Harnessing Lab Knowledge for Real-World Action Recognition

Much research on human action recognition has been oriented toward the performance gain on lab-collected datasets. Yet real-world videos are more diverse, with more complicated actions and often only a few of them are precisely labeled. Thus, recognizing actions from these videos is a tough mission. The paucity of labeled real-world videos motivates us to “borrow” strength from other resources. Specifically, considering that many lab datasets are available, we propose to harness lab datasets to facilitate the action recognition in real-world videos given that the lab and real-world datasets are related. As their action categories are usually inconsistent, we design a multi-task learning framework to jointly optimize the classifiers for both sides. The general Schatten \(p\) -norm is exerted on the two classifiers to explore the shared knowledge between them. In this way, our framework is able to mine the shared knowledge between two datasets even if the two have different action categories, which is a major virtue of our method. The shared knowledge is further used to improve the action recognition in the real-world videos. Extensive experiments are performed on real-world datasets with promising results.     

Harnessing Digital Evolution

In digital evolution, self-replicating computer programs-digital organisms-experience mutations and selective pressures, potentially producing computational systems that, like natural organisms, adapt to their environment and protect themselves from threats. Such organisms can help guide the design of computer software.     

Harnessing Mainframe Strengths for an Enterprisewide Backup Solution

Abstract

Businesses have learned that perimeter security is no longer enough to protect critical data, and many are now touting the benefits of encrypting the data held in storage and backup systems. Driven largely by the awareness of security breaches, lawmakers, credit card issuers, and consumers themselves are holding organizations accountable for the protection of personal data. Today, businesses that suffer a security breach in which customer data is lost or stolen face widespread negative publicity, lost business, lawsuits, and fines that can threaten their viability. Although it's easy to immediately think that the storage or backup systems were compromised, it's important to note that, in an analysis of 45 of the reported incidents of data theft that occurred in the first half of 2005, only a small percentage were due to theft or loss of backup tapes. Far more prevalent were incidents in which insiders or outside attackers gained access to sensitive information through application-level attacks — attacks storage-level encryption wouldn't have prevented. This is why it is important for businesses to encrypt data at the Web, application, or database layer. Encrypting data as it enters the business, rather than having it stay in a readable state while it is used in various applications throughout the network, protects that data from both internal and external threats.     

Fuzzy cognitive maps for artificial emotions forecasting

At the present, emotion is considered as a critical point of human behaviour, and thus it should be embedded within the reasoning module when an intelligent system or a autonomous robot aims to emulate or anticipate human reactions. Therefore, current research in Artificial Intelligence shows an increasing interest in artificial emotion research for developing human-like systems. Based on Thayer's emotion model and Fuzzy Cognitive Maps, this paper presents a proposal for forecasting artificial emotions. It provides an innovative method for forecasting artificial emotions and designing an affective decision system. This work includes an experiment with three simulated artificial scenarios for testing the proposal. Each scenario generate different emotions according to the artificial experimental model.     

Harnessing Cloud Technologies for a Virtualized Distributed Computing Infrastructure

The InterGrid system aims to provide an execution environment for running applications on top of interconnected infrastructures. The system uses virtual machines as building blocks to construct execution environments that span multiple computing sites. Such environments can be extended to operate on cloud infrastructures, such as Amazon EC2. This article provides an abstract view of the proposed architecture and its implementation; experiments show the scalability of an InterGrid-managed infrastructure and how the system can benefit from using the cloud.     

Agents with emotions

This paper discusses the role of emotions in artificial agent design and implementation. The syntax and semantics of a simplified version of a logic‐based agent‐oriented programming language is presented. This programming language facilitates the implementation of artificial agents with emotions. Four types of emotions are distinguished: happiness, sadness, anger, and fear. These emotions are defined relative to agent's goals and plans. The emotions result from the agent's deliberation process and influence the deliberation process. The semantics of each emotion type is incorporated in the transition semantics of the presented agent‐oriented programming language. © 2010 Wiley Periodicals, Inc.     

Harnessing agile concepts for the development of Intelligent Systems

Traditional and current approaches to intelligent systems design, have led to the creation of sophisticated and computationally-intensive packages and environments, for a wide range of applications. This paper proposes methods with which to extend the functionality of such systems, borrowing knowledge management concepts from the field of Agile Manufacturing. As such, this paper proposes that the future of intelligent systems design should be based not only upon the continuing development of artificial intelligence techniques, but also effective methods for harnessing human skills and core competencies to achieve these aims. Amir M. Sharif: He obtained his BEng (Hons) in Aeronautical Engineering from City University (London) in 1994 and is a research student in the Department of Information Systems and Computing, Brunel University (UK) currently completing his Ph.D in artificial intelligence. Amir maitains close links with both industry and academia and research interests include Evolutionary and Knowledge Based Systems, IT/IS investment evaluation, Information Management and E-commerce/Supply Chain Management. He has published in internationally refereed journals and spoken at conferences world-wide and is a member of numerours computer science-related journal and conference program committee boards. He is an Associate Member of the Institute of Electrical Engineers (AMIEE) and also has student membership of the Association for Computing Machinery (ACM) and Institute of Electrical and Electronic Engineers.     

Using emotions for the development of human-agent societies

Human-agent societies refer to applications where virtual agents and humans coexist and interact transparently into a fully integrated environment. One of the most important aspects in this kind of applications is including emotional states of the agents (humans or not) in the decision-making process. In this sense, this paper presents the applicability of the JaCalIVE (Jason Cartago implemented intelligent virtual environment) framework for developing this kind of society. Specifically, the paper presents an ambient intelligence application where humans are immersed into a system that extracts and analyzes the emotional state of a human group. A social emotional model is employed to try to maximize the welfare of those humans by playing the most appropriate music in every moment.     

Group emotions: the social and cognitive functions of emotions in argumentation

The learning sciences of today recognize the tri-dimensional nature of learning as involving cognitive, social and emotional phenomena. However, many computer-supported argumentation systems still fail in addressing the socio-emotional aspects of group reasoning, perhaps due to a lack of an integrated theoretical vision of how these three dimensions interrelate to each other. This paper presents a multi-dimensional and multi-level model of the role of emotions in argumentation, inspired from a multidisciplinary literature review and extensive previous empirical work on an international corpus of face-to-face student debates. At the crossroads of argumentation studies and research on collaborative learning, employing a linguistic perspective, we specify the social and cognitive functions of emotions in argumentation. The cognitive function of emotions refers to the cognitive and discursive process of schematization (Grize, 1996, 1997). The social function of emotions refers to recognition-oriented behaviors that correspond to engagement into specific types of group talk (e. g. Mercer in Learning and Instruction 6(4), 359–377, 1996). An in depth presentation of two case studies then enables us to refine the relation between social and cognitive functions of emotions. A first case gives arguments for associating low-intensity emotional framing, on the cognitive side, with cumulative talk, on the social side. A second case shows a correlation between high-intensity emotional framing, and disputational talk. We then propose a hypothetical generalization from these two cases, adding an element to the initial model. In conclusion, we discuss how better understanding the relations between cognition and social and emotional phenomena can inform pedagogical design for CSCL.     

Harnessing the strengths of anytime algorithms for constant data streams

Anytime algorithms have been proposed for many different applications, e.g., in data mining. Their strengths are the ability to first provide a result after a very short initialization and second to improve their result with additional time. Therefore, anytime algorithms have so far been used when the available processing time varies, e.g., on varying data streams. In this paper we propose to employ anytime algorithms on constant data streams, i.e., for tasks with constant time allowance. We introduce two approaches that harness the strengths of anytime algorithms on constant data streams and thereby improve the over all quality of the result with respect to the corresponding budget algorithm. We derive formulas for the expected performance gain and demonstrate the effectiveness of our novel approaches using existing anytime algorithms on benchmark data sets.     

Automatic detection of depression symptoms in twitter using multimodal analysis

The Journal of Supercomputing - Depression is the most prevalent mental disorder that can lead to suicide. Due to the tendency of people to share their thoughts on social platforms, social data...     

Behavioral task processing for cognitive robots using artificial emotions

This paper presents an artificial emotional-cognitive system-based autonomous robot control architecture for a four-wheel driven and four-wheel steered mobile robot. Discrete stochastic state-space mathematical model is considered for behavioral and emotional transition processes of the autonomous mobile robot in the dynamic realistic environment. The term of cognitive mechanism system which is composed from rule base and reinforcement self-learning algorithm explain all of the deliberative events such as learning, reasoning and memory (rule spaces) of the autonomous mobile robot. The artificial cognitive model of autonomous robot control architecture has a dynamic associative memory including behavioral transition rules which are able to be learned for achieving multi-objective robot tasks. Motivation module of architecture has been considered as behavioral gain effect generator for achieving multi-objective robot tasks. According to emotional and behavioral state transition probabilities, artificial emotions determine sequences of behaviors for long-term action planning. Also reinforcement self-learning and reasoning ability of artificial cognitive model and motivational gain effects of proposed architecture can be observed on the executing behavioral sequences during simulation. The posture and speed of the robot and the configurations, speeds and torques of the wheels and all deliberative and cognitive events can be observed from the simulation plant and virtual reality viewer. This study constitutes basis for the multi-goal robot tasks and artificial emotions and cognitive mechanism-based behavior generation experiments on a real mobile robot.     

Ontological reasoning for improving the treatment of emotions in text

With the advent of affective computing, the task of adequately identifying, representing and processing the emotional connotations of text has acquired importance. Two problems facing this task are addressed in this paper: the composition of sentence emotion from word emotion, and a representation of emotion that allows easy conversion between existing computational representations. The emotion of a sentence of text should be derived by composition of the emotions of the words in the sentence, but no method has been proposed so far to model this compositionality. Of the various existing approaches for representing emotions, some are better suited for some problems and some for others, but there is no easy way of converting from one to another. This paper presents a system that addresses these two problems by reasoning with two ontologies implemented with Semantic Web technologies: one designed to represent word dependency relations within a sentence, and one designed to represent emotions. The ontology of word dependency relies on roles to represent the way emotional contributions project over word dependencies. By applying automated classification of mark-up results in terms of the emotion ontology the system can interpret unrestricted input in terms of a restricted set of concepts for which particular rules are provided. The rules applied at the end of the process provide configuration parameters for a system for emotional voice synthesis.     

Harnessing Green IT: Principles and Practices

In addition to moving itself in a greener direction and leveraging other environmental initiatives, IT could help create green awareness among IT professionals, businesses, and the general public by assisting in building communities, engaging groups in participatory decisions, and supporting education and green advocacy campaigns. Along these lines, tools such as environmental Web portals, blogs, wikis, and interactive simulations of the environmental impact of an activity could offer assistance. Green IT is an economic, as well as an environmental, imperative. Greening IT is and will continue to be a necessity, not an option. Green IT represents a dramatic change in priority in the IT industry. So far, the industry has been focusing on IT equipment processing power and associated equipment spending. It's not been concerned with other requirements such as power, cooling, and data center space. However, going forward, the IT industry will need to deal with all of the infrastructure requirements and the environmental impact of IT and its use. The challenges of green IT are immense; however, recent developments indicate that the IT industry has the will and conviction to tackle our environmental issues head-on. The IT sector and users must develop a positive attitude toward addressing environmental concerns and adopt forward-looking, green-friendly policies and practices.