Computer Sciences Commons^™

An Efficient Transformer-Based Model For Vietnamese Punctuation Prediction, Hieu Tran, Cuong V. Dinh, Hong Quang Pham, Binh T. Nguyen

Research Collection School Of Computing and Information Systems

In both formal and informal texts, missing punctuation marks make the texts confusing and challenging to read. This paper aims to conduct exhaustive experiments to investigate the benefits of the pre-trained Transformer-based models on two Vietnamese punctuation datasets. The experimental results show our models can achieve encouraging results, and adding Bi-LSTM or/and CRF layers on top of the proposed models can also boost model performance. Finally, our best model can significantly bypass state-of-the-art approaches on both the novel and news datasets for the Vietnamese language. It can gain the corresponding performance up to 21.45%21.45% and 18.27%18.27% in the overall F1-scores.

Stealing Deep Reinforcement Learning Models For Fun And Profit, Kangjie Chen, Shangwei Guo, Tianwei Zhang, Xiaofei Xie, Yang Liu

Research Collection School Of Computing and Information Systems

This paper presents the first model extraction attack against Deep Reinforcement Learning (DRL), which enables an external adversary to precisely recover a black-box DRL model only from its interaction with the environment. Model extraction attacks against supervised Deep Learning models have been widely studied. However, those techniques cannot be applied to the reinforcement learning scenario due to DRL models' high complexity, stochasticity and limited observable information. We propose a novel methodology to overcome the above challenges. The key insight of our approach is that the process of DRL model extraction is equivalent to imitation learning, a well-established solution to learn …

Simulating Subject Communities In Case Law Citation Networks, Jerrold Tsin Howe Soh

Research Collection Yong Pung How School Of Law

We propose and evaluate generative models for case law citation networks that account for legal authority, subject relevance, and time decay. Since Common Law systems rely heavily on citations to precedent, case law citation networks present a special type of citation graph which existing models do not adequately reproduce. We describe a general framework for simulating node and edge generation processes in such networks, including a procedure for simulating case subjects, and experiment with four methods of modelling subject relevance: using subject similarity as linear features, as fitness coefficients, constraining the citable graph by subject, and computing subject-sensitive PageRank scores. …

A Look Into Increasing The Number Of Veterans And Former Government Employees Converting To Career And Technical Cybersecurity Teachers, Vukica M. Jovanovic, Michael Anthony Crespo, Drew E. Brown, Deborah Marshall, Otilia Popescu, Murat Kuzlu, Petros J. Katsioloudis, Linda Vahala

Engineering Technology Faculty Publications

The current state of technology with recent explosions in the digital processing of paperwork, computer networking use, and online and virtual approaches to areas, which until very recently had traditional and non-computerized ways of operating, led to a steady increase in the demand for jobs in the area of computer science and cybersecurity. The education system, the pipeline for the incoming workforce, needs to keep up with this tremendous pace in technology and the job market. The current K-12 school system has been extensively challenged to fill out necessary positions in order to address the increasing need for programs that …

Frameaxis: Characterizing Microframe Bias And Intensity With Word Embedding, Haewoon Kwak, Jisun An, Elise Jing Jing, Yong-Yeol Ahn

Research Collection School Of Computing and Information Systems

Framing is a process of emphasizing a certain aspect of an issue over the others, nudging readers or listeners towards different positions on the issue even without making a biased argument. Here, we propose FrameAxis, a method for characterizing documents by identifying the most relevant semantic axes (“microframes”) that are overrepresented in the text using word embedding. Our unsupervised approach can be readily applied to large datasets because it does not require manual annotations. It can also provide nuanced insights by considering a rich set of semantic axes. FrameAxis is designed to quantitatively tease out two important dimensions of how …

Order-Agnostic Cross Entropy For Non-Autoregressive Machine Translation, Cunxiao Du, Zhaopeng Tu, Jing Jiang

Research Collection School Of Computing and Information Systems

We propose a new training objective named orderagnostic cross entropy (OAXE) for fully nonautoregressive translation (NAT) models. OAXE improves the standard cross-entropy loss to ameliorate the effect of word reordering, which is a common source of the critical multimodality problem in NAT. Concretely, OAXE removes the penalty for word order errors, and computes the cross entropy loss based on the best possible alignment between model predictions and target tokens. Since the log loss is very sensitive to invalid references, we leverage cross entropy initialization and loss truncation to ensure the model focuses on a good part of the search space. …

A Coprocessor-Based Introspection Framework Via Intel Management Engine, Lei Zhou, Fengwei Zhang, Jidong Xiao, Kevin Leach, Westley Weimer, Xuhua Ding, Guojun Wang

Research Collection School Of Computing and Information Systems

During the past decade, virtualization-based (e.g., virtual machine introspection) and hardware-assisted approaches (e.g., x86 SMM and ARM TrustZone) have been used to defend against low-level malware such as rootkits. However, these approaches either require a large Trusted Computing Base (TCB) or they must share CPU time with the operating system, disrupting normal execution. In this article, we propose an introspection framework called NIGHTHAWK that transparently checks system integrity and monitor the runtime state of target system. NIGHTHAWK leverages the Intel Management Engine (IME), a co-processor that runs in isolation from the main CPU. By using the IME, our approach has …

Recent Advances In Network-Based Methods For Disease Gene Prediction, Sezin Kircali Ata, Min Wu, Yuan Fang, Ou-Yang Le, Chee Keong Kwoh, Xiao-Li Li

Research Collection School Of Computing and Information Systems

Disease-gene association through Genome-wide association study (GWAS) is an arduous task for researchers. Investigating single nucleotide polymorphisms (SNPs) that correlate with specific diseases needs statistical analysis of associations. Considering the huge number of possible mutations, in addition to its high cost, another important drawback of GWAS analysis is the large number of false-positives. Thus, researchers search for more evidence to cross-check their results through different sources. To provide the researchers with alternative and complementary low-cost disease-gene association evidence, computational approaches come into play. Since molecular networks are able to capture complex interplay among molecules in diseases, they become one of …

Exploring Cross-Modality Utilization In Recommender Systems, Quoc Tuan Truong, Aghiles Salah, Thanh-Binh Tran, Jingyao Guo, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Multimodal recommender systems alleviate the sparsity of historical user-item interactions. They are commonly catalogued based on the type of auxiliary data (modality) they leverage, such as preference data plus user-network (social), user/item texts (textual), or item images (visual) respectively. One consequence of this categorization is the tendency for virtual walls to arise between modalities. For instance, a study involving images would compare to only baselines ostensibly designed for images. However, a closer look at existing models' statistical assumptions about any one modality would reveal that many could work just as well with other modalities. Therefore, we pursue a systematic investigation …

The Multi-Vehicle Cycle Inventory Routing Problem: Formulation And A Metaheuristic Approach, Vincent F. Yu, Audrey Tedja Widjaja, Aldy Gunawan, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

This paper presents a new variant of the Multi-Vehicle Cyclic Inventory Routing Problem (MV-CIRP) which aims to determine a subset of customers to be visited, the appropriate number of vehicles used, and the corresponding cycle time and route sequence, such that the total cost (e.g. transportation, inventory, and rewards) is minimized. The MV-CIRP is formulated as a mixed-integer nonlinear programming model. We propose a Simulated Annealing (SA) based algorithm to solve the problem. SA is first tested on the available benchmark Single-Vehicle CIRP (SV-CIRP) instances and compared to the state-of-the-art algorithms. SA is then tested on the benchmark MV-CIRP instances …

On The Generalizability Of Neural Program Models With Respect To Semantic-Preserving Program Transformations, Md Rafiqul Islam Rabin, Nghi D. Q. Bui, Ke Wang, Yijun Yu, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Context: With the prevalence of publicly available source code repositories to train deep neural network models, neural program models can do well in source code analysis tasks such as predicting method names in given programs that cannot be easily done by traditional program analysis techniques. Although such neural program models have been tested on various existing datasets, the extent to which they generalize to unforeseen source code is largely unknown. Objective: Since it is very challenging to test neural program models on all unforeseen programs, in this paper, we propose to evaluate the generalizability of neural program models with respect …

Vibransee: Enabling Simultaneous Visible Light Communication And Sensing, Ila Nitin Gokarn, Archan Misra

Research Collection School Of Computing and Information Systems

Driven by the ubiquitous proliferation of low-cost LED luminaires, visible light communication (VLC) has been established as a high-speed communications technology based on the high-frequency modulation of an optical source. In parallel, Visible Light Sensing (VLS) has recently demonstrated how vision-based at-a-distance sensing of mechanical vibrations (e.g., of factory equipment) can be performed using high frequency optical strobing. However, to date, exemplars of VLC and VLS have been explored in isolation, without consideration of their mutual dependencies. In this work, we explore whether and how high-throughput VLC and high-coverage VLS can be simultaneously supported. We first demonstrate the existence of …

Efficient White-Box Fairness Testing Through Gradient Search, Lingfeng Zhang, Yueling Zhang, Min Zhang

Research Collection School Of Computing and Information Systems

Deep learning (DL) systems are increasingly deployed for autonomous decision-making in a wide range of applications. Apart from the robustness and safety, fairness is also an important property that a well-designed DL system should have. To evaluate and improve individual fairness of a model, systematic test case generation for identifying individual discriminatory instances in the input space is essential. In this paper, we propose a framework EIDIG for efficiently discovering individual fairness violation. Our technique combines a global generation phase for rapidly generating a set of diverse discriminatory seeds with a local generation phase for generating as many individual discriminatory …

Task Similarity Aware Meta Learning: Theory-Inspired Improvement On Maml, Pan Zhou, Yingtian Zpu, Xiaotong Yuan, Jiashi Feng, Caiming Xiong, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Few-shot learning ability is heavily desired for machine intelligence. By meta-learning a model initialization from training tasks with fast adaptation ability to new tasks, model-agnostic meta-learning (MAML) has achieved remarkable success in a number of few-shot learning applications. However, theoretical understandings on the learning ability of MAML remain absent yet, hindering developing new and more advanced meta learning methods in a principled way. In this work, we solve this problem by theoretically justifying the fast adaptation capability of MAML when applied to new tasks. Specifically, we prove that the learnt meta-initialization can benefit the fast adaptation to new tasks with …

Bias Field Poses A Threat To Dnn-Based X-Ray Recognition, Bingyu Tian, Qing Guo, Felix Juefei-Xu, Wen Le Chan, Yupeng Cheng, Xiaohong Li, Xiaofei Xie, Shengchao Qin

Research Collection School Of Computing and Information Systems

Chest X-ray plays a key role in screening and diagnosis of many lung diseases including the COVID-19. Many works construct deep neural networks (DNNs) for chest X-ray images to realize automated and efficient diagnosis of lung diseases. However, bias field caused by the improper medical image acquisition process widely exists in the chest X-ray images while the robustness of DNNs to the bias field is rarely explored, posing a threat to the X-ray-based automated diagnosis system. In this paper, we study this problem based on the adversarial attack and propose a brand new attack, i.e., adversarial bias field attack where …

Addressing The ‘Unseens’: Digital Wellbeing In The Remote Workplace, Holtjona Galanxhi, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

The ubiquity of sophisticated devices, along with uninterrupted access to the Internet and organizational computerized systems, allows for the “anyplace” workplace to be established. Technology has the potential to deliberately or inadvertently impact psychological wellbeing. Specific psychological demands are inadvertently imposed on remote employees whose permanent online presence is required. Hence, it is important to understand factors affecting digital wellbeing and steps that can be taken to maximize the wellbeing of remote employees. This paper provides suggestions for future research on studying the digital wellbeing of (fully or partially) remote employees. A research framework is proposed to demonstrate the different …

Make It Easy: An Effective End-To-End Entity Alignment Framework, Congcong Ge, Xiaoze Liu, Lu Chen Chen, Baihua Zheng, Yunjun Gao

Research Collection School Of Computing and Information Systems

Entity alignment (EA) is a prerequisite for enlarging the coverage of a unified knowledge graph. Previous EA approaches either restrain the performance due to inadequate information utilization or need labor-intensive pre-processing to get external or reliable information to perform the EA task. This paper proposes EASY, an effective end-to-end EA framework, which is able to (i) remove the labor-intensive pre-processing by fully discovering the name information provided by the entities themselves; and (ii) jointly fuse the features captured by the names of entities and the structural information of the graph to improve the EA results. Specifically, EASY first introduces NEAP, …

Measuring The Relationship Of Gender Misclassification And Automated Face Recognition Match Accuracy Relative To Skin Tone, Afi Edem-Edi Gbekevi

Theses and Dissertations

The gap of accuracy observed in some commercial face analytic systems based on race and gender raised questions about the equity and fairness of those systems. Since these systems are part of several applications today, some more critical than others, it urges designers to detect and mitigate any sources of bias. In this thesis, we begin by clarifying the confusion between face analytic, face recognition, and face processing systems. Then, we analyze gender classification accuracy using two datasets and three classifiers. The Pilot Parliaments Benchmark dataset is examined with an open-source algorithm to corroborate the gender shade. Secondly, the Morph …

Move: Mobile Observers Variants And Extensions, Ryan Florin

Computer Science Theses & Dissertations

Traffic state estimation is a fundamental task of Intelligent Transportation Systems. Recent advances in sensor technology and emerging computer and vehicular communications paradigms have brought the task of estimating traffic state parameters in real-time within reach.

This has led to the main research question of this thesis: Can a vehicle accurately estimate traffic parameters using onboard resources shared through CV technology in a lightweight manner without utilizing centralized or roadside infrastructure?

In 1954 Wardrop and Charlesworth proposed the Moving Observer method to measure traffic parameters based on an observed number of vehicle passes. We start by proposing methods for detecting …

Methods For Detecting Floodwater On Roadways From Ground Level Images, Cem Sazara

Computational Modeling & Simulation Engineering Theses & Dissertations

Recent research and statistics show that the frequency of flooding in the world has been increasing and impacting flood-prone communities severely. This natural disaster causes significant damages to human life and properties, inundates roads, overwhelms drainage systems, and disrupts essential services and economic activities. The focus of this dissertation is to use machine learning methods to automatically detect floodwater in images from ground level in support of the frequently impacted communities. The ground level images can be retrieved from multiple sources, including the ones that are taken by mobile phone cameras as communities record the state of their flooded streets. …

Analysis Of The Slo Bay Microbiome From A Network Perspective, Lien Viet Nguyen

Master's Theses

Microorganisms are key players in the ecosystem functioning. In this thesis, we developed a framework to preprocess raw microbiome data, build a correlation network, and analyze co-occurrence patterns between microbes. We then applied this framework to a marine microbiome dataset. The dataset used in this study comes from a year-long time-series to characterize the microbial communities in our coastal waters off the Cal Poly Pier. In analyzing this dataset, we were able to observe and confirm previously discovered patterns of interactions and generate hypotheses about new patterns. The analysis of co-occurrences between prokaryotic and eukaryotic taxa is relatively novel and …

A Digital One Degree Of Freedom Model Of An Electromagnetic Position Sensor, Michelle Elizabeth Weinmann

Mechanical & Aerospace Engineering Theses & Dissertations

The purpose of this project was to improve an existing system currently in use by NASA Langley Research Center (LaRC). The 6-inch Magnetic Suspension and Balance System (MSBS) built at MIT is operational with control in three degrees of freedom, with two additional degrees of freedom exhibiting passive stability. The means for measuring model displacement within the magnetic environment is an Electromagnetic Position Sensor (EPS), consisting of excitation coils at 20 kHz and multiple sets of pickup coils. The pickup coil voltages are proportional to model displacement in each degree of freedom. However, the EPS electronic signal processing system is …

Effect Of Excess Tellurium And Lead On Defor-Mation - Characteristics Of Polycrystalline Pbte Films, Yu.Yu. Vaitkus, Otajonov Salimjon

Scientific Bulletin. Physical and Mathematical Research

In this work, we studied the ef-fect of excess tellurium and lead on the defor-mation characteristics of polycrystalline PbTe films obtained on different substrates. It was found that the resistance of the films first increases and reach-es a maximum, and with a further increase in the level of deformation, it decreases and the sign of the tensile resistance begins to change, which are associated with the presence of internal stresses in the films. It was also shown that with an increase in the amount of lead in the composition of the PbTe film, the electrical conductivity increases in com-parison with …

Structure And Electrophysical Properties Of A Solid Solution (Gaas1-Δbiδ)1-X-Y(Ge2)X(Znse)Y, S.Z. Zainabidinov, I.N. Karimov, Hotamjon Mansurov, Akramjon Boboev, Dilkhayotjon Pulatjon Ugli Abdurakhimov

Scientific Bulletin. Physical and Mathematical Research

This paper shows the possibility of growing a single-crystal solid solution of substitution (GaAs1-δBiδ)1-x-y(Ge2)x(ZnSe)y on GaAs substrates by liquid-phase epitaxy from a bismuthcontaining solution-melt. The grown films had a ptype of conductivity with a current carrier concentration of 1,86·1017 сm-3, a mobility of р = 300 cm2/V·s, and a resistivity of 0,13 Ohms·cm. Structural studies have shown that the epitaxial films have a sphalerite structure of the ZnS type and are monocrystalline with an orientation of (100). The crystal lattice parameter of the film was af = 0,56697 nm. Studies of current-voltage characteris-tics of n-GaAs – p-(GaAs1-δBiδ)1-x-y(Ge2)x(ZnSe)y heterostructures at different …

Simulation Of Self-Heating Effect In Mosfet Based On 2d Mos2, Atabek E. Atamuratov, Xushnudbek Sh. Saparov, A Yusupov, Frank Schwierz

Scientific Bulletin. Physical and Mathematical Research

One of the main trends of today's electronics is the decreasing the sizes of MOSFET up to nanometer scale. In this connection there are two main views to the perspective of scaling. According to one of them limit of scaling is reached at sizes 10 nm order, however according to second view, still there are opportunity to decrease transistor to more lower sizes. In accordance with second approach it is suggested to continue the size scaling by modification the transistor structure or by using the new materials, particularly one or two dimensional materials. One of such suggestions is the designing …

Method Of Characteristics For Solving The Problem Of Gas Outflow From An Elementary Sec-Tion Of A Gas Pipeline, Madaminjon K. Mahkamov, S.S. Akhmadjonov, I.K. Khujaev

Scientific Bulletin. Physical and Mathematical Research

Numerous problems based on equations of hyperbolic type are solved by the method of characteristics when boundary conditions of the first, second and third kinds are set on the boundary. These include, in particular, the problems of pipeline transportation of various media. The quasi-one-dimensional equations of conservation of mass and momentum are linearized and separate equations are drawn up for a specific indicator (flow rate, gas pressure) of the process. This approach is associated with the tradition of forming boundary conditions and solving problems only with respect to a specific indicator, in particu-lar, with respect to pressure, velocity, and flow …

Electrophysical Properties Of Supercapacitor On The Basis Of New Gel Polymer Electrolyte, J.A. Shodmanov, Azamat Boymirzaev

Scientific Bulletin. Physical and Mathematical Research

The results showed a slight increase in internal resistance under the influence of bending and confirmed that the equivalent circuit model of electrons did not change under bending conditions as indicated in graphically illustrated the results by cyclic voltamperometry (TsV) at a scanning speed of 10 mV / s under the above bending angles of the SK prepared on the basis of PG 10 GPE. From ex-periments we found that the shapes are almost rec-tangular, with no redox peaks observed. We can see that the area of the TsV curves changes slightly as the bending angle increases, but this does …

Influence Of A Strong Magnetic Field On Fermi Energy Oscillations In Two-Dimensional Semiconductor Materials, Gafur Gulyamov, Ulugbek Inayatillyevich Erkaboev, Rustam Gulomzhonovich Rakhimov, Nozimjon Sayidov Sayidov, Jasurbek Mirzaev

Scientific Bulletin. Physical and Mathematical Research

This article discusses the effect of a quantizing magnetic field and temperature on Fermi energy oscillations in nanoscale semiconductor materials. A generalized mathematical expression is obtained for calculating the dependence of the Fermi energy oscillations on the magnetic field, temperature, and thickness of the quantum well. It is shown that the Fermi energy in nanoscale semiconductor materials under a quantizing magnetic field is quantized. The proposed theory explains the experimental results in two-dimensional semiconductor structures with a parabolic dispersion law.

Determination Of The Specific Thermo Emf Of Granulated Silicon Doped With Alkaline Metals., B.M. Abdurakhmanov, Zarnigor Sohibova, M.M. Adilov

Scientific Bulletin. Physical and Mathematical Research

The value of the specific thermo EMF is one of the most important thermoelectric parameters of a material and in practice is estimat-ed mainly by two well-known methods - integral and differential. To measure the thermo EMF of granular silicon, we used a differential method. In this work, the thermoelectric properties of granular silicon containing alkali metal atoms have been studied, the presence of which, for example, in single-crystal structures makes it possible to improve the characteristics of a number of devices, and in polycrystalline ones, the effect of grain boundaries on the electrical properties, in particular, to reduce the …

The State Of Solar Energy In Uzbekistan In The Framework Of The Devel-Opment Of Renewable Energy Sources, E.Z. Imamov, Ramizulla Abdullaevich Muminov, Temur Asfandiyarovich Djalalov, I.Sh. Abdullaeva

Scientific Bulletin. Physical and Mathematical Research

The paper analyzes the possibilities of renewable energy sources to become the main sources of ener-gy that can in the future replace traditional technologies for the production of thermal and electrical energy based on the use of fossil fuels and nuclear energy.

Technological approaches are considered that make it possible to significantly increase the efficiency of solar energy, and it is also shown that such a possibility can be realized by using weakly crystalline and cheap modifications of silicon, which have previously passed the corresponding nanotechnological effect.