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Full-Text Articles in Entire DC Network
Arivu: Making Networked Mobile Games Green: A Scalable Power-Aware Middleware, Anand Bhojan, Ananda L. Akhihebbal L., Mun Choon Chan, Rajesh Krishna Balan
Arivu: Making Networked Mobile Games Green: A Scalable Power-Aware Middleware, Anand Bhojan, Ananda L. Akhihebbal L., Mun Choon Chan, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
With the improved processing power, graphic quality and high-speed wireless connection in recent generations of mobile phones, it looks more attractive than ever to introduce networked games on these devices. However, these games consume higher levels of energy. While device features and application resource requirements are rapidly growing, the battery technologies are not growing at the same pace. Therefore, the main concern is the limitation of the battery power of such portable devices to support potentially long-hour of game play. In this paper we present ARIVU, a scalable power aware middleware that dynamically controls the energy consumption of wireless interface …
Formal Modeling And Validation Of Stateflow Diagrams, Chunqing Chen, Jun Sun, Yang Liu, Jin Song Dong, Manchun Zheng
Formal Modeling And Validation Of Stateflow Diagrams, Chunqing Chen, Jun Sun, Yang Liu, Jin Song Dong, Manchun Zheng
Research Collection School Of Computing and Information Systems
Stateflow is an industrial tool for modeling and simulating control systems in model-based development. In this paper, we present our latest work on automatic verification of Stateflow using model-checking techniques. We propose an approach to systematically translate Stateflow diagrams to a formal modeling language called CSP# by precisely following Stateflow’s execution semantics, which is described by examples. A translator is developed inside the Process Analysis Toolkit (PAT) model checker to automate this process with the support of various Stateflow advanced modeling features. Formal analysis can be conducted on the transformed CSP# with PAT’s simulation and model-checking power. Using our approach, …
An Improved K-Nearest-Neighbor Algorithm For Text Categorization, Shengyi Jiang, Guansong Pang, Meiling Wu, Limin Kuang
An Improved K-Nearest-Neighbor Algorithm For Text Categorization, Shengyi Jiang, Guansong Pang, Meiling Wu, Limin Kuang
Research Collection School Of Computing and Information Systems
Text categorization is a significant tool to manage and organize the surging text data. Many text categorization algorithms have been explored in previous literatures, such as KNN, Naive Bayes and Support Vector Machine. KNN text categorization is an effective but less efficient classification method. In this paper, we propose an improved KNN algorithm for text categorization, which builds the classification model by combining constrained one pass clustering algorithm and KNN text categorization. Empirical results on three benchmark corpora show that our algorithm can reduce the text similarity computation substantially and outperform the-state-of-the-art KNN, Naive Bayes and Support Vector Machine classifiers. …
Simultaneous Camera Pose And Correspondence Estimation With Motion Coherence, Wen-Yan Lin, Loong-Fah Cheong, Ping Tan, Guo Dong, Siying Liu
Simultaneous Camera Pose And Correspondence Estimation With Motion Coherence, Wen-Yan Lin, Loong-Fah Cheong, Ping Tan, Guo Dong, Siying Liu
Research Collection School Of Computing and Information Systems
Traditionally, the camera pose recovery problem has been formulated as one of estimating the optimal camera pose given a set of point correspondences. This critically depends on the accuracy of the point correspondences and would have problems in dealing with ambiguous features such as edge contours and high visual clutter. Joint estimation of camera pose and correspondence attempts to improve performance by explicitly acknowledging the chicken and egg nature of the pose and correspondence problem. However, such joint approaches for the two-view problem are still few and even then, they face problems when scenes contain largely edge cues with few …
Self‐Regulating Action Exploration In Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Yuan-Sin Tan
Self‐Regulating Action Exploration In Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Yuan-Sin Tan
Research Collection School Of Computing and Information Systems
The basic tenet of a learning process is for an agent to learn for only as much and as long as it is necessary. With reinforcement learning, the learning process is divided between exploration and exploitation. Given the complexity of the problem domain and the randomness of the learning process, the exact duration of the reinforcement learning process can never be known with certainty. Using an inaccurate number of training iterations leads either to the non-convergence or the over-training of the learning agent. This work addresses such issues by proposing a technique to self-regulate the exploration rate and training duration …
Systems And Methods For Transaction Account Offerings, Clinton Allen, Michael Digregorio, Glade Erikson, Deepinder Gulati, Jacob Plammoottil Jacob, Sanjiv Khosla, Seema Chokshi
Systems And Methods For Transaction Account Offerings, Clinton Allen, Michael Digregorio, Glade Erikson, Deepinder Gulati, Jacob Plammoottil Jacob, Sanjiv Khosla, Seema Chokshi
Research Collection School Of Computing and Information Systems
A method for receiving a user input for providing offerings is disclosed. Fields may be populated for creating a database query for matching a selection of offerings to a population of customers. Data may be received from the database, in response to interactively building the query and/or executing the query. Multiple rank ordered results may be produced for comparison, wherein the producing uses preprogrammed analytics, data from the database and user input, and wherein the results include customer lists linked to a distinct offering and a preferred delivery channel of the offering to a customer. A transaction account may be …
Learning Bregman Distance Functions For Semi-Supervised Clustering, Lei Wu, Chu Hong Hoi, Rong Jin, Jianke Zhu, N. Yu
Learning Bregman Distance Functions For Semi-Supervised Clustering, Lei Wu, Chu Hong Hoi, Rong Jin, Jianke Zhu, N. Yu
Research Collection School Of Computing and Information Systems
Learning distance functions with side information plays a key role in many data mining applications. Conventional distance metric learning approaches often assume that the target distance function is represented in some form of Mahalanobis distance. These approaches usually work well when data are in low dimensionality, but often become computationally expensive or even infeasible when handling high-dimensional data. In this paper, we propose a novel scheme of learning nonlinear distance functions with side information. It aims to learn a Bregman distance function using a nonparametric approach that is similar to Support Vector Machines. We emphasize that the proposed scheme is …
Tweets And Votes: A Study Of The 2011 Singapore General Election, Marko M. Skoric, Nathaniel D. Poor, Palakorn Achananuparp, Ee Peng Lim, Jing Jiang
Tweets And Votes: A Study Of The 2011 Singapore General Election, Marko M. Skoric, Nathaniel D. Poor, Palakorn Achananuparp, Ee Peng Lim, Jing Jiang
Research Collection School Of Computing and Information Systems
This study focuses on the uses of Twitter during the elections, examining whether the messages posted online are reflective of the climate of public opinion. Using Twitter data obtained during the official campaign period of the 2011 Singapore General Election, we test the predictive power of tweets in forecasting the election results. In line with some previous studies, we find that during the elections the Twitter sphere represents a rich source of data for gauging public opinion and that the frequency of tweets mentioning names of political parties, political candidates and contested constituencies could be used to make predictions about …
Dynamic Secure Cloud Storage With Provenance, Sherman S. M. Chow, Cheng-Kang Chu, Xinyi Huang, Jianying Zhou, Robert H. Deng
Dynamic Secure Cloud Storage With Provenance, Sherman S. M. Chow, Cheng-Kang Chu, Xinyi Huang, Jianying Zhou, Robert H. Deng
Research Collection School Of Computing and Information Systems
One concern in using cloud storage is that the sensitive data should be confidential to the servers which are outside the trust domain of data owners. Another issue is that the user may want to preserve his/her anonymity in the sharing or accessing of the data (such as in Web 2.0 applications). To fully enjoy the benefits of cloud storage, we need a confidential data sharing mechanism which is fine-grained (one can specify who can access which classes of his/her encrypted files), dynamic (the total number of users is not fixed in the setup, and any new user can decrypt …
Evaluating The Use Of A Mobile Annotation System For Geography Education, Dion Hoe-Lian Goh, Khasfariyati Razikin, Chei Sian Lee, Ee Peng Lim, Kalyani Chatterjea, Chew-Hung Chang
Evaluating The Use Of A Mobile Annotation System For Geography Education, Dion Hoe-Lian Goh, Khasfariyati Razikin, Chei Sian Lee, Ee Peng Lim, Kalyani Chatterjea, Chew-Hung Chang
Research Collection School Of Computing and Information Systems
Mobile devices used in educational settings are usually employed within a collaborative learning activity in which learning takes place in the form of social interactions between team members while performing a shared task. The authors aim to introduce MobiTOP (Mobile Tagging of Objects and People), a mobile annotation system that allows users to contribute and share geospatial multimedia annotations via mobile devices. Field observations and interviews were conducted. A group of trainee teachers involved in a geography field study were instructed to identify rock formations by collaborating with each other using the MobiTOP system. The trainee teachers who were in …
Imbalance Challenge Of Enacting Information Privacy Safeguards In Healthcare: A Grounded Theory Approach, Rachida Parks, Heng Xu, Chao-Hsien Chu
Imbalance Challenge Of Enacting Information Privacy Safeguards In Healthcare: A Grounded Theory Approach, Rachida Parks, Heng Xu, Chao-Hsien Chu
Research Collection School Of Computing and Information Systems
Healthcare organizations face significant challenges in designing and implementing the appropriate safeguards to mitigate information privacy threats. While many studies examined various technical and behavioral safeguards to protect the confidentiality and privacy of patient information, very little is known about the actual outcomes and implications of the privacy practices in which organizations engage. There is little research theoretically explaining the outcomes of enacting privacy safeguards and subsequent effects on privacy compliance. This paper reports the results of a grounded theory study investigating the intended consequences (positive impacts) and unintended (negative impacts) consequences of enacting privacy safeguards in healthcare organizations. An …
A Survey On Privacy Frameworks For Rfid Authentication, Chunhua Su, Yingjiu Li, Yunlei Zhao, Robert H. Deng, Yiming Zhao, Jianying Zhou
A Survey On Privacy Frameworks For Rfid Authentication, Chunhua Su, Yingjiu Li, Yunlei Zhao, Robert H. Deng, Yiming Zhao, Jianying Zhou
Research Collection School Of Computing and Information Systems
Due to rapid growth of RFID system applications, the security and privacy problems become more and more important to guarantee the validity of RFID systems. Without introducing proper privacy protection mechanisms, widespread deployment of RFID could raise privacy concerns to both companies and individuals. As a fundamental issue for the design and analysis of secure RFID systems, some formal RFID privacy frameworks were proposed in recent years to give the principles for evaluating the security and privacy in RFID system. However, readers can be confused with so many proposed frameworks. In this paper, we make a comparative and survey study …
Content Contribution In Social Media: The Case Of Youtube, Qian Tang, Bin Gu, Andrew B. Whinston
Content Contribution In Social Media: The Case Of Youtube, Qian Tang, Bin Gu, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
Social media allows individuals and businesses to contribute contents for public viewing. However, little is known about the underlying incentives that why content providers derive utilities from such activities. In this study, we build a dynamic structural model to recover the utility function for content providers. Our model distinguishes short-term payoffs based on ad revenue sharing from long-term payoffs driven by content providers' reputation. The model was estimated using a panel data of 914 top 1000 video providers on You Tube from Jun 7th, 2010, to Aug 7th, 2011 since top providers are more likely to be encouraged by these …
Optimal Decision Making For Online Referral Marketing, Zhiling Guo
Optimal Decision Making For Online Referral Marketing, Zhiling Guo
Research Collection School Of Computing and Information Systems
Widely available web 2.0 technologies not only bring rich and interactive user experiences, but also easily help users advertise products or services on their own blogs and social network webpages. Online referral marketing, for example, is a business practice that rewards customers who successfully refer other customers to a website or upon completion of a sale usually via their own social contacts. The referral rewards come in different forms such as shopping vouchers, redeemable points, discounts, prizes, cash payments, etc. We develop an analytical model to evaluate the business potential of incorporating an online referral marketing program into the firm's …
A Fuzzy Logic Multi-Criteria Decision Framework For Selecting It Service Providers, Amir Karami, Zhiling Guo
A Fuzzy Logic Multi-Criteria Decision Framework For Selecting It Service Providers, Amir Karami, Zhiling Guo
Research Collection School Of Computing and Information Systems
Selecting IT service providers in information systems outsourcing involves both qualitative and quantitative evaluations. This paper proposes an integrated multi-criteria decision-making (MCDM) framework to effectively handle uncertainty and subjectivity in the vendor selection process. The proposed methods apply fuzzy logic approach to integrate qualitative survey data into traditional multi-criteria decision models such as data envelope analysis (DEA), analytical hierarchy process (AHP) methods, and TOPSIS. Based on case studies from Iranian banking industry, we empirically test the proposed framework and show it is superior to existing methods. We demonstrate that the fuzzy logic approach provides a robust analysis for vendor selection …
Preface: Trends In Natural And Machine Intelligence, Jonathan H. Chan, Ah-Hwee Tan
Preface: Trends In Natural And Machine Intelligence, Jonathan H. Chan, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Trends in natural and machine intelligence are increasingly reflecting a convergence in these two well-established fields of study. The Third International Neural Network Society Winter Conference (INNS-WC 2012) was held in Bangkok, Thailand, on October 3-5, 2012. INNS-WC2012, with an aim to bring together scientists, practitioners, and students worldwide, to discuss the past, present, and future challenges and trends in the area of natural and machine intelligence. This event has been a bi-annual conference of the International Neural Network Society (INNS) to provide a forum for international researchers to exchange latest ideas and advances on neural networks and related discipline.
Modeling And Compressing 3-D Facial Expressions Using Geometry Videos, Jiazhi Xia, Dao T. P. Quynh, Ying He, Xiaoming Chen, Steven C. H. Hoi
Modeling And Compressing 3-D Facial Expressions Using Geometry Videos, Jiazhi Xia, Dao T. P. Quynh, Ying He, Xiaoming Chen, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
In this paper, we present a novel geometry video (GV) framework to model and compress 3-D facial expressions. GV bridges the gap of 3-D motion data and 2-D video, and provides a natural way to apply the well-studied video processing techniques to motion data processing. Our framework includes a set of algorithms to construct GVs, such as hole filling, geodesic-based face segmentation, expression-invariant parameterization (EIP), and GV compression. Our EIP algorithm can guarantee the exact correspondence of the salient features (eyes, mouth, and nose) in different frames, which leads to GVs with better spatial and temporal coherence than that of …
A New Efficient Optimistic Fair Exchange Protocol Without Random Oracles, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
A New Efficient Optimistic Fair Exchange Protocol Without Random Oracles, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Research Collection School Of Computing and Information Systems
Optimistic fair exchange (OFE) is a kind of protocols to solve the problem of fair exchange between two parties. Most of the previous work on this topic are provably secure in the random oracle model. In this work, we propose a new construction of OFE from another cryptographic primitive, called time capsule signature. The construction is efficient and brings almost no overhead other than the primitive itself. The security of our new construction is based on that of the underlying primitive without relying on the random oracle heuristic. Applying our generic construction to the time capsule signature scheme recently proposed …
Crowd Documentation: Exploring The Coverage And The Dynamics Of Api Discussions On Stack Overflow, Chris Parnin, Christoph Treude, Lars Grammel, Margaret-Anne Storey
Crowd Documentation: Exploring The Coverage And The Dynamics Of Api Discussions On Stack Overflow, Chris Parnin, Christoph Treude, Lars Grammel, Margaret-Anne Storey
Research Collection School Of Computing and Information Systems
Traditionally, many types of software documentation, such as API documentation, require a process where a few people write for many potential users. The resulting documentation, when it exists, is often of poor quality and lacks sufficient examples and explanations. In this paper, we report on an empirical study to investigate how Question and Answer (Q&A) websites, such as Stack Overflow, facilitate crowd documentation — knowledge that is written by many and read by many. We examine the crowd documentation for three popular APIs: Android, GWT, and the Java programming language. We collect usage data using Google Code Search, and analyze …
Topic Based Query Suggestions For Video Search, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia
Topic Based Query Suggestions For Video Search, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia
Research Collection School Of Computing and Information Systems
Query suggestion is an assistive technology mechanism commonly used in search engines to enable a user to formulate their search queries by predicting or completing the next few query words that the user is likely to type. In most implementations, the suggestions are mined from query log and use some simple measure of query similarity such as query frequency or lexicographical matching. In this paper, we propose an alternative method of presenting query suggestions by their thematic topics. Our method adopts a document-centric approach to mine topics in the corpus, and does not require the availability of a query log. …
Road: A New Spatial Object Search Framework For Road Networks, Ken C. K. Lee, Wang-Chien Lee, Baihua Zheng, Yuan Tian
Road: A New Spatial Object Search Framework For Road Networks, Ken C. K. Lee, Wang-Chien Lee, Baihua Zheng, Yuan Tian
Research Collection School Of Computing and Information Systems
In this paper, we present a new system framework called ROAD for spatial object search on road networks. ROAD is extensible to diverse object types and efficient for processing various location-dependent spatial queries (LDSQs), as it maintains objects separately from a given network and adopts an effective search space pruning technique. Based on our analysis on the two essential operations for LDSQ processing, namely, network traversal and object lookup, ROAD organizes a large road network as a hierarchy of interconnected regional subnetworks (called Rnets). Each Rnet is augmented with 1) shortcuts and 2) object abstracts to accelerate network traversals and …
Mining Diversity On Social Media Networks, Lu Liu, Feida Zhu, Meng Jiang, Jiawei Han, Lifeng Sun, Shiqiang Yang
Mining Diversity On Social Media Networks, Lu Liu, Feida Zhu, Meng Jiang, Jiawei Han, Lifeng Sun, Shiqiang Yang
Research Collection School Of Computing and Information Systems
The fast development of multimedia technology and increasing availability of network bandwidth has given rise to an abundance of network data as a result of all the ever-booming social media and social websites in recent years, e.g., Flickr, Youtube, MySpace, Facebook, etc. Social network analysis has therefore become a critical problem attracting enthusiasm from both academia and industry. However, an important measure that captures a participant’s diversity in the network has been largely neglected in previous studies. Namely, diversity characterizes how diverse a given node connects with its peers. In this paper, we give a comprehensive study of this concept. …
Structural Analysis In Multi-Relational Social Networks, Bingtian Dai, Freddy Chua, Ee Peng Lim
Structural Analysis In Multi-Relational Social Networks, Bingtian Dai, Freddy Chua, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Modern social networks often consist of multiple relations among individuals. Understanding the structure of such multi-relational network is essential. In sociology, one way of structural analysis is to identify different positions and roles using blockmodels. In this paper, we generalize stochastic blockmodels to Generalized Stochastic Blockmodels (GSBM) for performing positional and role analysis on multi-relational networks. Our GSBM generalizes many different kinds of Multivariate Probability Distribution Function (MVPDF) to model different kinds of multirelational networks. In particular, we propose to use multivariate Poisson distribution for multi-relational social networks.
A Hybridized Lagrangian Relaxation And Simulated Annealing Method For The Course Timetabling Problem, Aldy Gunawan, Kim Leng Poh
A Hybridized Lagrangian Relaxation And Simulated Annealing Method For The Course Timetabling Problem, Aldy Gunawan, Kim Leng Poh
Research Collection School Of Computing and Information Systems
This paper describes a timetabling problem at universities, where a master course timetable is given extrinsically and conflicts due to students' course enrollment do not need to be considered. A solver for the problem, which integrates both teacher assignment and course scheduling, is described. An initial solution is obtained by a mathematical programming approach based on Lagrangian relaxation. This solution is further improved by a simulated annealing algorithm. The proposed method has been tested on instances from a university in Indonesia, as well as on several randomly generated datasets, and the corresponding computational results are reported.
Information Extraction From Text, Jing Jiang
Information Extraction From Text, Jing Jiang
Research Collection School Of Computing and Information Systems
Information extraction is the task of finding structured information from unstructured or semi-structured text. It is an important task in text mining and has been extensively studied in various research communities including natural language processing, information retrieval and Web mining. It has a wide range of applications in domains such as biomedical literature mining and business intelligence. Two fundamental tasks of information extraction are named entity recognition and relation extraction. The former refers to finding names of entities such as people, organizations and locations. The latter refers to finding the semantic relations such as FounderOf and HeadquarteredIn between entities. In …
Multi-Party Multi-Period Supply Chain Coordination, Thin Yin Leong, Michelle Lee Fong Cheong
Multi-Party Multi-Period Supply Chain Coordination, Thin Yin Leong, Michelle Lee Fong Cheong
Research Collection School Of Computing and Information Systems
We apply combinatorial auction as a coordination mechanism to smooth demands placed on suppliers' limited production capacities, allowing several manufacturers to share common suppliers effectively. Products are bidders bidding for parts from suppliers, consuming their capacities in different time periods. The fourth party logistic (4PL) provider acts as the auctioneer to coordinate bids and perform price iterations. We leverage on the strong links between the Lagrangian relaxation method and combinatorial auction, where the Lagrange multipliers serve as the supply capacity reserve prices, to balance the demand and supply of capacities. To prevent cyclic behaviour and to increase convergence speed, we …
A Sentiment Analysis Of Singapore Presidential Election 2011 Using Twitter Data With Census Correction, Murphy Junyu Choy, Michelle Lee Fong Cheong, Nang Laik Ma, Ping Shung Koo
A Sentiment Analysis Of Singapore Presidential Election 2011 Using Twitter Data With Census Correction, Murphy Junyu Choy, Michelle Lee Fong Cheong, Nang Laik Ma, Ping Shung Koo
Research Collection School Of Computing and Information Systems
Sentiment analysis is a new area in text analytics where it focuses on the analysis and understanding of the human emotions from the text patterns. This new form of analysis has been widely adopted in customer relationship management especially in the context of complaint management. However, sentiment analysis using Twitter data has remained extremely difficult to manage due to sampling biasness. In this paper, we will discuss about the application of reweighting techniques in conjunction with online sentiment divisions to predict the vote percentage that individual presidential candidate in Singapore will receive in the Presidential Election 2011. There will be …
Robust Local Search For Solving Rcpsp/Max With Durational Uncertainty, Na Fu, Hoong Chuin Lau, Pradeep Varakantham, Fei Xiao
Robust Local Search For Solving Rcpsp/Max With Durational Uncertainty, Na Fu, Hoong Chuin Lau, Pradeep Varakantham, Fei Xiao
Research Collection School Of Computing and Information Systems
Scheduling problems in manufacturing, logistics and project management have frequently been modeled using the framework of Resource Constrained Project Scheduling Problems with minimum and maximum time lags (RCPSP/max). Due to the importance of these problems, providing scalable solution schedules for RCPSP/max problems is a topic of extensive research. However, all existing methods for solving RCPSP/max assume that durations of activities are known with certainty, an assumption that does not hold in real world scheduling problems where unexpected external events such as manpower availability, weather changes, etc. lead to delays or advances in completion of activities. Thus, in this paper, our …
Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau
Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …
Consumer-Driven Innovation Management, Arcot Desai Narasimhalu, Shekhar Mitra
Consumer-Driven Innovation Management, Arcot Desai Narasimhalu, Shekhar Mitra
Research Collection School Of Computing and Information Systems
The evolution of human society leads to increased affluence and prosperity of certain populations, sometimes at the expense of well-established markets. Market leaders in products and services tend to be so focused on their current customer base that they are caught off guard with the changes in markets created by the evolution. These changes often go unnoticed until it is too late. The change in customer base often requires the repositioning of products and services through innovations, which address new and emerging markets. Some of these changes could potentially result in tectonic market shifts that force innovation managers to involve …