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Full-Text Articles in Entire DC Network
A Hybrid Agent Architecture Integrating Desire, Intention And Reinforcement Learning, Ah-Hwee Tan, Yew-Soon Ong, Akejariyawong Tapanuj
A Hybrid Agent Architecture Integrating Desire, Intention And Reinforcement Learning, Ah-Hwee Tan, Yew-Soon Ong, Akejariyawong Tapanuj
Research Collection School Of Computing and Information Systems
This paper presents a hybrid agent architecture that integrates the behaviours of BDI agents, specifically desire and intention, with a neural network based reinforcement learner known as Temporal DifferenceFusion Architecture for Learning and COgNition (TD-FALCON). With the explicit maintenance of goals, the agent performs reinforcement learning with the awareness of its objectives instead of relying on external reinforcement signals. More importantly, the intention module equips the hybrid architecture with deliberative planning capabilities, enabling the agent to purposefully maintain an agenda of actions to perform and reducing the need of constantly sensing the environment. Through reinforcement learning, plans can also be …
Heuristic Algorithms For Balanced Multi-Way Number Partitioning, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang
Heuristic Algorithms For Balanced Multi-Way Number Partitioning, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
Balanced multi-way number partitioning (BMNP) seeks to split a collection of numbers into subsets with (roughly) the same cardinality and subset sum. The problem is NP-hard, and there are several exact and approximate algorithms for it. However, existing exact algorithms solve only the simpler, balanced two-way number partitioning variant, whereas the most effective approximate algorithm, BLDM, may produce widely varying subset sums. In this paper, we introduce the LRM algorithm that lowers the expected spread in subset sums to one third that of BLDM for uniformly distributed numbers and odd subset cardinalities. We also propose Meld, a novel strategy for …
Linking Entities To A Knowledge Base With Query Expansion, Swapna Gottipati, Jing Jiang
Linking Entities To A Knowledge Base With Query Expansion, Swapna Gottipati, Jing Jiang
Research Collection School Of Computing and Information Systems
In this paper we present a novel approach to entity linking based on a statistical language model-based information retrieval with query expansion. We use both local contexts and global world knowledge to expand query language models. We place a strong emphasis on named entities in the local contexts and explore a positional language model to weigh them differently based on their distances to the query. Our experiments on the TAC-KBP 2010 data show that incorporating such contextual information indeed aids in disambiguating the named entities and consistently improves the entity linking performance. Compared with the official results from KBP 2010 …
Generating Aspect-Oriented Multi-Document Summarization With Event-Aspect Model, Peng Li, Yinglin Wang, Wei Gao, Jing Jiang
Generating Aspect-Oriented Multi-Document Summarization With Event-Aspect Model, Peng Li, Yinglin Wang, Wei Gao, Jing Jiang
Research Collection School Of Computing and Information Systems
In this paper, we propose a novel approach to automatic generation of aspect-oriented summaries from multiple documents. We first develop an event-aspect LDA model to cluster sentences into aspects. We then use extended LexRank algorithm to rank the sentences in each cluster. We use Integer Linear Programming for sentence selection. Key features of our method include automatic grouping of semantically related sentences and sentence ranking based on extension of random walk model. Also, we implement a new sentence compression algorithm which use dependency tree instead of parser tree. We compare our method with four baseline methods. Quantitative evaluation based on …
Finding Robust-Under-Risk Solutions For Flowshop Scheduling, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau
Finding Robust-Under-Risk Solutions For Flowshop Scheduling, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We propose and explore, in the context of benchmark problems for flowshop scheduling, a risk-based concept of robustness for optimization problems. This risk-based concept is in distinction to, and complements, the uncertainty-based concept employed in the field known as robust optimization. Implementation of our concept requires problem solution methods that sample the solution space intelligently and that produce large numbers of distinct sample points. With these solutions to hand, their robustness scores are easily obtained and heuristically robust solutions found. We find evolutionary computation to be effective for this purpose on these problems.
Parallel Learning To Rank For Information Retrieval, Shuaiqiang Wang, Byron J. Gao, Ke Wang, Hady W. Lauw
Parallel Learning To Rank For Information Retrieval, Shuaiqiang Wang, Byron J. Gao, Ke Wang, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Learning to rank represents a category of effective ranking methods for information retrieval. While the primary concern of existing research has been accuracy, learning efficiency is becoming an important issue due to the unprecedented availability of large-scale training data and the need for continuous update of ranking functions. In this paper, we investigate parallel learning to rank, targeting simultaneous improvement in accuracy and efficiency.
Real-World Parameter Tuning Using Factorial Design With Parameter Decomposition, Aldy Gunawan, Hoong Chuin Lau, Elaine Wong
Real-World Parameter Tuning Using Factorial Design With Parameter Decomposition, Aldy Gunawan, Hoong Chuin Lau, Elaine Wong
Research Collection School Of Computing and Information Systems
In this paper, we explore the idea of improving the efficiency of factorial design for parameter tuning of metaheuristics. In a standard full factorial design, the number of runs increases exponentially as the number of parameters. To reduce the parameter search space, one option is to first partition parameters into disjoint categories. While this may be done manually based on user guidance, an automated approach proposed in this paper is to apply a fractional factorial design to partition parameters based on their main effects where each partition is then tuned independently. With a careful choice of fractional design, our approach …
Unsupervised Discovery Of Discourse Relations For Eliminating Intra-Sentence Polarity Ambiguities, Lanjun Zhou, Binyang Li, Wei Gao, Zhongyu Wei, Kam-Fai Wong
Unsupervised Discovery Of Discourse Relations For Eliminating Intra-Sentence Polarity Ambiguities, Lanjun Zhou, Binyang Li, Wei Gao, Zhongyu Wei, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Polarity classification of opinionated sentences with both positive and negative sentiments1 is a key challenge in sentiment analysis. This paper presents a novel unsupervised method for discovering intra-sentence level discourse relations for eliminating polarity ambiguities. Firstly, a discourse scheme with discourse constraints on polarity was defined empirically based on Rhetorical Structure Theory (RST). Then, a small set of cuephrase-based patterns were utilized to collect a large number of discourse instances which were later converted to semantic sequential representations (SSRs). Finally, an unsupervised method was adopted to generate, weigh and filter new SSRs without cue phrases for recognizing discourse relations. Experimental …
Relevant Knowledge Helps In Choosing Right Teacher: Active Query Selection For Ranking Adaptation, Peng Cai, Wei Gao, Kam-Fai Wong, Aoying Zhou
Relevant Knowledge Helps In Choosing Right Teacher: Active Query Selection For Ranking Adaptation, Peng Cai, Wei Gao, Kam-Fai Wong, Aoying Zhou
Research Collection School Of Computing and Information Systems
Learning to adapt in a new setting is a common challenge to our knowledge and capability. New life would be easier if we actively pursued supervision from the right mentor chosen with our relevant but limited prior knowledge. This variant principle of active learning seems intuitively useful to many domain adaptation problems. In this paper, we substantiate its power for advancing automatic ranking adaptation, which is important in web search since it's prohibitive to gather enough labeled data for every search domain for fully training domain-specific rankers. For the cost-effectiveness, it is expected that only those most informative instances in …
Scalable Multiagent Planning Using Probabilistic Inference, Akshat Kumar, Shlomo Zilberstein, Marc Toussaint
Scalable Multiagent Planning Using Probabilistic Inference, Akshat Kumar, Shlomo Zilberstein, Marc Toussaint
Research Collection School Of Computing and Information Systems
Multiagent planning has seen much progress with the development of formal models such as Dec-POMDPs. However, the complexity of these models -- NEXP-Complete even for two agents -- has limited scalability. We identify certain mild conditions that are sufficient to make multiagent planning amenable to a scalable approximation w.r.t. the number of agents. This is achieved by constructing a graphical model in which likelihood maximization is equivalent to plan optimization. Using the Expectation-Maximization framework for likelihood maximization, we show that the necessary inference can be decomposed into processes that often involve a small subset of agents, thereby facilitating scalability. We …
Cio Reporting Structure, Strategic Positioning, And Firm Performance, Rajiv D Banker, Nan Hu, Paul A Pavlou, Jerry Luftman
Cio Reporting Structure, Strategic Positioning, And Firm Performance, Rajiv D Banker, Nan Hu, Paul A Pavlou, Jerry Luftman
Research Collection School Of Computing and Information Systems
Almost 30 years after the introduction of the CIO position, the ideal CIO reporting structure (whether the CIO should report to the CEO or the CFO) is yet to be identified. There is an intuitive assumption among some proponents of IT that the CIO should always report to the CEO to promote the importance of IT and the CIO's clout in the firm, while some adversaries of IT call for a CIO—CFO reporting structure to keep a tab on IT spending. However, we challenge these two ad hoc prescriptions by arguing that neither CIO reporting structure is necessarily optimal, and …
Optimizing Sensor Data Acquisition For Energy-Efficient Smartphone-Based Continuous Event Processing, Archan Misra, Lipyeow Lim
Optimizing Sensor Data Acquisition For Energy-Efficient Smartphone-Based Continuous Event Processing, Archan Misra, Lipyeow Lim
Research Collection School Of Computing and Information Systems
Many pervasive applications, such as activity recognition or remote wellness monitoring, utilize a personal mobile device (aka smartphone) to perform continuous processing of data streams acquired from locally-connected, wearable, sensors. To ensure the continuous operation of such applications on a battery-limited mobile device, it is essential to dramatically reduce the energy overhead associated with the process of sensor data acquisition and processing. To achieve this goal, this paper introduces a technique of "acquisition-cost" aware continuous query processing, as part of the Acquisition Cost-Aware Query Adaptation (ACQUA) framework. ACQUA replaces the current paradigm, where the data is typically streamed (pushed) from …
Continuous Visible Nearest Neighbor Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li, Xiaofa Guo
Continuous Visible Nearest Neighbor Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li, Xiaofa Guo
Research Collection School Of Computing and Information Systems
In this paper, we identify and solve a new type of spatial queries, called continuous visible nearest neighbor (CVNN) search. Given a data set P, an obstacle set O, and a query line segment q in a two-dimensional space, a CVNN query returns a set of $${\langle p, R\rangle}$$ tuples such that $${p \in P}$$ is the nearest neighbor to every point r along the interval $${R \subseteq q}$$ as well as pis visible to r. Note that p may be NULL, meaning that all points in P are invisible to all points in R due to the obstruction of …
A Feature Based Frequency Domain Analysis Algorithm For Fault Detection Of Induction Motors, Zhaoxia Wang, C. S. Chang, Zhang Yifan
A Feature Based Frequency Domain Analysis Algorithm For Fault Detection Of Induction Motors, Zhaoxia Wang, C. S. Chang, Zhang Yifan
Research Collection School Of Computing and Information Systems
This paper studies the stator currents collected from several inverter-fed laboratory induction motors and proposes a new feature based frequency domain analysis method for performing the detection of induction motor faults, such as the broken rotor-bar or bearing fault. The mathematical formulation is presented to calculate the features, which are called FFT-ICA features in this paper. The obtained FFT-ICA features are normalized by using healthy motor as benchmarks to establish a feature database for fault detection. Compare with conventional frequency-domain analysis method, no prior knowledge of the motor parameters or other measurements are required for calculating features. Only one phase …
Supervisory Evolutionary Optimization Strategy For Adaptive Maintenance Schedules, Zhaoxia Wang, C. S. Chang
Supervisory Evolutionary Optimization Strategy For Adaptive Maintenance Schedules, Zhaoxia Wang, C. S. Chang
Research Collection School Of Computing and Information Systems
No abstract provided.
Topical Keyphrase Extraction From Twitter, Xin Zhao, Jing Jiang, Jing He, Yang Song, Palakorn Achananuparp, Ee Peng Lim, Xiaoming Li
Topical Keyphrase Extraction From Twitter, Xin Zhao, Jing Jiang, Jing He, Yang Song, Palakorn Achananuparp, Ee Peng Lim, Xiaoming Li
Research Collection School Of Computing and Information Systems
Summarizing and analyzing Twitter content is an important and challenging task. In this paper, we propose to extract topical keyphrases as one way to summarize Twitter. We propose a context-sensitive topical PageRank method for keyword ranking and a probabilistic scoring function that considers both relevance and interestingness of keyphrases for keyphrase ranking. We evaluate our proposed methods on a large Twitter data set. Experiments show that these methods are very effective for topical keyphrase extraction.
Kb-Anonymity: A Model For Anonymized Behavior-Preserving Test And Debugging Data, Aditya Budi, David Lo, Lingxiao Jiang, Lucia Lucia
Kb-Anonymity: A Model For Anonymized Behavior-Preserving Test And Debugging Data, Aditya Budi, David Lo, Lingxiao Jiang, Lucia Lucia
Research Collection School Of Computing and Information Systems
It is often very expensive and practically infeasible to generate test cases that can exercise all possible program states in a program. This is especially true for a medium or large industrial system. In practice, industrial clients of the system often have a set of input data collected either before the system is built or after the deployment of a previous version of the system. Such data are highly valuable as they represent the operations that matter in a client's daily business and may be used to extensively test the system. However, such data often carries sensitive information and cannot …
Real-Time Trip Information Service For A Large Taxi Fleet, Rajesh Krishna Balan, Nguyen Xuan Khoa, Lingxiao Jiang
Real-Time Trip Information Service For A Large Taxi Fleet, Rajesh Krishna Balan, Nguyen Xuan Khoa, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
In this paper, we describe the design, analysis, implementation, and operational deployment of a real-time trip information system that provides passengers with the expected fare and trip duration of the taxi ride they are planning to take. This system was built in cooperation with a taxi operator that operates more than 15,000 taxis in Singapore. We first describe the overall system design and then explain the efficient algorithms used to achieve our predictions based on up to 21 months of historical data consisting of approximately 250 million paid taxi trips. We then describe various optimisations (involving region sizes, amount of …
Using Service Responsibility Tables To Supplement Uml In Analyzing E-Service Systems, Xin Tan, Steven Alter, Keng Siau
Using Service Responsibility Tables To Supplement Uml In Analyzing E-Service Systems, Xin Tan, Steven Alter, Keng Siau
Research Collection School Of Computing and Information Systems
This paper proposes using Service Responsibility Tables (SRTs) as a tool in analyzing e-service systems. First it discusses difficulties and deficiencies of using formal modeling languages such as UML in analyzing e-service systems. It proposes using SRTs as an informal language and lightweight analytical tool to be used by business professionals in analyzing e-service systems. SRTs are based on a service value chain framework but do not rely on abstract concepts and constructs, and therefore can be used by business professionals to supplement UML. We suggest a set of heuristics for transforming SRTs into two key UML diagrams, thereby illustrating …
Getting To Global Yes! Designing A Distributed Student Collaboration, Selma Limam Mansar, Randy Weinberg, Benjamin Kok Siew Gan
Getting To Global Yes! Designing A Distributed Student Collaboration, Selma Limam Mansar, Randy Weinberg, Benjamin Kok Siew Gan
Research Collection School Of Computing and Information Systems
The authors have taught a course called 'Global Project Management' for four years, engaging students in three international locations in hands-on distance projects. The distance projects are intended to provide students with enriching, realistic global project experience. With experience, improved planning and better coordination, each iteration of the distance projects has improved. In this paper, the authors present lessons learned and a mind map demonstrating key aspects of design of global hands-on projects.
Hierarchical Identity-Based Chameleon Hash And Its Applications, Feng Bao, Robert H. Deng, Xuhua Ding, Junzuo Lai, Yunlei Zhao
Hierarchical Identity-Based Chameleon Hash And Its Applications, Feng Bao, Robert H. Deng, Xuhua Ding, Junzuo Lai, Yunlei Zhao
Research Collection School Of Computing and Information Systems
At ACNS 2008, Canard et al. introduced the notion of trapdoor sanitizable signature (TSS) based on identity-based chameleon hash (IBCH). Trapdoor sanitizable signatures allow the signer of a message to delegate, at any time, the power of sanitization to possibly several entities who can modify predetermined parts of the message and generate a new signature on the sanitized message without interacting with the original signer. In this paper, we introduce the notion of hierarchical identity-based chameleon hash (HIBCH), which is a hierarchical extension of IBCH. We show that HIBCH can be used to construct other cryptographic primitives, including hierarchical trapdoor …
A Quality Metric For Sustainable Innovations, Arcot Desai Narasimhalu
A Quality Metric For Sustainable Innovations, Arcot Desai Narasimhalu
Research Collection School Of Computing and Information Systems
Sustainability has become a major concern for nations and firms especially since the Kyoto Protocol was defined in 1997. While there have been several studies on benchmarks for national innovation systems and effectiveness of innovation management within firms there is as yet no reasonable metric for determining the quality of an innovation much less its quality relating to sustainability? Similarly, there have been several studies on sustainability but that such research groups have also not focused on developing a metric for denoting the quality of sustainable innovations. This paper offers a metric that defines the quality of an innovation, especially …
High-Performance Composite Event Monitoring System Supporting Large Numbers Of Queries And Sources, Sangjeong Lee, Youngki Lee, Byoungjip Kim, K. Selcuk Candan, Yunseok Rhee, Junehwa Song
High-Performance Composite Event Monitoring System Supporting Large Numbers Of Queries And Sources, Sangjeong Lee, Youngki Lee, Byoungjip Kim, K. Selcuk Candan, Yunseok Rhee, Junehwa Song
Research Collection School Of Computing and Information Systems
This paper presents a novel data structure, called Event-centric Composable Queue (ECQ), a basic building block of a new scalable composite event monitoring (CEM) framework, SCEMon. In particular, we focus on the scalability issues when large numbers of CEM queries and event sources exist in upcoming CEM environments. To address these challenges effectively, we take an event-centric sharing approach rather than dealing with queries and sources separately. ECQ is a shared queue, which stores incoming event instances of a primitive event class. ECQs are designed to facilitate efficient shared evaluations of multiple queries over very large volumes of event streams …
Smoothly Varying Affine Stitching, Wen-Yan Lin, Siying Liu, Yasuyuki Matsuhita, Tian-Tsong Ng, Loong-Fah Cheong
Smoothly Varying Affine Stitching, Wen-Yan Lin, Siying Liu, Yasuyuki Matsuhita, Tian-Tsong Ng, Loong-Fah Cheong
Research Collection School Of Computing and Information Systems
Traditional image stitching using parametric transforms such as homography, only produces perceptually correct composites for planar scenes or parallax free camera motion between source frames. This limits mosaicing to source images taken from the same physical location. In this paper, we introduce a smoothly varying affine stitching field which is flexible enough to handle parallax while retaining the good extrapolation and occlusion handling properties of parametric transforms. Our algorithm which jointly estimates both the stitching field and correspondence, permits the stitching of general motion source images, provided the scenes do not contain abrupt protrusions.
On Combining State Space Reductions With Global Fairness Assumptions, Shao Jie Zhang, Jun Sun, Jun Pang, Yang Liu, Jin Song Dong
On Combining State Space Reductions With Global Fairness Assumptions, Shao Jie Zhang, Jun Sun, Jun Pang, Yang Liu, Jin Song Dong
Research Collection School Of Computing and Information Systems
Model checking has established itself as an effective system analysis method, as it is capable of proving/dis-proving properties automatically. Its application to practical systems is however limited by state space explosion. Among effective state reduction techniques are symmetry reduction and partial order reduction. Global fairness often plays a vital role in designing self-stabilizing population protocols. It is known that combining fairness and symmetry reduction is nontrivial. In this work, we first show that global fairness, unlike weak/strong fairness, can be combined with symmetry reduction. We extend the PAT model checker with the technique and demonstrate its usability by verifying recently …
Adaptive Display Power Management For Mobile Games, Bhojan Anand, Karthik Thirugnanam, Jeena Sebastian, Pravein G. Kannan, Akhihebbal L. Ananda, Mun Choon Chan, Rajesh Krishna Balan
Adaptive Display Power Management For Mobile Games, Bhojan Anand, Karthik Thirugnanam, Jeena Sebastian, Pravein G. Kannan, Akhihebbal L. Ananda, Mun Choon Chan, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
In this paper, we show how tone mapping techniques can be used to dynamically increase the image brightness, thus allowing the LCD backlight levels to be reduced. This saves significant power as the majority of the LCD’s display power is consumed by its backlight. The Gamma function (or equivalent) can be efficiently implemented in smartphones with minimal resource cost. We describe how we overcame the Gamma function’s non-linear nature by using adaptive thresholds to apply different Gamma values to images with differing brightness levels. These adaptive thresholds allow us to save significant amounts of power while preserving the image quality. …
Fully Secure Cipertext-Policy Hiding Cp-Abe, Junzuo Lai, Robert H. Deng, Yingjiu Li
Fully Secure Cipertext-Policy Hiding Cp-Abe, Junzuo Lai, Robert H. Deng, Yingjiu Li
Research Collection School Of Computing and Information Systems
In ciphertext-policy attributed-based encryption (CP-ABE), each ciphertext is labeled by the encryptor with an access structure (also called ciphertext policy) and each private key is associated with a set of attributes. A user should be able to decrypt a ciphertext if and only if his private key attributes satisfy the access structure.The traditional security property of CP-ABE is plaintext privacy, which ciphertexts reveal no information about the underlying plaintext. At ACNS’08, Nishide, Yoneyama and Ohta introduced the notion of ciphertext-policy hiding CP-ABE. In addition to protecting the privacy of plaintexts, ciphertext-policy hiding CP-ABE also protects the description of the access …
A Solution With Security Concern For Rfid-Based Track And Trace Services In Epcglobal-Enabled Supply Chains, Wei He, Yingjiu Li, Kevin Chiew, Tieyan Li, Eng Wah Lee
A Solution With Security Concern For Rfid-Based Track And Trace Services In Epcglobal-Enabled Supply Chains, Wei He, Yingjiu Li, Kevin Chiew, Tieyan Li, Eng Wah Lee
Research Collection School Of Computing and Information Systems
A supply chain represents the flow of materials, information, and finance as they move through supply chain partners such as manufacturers, suppliers, distributors, retailers, and consumers. The track & trace services in supply chains can help improve supply chain visibility and efficiency, and prevent counterfeiting and stealing of products thus enhance security. Track & trace services in supply chains require identification of items, capture of events as items move through supply chains, and query of events of items. RFID (radio frequency identification) is a technology that allows to identify objects simultaneously in a fully automated manner via radio waves. This …
Online Fault Detection Of Induction Motors Using Frequency Domain Independent Components Analysis, Zhaoxia Wang, C. S. Chang
Online Fault Detection Of Induction Motors Using Frequency Domain Independent Components Analysis, Zhaoxia Wang, C. S. Chang
Research Collection School Of Computing and Information Systems
This paper proposes an online fault detection method for induction motors using frequency-domain independent component analysis. Frequency-domain results, which are obtained by applying Fast Fourier Transform (FFT) to measured stator current time-domain waveforms, are analyzed with the aim of extracting frequency signatures of healthy and faulty motors with broken rotor-bar or bearing problem. Independent components analysis (ICA) is applied for such an aim to the FFT results. The obtained independent components as well as the FFT results are then used to obtain the combined fault signatures. The proposed method overcomes problems occurring in many existing FFT-based methods. Results using laboratory-collected …
Towards Human-Like Social Multi-Agents With Memetic Automaton, Liang Feng, Yew-Soon Ong, Ah-Hwee Tan, Xian-Shun Chen
Towards Human-Like Social Multi-Agents With Memetic Automaton, Liang Feng, Yew-Soon Ong, Ah-Hwee Tan, Xian-Shun Chen
Research Collection School Of Computing and Information Systems
Memetics is a new science that has attracted increasing attentions in the recent decades. Beyond the formalism of simple hybrids, adaptive hybrids and memetic algorithms, the notion of memetic automaton as an adaptive entity that is self-contained and uses memes as building blocks of information is recently conceptualized in the context of computational intelligence as potential tools for effective problem-solving [1]. Taking this cue, this paper embarks a study on Memetic Multiagent system (MeM) towards human-like social agents with memetic automaton. Particularly, we introduce a potentially rich meme-inspired design and operational model, with Darwin’s theory of natural selections and Dawkins’ …