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Articles 2311 - 2340 of 4322

Full-Text Articles in Computer Sciences

Fusing Mobile, Wearable And Infrastructure Sensing For Immersive Daily Lifestyle Analytics, Sougata Sen Jun 2017

Fusing Mobile, Wearable And Infrastructure Sensing For Immersive Daily Lifestyle Analytics, Sougata Sen

Dissertations and Theses Collection

With the prevalence of sensors in public infrastructure as well as in personal devices, exploitation of data from these sensors to monitor and profile basic activities (e.g., locomotive states such as walking, and gestural actions such as smoking) has gained popularity. Basic activities identified by these sensors will drive the next generation of lifestyle monitoring applications and services. To provide more advanced and personalized services, these next-generation systems will need to capture and understand increasingly finer-grained details of various common daily life activities. In this dissertation, I demonstrate the possibility of building systems using offthe- shelf devices, that not only …

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Recommending Personalized Schedules In Urban Environments, Cen Chen Jun 2017

Recommending Personalized Schedules In Urban Environments, Cen Chen

Dissertations and Theses Collection

In this thesis, we are broadly interested in solving real world problems that involve decision support for coordinating agent movements in dynamic urban environments, where people are agents exhibiting different human behavior patterns and preferences. The rapid development of mobile technologies makes it easier to capture agent behavioral and preference information. Such rich agent specific information, coupled with the explosive growth of computational power, opens many opportunities that we could potentially leverage, to better guide/influence the agents in urban environments. The purpose of this thesis is to investigate how we can effectively and efficiently guide and coordinate the agents with …

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Senior Project: Calendar, Jason L. Chin Jun 2017

Senior Project: Calendar, Jason L. Chin

Computer Science and Software Engineering

This calendar application is meant to help individuals with busy schedules. Those who must balance their time between working on multiple simultaneous projects would categorize key users. In the application, users will be able to participate in multiple projects at any one time. When a user is in a project, they will be able to create tasks, add tasks, be assigned to tasks, and add other users to the project. A key feature in this application is that each user is provided a personal project. In their personal project, any task assigned to the user from any project, will be …

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Unreal Engine 4 Rpg, Jacob W. Russ, Jeffrey J. Nunez Jun 2017

Unreal Engine 4 Rpg, Jacob W. Russ, Jeffrey J. Nunez

Computer Engineering

Classic RPG videogames have become few and far between in the Western market over the years as modern RPG systems have gained popularity. The purpose of this project is to present a vertical slice of a hybrid RPG game that takes the gameplay mechanics and styles of classic RPG videogames and infuses them with a modern presentation. Through the use of the powerful Unreal Engine 4 graphics engine, this project is able to combine impressive graphical fidelity with modernized systems to fuel a videogame that is undeniably a classic RPG at heart. This is not a full game, but a …

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Computer Vision Based Route Mapping, Ryan S. Kehlenbeck, Zachary Cody Jun 2017

Computer Vision Based Route Mapping, Ryan S. Kehlenbeck, Zachary Cody

Computer Science and Software Engineering

The problem our project solves is the integration of edge detection techniques with mapping libraries to display routes based on images. To do this, we used the OpenCV library within an Android application. This application lets a user import an image from their device, and uses edge detection to pull out a path from the image. The application can find the user's location and uses it alongside the path data from the image to create a route using the physical roads near the location. The shape of the route matches the edges from the given image and the user can …

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Understanding Android App Piggybacking: A Systematic Study Of Malicious Code Grafting, Li Li, Daoyuan Li, Tegawende F. Bissyande, Jacques Klein, Yves Le Traon, David Lo, Lorenzo Cavallaro Jun 2017

Understanding Android App Piggybacking: A Systematic Study Of Malicious Code Grafting, Li Li, Daoyuan Li, Tegawende F. Bissyande, Jacques Klein, Yves Le Traon, David Lo, Lorenzo Cavallaro

Research Collection School Of Computing and Information Systems

The Android packaging model offers ample opportunities for malware writers to piggyback malicious code in popular apps, which can then be easily spread to a large user base. Although recent research has produced approaches and tools to identify piggybacked apps, the literature lacks a comprehensive investigation into such phenomenon. We fill this gap by: 1) systematically building a large set of piggybacked and benign apps pairs, which we release to the community; 2) empirically studying the characteristics of malicious piggybacked apps in comparison with their benign counterparts; and 3) providing insights on piggybacking processes. Among several findings providing insights analysis …

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Demo: Deepmon - Building Mobile Gpu Deep Learning Models For Continuous Vision Applications, Loc Nguyen Huynh, Rajesh Krishna Balan, Youngki Lee Jun 2017

Demo: Deepmon - Building Mobile Gpu Deep Learning Models For Continuous Vision Applications, Loc Nguyen Huynh, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

Deep learning has revolutionized vision sensing applications in terms of accuracy comparing to other techniques. Its breakthrough comes from the ability to extract complex high level features directly from sensor data. However, deep learning models are still yet to be natively supported on mobile devices due to high computational requirements. In this paper, we present DeepMon, a next generation of DeepSense [1] framework, to enable deep learning models on conventional mobile devices (e.g. Samsung Galaxy S7) for continuous vision sensing applications. Firstly, Deep-Mon exploits similarity between consecutive video frames for intermediate data caching within models to enhance inference latency. Secondly, …

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Rack: Code Search In The Ide Using Crowdsourced Knowledge, Mohammad Masudur Rahman, Chanchal K. Roy, David Lo Jun 2017

Rack: Code Search In The Ide Using Crowdsourced Knowledge, Mohammad Masudur Rahman, Chanchal K. Roy, David Lo

Research Collection School Of Computing and Information Systems

Traditional code search engines often do not perform well with natural language queries since they mostly apply keyword matching. These engines thus require carefully designed queries containing information about programming APIs for code search. Unfortunately, existing studies suggest that preparing an effective query for code search is both challenging and time consuming for the developers. In this paper, we propose a novel code search tool-RACK-that returns relevant source code for a given code search query written in natural language text. The tool first translates the query into a list of relevant API classes by mining keyword-API associations from the crowdsourced …

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An Effective Change Recommendation Approach For Supplementary Bug Fixes, Xin Xia, David Lo Jun 2017

An Effective Change Recommendation Approach For Supplementary Bug Fixes, Xin Xia, David Lo

Research Collection School Of Computing and Information Systems

Bug fixing is one of the most important activities during software development and maintenance. A substantial number of bugs are often fixed more than once due to incomplete initial fixes which need to be followed up by supplementary fixes. Automatically recommending relevant change locations for supplementary bug fixes can help developers to improve their productivity. It also help improve the reliability of systems by highlighting locations that a developer potentially needs to change to completely remove a bug. Unfortunately, a recent study by Park et al. shows that many change recommendation techniques do not work for supplementary bug fixes. In …

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An Exploratory Study Of Functionality And Learning Resources Of Web Apis On Programmableweb, Yuan Tian, Pavneet Singh Kochhar, David Lo Jun 2017

An Exploratory Study Of Functionality And Learning Resources Of Web Apis On Programmableweb, Yuan Tian, Pavneet Singh Kochhar, David Lo

Research Collection School Of Computing and Information Systems

Web APIs provide various functionalities that can be leveraged by developers in building their applications. ProgrammableWeb, which is the largest and most active web API and mashup collection, provides a record of thousands of web APIs and mashups. However, important properties about these large number of web APIs, such as their functionality and support/resources for learning, have never been studied by the existing research work. In this study, we perform an exploratory analysis on functionality and learning resources of 9,883 web APIs and 4,315 mashups listed on ProgrammableWeb, and find that: (1) web APIs provide a wide range of functionalities …

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Breathprint: Breathing Acoustics-Based User Authentication, Jagmohan Chauhan, Yining Hu, Suranga Sereviratne, Archan Misra, Aruna Sereviratne, Youngki Lee Jun 2017

Breathprint: Breathing Acoustics-Based User Authentication, Jagmohan Chauhan, Yining Hu, Suranga Sereviratne, Archan Misra, Aruna Sereviratne, Youngki Lee

Research Collection School Of Computing and Information Systems

We propose BreathPrint, a new behavioural biometric signature based on audio features derived from an individual's commonplace breathing gestures. Specifically, BreathPrint uses the audio signatures associated with the three individual gestures: sniff, normal, and deep breathing, which are sufficiently different across individuals. Using these three breathing gestures, we develop the processing pipeline that identifies users via the microphone sensor on smartphones and wearable devices. In BreathPrint, a user performs breathing gestures while holding the device very close to their nose. Using off-the-shelf hardware, we experimentally evaluate the BreathPrint prototype with 10 users, observed over seven days. We show that users …

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Measuring The Declared Sdk Versions And Their Consistency With Api Calls In Android Apps, Daoyuan Wu, Ximing Liu, Jiayun Xu, David Lo, Debin Gao Jun 2017

Measuring The Declared Sdk Versions And Their Consistency With Api Calls In Android Apps, Daoyuan Wu, Ximing Liu, Jiayun Xu, David Lo, Debin Gao

Research Collection School Of Computing and Information Systems

Android has been the most popular smartphone system, with multiple platform versions (e.g., KITKAT and Lollipop) active in the market. To manage the application’s compatibility with one or more platform versions, Android allows apps to declare the supported platform SDK versions in their manifest files. In this paper, we make a first effort to study this modern software mechanism. Our objective is to measure the current practice of the declared SDK versions (which we term as DSDK versions afterwards) in real apps, and the consistency between the DSDK versions and their app API calls. To this end, we perform a …

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Employing Smartwatch For Enhanced Password Authentication, Bing Chang, Ximing Liu, Yingjiu Li, Pingjian Wang, Wen-Tao Zhu, Zhan Wang Jun 2017

Employing Smartwatch For Enhanced Password Authentication, Bing Chang, Ximing Liu, Yingjiu Li, Pingjian Wang, Wen-Tao Zhu, Zhan Wang

Research Collection School Of Computing and Information Systems

This paper presents an enhanced password authentication scheme by systematically exploiting the motion sensors in a smartwatch. We extract unique features from the sensor data when a smartwatch bearer types his/her password (or PIN), and train certain machine learning classifiers using these features. We then implement smartwatch-aided password authentication using the classifiers. Our scheme is user-friendly since it does not require users to perform any additional actions when typing passwords or PINs other than wearing smartwatches. We conduct a user study involving 51 participants on the developed prototype so as to evaluate its feasibility and performance. Experimental results show that …

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Ubiear: Bringing Location-Independent Sound Awareness To The Hard-Of-Hearing People With Smartphones, Sicong Liu, Zimu Zhou, Junzhao Du, Longfei Shangguan, Jun Han, Xin Wang Jun 2017

Ubiear: Bringing Location-Independent Sound Awareness To The Hard-Of-Hearing People With Smartphones, Sicong Liu, Zimu Zhou, Junzhao Du, Longfei Shangguan, Jun Han, Xin Wang

Research Collection School Of Computing and Information Systems

Non-speech sound-awareness is important to improve the quality of life for the deaf and hard-of-hearing (DHH) people. DHH people, especially the young, are not always satisfied with their hearing aids. According to the interviews with 60 young hard-of-hearing students, a ubiquitous sound-awareness tool for emergency and social events that works in diverse environments is desired. In this paper, we design UbiEar, a smartphone-based acoustic event sensing and notification system. Core techniques in UbiEar are a light-weight deep convolution neural network to enable location-independent acoustic event recognition on commodity smartphons, and a set of mechanisms for prompt and energy-efficient acoustic sensing. …

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Battery-Aware Mobile Data Service, Liang He, Guozhu Meng, Yu Gu, Cong Liu, Jun Sun, Ting Zhu, Yang Liu, Kang G. Shin Jun 2017

Battery-Aware Mobile Data Service, Liang He, Guozhu Meng, Yu Gu, Cong Liu, Jun Sun, Ting Zhu, Yang Liu, Kang G. Shin

Research Collection School Of Computing and Information Systems

Significant research has been devoted to reduce the energy consumption of mobile devices, but how to increase their energy supply has received far less attention. Moreover, reducing the energy consumption alone does not always extend the device operation time due to a unique battery property - the capacity it delivers hinges critically upon how it is discharged. In this paper, we propose B-MODS, a novel design of battery-aware mobile data service on mobile devices. B-MODS constructs battery-friendly discharge patterns utilizing the recovery effect so as to increase the capacity delivered from batteries while meeting data service requirements. We implement B-MODS …

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Exception Handling Bug Hazards In Android: Results From A Mining Study And An Exploratory Survey, Roberta Coelho, Lucas Almeida, Georgios Gousios, Arie Van Deursen, Christoph Treude Jun 2017

Exception Handling Bug Hazards In Android: Results From A Mining Study And An Exploratory Survey, Roberta Coelho, Lucas Almeida, Georgios Gousios, Arie Van Deursen, Christoph Treude

Research Collection School Of Computing and Information Systems

Adequate handling of exceptions has proven difficult for many software engineers. Mobile app developers in particular, have to cope with compatibility, middleware, memory constraints, and battery restrictions. The goal of this paper is to obtain a thorough understanding of common exception handling bug hazards that app developers face. To that end, we first provide a detailed empirical study of over 6,000 Java exception stack traces we extracted from over 600 open source Android projects. Key insights from this study include common causes for system crashes, and common chains of wrappings between checked and unchecked exceptions. Furthermore, we provide a survey …

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Using Contextual Information To Predict Co-Changes, Igor Scaliante Wiese, Reginaldo Ré, Igor Steinmacher, Rodrigo Takashi Kuroda, Gustavo A. Oliva, Christoph Treude, Marco Aurélio Gerosa Jun 2017

Using Contextual Information To Predict Co-Changes, Igor Scaliante Wiese, Reginaldo Ré, Igor Steinmacher, Rodrigo Takashi Kuroda, Gustavo A. Oliva, Christoph Treude, Marco Aurélio Gerosa

Research Collection School Of Computing and Information Systems

Background: Co-change prediction makes developers aware of which artifacts will change together with the artifact they are working on. In the past, researchers relied on structural analysis to build prediction models. More recently, hybrid approaches relying on historical information and textual analysis have been proposed. Despite the advances in the area, software developers still do not use these approaches widely, presumably because of the number of false recommendations. We conjecture that the contextual information of software changes collected from issues, developers’ communication, and commit metadata captures the change patterns of software artifacts and can improve the prediction models. Objective: Our …

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Webapirec: Recommending Web Apis To Software Projects Via Personalized Ranking, Ferdian Thung, Richard J. Oentaryo, David Lo, Yuan Tian Jun 2017

Webapirec: Recommending Web Apis To Software Projects Via Personalized Ranking, Ferdian Thung, Richard J. Oentaryo, David Lo, Yuan Tian

Research Collection School Of Computing and Information Systems

Application programming interfaces (APIs) offer a plethora of functionalities for developers to reuse without reinventing the wheel. Identifying the appropriate APIs given a project requirement is critical for the success of a project, as many functionalities can be reused to achieve faster development. However, the massive number of APIs would often hinder the developers' ability to quickly find the right APIs. In this light, we propose a new, automated approach called WebAPIRec that takes as input a project profile and outputs a ranked list of web APIs that can be used to implement the project. At its heart, WebAPIRec employs …

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Processing Long Queries Against Short Text: Top-K Advertisement Matching In News Stream Applications, Dongxiang Zhang, Yuchen Li, Ju Fan, Lianli Gao, Fumin Shen, Heng Tao Shen Jun 2017

Processing Long Queries Against Short Text: Top-K Advertisement Matching In News Stream Applications, Dongxiang Zhang, Yuchen Li, Ju Fan, Lianli Gao, Fumin Shen, Heng Tao Shen

Research Collection School Of Computing and Information Systems

Many real applications in real-time news stream advertising call for efficient processing of long queriesagainst short text. In such applications, dynamic news feeds are regarded as queries to match against anadvertisement (ad) database for retrieving the k most relevant ads. The existing approaches to keywordretrieval cannot work well in this search scenario when queries are triggered at a very high frequency.To address the problem, we introduce new techniques to significantly improve search performance. First,we devise a two-level partitioning for tight upper bound estimation and a lazy evaluation scheme to delayfull evaluation of unpromising candidates, which can bring three to four …

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Scan: Multi-Hop Calibration For Mobile Sensor Arrays, Balz Maag, Zimu Zhou, Olga Saukh, Lothar Thiele Jun 2017

Scan: Multi-Hop Calibration For Mobile Sensor Arrays, Balz Maag, Zimu Zhou, Olga Saukh, Lothar Thiele

Research Collection School Of Computing and Information Systems

Urban air pollution monitoring with mobile, portable, low-cost sensors has attracted increasing research interest for their wide spatial coverage and affordable expenses to the general public. However, low-cost air quality sensors not only drift over time but also suffer from cross-sensitivities and dependency on meteorological effects. Therefore calibration of measurements from low-cost sensors is indispensable to guarantee data accuracy and consistency to be fit for quantitative studies on air pollution. In this work we propose sensor array network calibration (SCAN), a multi-hop calibration technique for dependent low-cost sensors. SCAN is applicable to sets of co-located, heterogeneous sensors, known as sensor …

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Deepmon: Mobile Gpu-Based Deep Learning Framework For Continuous Vision Applications, Nguyen Loc Huynh, Youngki Lee, Rajesh Krishna Balan Jun 2017

Deepmon: Mobile Gpu-Based Deep Learning Framework For Continuous Vision Applications, Nguyen Loc Huynh, Youngki Lee, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

The rapid emergence of head-mounted devices such as the Microsoft Holo-lens enables a wide variety of continuous vision applications. Such applications often adopt deep-learning algorithms such as CNN and RNN to extract rich contextual information from the first-person-view video streams. Despite the high accuracy, use of deep learning algorithms in mobile devices raises critical challenges, i.e., high processing latency and power consumption. In this paper, we propose DeepMon, a mobile deep learning inference system to run a variety of deep learning inferences purely on a mobile device in a fast and energy-efficient manner. For this, we designed a suite of …

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Towards Unobtrusive Mental Well-Being Monitoring For Independent-Living Elderly, Sinh Huynh, Hwee-Pink Tan, Youngki Lee Jun 2017

Towards Unobtrusive Mental Well-Being Monitoring For Independent-Living Elderly, Sinh Huynh, Hwee-Pink Tan, Youngki Lee

Research Collection School Of Computing and Information Systems

It is essential to proactively detect mental health problems such as loneliness and depression in the independently-living elderly for timely intervention by caregivers. In this paper, we introduce an unobtrusive sensor-enabled monitoring system that has been deployed to 50 government housing ats with the independent-living elderly for two years. Then, we also present our initial findings from the 6-month sensor data between August 2015 and April 2016 as well as the survey data to measure the subjective well-being indicator. Our study showed the promising results that "room-level movements within a house" and "going out" behavior captured by our simple sensor …

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Bug Characteristics In Blockchain Systems: A Large-Scale Empirical Study, Zhiyuan Wan, David Lo, Xin Xia, Liang Cai Jun 2017

Bug Characteristics In Blockchain Systems: A Large-Scale Empirical Study, Zhiyuan Wan, David Lo, Xin Xia, Liang Cai

Research Collection School Of Computing and Information Systems

Bugs severely hurt blockchain system dependability. A thorough understanding of blockchain bug characteristics is required to design effective tools for preventing, detecting and mitigating bugs. We perform an empirical study on bug characteristics in eight representative open source blockchain systems. First, we manually examine 1,108 bug reports to understand the nature of the reported bugs. Second, we leverage card sorting to label the bug reports, and obtain ten bug categories in blockchain systems. We further investigate the frequency distribution of bug categories across projects and programming languages. Finally, we study the relationship between bug categories and bug fixing time. The …

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Experiences In Building A Real-World Eating Recogniser, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee Jun 2017

Experiences In Building A Real-World Eating Recogniser, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

In this paper, we describe the progressive design of the gesture recognition module of an automated food journaling system - Annapurna. Annapurna runs on a smartwatch and utilises data from the inertial sensors to first identify eating gestures, and then captures food images which are presented to the user in the form of a food journal. We detail the lessons we learnt from multiple in-the-wild studies, and show how eating recognizer is refined to tackle challenges such as (i) high gestural diversity, and (ii) non-eating activities with similar gestural signatures. Annapurna is finally robust (identifying eating across a wide diversity …

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Revisiting Assert Use In Github Projects, Pavneet Singh Kochhar, David Lo Jun 2017

Revisiting Assert Use In Github Projects, Pavneet Singh Kochhar, David Lo

Research Collection School Of Computing and Information Systems

Assertions are often used to test the assumptions that developers have about a program. An assertion contains a boolean expression which developers believe to be true at a particular program point. It throws an error if the expression is not satisfied, which helps developers to detect and correct bugs. Since assertions make developer assumptions explicit, assertions are also believed to improve under-standability of code. Recently, Casalnuovo et al. analyse C and C++ programs to understand the relationship between assertion usage and defect occurrence. Their results show that asserts have a small effect on reducing the density of bugs and developers …

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Exploiting Android System Services Through Bypassing Service Helpers, Yachong Gu, Yao Cheng, Lingyun Ying, Yemian Lu, Qi Li, Purui Su Jun 2017

Exploiting Android System Services Through Bypassing Service Helpers, Yachong Gu, Yao Cheng, Lingyun Ying, Yemian Lu, Qi Li, Purui Su

Research Collection School Of Computing and Information Systems

Android allows applications to communicate with system service via system service helper so that applications can use various functions wrapped in the system services. Meanwhile, system services leverage the service helpers to enforce security mechanisms, e.g. input parameter validation, to protect themselves against attacks. However, service helpers can be easily bypassed, which poses severe security and privacy threats to system services, e.g., privilege escalation, function execution without users’ interactions, system service crash, and DoS attacks. In this paper, we perform the first systematic study on such vulnerabilities and investigate their impacts. We develop a tool to analyze all system services …

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Enabling Gesture-Based Interactions With Objects, Longfei Shangguan, Zimu Zhou, Kyle Jamieson Jun 2017

Enabling Gesture-Based Interactions With Objects, Longfei Shangguan, Zimu Zhou, Kyle Jamieson

Research Collection School Of Computing and Information Systems

No abstract provided.

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Collaboration In 360° Videochat: Challenges And Opportunities, Anthony Tang, Omid Fakourfar, Carman Neustaedter, Scott Bateman Jun 2017

Collaboration In 360° Videochat: Challenges And Opportunities, Anthony Tang, Omid Fakourfar, Carman Neustaedter, Scott Bateman

Research Collection School Of Computing and Information Systems

We designed a videochat experience where one participant can experience a remote environment from a 360° camera. This allows the remote user to view and explore the environment without necessitating interaction from the local participant. We designed and conducted an observational study to understand the experience, and the challenges that people might encounter. In a study with 32 participants (16 pairs), we found that remote participants could actively participate in the experience with the environment in ways that are not possible with current mobile video chat. However, we also found that participants had challenges in communicating location and orientation information …

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On The Similarities Between Random Regret Minimization And Mother Logit: The Case Of Recursive Route Choice Models, Tien Mai, Fabian Bastin, Emma Frejinger Jun 2017

On The Similarities Between Random Regret Minimization And Mother Logit: The Case Of Recursive Route Choice Models, Tien Mai, Fabian Bastin, Emma Frejinger

Research Collection School Of Computing and Information Systems

This paper focuses on the comparison of the random regret minimization (RRM) and mother logit models for analyzing the choice between alternatives having deterministic attributes. The mother logit model allows utilities of a given alternative to depend on attributes of other alternatives. It was designed to relax the independence from irrelevant alternatives (IIA) property while keeping the random terms independently and identically distributed extreme value distributed (McFadden et al., 1978).We adapt and extend the RRM model proposed by Chorus (2014) to the case of recursive logit (RL) route choice models (Fosgerau et al., 2013). We argue that these RRM models …

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Is The Whole Greater Than The Sum Of Its Parts?, Liangyue Li, Hanghang Tong, Yong Wang, Conglei Shi, Nan Cao, Norbou Buchler Jun 2017

Is The Whole Greater Than The Sum Of Its Parts?, Liangyue Li, Hanghang Tong, Yong Wang, Conglei Shi, Nan Cao, Norbou Buchler

Research Collection School Of Computing and Information Systems

The PART-WHOLE relationship routinely finds itself in many disciplines, ranging from collaborative teams, crowdsourcing, autonomous systems to networked systems. From the algorithmic perspective, the existing work has primarily focused on predicting the outcomes of the whole and parts, by either separate models or linear joint models, which assume the outcome of the parts has a linear and independent effect on the outcome of the whole. In this paper, we propose a joint predictive method named PAROLE to simultaneously and mutually predict the part and whole outcomes. The proposed method offers two distinct advantages over the existing work. First (Model Generality), …

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