Artificial Intelligence and Robotics Commons^™

Rehabilitation Training System Based On Brain Computer Interface, Banghua Yang, Li Bo

Journal of System Simulation

Abstract: Brain-computer interface (BCI) is a new communication and control method. The BCI rehabilitation training system was developed for rehabilitation training of post-stroke patients by using MATLAB and VC++ hybrid programming method. By decoding the EEG signal, the patient's movement intention can be recognized accurately in real time, then the work of the rehabilitation peripheral is triggered to give feedback from the visual, auditory, and tactile. The patient's active rehabilitation is achieved through the system. The system has the characteristics of user-friendly interface, modular algorithm, high online recognition rate; and it can be used as a reference for BCI-based …

Modeling And Simulation Of Inter-City Passenger Travel Service Flow Based On Petri Net, Qipeng Sun, Guo Xin, Ma Fei

Journal of System Simulation

Abstract: On the basis of inter-city passenger travel chain, the inter-city passenger transport service process is studied; the Petri net language is used for establishing and simulating the model of inter-city passenger transport service process based on the Visual Object Net++; and the simulation results are used for verifying the reliability of the established model with the theory of petri net, while the model is transformed into a homogeneous Markov chain with the process. The detailed analysis on the city subway of the inter-city passenger transport service process was carried out. By modeling and simulating, the derived value of …

High-Pass Difference Features Based Image Quality Assessment, Wang Rui, Li Ping, Bin Sheng, Congbin Qiao, Lizhuang Ma, Enhua Wu

Journal of System Simulation

Abstract: Current methods of image quality assessment only can assess the quality of images under the same type of image distortion. In order to fix such weaknesses, this paper is designed based on the image features of natural scene statistics and proposes a new metric method using high-pass filter for detecting features. The approach computes locally the normalized luminance; selects features such as the difference of RGB channels via high-pass filter, image gradient, sharpness, contrast, etc.; and analyzes and gathers features in the metric method trained by logistic regression. Experimental results show that the proposed method can work efficiently under …

Design And Research On Simulation Model Of Limestone-Wet Flue Gas Desulfurization Absorption Tower, Zhang Yue, Han Pu, Zhang Xiang

Journal of System Simulation

Abstract: The mass transfer and chemical reaction processes of wet flue gas desulfurization (FGD) are very complex. It is helpful to improve the operation level of desulfurization site by studying the internal mechanism and establishing a high precision mechanism model. The absorption tower is divided into some regions, and the modeling targets in different regions are determined. The sulfur dioxide absorption region is divided into different heights of the "cell" by the slurry droplet falling distance and exposure time. According to the motion characteristics and mass transfer process, the desulfurization efficiency and pressure drop are calculated, and the absorption efficiency …

Indoor Scene Generation Based On Case-Based Reasoning And Collaborative Filtering, Peihua Song, Jinyuan Jia

Journal of System Simulation

Abstract: To solve the problem of time-consuming and single scene generation in indoor scene generation, we propose an indoor scene generation algorithm based on case-based reasoning and collaborative filtering techniques. The algorithm of functional area division is performed on the two-dimensional room floor plan. Thecase-based reasoning is used to generate 3D scenes; and the collaborative filtering is used to generate diverse indoor scenes. A scene evaluation method based on user feedback information is proposed. Experiments were carried out on the living room and bedroom to generate scenes. The experimental results show that the proposed algorithm is effective. The running time …

Simulation Algorithm Of Streak Tube Multi-Spectral Laser 3d Imaging System, Jingya Cao, Shaokun Han, Wenze Xia, Wang Liang

Journal of System Simulation

Abstract: The streak tube laser three-dimensional imaging system is one of the most promising practical laser imaging systems, because of its high precision, large field of view and high frame frequency. A multispectral imaging simulation algorithm for multi-slit streak tube is proposed based on the research of the multi-spectral imaging. The derivation of the main structural parameters is given. The influence of the number of different detectors on the time resolution and spatial resolution of the system is analyzed. In the model of the simulation system, the laser echo signals of multiple wavelength bands are fed into the photocathode of …

Visualization Platform Of Lightweight Toxic Gases Dispersion, Jinyuan Jia, Xinzhi Zhao, Panjing Li

Journal of System Simulation

Abstract: The sudden accidents usually emit large quantities of toxic gases and harmful pollutants in a short time. It is very necessary and meaningful to predict and visualize the dispersing trend of those toxic gases over Internet as accurate and fast as possible for people to evacuate safely and immediately. We propose a lightweight simulation for air pollution dispersion based on the Gaussian puff model. With this method, we can visualize the procedure of toxic gas dispersing on a webpage in real-time. we can also estimate the pollution of toxic gas dispersion trend and analyze their further pollution effects on …

Hardware-In-The-Loop Simulation Method For Laser Active Imaging Guidance, Zhang Qing, Yijie Li

Journal of System Simulation

Abstract: The system of laser active imaging guidance hardware-in-the-loop simulation is a significant system for testing and validating the capability of laser active imaging guidance and control, it also means a lot in practical applications. The composition of guidance and control system for the laser active imaging aerocraft is analyzed, and the purpose and test flow for the hardware-in-the-loop simulation system are introduced. The integrated project for laser active imaging guidance hardware-in-the-loop simulation system is designed. The functions and elements for the crucial simulation equipment of laser active imaging echo simulator are analyzed; the elements of model composition and …

Improved Dv-Hop Localization Scheme Based On The Best Path Matching Strategy, Qinqin Shi, Xu Qiang, Jianping Zhang

Journal of System Simulation

Abstract: Improvement strategies are provided in view of the fact that the original DV-Hop (Distance, Vector-Hop) method has great error in distance estimation due to the network anisotropy in practical applications and the sensitivity of its location derivation algorithm to the range error. In the distance estimation step, a strategy of computing path similarity parameter is proposed to find out the most similar beacon-beacon path to beacon-node path; in the position calculation step, a modified PSO (Particle Swarm Optimization) algorithm is added after the initial position of an unknown node being derived using Lateration algorithm. Simulation shows that compared with …

Traffic Dynamic Regulation And Control Technology In The Central Area Of Nanning City, Yiman Du, Hongfan Su, Jianping Wu, Chen Yu, Huang Lin, Longfei Liu

Journal of System Simulation

Abstract: As the transportation develops rapidly, the traffic burden increases in downtown areas, especially in the areas of convention center, government building, and business & financial center, which exacerbates traffic congestion nearby. Conventional traffic control measures taken include stagger shifts, congestion charging, and tail number limit. Interests of multi aspects are involved in these measures, which has broad effect. The traffic managers now begin to ameliorate traffic burden by technical methods. A feedback-gate control based regional traffic volume control method was proposed and a microscopic simulation was adopted. This reasearch aims to ameliorate traffic pressure and balance traffic flow through …

Gesture Recognition Method Based On Multi-Feature Fusion, Yuanming Wang, Zhang Jun, Yuanhui Qin, Xiujuan Chai

Journal of System Simulation

Abstract: Aiming at the specific application requirements of command gesture for flight deck, a gesture recognition method based on multi-feature fusion is proposed. The 3D trajectory feature vector and hand sparse representation are established from two aspects of the trajectory and posture based on the visual information collected by depth camera. On the one hand, the gesture is recognized through normalization resampling and alignment based on the trajectory feature. On the other hand, the gesture is recognized through sparse representation alignment based on the HOG feature. The recognition results are fused effectively. The experimental results indicate that our …

Session: 4 Multilinear Subspace Learning And Its Applications To Machine Learning, Randy Hoover, Kyle Caudle Dr., Karen Braman Dr.

SDSU Data Science Symposium

Multi-dimensional data analysis has seen increased interest in recent years. With more and more data arriving as 2-dimensional arrays (images) as opposed to 1-dimensioanl arrays (signals), new methods for dimensionality reduction, data analysis, and machine learning have been pursued. Most notably have been the Canonical Decompositions/Parallel Factors (commonly referred to as CP) and Tucker decompositions (commonly regarded as a high order SVD: HOSVD). In the current research we present an alternate method for computing singular value and eigenvalue decompositions on multi-way data through an algebra of circulants and illustrate their application to two well-known machine learning methods: Multi-Linear Principal Component …

Cs04all: Machine Learning Module, Hunter R. Johnson

Open Educational Resources

These are materials that may be used in a CS0 course as a light introduction to machine learning.

The materials are mostly Jupyter notebooks which contain a combination of labwork and lecture notes. There are notebooks on Classification, An Introduction to Numpy, and An Introduction to Pandas.

There are also two assessments that could be assigned to students. One is an essay assignment in which students are asked to read and respond to an article on machine bias. The other is a lab-like exercise in which students use pandas and numpy to extract useful information about subway ridership in NYC. …

Cs04all: Natural Language Processing Project, Hunter R. Johnson

Open Educational Resources

In this archive there are two activities/assignments suitable for use in a CS0 or Intro course which uses Python.

In the first activity, students are asked to "fill in the code" in a series of short programs that compute a similarity metric (cosine similarity) for text documents. This involves string tokenization, and frequency counting using Python string methods and datatypes.

https://cocalc.com/share/bde99afd-76c8-493d-9608-db9019bcd346/171/Proj1?viewer=share/

In the second activity (taken directly from Think Python 2e) students use a pronunciation dictionary to solve a riddle involving homophones.

https://cocalc.com/share/bde99afd-76c8-493d-9608-db9019bcd346/171/Dicts2?viewer=share/

This OER material was produced as a result of the CS04ALL CUNY OER project

Bots In Libraries: They're Coming For Your Jobs (Or Is It?), Salihin Mohammed Ali

Research Collection Library

With advancements in Artificial Intelligence (AI) and Machine Learning (ML), we have seen a rise in the use of bots, specifically chatbots, to deliver information services. Motivated by the Smart Nation programme, these chatbots have sprung up in sectors as transport, healthcare, banking and education in Singapore. What are these chatbots? How do they work? Will they take our jobs? SMU Libraries tries to answer these questions by delving into the mechanics of creating chatbots. The proof-of-concept aims to find out and understand use cases where these bots can be useful to delivering library information services to its campus community. …

Weakly-Admissible Semantics And The Propagation Of Ambiguity In Abstract Argumentation Semantics, Pierpaolo Dondio

Other

The concept of ambiguous literals of defeasible logics is mapped to the set of undecided arguments identified by an argumentation semantics. It follows that Dung’s complete semantics are all ambiguity propagating, since the undecided status of an attacking argument is always propagated to the attacked argument, unless the latter is defeated by another accepted argument. In this paper we investigate a novel family of abstract argumentation semantics, called weakly-admissible semantics, where we do not require an acceptable argument to be necessarily defended from the attacks of undecided arguments. Weakly-admissible semantics are conflict-free, ambiguity blocking, non-admissible (in Dung’s sense), but employing …

Culture Clubs: Processing Speech By Deriving And Exploiting Linguistic Subcultures, David Guy Brizan

Dissertations, Theses, and Capstone Projects

Spoken language understanding systems are error-prone for several reasons, including individual speech variability. This is manifested in many ways, among which are differences in pronunciation, lexical inventory, grammar and disfluencies. There is, however, a lot of evidence pointing to stable language usage within subgroups of a language population. We call these subgroups linguistic subcultures.

The two broad problems are defined and a survey of the work in this space is performed. The two broad problems are: linguistic subculture detection, commonly performed via Language Identification, Accent Identification or Dialect Identification approaches; and speech and language processing tasks taken which may see …

Deep Learning Based Medical Image Analysis With Limited Data, Jiaxing Tan

Dissertations, Theses, and Capstone Projects

Deep Learning Methods have shown its great effort in the area of Computer Vision. However, when solving the problems of medical imaging, deep learning’s power is confined by limited data available. We present a series of novel methodologies for solving medical imaging analysis problems with limited Computed tomography (CT) scans available. Our method, based on deep learning, with different strategies, including using Generative Adversar- ial Networks, two-stage training, infusing the expert knowledge, voting based or converting to other space, solves the data set limitation issue for the cur- rent medical imaging problems, specifically cancer detection and diagnosis, and shows very …

Artificial Intelligence Hits The Barrier Of Meaning, Melanie Mitchell

Computer Science Faculty Publications and Presentations

Today’s AI systems sorely lack the essence of human intelligence: Understanding the situations we experience, being able to grasp their meaning. The lack of humanlike understanding in machines is underscored by recent studies demonstrating lack of robustness of state-of-the-art deep-learning systems. Deeper networks and larger datasets alone are not likely to unlock AI’s “barrier of meaning”; instead the field will need to embrace its original roots as an interdisciplinary science of intelligence.

Transnfcm: Translation-Based Neural Fashion Compatibility Modeling, Xun Yang, Yunshan Ma, Lizi Liao, Meng Wang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Identifying mix-and-match relationships between fashion items is an urgent task in a fashion e-commerce recommender system. It will significantly enhance user experience and satisfaction. However, due to the challenges of inferring the rich yet complicated set of compatibility patterns in a large e-commerce corpus of fashion items, this task is still underexplored. Inspired by the recent advances in multi-relational knowledge representation learning and deep neural networks, this paper proposes a novel Translation-based Neural Fashion Compatibility Modeling (TransNFCM) framework, which jointly optimizes fashion item embeddings and category-specific complementary relations in a unified space via an end-to-end learning manner. TransNFCM places items …