Digital Commons Network^™

Threshold Attribute-Based Credentials With Redactable Signature, Rui Shi, Huamin Feng, Yang Yang, Feng Yuan, Yingjiu Li, Hwee Hwa Pang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Threshold attribute-based credentials are suitable for decentralized systems such as blockchains as such systems generally assume that authenticity, confidentiality, and availability can still be guaranteed in the presence of a threshold number of dishonest or faulty nodes. Coconut (NDSS'19) was the first selective disclosure attribute-based credentials scheme supporting threshold issuance. However, it does not support threshold tracing of user identities and threshold revocation of user credentials, which is desired for internal governance such as identity management, data auditing, and accountability. The communication and computation complexities of Coconut for verifying credentials are linear in the number of each user's attributes and …

K-St: A Formal Executable Semantics Of The Structured Text Language For Plcs, Kun Wang, Jingyi Wang, Christopher M. Poskitt, Xiangxiang Chen, Jun Sun, Peng Cheng

Research Collection School Of Computing and Information Systems

Programmable Logic Controllers (PLCs) are responsible for automating process control in many industrial systems (e.g. in manufacturing and public infrastructure), and thus it is critical to ensure that they operate correctly and safely. The majority of PLCs are programmed in languages such as Structured Text (ST). However, a lack of formal semantics makes it difficult to ascertain the correctness of their translators and compilers, which vary from vendor-to-vendor. In this work, we develop K-ST, a formal executable semantics for ST in the K framework. Defined with respect to the IEC 61131-3 standard and PLC vendor manuals, K-ST is a high-level …

Experimental Comparison Of Features, Analyses, And Classifiers For Android Malware Detection, Lwin Khin Shar, Biniam Fisseha Demissie, Mariano Ceccato, Naing Tun Yan, David Lo, Lingxiao Jiang, Christoph Bienert

Research Collection School Of Computing and Information Systems

Android malware detection has been an active area of research. In the past decade, several machine learning-based approaches based on different types of features that may characterize Android malware behaviors have been proposed. The usually-analyzed features include API usages and sequences at various abstraction levels (e.g., class and package), extracted using static or dynamic analysis. Additionally, features that characterize permission uses, native API calls and reflection have also been analyzed. Initial works used conventional classifiers such as Random Forest to learn on those features. In recent years, deep learning-based classifiers such as Recurrent Neural Network have been explored. Considering various …

Generative Model-Based Testing On Decision-Making Policies, Zhuo Li, Xiongfei Wu, Derui Zhu, Mingfei Cheng, Siyuan Chen, Fuyuan Zhang, Xiaofei Xie, Lei Ma, Jianjun Zhao

Research Collection School Of Computing and Information Systems

The reliability of decision-making policies is urgently important today as they have established the fundamentals of many critical applications, such as autonomous driving and robotics. To ensure reliability, there have been a number of research efforts on testing decision-making policies that solve Markov decision processes (MDPs). However, due to the deep neural network (DNN)-based inherit and infinite state space, developing scalable and effective testing frameworks for decision-making policies still remains open and challenging.In this paper, we present an effective testing framework for decision-making policies. The framework adopts a generative diffusion model-based test case generator that can easily adapt to different …

Edge Distraction-Aware Salient Object Detection, Sucheng Ren, Wenxi Liu, Jianbo Jiao, Guoqiang Han, Shengfeng He

Research Collection School Of Computing and Information Systems

Integrating low-level edge features has been proven to be effective in preserving clear boundaries of salient objects. However, the locality of edge features makes it difficult to capture globally salient edges, leading to distraction in the final predictions. To address this problem, we propose to produce distraction-free edge features by incorporating cross-scale holistic interdependencies between high-level features. In particular, we first formulate our edge features extraction process as a boundary-filling problem. In this way, we enforce edge features to focus on closed boundaries instead of those disconnected background edges. Second, we propose to explore cross-scale holistic contextual connections between every …

Grasp Solution Approach For The E-Waste Collection Problem, Aldy Gunawan, Dang Viet Anh Nguyen, Pham Kien Minh Nguyen, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

The digital economy has brought significant advancements in electronic devices, increasing convenience and comfort in people’s lives. However, this progress has also led to a shorter life cycle for these devices due to rapid advancements in hardware and software technology. As a result, e-waste collection and recycling have become vital for protecting the environment and people’s health. From the operations research perspective, the e-waste collection problem can be modeled as the Heterogeneous Vehicle Routing Problem with Multiple Time Windows (HVRP-MTW). This study proposes a metaheuristic based on the Greedy Randomized Adaptive Search Procedure complemented by Path Relinking (GRASP-PR) to solve …

When Routing Meets Recommendation: Solving Dynamic Order Recommendations Problem In Peer-To-Peer Logistics Platforms, Zhiqin Zhang, Waldy Joe, Yuyang Er, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Peer-to-Peer (P2P) logistics platforms, unlike traditional last-mile logistics providers, do not have dedicated delivery resources (both vehicles and drivers). Thus, the efficiency of such operating model lies in the successful matching of demand and supply, i.e., how to match the delivery tasks with suitable drivers that will result in successful assignment and completion of the tasks. We consider a Same-Day Delivery Problem (SDDP) involving a P2P logistics platform where new orders arrive dynamically and the platform operator needs to generate a list of recommended orders to the crowdsourced drivers. We formulate this problem as a Dynamic Order Recommendations Problem (DORP). …

Autodebloater: Automated Android App Debloating, Jiakun Liu, Xing Hu, Thung Ferdian, Shahar Maoz, Eran Toch, Debin Gao, David Lo

Research Collection School Of Computing and Information Systems

Android applications are getting bigger with an increasing number of features. However, not all the features are needed by a specific user. The unnecessary features can increase the attack surface and cost additional resources (e.g., storage and memory). Therefore, it is important to remove unnecessary features from Android applications. However, it is difficult for the end users to fully explore the apps to identify the unnecessary features, and there is no off-the-shelf tool available to assist users to debloat the apps by themselves. In this work, we propose AutoDebloater to debloat Android applications automatically for end users. AutoDebloater is a …

Hercules: Boosting The Performance Of Privacy-Preserving Federated Learning, Guowen Xu, Xingshuo Han, Shengmin Xu, Tianwei Zhang, Hongwei Li, Xinyi Huang, Robert H. Deng

Research Collection School Of Computing and Information Systems

In this paper, we address the problem of privacy-preserving federated neural network training with N users. We present Hercules, an efficient and high-precision training framework that can tolerate collusion of up to N−1 users. Hercules follows the POSEIDON framework proposed by Sav et al. (NDSS’21), but makes a qualitative leap in performance with the following contributions: (i) we design a novel parallel homomorphic computation method for matrix operations, which enables fast Single Instruction and Multiple Data (SIMD) operations over ciphertexts. For the multiplication of two h×h dimensional matrices, our method reduces the computation complexity from O(h3) to O(h) . This …

Graph-Level Anomaly Detection Via Hierarchical Memory Networks, Chaoxi Niu, Guansong Pang, Ling Chen

Research Collection School Of Computing and Information Systems

Graph-level anomaly detection aims to identify abnormal graphs that exhibit deviant structures and node attributes compared to the majority in a graph set. One primary challenge is to learn normal patterns manifested in both fine-grained and holistic views of graphs for identifying graphs that are abnormal in part or in whole. To tackle this challenge, we propose a novel approach called Hierarchical Memory Networks (HimNet), which learns hierarchical memory modules---node and graph memory modules---via a graph autoencoder network architecture. The node-level memory module is trained to model fine-grained, internal graph interactions among nodes for detecting locally abnormal graphs, while the …

Understanding Multi-Homing And Switching By Platform Drivers, Xiaotong Guo, Andreas Haupt, Hai Wang, Rida Qadri, Jinhua Zhao

Research Collection School Of Computing and Information Systems

Freelance drivers in the shared mobility market frequently switch or work for multiple platforms, affecting driver labor supply. Due to the importance of driver labor supply for the shared mobility market, understanding drivers’ switching and multi-homing behavior is vital to managing service quality on – and effective regulation of – mobility platforms. However, a lack of individual-level data on driver behavior has thus far impeded a deeper understanding. This paper taxonomizes and estimates perceived switching and multi-homing frictions on mobility platforms. Based on a structural model of driver labor supply, we estimate switching and multi-homing costs in a platform duopoly …

Arduinoprog: Towards Automating Arduino Programming, Imam Nur Bani Yusuf, Diyanah Binte Abdul Jamal, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Writing code for Arduino poses unique challenges. A developer 1) needs hardware-specific knowledge about the interface configuration between the Arduino controller and the I/Ohardware, 2) identifies a suitable driver library for the I/O hardware, and 3) follows certain usage patterns of the driver library in order to use them properly. In this work, based on a study of real-world user queries posted in the Arduino forum, we propose ArduinoProg to address such challenges. ArduinoProg consists of three components, i.e., Library Retriever, Configuration Classifier, and Pattern Generator. Given a query, Library Retriever retrieves library names relevant to the I/O hardware identified …

Are We Ready To Embrace Generative Ai For Software Q&A?, Bowen Xu, Thanh-Dat Nguyen, Thanh Le-Cong, Thong Hoang, Jiakun Liu, Kisub Kim, Chen Gong, Changan Niu, Chenyu Wang, David Lo, David Lo

Research Collection School Of Computing and Information Systems

Stack Overflow, the world's largest software Q&A (SQA) website, is facing a significant traffic drop due to the emergence of generative AI techniques. ChatGPT is banned by Stack Overflow after only 6 days from its release. The main reason provided by the official Stack Overflow is that the answers generated by ChatGPT are of low quality. To verify this, we conduct a comparative evaluation of human-written and ChatGPT-generated answers. Our methodology employs both automatic comparison and a manual study. Our results suggest that human-written and ChatGPT-generated answers are semantically similar, however, human-written answers outperform ChatGPT-generated ones consistently across multiple aspects, …

The Devil Is In The Tails: How Long-Tailed Code Distributions Impact Large Language Models, Xin Zhou, Kisub Kim, Bowen Xu, Jiakun Liu, Donggyun Han, David Lo

Research Collection School Of Computing and Information Systems

Learning-based techniques, especially advanced Large Language Models (LLMs) for code, have gained considerable popularity in various software engineering (SE) tasks. However, most existing works focus on designing better learning-based models and pay less attention to the properties of datasets. Learning-based models, including popular LLMs for code, heavily rely on data, and the data's properties (e.g., data distribution) could significantly affect their behavior. We conducted an exploratory study on the distribution of SE data and found that such data usually follows a skewed distribution (i.e., long-tailed distribution) where a small number of classes have an extensive collection of samples, while a …

Real: A Representative Error-Driven Approach For Active Learning, Cheng Chen, Yong Wang, Lizi Liao, Yueguo Chen, Xiaoyong Du

Research Collection School Of Computing and Information Systems

Given a limited labeling budget, active learning (al) aims to sample the most informative instances from an unlabeled pool to acquire labels for subsequent model training. To achieve this, al typically measures the informativeness of unlabeled instances based on uncertainty and diversity. However, it does not consider erroneous instances with their neighborhood error density, which have great potential to improve the model performance. To address this limitation, we propose Real, a novel approach to select data instances with Representative Errors for Active Learning. It identifies minority predictions as pseudo errors within a cluster and allocates an adaptive sampling budget for …

A Learning‑Based Approach For Estimating Inertial Properties Of Unknown Objects From Encoder Discrepancies, Zizhou Lao, Yuanfeng Han, Yunshan Ma, Gregory S. Chirikjian

Research Collection School Of Computing and Information Systems

Many robots utilize commercial force/torque sensors to identify inertial properties of unknown objects. However, such sensors can be difficult to apply to small-sized robots due to their weight, size, and cost. In this letter, we propose a learning-based approach for estimating the mass and center of mass (COM) of unknown objects without using force/torque sensors at the end effector or on the joints. In our method, a robot arm carries an unknown object as it moves through multiple discrete configurations. Measurements are collected when the robot reaches each discrete configuration and stops. A neural network then estimates joint torques from …

Do Metrics Improve When Continuity Of Care Nurses Follow Chronic Disease Patients In The Ambulatory Setting?, Lura Cynthia Lunsford

Electronic Theses and Dissertations

Navigating the complex, fragmented U.S. healthcare system presents patient challenges that result in increased utilization and consequent increases in the cost of care. This program evaluation was conducted to determine the impact of ambulatory assigned continuity of care nurses (COCN) on patient outcomes in terms of length of stay, return visits to the emergency department, and readmissions to the hospital within 30 days of discharge. Between June 1, 2020, and May 31, 2022, there were 26,912 admissions with general risk scores between 1 and 100. Undersampling technique was conducted to create a 1:2 balance of 3,502 patients admitted with an …

Exploring Habits Of Well-Being Rooted In Resiliency Among Ministry Leaders Having Experienced A Leadership Transition Of Senior Pastor In The Church: A Case Study, Eric D. Willis

Electronic Theses and Dissertations

This qualitative phenomenological single case study sought to understand potential influence of well-being and resilience of ministry leaders where an unplanned leadership transition had occurred. With an interest in personal well-being of ministry leaders, the researcher was curious how those who remained on church staff endured a 2-year period between the departure of one senior pastor and the hiring of a new senior pastor. Much of the existing research on church leadership transitions focused on the negative factors associated with failures. Generally, there is a lack of understanding of the positive influences of well-being and resiliency. The researcher sought to …

Mental Health Education For Nurses Caring For Adults With Severe Mental Illness, Juliet O. Onyia

Electronic Theses and Dissertations

The focus of this study was on mental health education for nurses who care for adults with severe mental illness. Severe mental illness is rising, and nurses cannot adequately provide quality patient-centered care to the population due to poor knowledge. In this study, the knowledge and perceptions of mental illness and care among registered nurses in the community were assessed before and immediately after a mental illness educational session. A non-experimental quantitative descriptive study was conducted using convenience sampling in a home health setting. Dorothea Orem's self-care theory was the theoretical framework that guided the project. Instruments included the Mental …

Experimental Investigation On Coal Fines Migration Through Proppant Packs: Assessing Variation Of Formation Damage And Filtration Coefficients, Faisal Ur Rahman Awan, Mohsen Farrokhrouz, Hamed Akhondzadeh, Stefan Iglauer, Alireza Keshavarz

Research outputs 2022 to 2026

Coalbed methane reservoirs generate coal fines during production that cause irreversible damage to cleat conductivity. In severe scenarios, this can result in temporary closure of recovery operations from the gas well(s). In this work, we simulate the impact of coal fines on proppant conductivity. Four sets of experiments were conducted: effect of salinity – 0 to 3.5 NaCl wt.%, pH – 2 to 11, coal rank - anthracite, high volatile bituminous, and sub-bituminous; and 0.01 wt% additives – Sodium Dodecyl Benzene Sulfonate (SDBS) and Cetrimonium bromide (CTAB) and validated with established analytical models. Moreover, medical computed tomography of three extreme …

Micro-Scale Wettability Of Carbonate Rocks Via High-Resolution Esem Imaging, Khaloud Al-Naimi, Muhammad Arif, Mahmoud Aboushanab, Dalaver Anjum, Mohammed Al Kobaisi, Md Motiur Rahman, Mohamed Mahmoud, Stefan Iglauer

Research outputs 2022 to 2026

The wettability of several materials has been traditionally quantified using macro-scale contact angles. However, precise identification of the three-phase contact (TPC) line is often difficult due to the resolution limit of macro-scale setups. Moreover, micro-level surface chemical heterogeneities can have a notable impact on the predicted wetting behavior which limits macro-scale contact angles. Thus, here, we investigate the micro-scale water wettability of condensed micro-droplets on carbonate rock surfaces via a high-resolution Environmental Scanning Electron Microscopy (ESEM). Macro- and micro-scale contact angles were evaluated under three conditions: 1) natural carbonate surfaces, 2) surfaces aged in crude oil, and 3) surfaces aged …

Rethinking Acting In Concert: Activist Esg Stewardship Is Shareholder Democracy, Dan W. Puchniak, Umakanth Varottil

Research Collection Yong Pung How School Of Law

In May 2021, Engine No. 1, an investment fund, was lauded by the responsible investment community for successfully placing three dissident independent directors on ExxonMobil’s board. It achieved this by being a catalyst for institutional investors to become backers of environmental shareholder activism. The unprecedented success of Engine No. 1’s campaign has spurred calls for a new, more sustained, activist engagement model by institutional investors, now known as “activist stewardship”.However, there is a significant legal hurdle that has been almost entirely overlooked by those calling for this new approach for institutional investors to become activist stewards: acting in concert rules. …

Public Sentiments And The Influence Of Information-Seeking Preferences On Knowledge, Attitudes, Death Conversation And Receptiveness Towards Palliative Care: Results From A Nationwide Survey In Singapore, Su Lin Yeo, Raymond Han Lip Ng, Tan Ying Peh, May O. Lwin, Poh Heng Chong, Patricia Soek Hui Neo, Jamie Xuelian Zhou, Angel Lee

Research Collection Lee Kong Chian School Of Business

Background: Low awareness about palliative care among the global public and healthcare communities has been frequently cited as a persistent barrier to palliative care acceptance. Given that knowledge shapes attitudes and encourages receptiveness, it is critical to examine factors that influence the motivation to increase knowledge. Health information-seeking from individuals and media has been identified as a key factor, as the process of accessing and interpreting information to enhance knowledge has been shown to positively impact health behaviours. Objective: Our study aimed to uncover public sentiments toward palliative care in Singapore. A conceptual framework was additionally developed to investigate the …

Characterization And Quantification Of Adeno-Associated Virus Capsid-Loading States By Multi-Wavelength Analytical Ultracentrifugation With Ultrascan, Zhe Qu, Lauren Tomlinson, John Forsey, Viviana Gradinaru, Kazuhiro Oka, Borries Demeler

Faculty, Staff and Students Publications

Aim:

We present multi-wavelength (MW) analytical ultracentrifugation (AUC) methods offering superior accuracy for adeno-associated virus characterization and quantification.

Methods:

Experimental design guidelines are presented for MW sedimentation velocity and analytical buoyant density equilibrium AUC.

Results:

Our results were compared with dual-wavelength AUC, transmission electron microscopy and mass photometry. In contrast to dual-wavelength AUC, MW-AUC correctly quantifies adeno-associated virus capsid ratios and identifies contaminants. In contrast to transmission electron microscopy, partially filled capsids can also be detected and quantified. In contrast to mass photometry, first-principle results are obtained.

Conclusion:

Our study demonstrates the improved information provided by MW-AUC, highlighting the utility …

System Strength Shortfall Challenges For Renewable Energy-Based Power Systems: A Review, Md O. Qays, Iftekhar Ahmad, Daryoush Habibi, Asma Aziz, Thair Mahmoud

Research outputs 2022 to 2026

Renewable energy sources such as wind farms and solar power plants are replacing conventional coal-based synchronous generators (SGs) to achieve net-zero carbon emissions worldwide. SGs play an important role in enhancing system strength in a power system to make it more stable during voltage/frequency disruptions. However, traditional coal-fired SGs are being decommissioned in many parts of the world, owing to stringent environmental regulations and low levelized cost of energy of renewables. Consequently, maintaining system strength in a renewable energy-dominated power system has become a major challenge, and without adequate mitigation techniques, low system strength can potentially cause widespread power outages. …

Low-Frequency Laboratory Measurements Of The Elastic Properties Of Solids Using A Distributed Acoustic Sensing System, Vassily Mikhaltsevitch, Maxim Lebedev, Roman Pevzner, Alexey Yurikov, Konstantin Tertyshnikov

Research outputs 2022 to 2026

In recent decades, low-frequency (LF) experiments based on the forced-oscillation (FO) method have become common practice in many rock physics laboratories for measuring the elastic and anelastic properties of rocks. However, the use of the electronic displacement sensors in traditional acquisition systems of FO devices such as conventional capacitive transducers or strain gauges seriously limits both the efficiency and productivity of LF measurements, and, due to the limited contact area of the displacement sensors with a sample under test, increases the requirements for sample homogeneity. In this paper, we present the first results obtained in the development of a new …

Photothermal Catalysis: From Fundamentals To Practical Applications, Jinqiang Zhang, Haijun Chen, Xiaoguang Duan, Hongqi Sun, Shaobin Wang

Research outputs 2022 to 2026

Photothermal catalysis is an innovative approach that integrates photochemical and thermocatalytic processes to enable an efficient use of full-spectrum sunlight in catalyzing various chemical reactions for energy conversion and environmental governance. This approach has demonstrated competitive performance and energy efficiency compared to conventional techniques, making it suitable for large-scale applications. In this review, we will comprehensively examine the fundamentals and classification of photothermal catalysis and discuss detailed design principles of various types of photothermal catalysts, focusing on enhancing solar light absorption, improving internal electric field for more energetic hot carriers (EHC) and localized thermal energy (LTE), interfacial engineering for robust …

Harnessing The Power Of Neural Networks For The Investigation Of Solar-Driven Membrane Distillation Systems Under The Dynamic Operation Mode, Pooria Behnam, Masoumeh Zargar, Abdellah Shafieian, Amir Razmjou, Mehdi Khiadani

Research outputs 2022 to 2026

Accurate modeling of solar-driven direct contact membrane distillation systems (DCMD) can enhance the commercialization of these promising systems. However, the existing dynamic mathematical models for predicting the performance of these systems are complex and computationally expensive. This is due to the intermittent nature of solar energy and complex heat/mass transfer of different components of solar-driven DCMD systems (solar collectors, MD modules and storage tanks). This study applies a machine learning-based approach to model the dynamic nature of a solar-driven DCMD system for the first time. A small-scale rig was designed and fabricated to experimentally assess the performance of the system …

Ceramic Particles Reinforced Copper Matrix Composites Manufactured By Advanced Powder Metallurgy: Preparation, Performance, And Mechanisms, Yi-Fan Yan, Shu-Qing Kou, Hong-Yu Yang, Shi-Li Shu, Feng Qiu, Qi-Chuan Jiang, Lai-Chang Zhang

Research outputs 2022 to 2026

Copper matrix composites doped with ceramic particles are known to effectively enhance the mechanical properties, thermal expansion behavior and high-temperature stability of copper while maintaining high thermal and electrical conductivity. This greatly expands the applications of copper as a functional material in thermal and conductive components, including electronic packaging materials and heat sinks, brushes, integrated circuit lead frames. So far, endeavors have been focusing on how to choose suitable ceramic components and fully exert strengthening effect of ceramic particles in the copper matrix. This article reviews and analyzes the effects of preparation techniques and the characteristics of ceramic particles, including …

Host Interactions Of Novel Crassvirales Species Belonging To Multiple Families Infecting Bacterial Host, Bacteroides Cellulosilyticus Wh2host Interactions Of Novel Crassvirales Species Belonging To Multiple Families Infecting Bacterial Host, Bacteroides Cellulosilyticus Wh2, Bhavya Papudeshi, Lindsay Droit, Scott A Handley, David Wang, Et Al.

2020-Current year OA Pubs

Bacteroides, the prominent bacteria in the human gut, play a crucial role in degrading complex polysaccharides. Their abundance is influenced by phages belonging to the