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Articles 8071 - 8100 of 9003

Full-Text Articles in Computer Sciences

Learning To Classify E-Mail, Irena Koprinska, Josiah Poon, James Clark, Jason Yuk Hin Chan May 2007

Learning To Classify E-Mail, Irena Koprinska, Josiah Poon, James Clark, Jason Yuk Hin Chan

Research Collection School Of Computing and Information Systems

In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a supervised learning setting, we investigate the use of random forest for automatic e-mail filing into folders and spam e-mail filtering. We show that random forest is a good choice for these tasks as it runs fast on large and high dimensional databases, is easy to tune and is highly accurate, outperforming popular algorithms such as decision trees, support vector machines and naive Bayes. We introduce a new accurate feature selector with linear time complexity. …

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Forgery Attack To An Asymptotically Optimal Traitor Tracing Scheme, Yongdong Wu, Feng Bao, Robert H. Deng May 2007

Forgery Attack To An Asymptotically Optimal Traitor Tracing Scheme, Yongdong Wu, Feng Bao, Robert H. Deng

Research Collection School Of Computing and Information Systems

In this paper, we present a forgery attack to a black-box traitor tracing scheme [2] called as CPP scheme. CPP scheme has efficient transmission rate and allows the tracer to identify a traitor with just one invalid ciphertext. Since the original CPP scheme is vulnerable to the multi-key attack, we improved CPP to thwart the attack. However, CPP is vulnerable to a fatal forgery attack. In the forgery attack, two traitors can collude to forge all valid decryption keys. The forged keys appear as perfect genuine keys, can decrypt all protected content, but are untraceable by the tracer. Fortunately, we …

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Enhancing The Performance Of Semi-Supervised Classification Algorithms With Bridging, Jason Yuk Hin Chan, Josiah Poon, Irena Koprinska May 2007

Enhancing The Performance Of Semi-Supervised Classification Algorithms With Bridging, Jason Yuk Hin Chan, Josiah Poon, Irena Koprinska

Research Collection School Of Computing and Information Systems

Traditional supervised classification algorithms require a large number of labelled examples to perform accurately. Semi-supervised classification algorithms attempt to overcome this major limitation by also using unlabelled examples. Unlabelled examples have also been used to improve nearest neighbour text classification in a method called bridging. In this paper, we propose the use of bridging in a semi-supervised setting. We introduce a new bridging algorithm that can be used as a base classifier in any supervised approach such as co-training or selflearning. We empirically show that classification performance increases by improving the semi-supervised algorithm’s ability to correctly assign labels to previouslyunlabelled …

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Modeling Architectural Strategy Using Design Structure Networks, C. Jason Woodard May 2007

Modeling Architectural Strategy Using Design Structure Networks, C. Jason Woodard

Research Collection School Of Computing and Information Systems

System architects face the formidable task of purposefully shaping an evolving space of complex designs. Their task s further complicated when they lack full control of the design process, and therefore must anticipate the behavior of other stakeholders, including the designers of component products and competing systems. This paper presents a conceptual tool called a design structure network (DSN) to help architects and design scientists reason effectively about these situations. A DSN is a graphical representation of a system’s design space. DSNs improve on existing representation schemes by providing a compact and intuitive way to express design options—the ability to …

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Vulnerability Analysis Of Emap: An Efficient Rfid Mutual Authentication Protocol, Tieyan Li, Robert H. Deng Apr 2007

Vulnerability Analysis Of Emap: An Efficient Rfid Mutual Authentication Protocol, Tieyan Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

In this paper, we analyze the security vulnerabilities of EMAP, an efficient RFID mutual authentication protocol recently proposed by Peris-Lopez et al. (2006). We present two effective attacks, a de-synchronization attack and a full-disclosure attack, against the protocol. The former permanently disables the authentication capability of a RFID tag by destroying synchronization between the tag and the RFID reader. The latter completely compromises a tag by extracting all the secret information stored in the tag. The de-synchronization attack can be carried out in just round of interaction in EMAP while the full-disclosure attack is accomplished across several runs of EMAP. …

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Social Network Structures In Open Source Software Development Teams, Y. Long, Keng Siau Apr 2007

Social Network Structures In Open Source Software Development Teams, Y. Long, Keng Siau

Research Collection School Of Computing and Information Systems

Drawing on social network theories and previous studies, this research examines the dynamics of social network structures in open source software (OSS) teams. Three projects were selected from SourceForge.net in terms of their similarities as well as their differences. Monthly data were extracted from the bug tracking systems in order to achieve a longitudinal view of the interaction pattern of each project. Social network analysis was used to generate the indices of social structure. The finding suggests that the interaction pattern of OSS projects evolves from a single hub at the beginning to a corel periphery model as the projects …

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A Multimodal And Multilevel Ranking Framework For Content-Based Video Retrieval, Steven C. H. Hoi, Michael R. Lyu Apr 2007

A Multimodal And Multilevel Ranking Framework For Content-Based Video Retrieval, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

One critical task in content-based video retrieval is to rank search results with combinations of multimodal resources effectively. This paper proposes a novel multimodal and multilevel ranking framework for content-based video retrieval. The main idea of our approach is to represent videos by graphs and learn harmonic ranking functions through fusing multimodal resources over these graphs smoothly. We further tackle the efficiency issue by a multilevel learning scheme, which makes the semi-supervised ranking method practical for large-scale applications. Our empirical evaluations on TRECVID 2005 dataset show that the proposed multimodal and multilevel ranking framework is effective and promising for content-based …

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A Multimodal And Multilevel Ranking Framework For Content-Based Video Retrieval, Steven C. H. Hoi, Michael R. Lyu Apr 2007

A Multimodal And Multilevel Ranking Framework For Content-Based Video Retrieval, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

One critical task in content-based video retrieval is to rank search results with combinations of multimodal resources effectively. This paper proposes a novel multimodal and multilevel ranking framework for content-based video retrieval. The main idea of our approach is to represent videos by graphs and learn harmonic ranking functions through fusing multimodal resources over these graphs smoothly. We further tackle the efficiency issue by a multilevel learning scheme, which makes the semi-supervised ranking method practical for large-scale applications. Our empirical evaluations on TRECVID 2005 dataset show that the proposed multimodal and multilevel ranking framework is effective and promising for content-based …

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Mining Colossal Frequent Patterns By Core Pattern Fusion, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu, Hong Cheng Apr 2007

Mining Colossal Frequent Patterns By Core Pattern Fusion, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu, Hong Cheng

Research Collection School Of Computing and Information Systems

Extensive research for frequent-pattern mining in the past decade has brought forth a number of pattern mining algorithms that are both effective and efficient. However, the existing frequent-pattern mining algorithms encounter challenges at mining rather large patterns, called colossal frequent patterns, in the presence of an explosive number of frequent patterns. Colossal patterns are critical to many applications, especially in domains like bioinformatics. In this study, we investigate a novel mining approach called Pattern-Fusion to efficiently find a good approximation to the colossal patterns. With Pattern-Fusion, a colossal pattern is discovered by fusing its small core patterns in one step, …

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Summarizing Review Scores Of "Unequal" Reviewers, Hady W. Lauw, Ee Peng Lim, Ke Wang Apr 2007

Summarizing Review Scores Of "Unequal" Reviewers, Hady W. Lauw, Ee Peng Lim, Ke Wang

Research Collection School Of Computing and Information Systems

A frequently encountered problem in decision making is the following review problem: review a large number of objects and select a small number of the best ones. An example is selecting conference papers from a large number of submissions. This problem involves two sub-problems: assigning reviewers to each object, and summarizing reviewers ’ scores into an overall score that supposedly reflects the quality of an object. In this paper, we address the score summarization sub-problem for the scenario where a small number of reviewers evaluate each object. Simply averaging the scores may not work as even a single reviewer could …

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Valuing Information Technology Infrastructures: A Growth Options Approach, Qizhi Dai, Robert J. Kauffman, Salvatore T. March Mar 2007

Valuing Information Technology Infrastructures: A Growth Options Approach, Qizhi Dai, Robert J. Kauffman, Salvatore T. March

Research Collection School Of Computing and Information Systems

Decisions to invest in information technology (IT) infrastructure are often made based on an assessment of its immediate value to the organization. However, an important source of value comes from the fact that such technologies have the potential to be leveraged in the development of future applications. From a real options perspective, IT infrastructure investments create growth options that can be exercised if and when an organization decides to develop systems to provide new or enhanced IT capabilities. We present an analytical model based on real options that shows the process by which this potential is converted into business value, …

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Tube (Text-Cube) For Discovering Documentary Evidence Of Associations Among Entities, Hady Lauw, Ee Peng Lim, Hwee Hwa Pang Mar 2007

Tube (Text-Cube) For Discovering Documentary Evidence Of Associations Among Entities, Hady Lauw, Ee Peng Lim, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

User-driven discovery of associations among entities, and documents that provide evidence for these associations, is an important search task conducted by researchers and do-main information specialists. Entities here refer to real or abstract objects such as people, organizations, ideologies, etc. Associations are the inter-relationships among entities. Most current works in query-driven document retrieval and finding representative subgraphs are ill-suited for the task as they lack an awareness of entity types as well as an intuitive representation of associations. We propose the TUBE model, a text cube approach for discovering associations and documentary evidence of these associations. The model consists of …

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Privacy-Preserving Credentials Upon Trusted Computing Augmented Servers, Yanjiang Yang, Robert H. Deng, Feng Bao Mar 2007

Privacy-Preserving Credentials Upon Trusted Computing Augmented Servers, Yanjiang Yang, Robert H. Deng, Feng Bao

Research Collection School Of Computing and Information Systems

Credentials are an indispensable means for service access control in electronic commerce. However, regular credentials such as X.509 certificates and SPKI/SDSI certificates do not address user privacy at all, while anonymous credentials that protect user privacy are complex and have compatibility problems with existing PKIs. In this paper we propose privacy-preserving credentials, a concept between regular credentials and anonymous credentials. The privacy-preserving credentials enjoy the advantageous features of both regular credentials and anonymous credentials, and strike a balance between user anonymity and system complexity. We achieve this by employing computer servers equipped with TPMs (Trusted Platform Modules). We present a …

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Percentage-Based Hybrid Pattern Training With Neural Network Specific Cross Over, Sheng-Uei Guan, Kiruthika Ramanathan Mar 2007

Percentage-Based Hybrid Pattern Training With Neural Network Specific Cross Over, Sheng-Uei Guan, Kiruthika Ramanathan

Research Collection School Of Computing and Information Systems

In this paper, a new weight-setting method is proposed to improve the training time and generalization accuracy of feed-forward neural networks. This method introduces a percentage-based hybrid pattern training (PHP) scheme and aims to provide a solution to the problem dependency of other Genetic Algorithm (GA)-based Neural Network weight-setting methods. A neural network is trained using a neural network specific GA until a certain percentage of the training patterns is learned. The weights thus obtained are used as the initial weights for backpropagation (BP) training, which is then applied to complete the network training. Further improvement to the method was …

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Experiences With Tracking The Effects Of Changing Requirements On Morphbank: A Web-Based Bioinformatics Application, Subhajit Datta, Robert Van Engelen, David Gaitros, Neelima Jammigumpula Mar 2007

Experiences With Tracking The Effects Of Changing Requirements On Morphbank: A Web-Based Bioinformatics Application, Subhajit Datta, Robert Van Engelen, David Gaitros, Neelima Jammigumpula

Research Collection School Of Computing and Information Systems

In this paper, we present a case study of applying the metrics Mutation Index, Component Set, Dependency Index on Morphbank- a web based bioinformatics application - to track the effects of changing requirements on a software system and suggest design modifications to mitigate such impact. Morphbank is "an open web repository of biological images documenting specimen-based research in comparative anatomy, morphological phylogenetics, taxonomy and related fields focused on increasing our knowledge about biodiversity". This paper discusses the context of the case study, analyzes the results, highlights observations and learning, and mentions directions of future work.

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Malicious Kgc Attacks In Certificateless Cryptography, Man Ho Au, Jing Chen, Joseph K. Liu, Yi Mu, Duncan S. Wong, Guomin Yang, Guomin Yang Mar 2007

Malicious Kgc Attacks In Certificateless Cryptography, Man Ho Au, Jing Chen, Joseph K. Liu, Yi Mu, Duncan S. Wong, Guomin Yang, Guomin Yang

Research Collection School Of Computing and Information Systems

Identity-based cryptosystems have an inherent key escrow issue, that is, the Key Generation Center (KGC) always knows user secret key. If the KGC is malicious, it can always impersonate the user. Certificateless cryptography, introduced by Al-Riyami and Paterson in 2003, is intended to solve this problem. However, in all the previously proposed certificateless schemes, it is always assumed that the malicious KGC starts launching attacks (so-called Type II attacks) only after it has generated a master public/secret key pair honestly. In this paper, we propose new security models that remove this assumption for both certificateless signature and encryption schemes. Under …

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Efficient Algorithms For Machine Scheduling Problems With Earliness And Tardiness Penalties, Guang Feng, Hoong Chuin Lau Mar 2007

Efficient Algorithms For Machine Scheduling Problems With Earliness And Tardiness Penalties, Guang Feng, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In this paper, we study the multi-machine scheduling problem with earliness and tardiness penalties and sequence dependent setup times. This problem can be decomposed into two subproblems—sequencing and timetabling. Sequencing focuses on assigning each job to a fixed machine and determine the job sequence on each machine. We call such assignment a semi-schedule. Timetabling focuses on finding an executable schedule from the semi-schedule via idle-time insertion. Sequencing is strongly NP-hard in general. Although timetabling is polynomial-time solvable, it can become a computational bottleneck if the procedure is executed many times within a larger framework. This paper makes two contributions. We …

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Logistics Network Design With Supplier Consolidation Hubs And Multiple Shipment Options, Michelle L. F. Cheong, Rohit Bhatnagar, Stephen C. Graves Feb 2007

Logistics Network Design With Supplier Consolidation Hubs And Multiple Shipment Options, Michelle L. F. Cheong, Rohit Bhatnagar, Stephen C. Graves

Research Collection School Of Computing and Information Systems

An important service provided by third-party logistics (3PL) firms is to manage the inbound logistics of raw materials and components from multiple suppliers to several manufacturing plants. A key challenge for these 3PL firms is to determine how to coordinate and consolidate the transportation flow, so as to get the best overall logistics performance. One tactic is to establish consolidation hubs that collect shipments from several suppliers, consolidate these shipments, and direct the consolidated shipments to the appropriate manufacturing plant. We consider the network design problem to implement this tactic, namely deciding the number, location and operation of consolidation hubs …

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Mining Generalized Associations Of Semantic Relations From Textual Web Content, Tao Jiang, Ah-Hwee Tan, We Wang Feb 2007

Mining Generalized Associations Of Semantic Relations From Textual Web Content, Tao Jiang, Ah-Hwee Tan, We Wang

Research Collection School Of Computing and Information Systems

Traditional text mining techniques transform free text into flat bags of words representation, which does not preserve sufficient semantics for the purpose of knowledge discovery. In this paper, we present a two-step procedure to mine generalized associations of semantic relations conveyed by the textual content of Web documents. First, RDF (resource description framework) metadata representing semantic relations are extracted from raw text using a myriad of natural language processing techniques. The relation extraction process also creates a term taxonomy in the form of a sense hierarchy inferred from WordNet. Then, a novel generalized association pattern mining algorithm (GP-Close) is applied …

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Lecture Video Enhancement And Editing By Integrating Posture, Gesture, And Text, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong Feb 2007

Lecture Video Enhancement And Editing By Integrating Posture, Gesture, And Text, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong

Research Collection School Of Computing and Information Systems

This paper describes a novel framework for automatic lecture video editing by gesture, posture, and video text recognition. In content analysis, the trajectory of hand movement is tracked and the intentional gestures are automatically extracted for recognition. In addition, head pose is estimated through overcoming the difficulties due to the complex lighting conditions in classrooms. The aim of recognition is to characterize the flow of lecturing with a series of regional focuses depicted by human postures and gestures. The regions of interest (ROIs) in videos are semantically structured with text recognition and the aid of external documents. By tracing the …

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Towards Efficient Planning For Real World Partially Observable Domains, Pradeep R. Varakantham Feb 2007

Towards Efficient Planning For Real World Partially Observable Domains, Pradeep R. Varakantham

Research Collection School Of Computing and Information Systems

My research goal is to build large-scale intelligent systems (both single- and multi-agent) that reason with uncertainty in complex, real-world environments. I foresee an integration of such systems in many critical facets of human life ranging from intelligent assistants in hospitals to offices, from rescue agents in large scale disaster response to sensor agents tracking weather phenomena in earth observing sensor webs, and others. In my thesis, I have taken steps towards achieving this goal in the context of systems that operate in partially observable domains that also have transitional (non-deterministic outcomes to actions) uncertainty. Given this uncertainty, Partially Observable …

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Clustering And Combinatorial Optimization In Recursive Supervised Learning, Kiruthika Ramanathan, Sheng Uei Guan Feb 2007

Clustering And Combinatorial Optimization In Recursive Supervised Learning, Kiruthika Ramanathan, Sheng Uei Guan

Research Collection School Of Computing and Information Systems

The use of combinations of weak learners to learn a dataset has been shown to be better than the use of a single strong learner. In fact, the idea is so successful that boosting, an algorithm combining several weak learners for supervised learning, has been considered to be the best off the shelf classifier. However, some problems still exist, including determining the optimal number of weak learners and the over fitting of data. In an earlier work, we developed the RPHP algorithm which solves both these problems by using a combination of global search, weak learning and pattern distribution. In …

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Quality Of Service Routing Strategy Using Supervised Genetic Algorithm, Zhaoxia Wang, Yugeng Sun, Zhiyong Wang, Huayu Shen Feb 2007

Quality Of Service Routing Strategy Using Supervised Genetic Algorithm, Zhaoxia Wang, Yugeng Sun, Zhiyong Wang, Huayu Shen

Research Collection School Of Computing and Information Systems

A supervised genetic algorithm (SGA) is proposed to solve the quality of service (QoS) routing problems in computer networks. The supervised rules of intelligent concept are introduced into genetic algorithms (GAs) to solve the constraint optimization problem. One of the main characteristics of SGA is its searching space can be limited in feasible regions rather than infeasible regions. The superiority of SGA to other GAs lies in that some supervised search rules in which the information comes from the problems are incorporated into SGA. The simulation results show that SGA improves the ability of searching an optimum solution and accelerates …

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Moving-Object Detection, Association, And Selection In Home Videos, Zailiang Pan, Chong-Wah Ngo Feb 2007

Moving-Object Detection, Association, And Selection In Home Videos, Zailiang Pan, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Due to the prevalence of digital video camcorders, home videos have become an important part of life-logs of personal experiences. To enable efficient video parsing, a critical step is to automatically extract objects, events and scene characteristics present in videos. This paper addresses the problem of extracting objects from home videos. Automatic detection of objects is a classical yet difficult vision problem, particularly for videos with complex scenes and unrestricted domains. Compared with edited and surveillant videos, home videos captured in uncontrolled environment are usually coupled with several notable features such as shaking artifacts, irregular motions, and arbitrary settings. These …

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Searching And Tagging: Two Sides Of The Same Coin?, Qiaozhu Mei, Jing Jiang, Hang Su, Chengxiang Zhai Jan 2007

Searching And Tagging: Two Sides Of The Same Coin?, Qiaozhu Mei, Jing Jiang, Hang Su, Chengxiang Zhai

Research Collection School Of Computing and Information Systems

This paper presents the duality hypothesis of search and tagging, two important behaviors of web users. The hypothesis states that if a user views a document D in the search results for query Q, the user would tend to assign document $D$ a tag identical to or similar to Q; similarly, if a user tags a document D with a tag T, the user would tend to view document D if it is in the search results obtained using T as a query. We formalize this hypothesis with a unified probabilistic model for search and tagging, and show that empirical …

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Real-Time Supply Chain Control Via Multi-Agent Adjustable Autonomy, Hoong Chuin Lau, Lucas Agussurja, Ramesh Thangarajoo Jan 2007

Real-Time Supply Chain Control Via Multi-Agent Adjustable Autonomy, Hoong Chuin Lau, Lucas Agussurja, Ramesh Thangarajoo

Research Collection School Of Computing and Information Systems

Real-time supply chain management in a rapidly changing environment requires reactive and dynamic collaboration among participating entities. In this work, we model supply chain as a multi-agent system where agents are subject to an adjustable autonomy. The autonomy of an agent refers to its capability to make and influence decisions within a multi-agent system. Adjustable autonomy means changing the autonomy of the agents during runtime as a response to changes in the environment. In the context of a supply chain, different entities will have different autonomy levels and objective functions as the environment changes, and the goal is to design …

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Anticipatory Event Detection Via Classification, He Qi, Kuiyu Chang, Ee Peng Lim Jan 2007

Anticipatory Event Detection Via Classification, He Qi, Kuiyu Chang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

The idea of event detection is to identify interesting patterns from a constant stream of incoming news documents. Previous research in event detection has largely focused on identifying the first event or tracking subsequent events belonging to a set of pre-assigned topics such as earthquakes, airline disasters, etc. In this paper, we describe a new problem, called anticipatory event detection (AED), which aims to detect if a user-specified event has transpired. AED can be viewed as a personalized combination of event tracking and new event detection. We propose using sentence-level and document-level classification approaches to solve the AED problem for …

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Businessfinder: Harnessing Presence To Enable Live Yellow Pages For Small, Medium And Micro Mobile Businesses, D. Chakraborty, K. Dasgupta, S. Mittal, Archan Misra, C. Oberle, A. Gupta, E. Newmark Jan 2007

Businessfinder: Harnessing Presence To Enable Live Yellow Pages For Small, Medium And Micro Mobile Businesses, D. Chakraborty, K. Dasgupta, S. Mittal, Archan Misra, C. Oberle, A. Gupta, E. Newmark

Research Collection School Of Computing and Information Systems

Applications leveraging network presence in next-generation cellular networks have so far focused on subscription queries, where "presence" information is extracted from specific devices and sent to entities who have subscribed to such presence information. In this article we present BusinessFinder, a service that leverages the underlying cellular presence substrate to provide efficient, on-demand, context-aware matching of customer requests to nomadic micro businesses as well as small and medium businesses having a mobile workforce. Presence, in the context of BusinessFinder, is not simply limited to phone location and device status, but also encompasses dynamic attributes of vendors (both "mobile" and "static"), …

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Image Segmentation Using Multi-Coloured Active Illumination, Tze Ki (Xu Shuqi) Koh, Nicholas Miles, Barrie Hayes-Gill Jan 2007

Image Segmentation Using Multi-Coloured Active Illumination, Tze Ki (Xu Shuqi) Koh, Nicholas Miles, Barrie Hayes-Gill

Research Collection School Of Computing and Information Systems

In this paper, the use of active illumination is extended to image segmentation, specifically in the case of overlapping particles. This work is based on Multi-Flash Imaging (MFI), originally developed by Mitsubishi Electric Labs, to detect depth discontinuities. Illuminations of different wavelengths are projected from multiple positions, providing additional information about a scene compared to conventional segmentation techniques. Shadows are used to identify true object edges. The identification of non- occluded particles is made possible by exploiting the fact that shadows are cast on underlying particles. Implementation issues such as selecting the appropriate colour model and number of illuminations are …

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Iterated Weaker-Than-Weak Dominance, Shih-Fen Cheng, Michael P. Wellman Jan 2007

Iterated Weaker-Than-Weak Dominance, Shih-Fen Cheng, Michael P. Wellman

Research Collection School Of Computing and Information Systems

We introduce a weakening of standard gametheoretic δ-dominance conditions, called dominance, which enables more aggressive pruning of candidate strategies at the cost of solution accuracy. Equilibria of a game obtained by eliminating a δ-dominated strategy are guaranteed to be approximate equilibria of the original game, with degree of approximation bounded by the dominance parameter. We can apply elimination of δ-dominated strategies iteratively, but the for which a strategy may be eliminated depends on prior eliminations. We discuss implications of this order independence, and propose greedy heuristics for determining a sequence of eliminations to reduce the game as far as possible …

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