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Articles 2431 - 2460 of 4271
Full-Text Articles in Entire DC Network
Who Will Leave The Company?: A Large-Scale Industry Study Of Developer Turnover By Mining Monthly Work Report, Lingfeng Bao, Zhenchang Xing, Xin Xia, David Lo, Shanping Li
Who Will Leave The Company?: A Large-Scale Industry Study Of Developer Turnover By Mining Monthly Work Report, Lingfeng Bao, Zhenchang Xing, Xin Xia, David Lo, Shanping Li
Research Collection School Of Computing and Information Systems
Software developer turnover has become a big challenge for information technology (IT) companies. The departure of key software developers might cause big loss to an IT company since they also depart with important business knowledge and critical technical skills. Understanding developer turnover is very important for IT companies to retain talented developers and reduce the loss due to developers' departure. Previous studies mainly perform qualitative observations or simple statistical analysis of developers' activity data to understand developer turnover. In this paper, we investigate whether we can predict the turnover of software developers in non-open source companies by automatically analyzing monthly …
Collaborative Topic Regression For Online Recommender Systems: An Online And Bayesian Approach, Chenghao Liu, Tao Jin, Steven C. H. Hoi, Peilin Zhao, Jianling Sun
Collaborative Topic Regression For Online Recommender Systems: An Online And Bayesian Approach, Chenghao Liu, Tao Jin, Steven C. H. Hoi, Peilin Zhao, Jianling Sun
Research Collection School Of Computing and Information Systems
Collaborative Topic Regression (CTR) combines ideas of probabilistic matrix factorization (PMF) and topic modeling (such as LDA) for recommender systems, which has gained increasing success in many applications. Despite enjoying many advantages, the existing Batch Decoupled Inference algorithm for the CTR model has some critical limitations: First of all, it is designed to work in a batch learning manner, making it unsuitable to deal with streaming data or big data in real-world recommender systems. Secondly, in the existing algorithm, the item-specific topic proportions of LDA are fed to the downstream PMF but the rating information is not exploited in discovering …
A Neural Network Model For Semi-Supervised Review Aspect Identification, Ying Ding, Changlong Yu, Jing Jiang
A Neural Network Model For Semi-Supervised Review Aspect Identification, Ying Ding, Changlong Yu, Jing Jiang
Research Collection School Of Computing and Information Systems
Aspect identification is an important problem in opinion mining. It is usually solved in an unsupervised manner, and topic models have been widely used for the task. In this work, we propose a neural network model to identify aspects from reviews by learning their distributional vectors. A key difference of our neural network model from topic models is that we do not use multinomial word distributions but instead embedding vectors to generate words. Furthermore, to leverage review sentences labeled with aspect words, a sequence labeler based on Recurrent Neural Networks (RNNs) is incorporated into our neural network. The resulting model …
Provably Secure Attribute Based Signcryption With Delegated Computation And Efficient Key Updating, Hanshu Hong, Yunhao Xia, Zhixin Sun, Ximeng Liu
Provably Secure Attribute Based Signcryption With Delegated Computation And Efficient Key Updating, Hanshu Hong, Yunhao Xia, Zhixin Sun, Ximeng Liu
Research Collection School Of Computing and Information Systems
Equipped with the advantages of flexible access control and fine-grained authentication, attribute based signcryption is diffusely designed for security preservation in many scenarios. However, realizing efficient key evolution and reducing the calculation costs are two challenges which should be given full consideration in attribute based cryptosystem. In this paper, we present a key-policy attribute based signcryption scheme (KP-ABSC) with delegated computation and efficient key updating. In our scheme, an access structure is embedded into user’s private key, while ciphertexts corresponds a target attribute set. Only the two are matched can a user decrypt and verify the ciphertexts. When the access …
Household Informedness And Policy Analytics For The Collection And Recycling Of Household Hazardous Waste In California, Kustini Lim-Wavde, Robert J. Kauffman, Gregory S. Dawson
Household Informedness And Policy Analytics For The Collection And Recycling Of Household Hazardous Waste In California, Kustini Lim-Wavde, Robert J. Kauffman, Gregory S. Dawson
Research Collection School Of Computing and Information Systems
Collection and recycling of household hazardous waste (HHW) can vary due to differences in household incomes, demographics, material recyclability, and HHW collection programs. We evaluate the role of household informedness, the degree to which households have the necessary information to make utility-maximizing decisions about the handling of their waste. Household informedness seems to be influenced by HHW public education and environmental quality information. We assess the effects of household informedness on HHW collection and recycling using panel data, community surveys, drinking water compliance reports, and census data in California from 2004 to 2012. The results enable the calculation of …
Real-Time Prediction Of Length Of Stay Using Passive Wi-Fi Sensing, Truc Viet Le, Baoyang Song, Laura Wynter
Real-Time Prediction Of Length Of Stay Using Passive Wi-Fi Sensing, Truc Viet Le, Baoyang Song, Laura Wynter
Research Collection School Of Computing and Information Systems
The proliferation of wireless technologies in today's everyday life is one of the key drivers of the Internet of Things (IoT). In addition to being an enabler of connectivity, the vast penetration of wireless devices today gives rise to a secondary functionality as a means of tracking and localization of the devices themselves. Indeed, in order to discover and automatically connect to known Wi-Fi networks, mobile devices have to scan and broadcast the so-called probe requests on all available channels, which can be captured and analyzed in a non-intrusive manner. Thus, one of the key applications of this feature is …
Discovering Your Selling Points: Personalized Social Influential Tags Exploration, Yuchen Li, Kian-Lee Tan, Ju Fan, Dongxiang Zhang
Discovering Your Selling Points: Personalized Social Influential Tags Exploration, Yuchen Li, Kian-Lee Tan, Ju Fan, Dongxiang Zhang
Research Collection School Of Computing and Information Systems
Social influence has attracted significant attention owing to the prevalence of social networks (SNs). In this paper, we study a new social influence problem, called personalized social influential tags exploration (PITEX), to help any user in the SN explore how she influences the network. Given a target user, it finds a size-k tag set that maximizes this user’s social influence. We prove the problem is NP-hard to be approximated within any constant ratio. To solve it, we introduce a sampling-based framework, which has an approximation ratio of 1−ǫ 1+ǫ with high probabilistic guarantee. To speedup the computation, we devise more …
Search-Driven String Constraint Solving For Vulnerability Detection, Julian Thome, Lwin Khin Shar, Domenico Bianculli, Lionel Briand
Search-Driven String Constraint Solving For Vulnerability Detection, Julian Thome, Lwin Khin Shar, Domenico Bianculli, Lionel Briand
Research Collection School Of Computing and Information Systems
—Constraint solving is an essential technique for detecting vulnerabilities in programs, since it can reason about input sanitization and validation operations performed on user inputs. However, real-world programs typically contain complex string operations that challenge vulnerability detection. State-ofthe-art string constraint solvers support only a limited set of string operations and fail when they encounter an unsupported one; this leads to limited effectiveness in finding vulnerabilities. In this paper we propose a search-driven constraint solving technique that complements the support for complex string operations provided by any existing string constraint solver. Our technique uses a hybrid constraint solving procedure based on …
What Gets Media Attention And How Media Attention Evolves Over Time: Large-Scale Empirical Evidence From 196 Countries, Jisun An, Haewoon Kwak
What Gets Media Attention And How Media Attention Evolves Over Time: Large-Scale Empirical Evidence From 196 Countries, Jisun An, Haewoon Kwak
Research Collection School Of Computing and Information Systems
It is known that news topics, covered more frequently and over longer periods of time, are considered to be important to the public. Hence, what gets media attention and how me- dia attention evolves over time has been studied for decades in communication study. However, previous studies are con- fined to a few countries or a few topics, mainly due to lack of longitudinal global data. In this work, we use a large-scale news data compiled from 196 countries to provide empirical analyses of media attention dynamics.
Choosing An Nlp Library For Analyzing Software Documentation: A Systematic Literature Review And A Series Of Experiments, Fouad N. A. Al Omran, Christoph Treude
Choosing An Nlp Library For Analyzing Software Documentation: A Systematic Literature Review And A Series Of Experiments, Fouad N. A. Al Omran, Christoph Treude
Research Collection School Of Computing and Information Systems
To uncover interesting and actionable information from natural language documents authored by software developers, many researchers rely on "out-of-the-box" NLP libraries. However, software artifacts written in natural language are different from other textual documents due to the technical language used. In this paper, we first analyze the state of the art through a systematic literature review in which we find that only a small minority of papers justify their choice of an NLP library. We then report on a series of experiments in which we applied four state-of-the-art NLP libraries to publicly available software artifacts from three different sources. Our …
Machine Learning Approaches To Sentiment Analytics, W. Zhao, Keng Siau
Machine Learning Approaches To Sentiment Analytics, W. Zhao, Keng Siau
Research Collection School Of Computing and Information Systems
One key aspect of sentiment analytics is emotion classification. This research studies the use of machine learning approaches to classify human emotion. Two different machine learning approaches were compared in an experimental study. In one approach, emotions from both genders were used to train the machine. In another approach, genders were separated and two separate machines were used to learn the emotions of the two genders. We also manipulated the training sample sizes and study the effect of training sample sizes on the two machine learning approaches. Our preliminary results show that the approach where the genders were separated produces …
Robust Object Tracking Via Locality Sensitive Histograms, Shengfeng He, Rynson W.H Lau, Qingxiong Yang, Jiang Wang, Ming-Hsuan Yang
Robust Object Tracking Via Locality Sensitive Histograms, Shengfeng He, Rynson W.H Lau, Qingxiong Yang, Jiang Wang, Ming-Hsuan Yang
Research Collection School Of Computing and Information Systems
This paper presents a novel locality sensitive histogram (LSH) algorithm for visual tracking. Unlike the conventional image histogram that counts the frequency of occurrence of each intensity value by adding ones to the corresponding bin, an LSH is computed at each pixel location, and a floating-point value is added to the corresponding bin for each occurrence of an intensity value. The floating-point value exponentially reduces with respect to the distance to the pixel location where the histogram is computed. An efficient algorithm is proposed that enables the LSHs to be computed in time linear in the image size and the …
Watching 360° Videos Together, Anthony Tang, Omid Fakourfar
Watching 360° Videos Together, Anthony Tang, Omid Fakourfar
Research Collection School Of Computing and Information Systems
360° videos are made using omnidirectional cameras that capture a sphere around the camera. Viewers get an immersive experience by freely changing their field of view around the sphere. The problem is that current interfaces are designed for a single user, and we do not know what challenges groups of people will have when viewing these videos together. We report on the findings of a study where 16 pairs of participants watched 360° videos together in a "guided tour" scenario. Our findings indicate that while participants enjoyed the ability to view the scene independently, this caused challenges establishing joint references, …
Joint Optimization Of Resource Provisioning In Cloud Computing, Jonathan David Chase, Dusit Niyato
Joint Optimization Of Resource Provisioning In Cloud Computing, Jonathan David Chase, Dusit Niyato
Research Collection School Of Computing and Information Systems
Cloud computing exploits virtualization to provision resources efficiently. Increasingly, Virtual Machines (VMs) have high bandwidth requirements; however, previous research does not fully address the challenge of both VM and bandwidth provisioning. To efficiently provision resources, a joint approach that combines VMs and bandwidth allocation is required. Furthermore, in practice, demand is uncertain. Service providers allow the reservation of resources. However, due to the dangers of over-and under-provisioning, we employ stochastic programming to account for this risk. To improve the efficiency of the stochastic optimization, we reduce the problem space with a scenario tree reduction algorithm, that significantly increases tractability, whilst …
Follow-My-Lead: Intuitive Indoor Path Creation And Navigation Using See-Through Interactive Videos, Quentin Roy, Simon T. Perrault, Shengdong Zhao, Richard Davis, Anuroop Pattena Vaniyar, Velko Vechev, Youngki Lee, Archan Misra
Follow-My-Lead: Intuitive Indoor Path Creation And Navigation Using See-Through Interactive Videos, Quentin Roy, Simon T. Perrault, Shengdong Zhao, Richard Davis, Anuroop Pattena Vaniyar, Velko Vechev, Youngki Lee, Archan Misra
Research Collection School Of Computing and Information Systems
We present Follow-My-Lead, an alternative indoor navigation technique that uses visual information recorded on an actual navigation path as a navigational guide. Its design revealed a trade-off between the fidelity of information provided to users and their effort to acquire it. Our first experiment revealed that scrolling through a continuous image stream of the navigation path is highly informative, but it becomes tedious with constant use. Discrete image checkpoints require less effort, but can be confusing. A balance may be struck by adding fast video transitions between image checkpoints, but precise control is required to handle difficult situations. Authoring still …
Design And Implementation Of An Rfid-Based Customer Shopping Behavior Mining System, Zimu Zhou, Longfei Shangguan, Xiaolong Zheng, Lei Yang, Yunhao Liu
Design And Implementation Of An Rfid-Based Customer Shopping Behavior Mining System, Zimu Zhou, Longfei Shangguan, Xiaolong Zheng, Lei Yang, Yunhao Liu
Research Collection School Of Computing and Information Systems
Shopping behavior data is of great importance in understanding the effectiveness of marketing and merchandising campaigns. Online clothing stores are capable of capturing customer shopping behavior by analyzing the click streams and customer shopping carts. Retailers with physical clothing stores, however, still lack effective methods to comprehensively identify shopping behaviors. In this paper, we show that backscatter signals of passive RFID tags can be exploited to detect and record how customers browse stores, which garments they pay attention to, and which garments they usually pair up. The intuition is that the phase readings of tags attached to items will demonstrate …
Now You See It, Now You Don't! A Study Of Content Modification Behavior In Facebook, Fuxiang Chen, Ee-Peng Lim
Now You See It, Now You Don't! A Study Of Content Modification Behavior In Facebook, Fuxiang Chen, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Social media, as a major platform to disseminate information, has changed the way users and communities contribute content. In this paper, we aim to study content modifications on public Facebook pages operated by news media, community groups, and bloggers. We also study the possible reasons behind them, and their effects on user interaction. We conducted a detailed study of Content Censorship (CC) and Content Edit (CE) in Facebook using a detailed longitudinal dataset consisting of 57 public Facebook pages over 3 weeks covering 145,955 posts and 9,379,200 comments. We detected many CC and CE activities between 28% and 56% of …
A Compare-Aggregate Model For Matching Text Sequences, Shuohang Wang, Jing Jiang
A Compare-Aggregate Model For Matching Text Sequences, Shuohang Wang, Jing Jiang
Research Collection School Of Computing and Information Systems
Many NLP tasks including machine comprehension, answer selection and text entailment require the comparison between sequences. Matching the important units between sequences is a key to solve these problems. In this paper, we present a general "compare-aggregate" framework that performs word-level matching followed by aggregation using Convolutional Neural Networks. We particularly focus on the different comparison functions we can use to match two vectors. We use four different datasets to evaluate the model. We find that some simple comparison functions based on element-wise operations can work better than standard neural network and neural tensor network.
The Crowd Work Accessibility Problem, Saiganesh Swaminathan, Kotaro Hara, Jeffrey P. Bigham
The Crowd Work Accessibility Problem, Saiganesh Swaminathan, Kotaro Hara, Jeffrey P. Bigham
Research Collection School Of Computing and Information Systems
Crowd work is an increasingly prevalent and important kind of work. Because of its flexible nature, crowd work may offer benefits for people with disabilities. Unfortunately, people with disabilities currently lack access to much of this work because the tasks that are posted are often inaccessible. In this paper, we first characterize the accessibility of the tasks posted to a popular crowd marketplace, Amazon Mechanical Turk, by performing manual and automatic checks on 120 tasks from several common types. We then outline research directions that could have positive impact on this problem. Given ongoing and upcoming changes to the world …
Finding Causality And Responsibility For Probabilistic Reverse Skyline Query Non-Answers [Extended Abstract], Yunjun Gao, Qing Liu, Gang Chen, Linlin Zhou, Baihua Zheng
Finding Causality And Responsibility For Probabilistic Reverse Skyline Query Non-Answers [Extended Abstract], Yunjun Gao, Qing Liu, Gang Chen, Linlin Zhou, Baihua Zheng
Research Collection School Of Computing and Information Systems
This paper explores the causality and responsibility problem (CRP) for the non-answers to probabilistic reverse skyline queries (PRSQ). Towards this, we propose an efficient algorithm called CP to compute the causality and responsibility for the non-answers to PRSQ. CP first finds candidate causes, and then, it performs verification to obtain actual causes with their responsibilities, during which several strategies are used to boost efficiency. Extensive experiments using both real and synthetic data sets demonstrate the effectiveness and efficiency of the presented algorithms.
Identity-Based Data Outsourcing With Comprehensive Auditing In Clouds, Yujue Wang, Qianhong Wu, Bo Qin, Wenchang Shi, Robert H. Deng, Jiankun Hu
Identity-Based Data Outsourcing With Comprehensive Auditing In Clouds, Yujue Wang, Qianhong Wu, Bo Qin, Wenchang Shi, Robert H. Deng, Jiankun Hu
Research Collection School Of Computing and Information Systems
Cloud storage system provides facilitative file storage and sharing services for distributed clients. To address integrity, controllable outsourcing, and origin auditing concerns on outsourced files, we propose an identity-based data outsourcing (IBDO) scheme equipped with desirable features advantageous over existing proposals in securing outsourced data. First, our IBDO scheme allows a user to authorize dedicated proxies to upload data to the cloud storage server on her behalf, e.g., a company may authorize some employees to upload files to the company's cloud account in a controlled way. The proxies are identified and authorized with their recognizable identities, which eliminates complicated certificate …
Inferring Smartphone Keypress Via Smartwatch Inertial Sensing, Sougata Sen, Karan Grover, Vigneshwaran Subbaraju, Archan Misra
Inferring Smartphone Keypress Via Smartwatch Inertial Sensing, Sougata Sen, Karan Grover, Vigneshwaran Subbaraju, Archan Misra
Research Collection School Of Computing and Information Systems
Due to numerous benefits, sensor-rich smartwatchesand wrist-worn wearable devices are quickly gaining popularity.The popularity of these devices also raises privacy concerns. Inthis paper we explore one such privacy concern: the possibility ofextracting the location of a user’s touch-event on a smartphone,using the inertial sensor data of a smartwatch worn by the useron the same arm. This is a major concern not only because itmight be possible for an attacker to extract private and sensitiveinformation from the inputs provided but also because the attackmode utilises a device (smartwatch) that is distinct from thedevice being attacked (smartphone). Through a user study wefind …
On Analyzing User Topic-Specific Platform Preferences Across Multiple Social Media Sites, Roy Ka Wei Lee, Tuan Anh Hoang, Ee Peng Lim
On Analyzing User Topic-Specific Platform Preferences Across Multiple Social Media Sites, Roy Ka Wei Lee, Tuan Anh Hoang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Topic modeling has traditionally been studied for single text collections and applied to social media data represented in the form of text documents. With the emergence of many social media platforms, users find themselves using different social media for posting content and for social interaction. While many topics may be shared across social media platforms, users typically show preferences of certain social media platform(s) over others for certain topics. Such platform preferences may even be found at the individual level. To model social media topics as well as platform preferences of users, we propose a new topic model known as …
Machine Comprehension Using Match-Lstm And Answer Pointer, Shuohang Wang, Jing Jiang
Machine Comprehension Using Match-Lstm And Answer Pointer, Shuohang Wang, Jing Jiang
Research Collection School Of Computing and Information Systems
Machine comprehension of text is an important problem in natural language processing. A recently released dataset, the Stanford Question Answering Dataset (SQuAD), offers a large number of real questions and their answers created by humans through crowdsourcing. SQuAD provides a challenging testbed for evaluating machine comprehension algorithms, partly because compared with previous datasets, in SQuAD the answers do not come from a small set of candidate answers and they have variable lengths. We propose an end-to-end neural architecture for the task. The architecture is based on match-LSTM, a model we proposed previously for textual entailment, and Pointer Net, a sequence-to-sequence …
Related-Key Secure Key Encapsulation From Extended Computational Bilinear Diffie–Hellman, Brandon Qin, Shengli Liu, Shifeng Sun, Robert H. Deng, Dawu Gu
Related-Key Secure Key Encapsulation From Extended Computational Bilinear Diffie–Hellman, Brandon Qin, Shengli Liu, Shifeng Sun, Robert H. Deng, Dawu Gu
Research Collection School Of Computing and Information Systems
As a special type of fault injection attacks, Related-Key Attacks (RKAs) allow an adversary to manipulate a cryptographic key and subsequently observe the outcomes of the cryptographic scheme under these modified keys. In the real life, related-key attacks are already practical enough to be implemented on cryptographic devices. To avoid cryptographic devices suffering from related-key attacks, it is necessary to design a cryptographic scheme that resists against such attacks. This paper proposes an efficient RKA-secure Key Encapsulation Mechanism (KEM), in which the adversary can modify the secret key sk to any value f(sk), as long as, f is a polynomial …
On The Effectiveness Of Virtualization Based Memory Isolation On Multicore Platforms, Siqi Zhao, Xuhua Ding
On The Effectiveness Of Virtualization Based Memory Isolation On Multicore Platforms, Siqi Zhao, Xuhua Ding
Research Collection School Of Computing and Information Systems
Virtualization based memory isolation has beenwidely used as a security primitive in many security systems.This paper firstly provides an in-depth analysis of itseffectiveness in the multicore setting; a first in the literature.Our study reveals that memory isolation by itself is inadequatefor security. Due to the fundamental design choices inhardware, it faces several challenging issues including pagetable maintenance, address mapping validation and threadidentification. As demonstrated by our attacks implementedon XMHF and BitVisor, these issues undermine the security ofmemory isolation. Next, we propose a new isolation approachthat is immune to the aforementioned problems. In our design,the hypervisor constructs a fully isolated micro …
Collective Entity Linking In Tweets Over Space And Time, Wen Haw Chong, Ee-Peng Lim, William Cohen
Collective Entity Linking In Tweets Over Space And Time, Wen Haw Chong, Ee-Peng Lim, William Cohen
Research Collection School Of Computing and Information Systems
We propose collective entity linking over tweets that are close in space and time. This exploits the fact that events or geographical points of interest often result in related entities being mentioned in spatio-temporal proximity. Our approach directly applies to geocoded tweets. Where geocoded tweets are overly sparse among all tweets, we use a relaxed version of spatial proximity which utilizes both geocoded and non-geocoded tweets linked by common mentions. Entity linking is affected by noisy mentions extracted and incomplete knowledge bases. Moreover, to perform evaluation on the entity linking results, much manual annotation of mentions is often required. To …
Comparative Relation Generative Model, Maksim Tkachenko, Hady W. Lauw
Comparative Relation Generative Model, Maksim Tkachenko, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Online reviews are important decision aids to consumers. Other than helping users to evaluate individual products, reviews also support comparison shopping by comparing two (or more) products based on a specific aspect. However, making a comparison across two different reviews, written by different authors, is not always equitable due to the different standards and preferences of authors. Therefore, we focus on comparative sentences, whereby two products are compared directly by a review author within a sentence. We study the problem of comparative relation mining. Given a set of comparative sentences, each relating a pair of entities, our objective is three-fold: …
Understanding The Information-Based Transformation Of Strategy And Society, Eric K. Clemons, Rajiv M. Dewan, Robert J. Kauffman, Thomas A. Weber
Understanding The Information-Based Transformation Of Strategy And Society, Eric K. Clemons, Rajiv M. Dewan, Robert J. Kauffman, Thomas A. Weber
Research Collection School Of Computing and Information Systems
The world economy is undergoing dramatic changes, largely driven by the new availability of fine-grained information. Innovative ways of using data—large and small—have also prompted a rethinking of the boundaries for the combination and use of knowledge. The strategic design of information flows in the economy has the upside of higher economic rents and competitive advantage, as well as the downsides of wealth inequality and abuse of power. This has brought a wide range of regulatory challenges. To understand the nature of these sweeping changes, it is important to examine the new ways information is used, and how information flows …
Assessing The Language Of Chat For Teamwork Dialogue, Antonette Shibani, Elizabeth Koh, Vivian Lai, Kyong Jin Shim
Assessing The Language Of Chat For Teamwork Dialogue, Antonette Shibani, Elizabeth Koh, Vivian Lai, Kyong Jin Shim
Research Collection School Of Computing and Information Systems
In technology enhanced language learning, many pedagogical activities involve students in online discussion such as synchronous chat, in order to help them practice their language skills. Besides developing the language competency of students, it is also crucial to nurture their teamwork competencies for today's global and complex environment. Language communication is an important glue of teamwork. In order to assess the language of chat for teamwork dimensions, several text mining methods are pos sible. However, difficulties arise such as pre-processing being a black box and classification approaches and algorithms being dependent on the context. To address these issues, the study …