). We initiated this research to understand if providing a formal rating of the legal policies (privacy policies and TOS/TOUs) would be valuable to consumers (or Me-s). From our early qualitative discussions, we noticed that people were unclear on whether these policies were legally binding contracts or not. Thus, a secondary objective emerged to quantitatively explore whether people knew who these policies protected (if anyone), and if the policies were perceived …

Deep Learning-Based Quality Assessment Of Clinical Protocol Adherence In Fetal Ultrasound Dating Scans, Sevim Cengiz, Mohammad Yaqub

Computer Vision Faculty Publications

To assess fetal health during pregnancy, doctors use the gestational age (GA) calculation based on the Crown Rump Length (CRL) measurement in order to check for fetal size and growth trajectory. However, GA estimation based on CRL, requires proper positioning of calipers on the fetal crown and rump view, which is not always an easy plane to find, especially for an inexperienced sonographer. Finding a slightly oblique view from the true CRL view could lead to a different CRL value and therefore incorrect estimation of GA. This study presents an AI-based method for a quality assessment of the CRL view …

Automatic Segmentation Of Head And Neck Tumor: How Powerful Transformers Are?, Ikboljon Sobirov, Otabek Nazarov, Hussain Alasmawi, Mohammad Yaqub

Computer Vision Faculty Publications

Cancer is one of the leading causes of death worldwide, and head and neck (H&N) cancer is amongst the most prevalent types. Positron emission tomography and computed tomography are used to detect and segment the tumor region. Clinically, tumor segmentation is extensively time-consuming and prone to error. Machine learning, and deep learning in particular, can assist to automate this process, yielding results as accurate as the results of a clinician. In this research study, we develop a vision transformers-based method to automatically delineate H&N tumor, and compare its results to leading convolutional neural network (CNN)-based models. We use multi-modal data …

Is Contrastive Learning Suitable For Left Ventricular Segmentation In Echocardiographic Images?, Mohamed Saeed, Rand Muhtaseb, Mohammad Yaqub

Computer Vision Faculty Publications

Contrastive learning has proven useful in many applications where access to labelled data is limited. The lack of annotated data is particularly problematic in medical image segmenta-tion as it is difficult to have clinical experts manually annotate large volumes of data. One such task is the segmentation of cardiac structures in ultrasound images of the heart. In this paper, we argue whether or not contrastive pretraining is helpful for the segmentation of the left ventricle in echocardiography images. Furthermore, we study the effect of this on two segmentation networks, DeepLabV3, as well as the commonly used segmentation net-work, UNet. Our …

Is It Possible To Predict Mgmt Promoter Methylation From Brain Tumor Mri Scans Using Deep Learning Models?, Numan Saeed, Shahad Hardan, Kudaibergen Abutalip, Mohammad Yaqub

Computer Vision Faculty Publications

Glioblastoma is a common brain malignancy that tends to occur in older adults and is almost always lethal. The effectiveness of chemotherapy, being the standard treatment for most cancer types, can be improved if a particular genetic sequence in the tumor known as MGMT promoter is methylated. However, to identify the state of the MGMT promoter, the conventional approach is to perform a biopsy for genetic analysis, which is time and effort consuming. A couple of recent publications proposed a connection between the MGMT promoter state and the MRI scans of the tumor and hence suggested the use of deep …

Challenges In Covid-19 Chest X-Ray Classification: Problematic Data Or Ineffective Approaches?, Muhammad Ridzuan, Ameera Ali Bawazir, Ivo Gollini Navarrete, Ibrahim Almakky, Mohammad Yaqub

Computer Vision Faculty Publications

The value of quick, accurate, and confident diagnoses cannot be undermined to mitigate the effects of COVID-19 infection, particularly for severe cases. Enormous effort has been put towards developing deep learning methods to classify and detect COVID-19 infections from chest radiography images. However, recently some questions have been raised surrounding the clinical viability and effectiveness of such methods. In this work, we carry out extensive experiments on a large COVID-19 chest X-ray dataset to investigate the challenges faced with creating reliable solutions from both the data and machine learning perspectives. Accordingly, we offer an in-depth discussion into the challenges faced …

Factors Affecting Student Educational Choices Regarding Oer Material In Computer Science, Anastasia Angelopoulou, Rania Hodhod, Alfredo J. Perez

Computer Science Faculty Publications

The use of Open Educational Resources (OER) in course settings provides a solution to reduce the textbook barrier. Several published studies have concluded that high textbook costs may influence students' educational choices. However, there are other student characteristics that may be relevant to OER. In this work, we study various factors that may influence students' educational choices regarding OER and their impact on a student’s perspectives on OER use and quality. More specifically, we investigate whether there are significant differences in the frequency of use and perceived quality of the OER textbook based on gender, prior academic achievements, income, seniority, …

Modeling And Simulation Of Emergency Medical Resources Allocation In Shanghai During Covid-19, Changjia Fan, Yanqiu Du, Liang Di, Hu Kai, Jiayan Huang

Journal of System Simulation

Abstract: Modeling and simulating on the allocation of emergency medical resources in Shanghai with COVID-19 is carried out. Based on the SEIR model of infectious diseases, combined with the process of outpatients visiting and inpatients treatment, a SEIOWHR(susceptible-exposed-infected-outpatients- waiting to hospitalized-hospitalized-removed) system dynamics model is established. If the Wuhan epidemic occurred in Shanghai, based on the model, the amount of emergency medical resources needed, the gap time of medical resources and the disease progression of patients who are waiting to hospitalized under the different supply of medical resources is simulated, and the key factors in the allocation of medical …

A Fast Simulation Method For Ship Target Sar Signal Echo, Yuan Fei, Jianhong Li, Yin Hao, Yuhao Wang, Hong Sheng

Journal of System Simulation

Abstract: In order to meet the application requirements of synthetic aperture radar (SAR) in ocean remote sensing, a fast simulation method for the ship target SAR echo generation is presented, which carries out the accurate electromagnetic modeling to the important ship targets. “Four paths" model is used to calculate the complex echo between the ship target and sea surface, and the facet model is used to model the sea surface backscattering. After the two parts of echoes being synthesized, the SAR echo of whole scene is gotten, and the echo is processed by spot SAR imaging processing algorithm to verify …

Study On Bidirectional Coupling Of Human Thermal Comfort Parameters And Cabin Thermal Environment, Jue Qu, Dayan Wang, Wang Wei, Sina Dang

Journal of System Simulation

Abstract: At present, for the existing cockpit heat system, are studied more the airflow tissue parameters of the thermal environment and the human heat regulation is taken into account less, which leads to the low accuracy of simulation result evaluating the human thermal comfort. Through CFD (computational fluid dynamics) method, energy equation, RANS (reynolds-average navier-stokes) equation, and N-S(navier-stokes) equation, by combining the human temperature distribution with the cabin thermal environment parameters, the cabin heat system model based on the human heat regulation is established. The model considers the interacting influence of the human thermal regulation and the thermal environmental airflow …

Time-Varying Output Formation Tracking Control Of Discrete-Time Heterogeneous Multi-Agent Systems, Xiaolong Qi, Xuguang Yang

Journal of System Simulation

Abstract: Aiming at the discrete-time heterogeneous multi-agent systems with different dimensions and parameters, the time-varying output formation tracking control is studied by using the output regulation method. Assuming that the multi-agents system is consisted of multiple followers and multiple leaders, and the followers can't obtain the leaders' states, the distributed observers are designed by using the neighboring relative information. Based on the states of the distributed observers, the time-varying output formation tracking protocols and algorithm are presented by using the states feedback, and the sufficient conditions that guarantee the protocols' effectiveness are also given. The simulation results show that, …

Wsn Clustering Routing Protocol For Bridge Structure Health Monitoring, Li Gang, Caixia Zhang, Shaolin Hu, Xiangdong Wang, Guo Jing

Journal of System Simulation

Abstract: In the specific application of bridge structure health monitoring (BSHM), clustering based only on the geographic location of nodes or using a single-hop strategy to complete inter-cluster routing may cause the unstability of the entire wireless sensor networks(WSN). For WSN in BSHM scenario, the concept of "energy distribution" is proposed, and an energy balance clustering routing protocol energy balance protocol(EBP) is designed. The second clustering, the high-energy areas in WSN bear more energy consumption, and a multi hop strategy based on region division is designed to control the number of forwarding hops. The simulation results show that, compared with …

Optimization Of Household Electricity Consumption Period Based On Improved Multi-Objective Particle Swarm Optimization, Xiuying Yan, Miaomiao Dang

Journal of System Simulation

Abstract: Aiming at the household power load scheduling optimization, three objectives of the cost of electricity, satisfaction and user-side fluctuation degree are taken into comprehensive account. An improved adaptive weight multi-objective particle swarm optimization (IAW-MOPSO) algorithm is proposed to realize the scheduling optimization of household power load. The local improvement ability and global search ability of particle swarm optimization are balanced by updating the inertia weight of particle fitness value. The simulation results of five groups show that the proposed optimization strategy reduces the electricity charge by 29%, ensures the stability of electricity consumption in the peak period, and …

Adaptive Optimization In Feature-Based Slam Visual Odometry, Yanan Yu, Dunhuang Shi, Chunjie Hua

Journal of System Simulation

Abstract: Aiming to reduce the impact of dynamic environments on simultaneous localization and mapping (SLAM) of mobile robots, an adaptive optimization method in a feature-based visual odometry is proposed. The method helps to improve the invariance of image feature in illumination changing situation and to extract features effectively in areas where the texture information is not sufficient to make contributions to feature matching. Meanwhile, down sampling is applied to establish image pyramids and each scaled image is divided into cells based on a defined rule. Illumination adaptive nonlinear adjustments for each cell are applied to increase the image details, and …

Planning And Analysis On Uav Trajectory Based On Pce Method, Sijie Zeng, Yan Liang, Xiaojun Duan

Journal of System Simulation

Abstract: Focusing on the uncertainty in the UAV trajectory planning, combined with the artificial potential energy method, a UAV trajectory planning method based on polynomial chaos expansion (PCE), which can also efficiently obtain the optimal parameters of the model based on artificial potential field method is proposed. The PCE proxy model is established, and the stochastic collocation method is used to quickly solve the problem, so as to avoid the insufficient computing resources. Through the Sobol sensitivity analysis, the calculation overhead of the uncertainty parameters in the trajectory planning model is reduced. Cases of UAV trajectory planning prove the effectiveness …

Research On Intelligent Vehicle Trajectory Tracking Control Based On Robust Model Prediction, Hongguang Lu, Shuen Zhao

Journal of System Simulation

Abstract: Aiming at the low control accuracy and poor robustness of traditional trajectory tracking controller based on the tracking error model in complex driving environment, a robust model predictive trajectory tracking control strategy is designed. The vehicle convex multicellular dynamic model is used to explicitly describe the vehicle dynamic characteristics, and the robust performance objective function is designed in combination with the trajectory tracking multi-objective constraint, and the state feedback control law is solved through the linear matrix inequality optimization. Feedforward control is introduced to eliminate the steady-state errors and improve the tracking accuracy. The simulation result shows that …

Agent- Based Research On Power Absorption Simulation Analysis Of Renewable Energy, Zhang Luan, Zhengjun Luo, Dequn Zhou

Journal of System Simulation

Abstract: Aiming at the “three abandonment”, a guarantee mechanism for the consumption of renewable energy power is proposed in our country. In order to stimulate the consumption of renewable energy power, a multi-agent simulation method is used to analyze the transaction behavior and interaction of market players, and the key factors affecting the consumption of renewable energy power is analyzed to simulated the consumption of renewable energy and the evolution of the number of active consumers. The results show that the subscribed green certificate can directly promote the consumption of renewable energy power, and it is necessary to comprehensively consider …

Autonomous Vehicle Path Tracking Control System Based On Energy Optimization, Xiaolong Wu, Fugen Xia, Chen Jing, Xu Jia

Journal of System Simulation

Abstract: Powertrain control is important to the dynamic performance and economy of driverless cars and a path following control strategy based on energy optimization is proposed. The control strategy includes two parts. The nonlinear model predictive control is used in the upper controller to calculate the required power parameters and front wheel angle. The lower-level controller is designed based on the optimal value of motor energy consumption which ensure the motor being always running at the optimal state of efficiency. In addition, the continuously variable transmission (CVT) is dynamically adjusted according to the motor state to meet the vehicle power …

Fault Tolerant Control And Simulation Of Quadrotor Based On Adaptive Observer, Zhao Jing, Wang Peng, Xiaoqian Ding, Guoping Jiang, Fengyu Xu, Yanfei Sun

Journal of System Simulation

Abstract: Focusing on the actuator fault of quadrotor, an integral backstepping sliding mode combined with adaptive observer is proposed to ensure the safety and reliability of the quadrotor. A dynamic model of the quadrotor with actuator fault are established. An adaptive observer is proposed to observe the state and estimate the actual value of the fault. The attitude fault tolerant controller and position controllers are designed by the method of integral backstepping combined with the sliding mode control to complete the trajectory tracking of attitude and position. The simulation results show that the control strategy can quickly and accurately track …