Generic adversary characteristics: summary report

International Nuclear Information System (INIS)

Stewart, J.B. Jr.; Davidson, J.J.; Jones, H.B.; Fulwiler, C.H.; Mullen, S.A.

1978-07-01

The adversaries studied were found to be complex, often unpredictable, and dynamic. The adversary typically goes through a complex decision-making process between the time a potential target is identified and the moment the decision to act is made. This study analyzes the adversary characteristics, and the following conclusions are made: one of the least likely methods of attack is an overt armed assault. Terrorists and psychotics depend upon a high degree of personal dedication. No single generic adversary group or individual exhibits strength in every characteristic. Physical danger appears to have some deterrent effect on all adversaries except the psychotics. Organized and professional criminals often try to recruit insiders. Disoriented persons, white-collar criminals, and disgruntled employees tend to operate as insiders. Professional criminals, many terrorist groups, some extremist protest groups, and certain disoriented persons plan carefully before initiating a criminal mission. Organized crime and miscellaneous criminal adversaries rely on deception and ruse to bypass security. After the decision to commit a crime, the resources deployed by terrorists or organized criminals will be a function of their perception of the operational requirements of the crime. The nature of ''threat'' is dynamic; adversary behavior and capability appear to be related to prevailing political, economic, and social conditions

Intelligence Strategy for Fourth Generation Warfare

National Research Council Canada - National Science Library

Jamison, Edward P

2006-01-01

...." They have named this new era of war "fourth generation warfare." Currently the Department of Defense's intelligence strategy is designed to defeat conventional adversaries vise a fourth generation warfare opponent...

A Secured Cognitive Agent based Multi-strategic Intelligent Search System

Directory of Open Access Journals (Sweden)

Neha Gulati

2018-04-01

Full Text Available Search Engine (SE is the most preferred information retrieval tool ubiquitously used. In spite of vast scale involvement of users in SE’s, their limited capabilities to understand the user/searcher context and emotions places high cognitive, perceptual and learning load on the user to maintain the search momentum. In this regard, the present work discusses a Cognitive Agent (CA based approach to support the user in Web-based search process. The work suggests a framework called Secured Cognitive Agent based Multi-strategic Intelligent Search System (CAbMsISS to assist the user in search process. It helps to reduce the contextual and emotional mismatch between the SE’s and user. After implementation of the proposed framework, performance analysis shows that CAbMsISS framework improves Query Retrieval Time (QRT and effectiveness for retrieving relevant results as compared to Present Search Engine (PSE. Supplementary to this, it also provides search suggestions when user accesses a resource previously tagged with negative emotions. Overall, the goal of the system is to enhance the search experience for keeping the user motivated. The framework provides suggestions through the search log that tracks the queries searched, resources accessed and emotions experienced during the search. The implemented framework also considers user security. Keywords: BDI model, Cognitive Agent, Emotion, Information retrieval, Intelligent search, Search Engine

Deep learning, audio adversaries, and music content analysis

DEFF Research Database (Denmark)

Kereliuk, Corey Mose; Sturm, Bob L.; Larsen, Jan

2015-01-01

We present the concept of adversarial audio in the context of deep neural networks (DNNs) for music content analysis. An adversary is an algorithm that makes minor perturbations to an input that cause major repercussions to the system response. In particular, we design an adversary for a DNN...... that takes as input short-time spectral magnitudes of recorded music and outputs a high-level music descriptor. We demonstrate how this adversary can make the DNN behave in any way with only extremely minor changes to the music recording signal. We show that the adversary cannot be neutralised by a simple...... filtering of the input. Finally, we discuss adversaries in the broader context of the evaluation of music content analysis systems....

Adversarial Feature Selection Against Evasion Attacks.

Science.gov (United States)

Zhang, Fei; Chan, Patrick P K; Biggio, Battista; Yeung, Daniel S; Roli, Fabio

2016-03-01

Pattern recognition and machine learning techniques have been increasingly adopted in adversarial settings such as spam, intrusion, and malware detection, although their security against well-crafted attacks that aim to evade detection by manipulating data at test time has not yet been thoroughly assessed. While previous work has been mainly focused on devising adversary-aware classification algorithms to counter evasion attempts, only few authors have considered the impact of using reduced feature sets on classifier security against the same attacks. An interesting, preliminary result is that classifier security to evasion may be even worsened by the application of feature selection. In this paper, we provide a more detailed investigation of this aspect, shedding some light on the security properties of feature selection against evasion attacks. Inspired by previous work on adversary-aware classifiers, we propose a novel adversary-aware feature selection model that can improve classifier security against evasion attacks, by incorporating specific assumptions on the adversary's data manipulation strategy. We focus on an efficient, wrapper-based implementation of our approach, and experimentally validate its soundness on different application examples, including spam and malware detection.

An Analysis of the Influence of Signals Intelligence Through Wargaming

National Research Council Canada - National Science Library

McCaffrey, Charles

2000-01-01

Signals intelligence (SIGINT), information derived from the monitoring, interception, decryption and evaluation of an adversary's electronic communications, has long been viewed as a significant factor in modem warfare...

Development of intelligent semantic search system for rubber research data in Thailand

Science.gov (United States)

Kaewboonma, Nattapong; Panawong, Jirapong; Pianhanuruk, Ekkawit; Buranarach, Marut

2017-10-01

The rubber production of Thailand increased not only by strong demand from the world market, but was also stimulated strongly through the replanting program of the Thai Government from 1961 onwards. With the continuous growth of rubber research data volume on the Web, the search for information has become a challenging task. Ontologies are used to improve the accuracy of information retrieval from the web by incorporating a degree of semantic analysis during the search. In this context, we propose an intelligent semantic search system for rubber research data in Thailand. The research methods included 1) analyzing domain knowledge, 2) ontologies development, and 3) intelligent semantic search system development to curate research data in trusted digital repositories may be shared among the wider Thailand rubber research community.

Intelligent search in Big Data

Science.gov (United States)

Birialtsev, E.; Bukharaev, N.; Gusenkov, A.

2017-10-01

An approach to data integration, aimed on the ontology-based intelligent search in Big Data, is considered in the case when information objects are represented in the form of relational databases (RDB), structurally marked by their schemes. The source of information for constructing an ontology and, later on, the organization of the search are texts in natural language, treated as semi-structured data. For the RDBs, these are comments on the names of tables and their attributes. Formal definition of RDBs integration model in terms of ontologies is given. Within framework of the model universal RDB representation ontology, oil production subject domain ontology and linguistic thesaurus of subject domain language are built. Technique of automatic SQL queries generation for subject domain specialists is proposed. On the base of it, information system for TATNEFT oil-producing company RDBs was implemented. Exploitation of the system showed good relevance with majority of queries.

Using plural modeling for predicting decisions made by adaptive adversaries

International Nuclear Information System (INIS)

Buede, Dennis M.; Mahoney, Suzanne; Ezell, Barry; Lathrop, John

2012-01-01

Incorporating an appropriate representation of the likelihood of terrorist decision outcomes into risk assessments associated with weapons of mass destruction attacks has been a significant problem for countries around the world. Developing these likelihoods gets at the heart of the most difficult predictive problems: human decision making, adaptive adversaries, and adversaries about which very little is known. A plural modeling approach is proposed that incorporates estimates of all critical uncertainties: who is the adversary and what skills and resources are available to him, what information is known to the adversary and what perceptions of the important facts are held by this group or individual, what does the adversary know about the countermeasure actions taken by the government in question, what are the adversary's objectives and the priorities of those objectives, what would trigger the adversary to start an attack and what kind of success does the adversary desire, how realistic is the adversary in estimating the success of an attack, how does the adversary make a decision and what type of model best predicts this decision-making process. A computational framework is defined to aggregate the predictions from a suite of models, based on this broad array of uncertainties. A validation approach is described that deals with a significant scarcity of data.

An analytic approach to cyber adversarial dynamics

Science.gov (United States)

Sweeney, Patrick; Cybenko, George

2012-06-01

To date, cyber security investment by both the government and commercial sectors has been largely driven by the myopic best response of players to the actions of their adversaries and their perception of the adversarial environment. However, current work in applying traditional game theory to cyber operations typically assumes that games exist with prescribed moves, strategies, and payos. This paper presents an analytic approach to characterizing the more realistic cyber adversarial metagame that we believe is being played. Examples show that understanding the dynamic metagame provides opportunities to exploit an adversary's anticipated attack strategy. A dynamic version of a graph-based attack-defend game is introduced, and a simulation shows how an optimal strategy can be selected for success in the dynamic environment.

WANDERER IN THE MIST: THE SEARCH FOR INTELLIGENCE, SURVEILLANCE, AND RECONNAISSANCE (ISR) STRATEGY

Science.gov (United States)

2017-06-01

the production of over 383,000 photographic prints to support various intelligence , mapping, and 15...WANDERER IN THE MIST: THE SEARCH FOR INTELLIGENCE , SURVEILLANCE, AND RECONNAISSANCE (ISR) STRATEGY BY MAJOR RYAN D. SKAGGS, USAF...program from the University of California at Los Angeles (UCLA) in 2004. He is a career intelligence officer with over 13 years of experience across a

Active Detection for Exposing Intelligent Attacks in Control Systems

Energy Technology Data Exchange (ETDEWEB)

Weerakkody, Sean [Carnegie Mellon Univ., Pittsburgh, PA (United States); Ozel, Omur [Carnegie Mellon Univ., Pittsburgh, PA (United States); Griffioen, Paul [Carnegie Mellon Univ., Pittsburgh, PA (United States); Sinopoli, Bruno [Carnegie Mellon Univ., Pittsburgh, PA (United States)

2017-07-01

In this paper, we consider approaches for detecting integrity attacks carried out by intelligent and resourceful adversaries in control systems. Passive detection techniques are often incorporated to identify malicious behavior. Here, the defender utilizes finely-tuned algorithms to process information and make a binary decision, whether the system is healthy or under attack. We demonstrate that passive detection can be ineffective against adversaries with model knowledge and access to a set of input/output channels. We then propose active detection as a tool to detect attacks. In active detection, the defender leverages degrees of freedom he has in the system to detect the adversary. Specifically, the defender will introduce a physical secret kept hidden from the adversary, which can be utilized to authenticate the dynamics. In this regard, we carefully review two approaches for active detection: physical watermarking at the control input, and a moving target approach for generating system dynamics. We examine practical considerations for implementing these technologies and discuss future research directions.

Knowledge in Artificial Intelligence Systems: Searching the Strategies for Application

OpenAIRE

Kornienko, Alla A.; Kornienko, Anatoly V.; Fofanov, Oleg B.; Chubik, Maxim P.

2015-01-01

The studies based on auto-epistemic logic are pointed out as an advanced direction for development of artificial intelligence (AI). Artificial intelligence is taken as a system that imitates the solution of complicated problems by human during the course of life. The structure of symbols and operations, by which intellectual solution is performed, as well as searching the strategic reference points for those solutions, which are caused by certain structures of symbols and operations, – are co...

Funding the Search for Extraterrestrial Intelligence with a Lottery Bond

OpenAIRE

Haqq-Misra, Jacob

2013-01-01

I propose the establishment of a SETI Lottery Bond to provide a continued source of funding for the search for extraterrestrial intelligence (SETI). The SETI Lottery Bond is a fixed rate perpetual bond with a lottery at maturity, where maturity occurs only upon discovery and confirmation of extraterrestrial intelligent life. Investors in the SETI Lottery Bond purchase shares that yield a fixed rate of interest that continues indefinitely until SETI succeeds---at which point a random subset of...

Cybervetting internet searches for vetting, investigations, and open-source intelligence

CERN Document Server

Appel, Edward J

2014-01-01

Section I Behavior and TechnologyThe Internet's Potential for Investigators and Intelligence OfficersIntroductionGrowth of Internet UseA Practitioner's PerspectiveThe SearchInternet Posts and the People They ProfileFinding the NeedlesThe Need for SpeedSufficiency of SearchesNotesBehavior OnlineInternet Use GrowthEvolution of Internet UsesPhysical World, Virtual ActivitiesConnections and DisconnectingNotesUse and Abuse: Crime and Mis

Using Machine Learning in Adversarial Environments.

Energy Technology Data Exchange (ETDEWEB)

Davis, Warren Leon [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2016-02-01

Intrusion/anomaly detection systems are among the first lines of cyber defense. Commonly, they either use signatures or machine learning (ML) to identify threats, but fail to account for sophisticated attackers trying to circumvent them. We propose to embed machine learning within a game theoretic framework that performs adversarial modeling, develops methods for optimizing operational response based on ML, and integrates the resulting optimization codebase into the existing ML infrastructure developed by the Hybrid LDRD. Our approach addresses three key shortcomings of ML in adversarial settings: 1) resulting classifiers are typically deterministic and, therefore, easy to reverse engineer; 2) ML approaches only address the prediction problem, but do not prescribe how one should operationalize predictions, nor account for operational costs and constraints; and 3) ML approaches do not model attackers’ response and can be circumvented by sophisticated adversaries. The principal novelty of our approach is to construct an optimization framework that blends ML, operational considerations, and a model predicting attackers reaction, with the goal of computing optimal moving target defense. One important challenge is to construct a realistic model of an adversary that is tractable, yet realistic. We aim to advance the science of attacker modeling by considering game-theoretic methods, and by engaging experimental subjects with red teaming experience in trying to actively circumvent an intrusion detection system, and learning a predictive model of such circumvention activities. In addition, we will generate metrics to test that a particular model of an adversary is consistent with available data.

Context-Aware Generative Adversarial Privacy

Directory of Open Access Journals (Sweden)

Chong Huang

2017-12-01

Full Text Available Preserving the utility of published datasets while simultaneously providing provable privacy guarantees is a well-known challenge. On the one hand, context-free privacy solutions, such as differential privacy, provide strong privacy guarantees, but often lead to a significant reduction in utility. On the other hand, context-aware privacy solutions, such as information theoretic privacy, achieve an improved privacy-utility tradeoff, but assume that the data holder has access to dataset statistics. We circumvent these limitations by introducing a novel context-aware privacy framework called generative adversarial privacy (GAP. GAP leverages recent advancements in generative adversarial networks (GANs to allow the data holder to learn privatization schemes from the dataset itself. Under GAP, learning the privacy mechanism is formulated as a constrained minimax game between two players: a privatizer that sanitizes the dataset in a way that limits the risk of inference attacks on the individuals’ private variables, and an adversary that tries to infer the private variables from the sanitized dataset. To evaluate GAP’s performance, we investigate two simple (yet canonical statistical dataset models: (a the binary data model; and (b the binary Gaussian mixture model. For both models, we derive game-theoretically optimal minimax privacy mechanisms, and show that the privacy mechanisms learned from data (in a generative adversarial fashion match the theoretically optimal ones. This demonstrates that our framework can be easily applied in practice, even in the absence of dataset statistics.

Context-Aware Generative Adversarial Privacy

Science.gov (United States)

Huang, Chong; Kairouz, Peter; Chen, Xiao; Sankar, Lalitha; Rajagopal, Ram

2017-12-01

Preserving the utility of published datasets while simultaneously providing provable privacy guarantees is a well-known challenge. On the one hand, context-free privacy solutions, such as differential privacy, provide strong privacy guarantees, but often lead to a significant reduction in utility. On the other hand, context-aware privacy solutions, such as information theoretic privacy, achieve an improved privacy-utility tradeoff, but assume that the data holder has access to dataset statistics. We circumvent these limitations by introducing a novel context-aware privacy framework called generative adversarial privacy (GAP). GAP leverages recent advancements in generative adversarial networks (GANs) to allow the data holder to learn privatization schemes from the dataset itself. Under GAP, learning the privacy mechanism is formulated as a constrained minimax game between two players: a privatizer that sanitizes the dataset in a way that limits the risk of inference attacks on the individuals' private variables, and an adversary that tries to infer the private variables from the sanitized dataset. To evaluate GAP's performance, we investigate two simple (yet canonical) statistical dataset models: (a) the binary data model, and (b) the binary Gaussian mixture model. For both models, we derive game-theoretically optimal minimax privacy mechanisms, and show that the privacy mechanisms learned from data (in a generative adversarial fashion) match the theoretically optimal ones. This demonstrates that our framework can be easily applied in practice, even in the absence of dataset statistics.

Intelligent agents for training on-board fire fighting

NARCIS (Netherlands)

Bosch, K. van den; Harbers, M.; Heuvelink, A.; Doesburg, W. van

2009-01-01

Simulation-based training in complex decision making often requires ample personnel for playing various roles (e.g. team mates, adversaries). Using intelligent agents may diminish the need for staff. However, to achieve goal-directed training, events in the simulation as well as the behavior of key

Artificial intelligence for Mariáš

OpenAIRE

Kaštánková, Petra

2016-01-01

This thesis focuses on the implementation of a card game, Mariáš, and an artificial intelligence for this game. The game is designed for three players and it can be played with either other human players, or with a computer adversary. The game is designed as a client-server application, whereby the player connects to the game using a web page. The basis of the artificial intelligence is the Minimax algorithm. To speed it up we use the Alpha-Beta pruning, hash tables for storing equivalent sta...

Optimizing Vector-Quantization Processor Architecture for Intelligent Query-Search Applications

Science.gov (United States)

Xu, Huaiyu; Mita, Yoshio; Shibata, Tadashi

2002-04-01

The architecture of a very large scale integration (VLSI) vector-quantization processor (VQP) has been optimized to develop a general-purpose intelligent query-search agent. The agent performs a similarity-based search in a large-volume database. Although similarity-based search processing is computationally very expensive, latency-free searches have become possible due to the highly parallel maximum-likelihood search architecture of the VQP chip. Three architectures of the VQP chip have been studied and their performances are compared. In order to give reasonable searching results according to the different policies, the concept of penalty function has been introduced into the VQP. An E-commerce real-estate agency system has been developed using the VQP chip implemented in a field-programmable gate array (FPGA) and the effectiveness of such an agency system has been demonstrated.

Computational Modeling of Cultural Dimensions in Adversary Organizations

Science.gov (United States)

2010-01-01

theatre of operations. 50 51 Chapter 5 Adversary Modeling Applications 5.1 Modeling Uncertainty in Adversary Behavior: Attacks in...Underestimate the Strength of Coalition Power 1 1 (= True) 1 1 1 -- Coalition Deploys Forces to Indonesia 1 1 2 1 2 -- Thai can Conduct Unilateral NEO 1 1

Security force-adversary engagement simulation

International Nuclear Information System (INIS)

Bennett, H.A.

1975-01-01

A dynamic simulation of a security force-adversary engagement has been developed to obtain a better understanding of the complexities involved in security systems. Factors affecting engagement outcomes were identified and interrelated to represent an ambush of an escorted nuclear fuel truck convoy by an adversary group. Other forms of engagement such as assault and skirmish also can be simulated through suitable parameter changes. The dynamic model can provide a relative evaluation of changes in security force levels, equipment, training, and tactics. Continued application and subsequent refinements of the model are expected to augment the understanding of component interaction within a guard-based security system

L factor: hope and fear in the search for extraterrestrial intelligence

Science.gov (United States)

Rubin, Charles T.

2001-08-01

The L factor in the Drake equation is widely understood to account for most of the variance in estimates of the number of extraterrestrial intelligences that might be contacted by the search for extraterrestrial intelligence (SETI). It is also among the hardest to quantify. An examination of discussions of the L factor in the popular and technical SETI literature suggests that attempts to estimate L involve a variety of potentially conflicting assumptions about civilizational lifespan that reflect hopes and fears about the human future.

David against Goliath: Coping with Adversarial Customers

DEFF Research Database (Denmark)

Alajoutsijärvi, Kimmo; Tikkanen, Henrikki; Skaates, Maria Anne

2001-01-01

future-oriented relationships with any of them. From the perspective of the SME, this kind of customer behaviour could even be described as harmful, since it often impedes the SME manager's long-term development of his or her business. This makes the balancing of adversarial customer relationships...... an aspect crucial to the long-term survival and success of the particular SME. In this article, we propose a three-fold approach through which SME managers could balance their relationships with this type of customer. Firstly, we review theoretical discussions about business relationships and adversariness......SME managers in many industries face the situation that they have to deal with a few important, large customer organisations that behave in an adversarial manner. These customers pit alternative suppliers against each other in order to achieve the lowest possible price, showing no intent to build...

StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks

OpenAIRE

Zhang, Han; Xu, Tao; Li, Hongsheng; Zhang, Shaoting; Wang, Xiaogang; Huang, Xiaolei; Metaxas, Dimitris

2017-01-01

Although Generative Adversarial Networks (GANs) have shown remarkable success in various tasks, they still face challenges in generating high quality images. In this paper, we propose Stacked Generative Adversarial Networks (StackGAN) aiming at generating high-resolution photo-realistic images. First, we propose a two-stage generative adversarial network architecture, StackGAN-v1, for text-to-image synthesis. The Stage-I GAN sketches the primitive shape and colors of the object based on given...

The role of social media in the intelligence cycle

NARCIS (Netherlands)

Forrester, B.; Hollander, K. den

2016-01-01

Social Media (SM) is a relatively new phenomenon. Intelligence agencies have been struggling to understand how to exploit the social pulse that flows from this source. The paper starts with a brief overview of SM with some examples of how it is being used by adversaries and how we might be able to

Recognizing and Imitating Programmer Style: Adversaries in Program Authorship Attribution

Directory of Open Access Journals (Sweden)

Simko Lucy

2018-01-01

Full Text Available Source code attribution classifiers have recently become powerful. We consider the possibility that an adversary could craft code with the intention of causing a misclassification, i.e., creating a forgery of another author’s programming style in order to hide the forger’s own identity or blame the other author. We find that it is possible for a non-expert adversary to defeat such a system. In order to inform the design of adversarially resistant source code attribution classifiers, we conduct two studies with C/C++ programmers to explore the potential tactics and capabilities both of such adversaries and, conversely, of human analysts doing source code authorship attribution. Through the quantitative and qualitative analysis of these studies, we (1 evaluate a state-of-the-art machine classifier against forgeries, (2 evaluate programmers as human analysts/forgery detectors, and (3 compile a set of modifications made to create forgeries. Based on our analyses, we then suggest features that future source code attribution systems might incorporate in order to be adversarially resistant.

The internet and intelligent machines: search engines, agents and robots

International Nuclear Information System (INIS)

Achenbach, S.; Alfke, H.

2000-01-01

The internet plays an important role in a growing number of medical applications. Finding relevant information is not always easy as the amount of available information on the Web is rising quickly. Even the best Search Engines can only collect links to a fraction of all existing Web pages. In addition, many of these indexed documents have been changed or deleted. The vast majority of information on the Web is not searchable with conventional methods. New search strategies, technologies and standards are combined in Intelligent Search Agents (ISA) an Robots, which can retrieve desired information in a specific approach. Conclusion: The article describes differences between ISAs and conventional Search Engines and how communication between Agents improves their ability to find information. Examples of existing ISAs are given and the possible influences on the current and future work in radiology is discussed. (orig.) [de

The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology.

Science.gov (United States)

Kadurin, Artur; Aliper, Alexander; Kazennov, Andrey; Mamoshina, Polina; Vanhaelen, Quentin; Khrabrov, Kuzma; Zhavoronkov, Alex

2017-02-14

Recent advances in deep learning and specifically in generative adversarial networks have demonstrated surprising results in generating new images and videos upon request even using natural language as input. In this paper we present the first application of generative adversarial autoencoders (AAE) for generating novel molecular fingerprints with a defined set of parameters. We developed a 7-layer AAE architecture with the latent middle layer serving as a discriminator. As an input and output the AAE uses a vector of binary fingerprints and concentration of the molecule. In the latent layer we also introduced a neuron responsible for growth inhibition percentage, which when negative indicates the reduction in the number of tumor cells after the treatment. To train the AAE we used the NCI-60 cell line assay data for 6252 compounds profiled on MCF-7 cell line. The output of the AAE was used to screen 72 million compounds in PubChem and select candidate molecules with potential anti-cancer properties. This approach is a proof of concept of an artificially-intelligent drug discovery engine, where AAEs are used to generate new molecular fingerprints with the desired molecular properties.

Generative Adversarial Networks for Noise Reduction in Low-Dose CT.

Science.gov (United States)

Wolterink, Jelmer M; Leiner, Tim; Viergever, Max A; Isgum, Ivana

2017-12-01

Noise is inherent to low-dose CT acquisition. We propose to train a convolutional neural network (CNN) jointly with an adversarial CNN to estimate routine-dose CT images from low-dose CT images and hence reduce noise. A generator CNN was trained to transform low-dose CT images into routine-dose CT images using voxelwise loss minimization. An adversarial discriminator CNN was simultaneously trained to distinguish the output of the generator from routine-dose CT images. The performance of this discriminator was used as an adversarial loss for the generator. Experiments were performed using CT images of an anthropomorphic phantom containing calcium inserts, as well as patient non-contrast-enhanced cardiac CT images. The phantom and patients were scanned at 20% and 100% routine clinical dose. Three training strategies were compared: the first used only voxelwise loss, the second combined voxelwise loss and adversarial loss, and the third used only adversarial loss. The results showed that training with only voxelwise loss resulted in the highest peak signal-to-noise ratio with respect to reference routine-dose images. However, CNNs trained with adversarial loss captured image statistics of routine-dose images better. Noise reduction improved quantification of low-density calcified inserts in phantom CT images and allowed coronary calcium scoring in low-dose patient CT images with high noise levels. Testing took less than 10 s per CT volume. CNN-based low-dose CT noise reduction in the image domain is feasible. Training with an adversarial network improves the CNNs ability to generate images with an appearance similar to that of reference routine-dose CT images.

Learning Adversary Modeling from Games

National Research Council Canada - National Science Library

Avellino, Paul

2007-01-01

.... In the computer age, highly accurate models and simulations of the enemy can be created. However, including the effects of motivations, capabilities, and weaknesses of adversaries in current wars is still extremely difficult...

The Breakthrough Listen Initiative and the Future of the Search for Intelligent Life

Science.gov (United States)

Enriquez, J. Emilio; Siemion, Andrew; Croft, Steve; Hellbourg, Greg; Lebofsky, Matt; MacMahon, David; Price, Danny; DeBoer, David; Werthimer, Dan

2017-05-01

Unprecedented recent results in the fields of exoplanets and astrobiology have dramatically increased the interest in the potential existence of intelligent life elsewhere in the galaxy. Additionally, the capabilities of modern Searches for Extraterrestrial Intelligence (SETI) have increased tremendously. Much of this improvement is due to the ongoing development of wide bandwidth radio instruments and the Moore's Law increase in computing power over the previous decades. Together, these instrumentation improvements allow for narrow band signal searches of billions of frequency channels at once.The Breakthrough Listen Initiative (BL) was launched on July 20, 2015 at the Royal Society in London, UK with the goal to conduct the most comprehensive and sensitive search for advanced life in humanity's history. Here we detail important milestones achieved during the first year and a half of the program. We describe the key BL SETI surveys and briefly describe current facilities, including the Green Bank Telescope, the Automated Planet Finder and the Parkes Observatory. We also mention the ongoing and potential collaborations focused on complementary sciences, these include pulse searches of pulsars and FRBs, as well as astrophysically powered radio emission from stars targeted by our program.We conclude with a brief view towards future SETI searches with upcoming next-generation radio facilities such as SKA and ngVLA.

Adversarial Advantage Actor-Critic Model for Task-Completion Dialogue Policy Learning

OpenAIRE

Peng, Baolin; Li, Xiujun; Gao, Jianfeng; Liu, Jingjing; Chen, Yun-Nung; Wong, Kam-Fai

2017-01-01

This paper presents a new method --- adversarial advantage actor-critic (Adversarial A2C), which significantly improves the efficiency of dialogue policy learning in task-completion dialogue systems. Inspired by generative adversarial networks (GAN), we train a discriminator to differentiate responses/actions generated by dialogue agents from responses/actions by experts. Then, we incorporate the discriminator as another critic into the advantage actor-critic (A2C) framework, to encourage the...

Learning consensus in adversarial environments

Science.gov (United States)

Vamvoudakis, Kyriakos G.; García Carrillo, Luis R.; Hespanha, João. P.

2013-05-01

This work presents a game theory-based consensus problem for leaderless multi-agent systems in the presence of adversarial inputs that are introducing disturbance to the dynamics. Given the presence of enemy components and the possibility of malicious cyber attacks compromising the security of networked teams, a position agreement must be reached by the networked mobile team based on environmental changes. The problem is addressed under a distributed decision making framework that is robust to possible cyber attacks, which has an advantage over centralized decision making in the sense that a decision maker is not required to access information from all the other decision makers. The proposed framework derives three tuning laws for every agent; one associated with the cost, one associated with the controller, and one with the adversarial input.

Toward Intelligent Autonomous Agents for Cyber Defense: Report of the 2017 Workshop by the North Atlantic Treaty Organization (NATO) Research Group IST-152 RTG

Science.gov (United States)

2018-04-18

simple example? 15. SUBJECT TERMS cybersecurity , cyber defense, autonomous agents, resilience, adversarial intelligence 16. SECURITY CLASSIFICATION...explained” based on other attack sequences (e.g., Kullback–Leibler [K-L] divergence). For example, the DARPA Explainable Artificial Intelligence ...a failure of humanity, not artificial intelligence . The notion of self-guidance approaches the field of robot ethics. How can autonomous agents be

Toward Intelligent Autonomous Agents for Cyber Defense: Report of the 2017 Workshop by the North Atlantic Treaty Organization (NATO) Research Group IST-152-RTG

Science.gov (United States)

2018-04-01

simple example? 15. SUBJECT TERMS cybersecurity , cyber defense, autonomous agents, resilience, adversarial intelligence 16. SECURITY CLASSIFICATION...explained” based on other attack sequences (e.g., Kullback–Leibler [K-L] divergence). For example, the DARPA Explainable Artificial Intelligence ...a failure of humanity, not artificial intelligence . The notion of self-guidance approaches the field of robot ethics. How can autonomous agents be

SETI pioneers scientists talk about their search for extraterrestrial intelligence

CERN Document Server

Swift, David W.

1990-01-01

Why did some scientists decide to conduct a search for extraterrestrial intelligence (SETI)? What factors in their personal development predisposed them to such a quest? What obstacles did they encounter along the way? David Swift interviewed the first scientists involved in the search & offers a fascinating overview of the emergence of this modern scientific endeavor. He allows some of the most imaginative scientific thinkers of our time to hold forth on their views regarding SETI & extraterrestrial life & on how the field has developed. Readers will react with a range of opinions as broad as those concerning the likelihood of success in SETI itself. ''A goldmine of original information.''

Decorrelated Jet Substructure Tagging using Adversarial Neural Networks

CERN Multimedia

CERN. Geneva

2017-01-01

We describe a strategy for constructing a neural network jet substructure tagger which powerfully discriminates boosted decay signals while remaining largely uncorrelated with the jet mass. This reduces the impact of systematic uncertainties in background modeling while enhancing signal purity, resulting in improved discovery significance relative to existing taggers. The network is trained using an adversarial strategy, resulting in a tagger that learns to balance classification accuracy with decorrelation. As a benchmark scenario, we consider the case where large-radius jets originating from a boosted Z' decay are discriminated from a background of nonresonant quark and gluon jets. We show that in the presence of systematic uncertainties on the background rate, our adversarially-trained, decorrelated tagger considerably outperforms a conventionally trained neural network, despite having a slightly worse signal-background separation power. We generalize the adversarial training technique to include a paramet...

Anthropomorphism in the search for extra-terrestrial intelligence - The limits of cognition?

Science.gov (United States)

Bohlmann, Ulrike M.; Bürger, Moritz J. F.

2018-02-01

The question "Are we alone?" lingers in the human mind since ancient times. Early human civilisations populated the heavens above with a multitude of Gods endowed with some all too human characteristics - from their outer appearance to their innermost motivations. En passant they created thereby their own cultural founding myths on which they built their understanding of the world and its phenomena and deduced as well rules for the functioning of their own society. Advancing technology has enabled us to conduct this human quest for knowledge with more scientific means: optical and radio-wavelengths are being monitored for messages by an extra-terrestrial intelligence and active messaging attempts have also been undertaken. Scenarios have been developed for a possible detection of extra-terrestrial intelligence and post-detection guidelines and protocols have been elaborated. The human responses to the whole array of questions concerning the potential existence, discovery of and communication/interaction with an extra-terrestrial intelligence share as one clear thread a profound anthropomorphism, which ascribes classical human behavioural patterns also to an extra-terrestrial intelligence in much the same way as our ancestors attributed comparable conducts to mythological figures. This paper aims at pinpointing this thread in a number of classical reactions to basic questions related to the search for extra-terrestrial intelligence. Many of these reactions are based on human motives such as curiosity and fear, rationalised by experience and historical analogy and modelled in the Science Fiction Culture by literature and movies. Scrutinising the classical hypothetical explanations of the Fermi paradox under the angle of a potentially undue anthropomorphism, this paper intends to assist in understanding our human epistemological limitations in the search for extra-terrestrial intelligence. This attempt is structured into a series of questions: I. Can we be alone? II

Intelligent energy allocation strategy for PHEV charging station using gravitational search algorithm

Science.gov (United States)

Rahman, Imran; Vasant, Pandian M.; Singh, Balbir Singh Mahinder; Abdullah-Al-Wadud, M.

2014-10-01

Recent researches towards the use of green technologies to reduce pollution and increase penetration of renewable energy sources in the transportation sector are gaining popularity. The development of the smart grid environment focusing on PHEVs may also heal some of the prevailing grid problems by enabling the implementation of Vehicle-to-Grid (V2G) concept. Intelligent energy management is an important issue which has already drawn much attention to researchers. Most of these works require formulation of mathematical models which extensively use computational intelligence-based optimization techniques to solve many technical problems. Higher penetration of PHEVs require adequate charging infrastructure as well as smart charging strategies. We used Gravitational Search Algorithm (GSA) to intelligently allocate energy to the PHEVs considering constraints such as energy price, remaining battery capacity, and remaining charging time.

Resilient Distributed Estimation Through Adversary Detection

Science.gov (United States)

Chen, Yuan; Kar, Soummya; Moura, Jose M. F.

2018-05-01

This paper studies resilient multi-agent distributed estimation of an unknown vector parameter when a subset of the agents is adversarial. We present and analyze a Flag Raising Distributed Estimator ($\\mathcal{FRDE}$) that allows the agents under attack to perform accurate parameter estimation and detect the adversarial agents. The $\\mathcal{FRDE}$ algorithm is a consensus+innovations estimator in which agents combine estimates of neighboring agents (consensus) with local sensing information (innovations). We establish that, under $\\mathcal{FRDE}$, either the uncompromised agents' estimates are almost surely consistent or the uncompromised agents detect compromised agents if and only if the network of uncompromised agents is connected and globally observable. Numerical examples illustrate the performance of $\\mathcal{FRDE}$.

Arguing with Adversaries: Aikido, Rhetoric, and the Art of Peace

Science.gov (United States)

Kroll, Barry M.

2008-01-01

The Japanese martial art of aikido affords a framework for understanding argument as harmonization rather than confrontation. Two movements, circling away ("tenkan") and entering in ("irimi"), suggest tactics for arguing with adversaries. The ethical imperative of aikido involves protecting one's adversary from harm, using the least force…

Monte-Carlo approach to the generation of adversary paths

International Nuclear Information System (INIS)

1977-01-01

This paper considers the definition of a threat as the sequence of events that might lead to adversary success. A nuclear facility is characterized as a weighted, labeled, directed graph, with critical adversary paths. A discrete-event, Monte-Carlo simulation model is used to estimate the probability of the critical paths. The model was tested for hypothetical facilities, with promising results

Creative Persuasion: A Study on Adversarial Behaviors and Strategies in Phishing Attacks.

Science.gov (United States)

Rajivan, Prashanth; Gonzalez, Cleotilde

2018-01-01

Success of phishing attacks depend on effective exploitation of human weaknesses. This research explores a largely ignored, but crucial aspect of phishing: the adversarial behavior. We aim at understanding human behaviors and strategies that adversaries use, and how these may determine the end-user response to phishing emails. We accomplish this through a novel experiment paradigm involving two phases. In the adversarial phase, 105 participants played the role of a phishing adversary who were incentivized to produce multiple phishing emails that would evade detection and persuade end-users to respond. In the end-user phase, 340 participants performed an email management task, where they examined and classified phishing emails generated by participants in phase-one along with benign emails. Participants in the adversary role, self-reported the strategies they employed in each email they created, and responded to a test of individual creativity. Data from both phases of the study was combined and analyzed, to measure the effect of adversarial behaviors on end-user response to phishing emails. We found that participants who persistently used specific attack strategies (e.g., sending notifications, use of authoritative tone, or expressing shared interest) in all their attempts were overall more successful, compared to others who explored different strategies in each attempt. We also found that strategies largely determined whether an end-user was more likely to respond to an email immediately, or delete it. Individual creativity was not a reliable predictor of adversarial performance, but it was a predictor of an adversary's ability to evade detection. In summary, the phishing example provided initially, the strategies used, and the participants' persistence with some of the strategies led to higher performance in persuading end-users to respond to phishing emails. These insights may be used to inform tools and training procedures to detect phishing strategies in

Taxonomies of Cyber Adversaries and Attacks: A Survey of Incidents and Approaches

Energy Technology Data Exchange (ETDEWEB)

Meyers, C A; Powers, S S; Faissol, D M

2009-10-08

In this paper we construct taxonomies of cyber adversaries and methods of attack, drawing from a survey of the literature in the area of cyber crime. We begin by addressing the scope of cyber crime, noting its prevalence and effects on the US economy. We then survey the literature on cyber adversaries, presenting a taxonomy of the different types of adversaries and their corresponding methods, motivations, maliciousness, and skill levels. Subsequently we survey the literature on cyber attacks, giving a taxonomy of the different classes of attacks, subtypes, and threat descriptions. The goal of this paper is to inform future studies of cyber security on the shape and characteristics of the risk space and its associated adversaries.

Science, religion, and the search for extraterrestrial intelligence

CERN Document Server

Wilkinson, David

2013-01-01

If the discovery of life elsewhere in the universe is just around the corner, what would be the consequences for religion? Would it represent another major conflict between science and religion, even leading to the death of faith? Some would suggest that the discovery of any suggestion of extraterrestrial life would have a greater impact than even the Copernican and Darwinian revolutions. It is now over 50 years since the first modern scientific papers were published on the search for extraterrestrial intelligence (SETI). Yet the religious implications of this search and possible discovery have never been systematically addressed in the scientific or theological arena. SETI is now entering its most important era of scientific development. New observation techniques are leading to the discovery of extra-solar planets daily, and the Kepler mission has already collected over 1000 planetary candidates. This deluge of data is transforming the scientific and popular view of the existence of extraterrestrial intel...

Towards Stable Adversarial Feature Learning for LiDAR based Loop Closure Detection

OpenAIRE

Xu, Lingyun; Yin, Peng; Luo, Haibo; Liu, Yunhui; Han, Jianda

2017-01-01

Stable feature extraction is the key for the Loop closure detection (LCD) task in the simultaneously localization and mapping (SLAM) framework. In our paper, the feature extraction is operated by using a generative adversarial networks (GANs) based unsupervised learning. GANs are powerful generative models, however, GANs based adversarial learning suffers from training instability. We find that the data-code joint distribution in the adversarial learning is a more complex manifold than in the...

MTGAN: Speaker Verification through Multitasking Triplet Generative Adversarial Networks

OpenAIRE

Ding, Wenhao; He, Liang

2018-01-01

In this paper, we propose an enhanced triplet method that improves the encoding process of embeddings by jointly utilizing generative adversarial mechanism and multitasking optimization. We extend our triplet encoder with Generative Adversarial Networks (GANs) and softmax loss function. GAN is introduced for increasing the generality and diversity of samples, while softmax is for reinforcing features about speakers. For simplification, we term our method Multitasking Triplet Generative Advers...

Towards an Iterated Game Model with Multiple Adversaries in Smart-World Systems

Directory of Open Access Journals (Sweden)

Xiaofei He

2018-02-01

Full Text Available Diverse and varied cyber-attacks challenge the operation of the smart-world system that is supported by Internet-of-Things (IoT (smart cities, smart grid, smart transportation, etc. and must be carefully and thoughtfully addressed before widespread adoption of the smart-world system can be fully realized. Although a number of research efforts have been devoted to defending against these threats, a majority of existing schemes focus on the development of a specific defensive strategy to deal with specific, often singular threats. In this paper, we address the issue of coalitional attacks, which can be launched by multiple adversaries cooperatively against the smart-world system such as smart cities. Particularly, we propose a game-theory based model to capture the interaction among multiple adversaries, and quantify the capacity of the defender based on the extended Iterated Public Goods Game (IPGG model. In the formalized game model, in each round of the attack, a participant can either cooperate by participating in the coalitional attack, or defect by standing aside. In our work, we consider the generic defensive strategy that has a probability to detect the coalitional attack. When the coalitional attack is detected, all participating adversaries are penalized. The expected payoff of each participant is derived through the equalizer strategy that provides participants with competitive benefits. The multiple adversaries with the collusive strategy are also considered. Via a combination of theoretical analysis and experimentation, our results show that no matter which strategies the adversaries choose (random strategy, win-stay-lose-shift strategy, or even the adaptive equalizer strategy, our formalized game model is capable of enabling the defender to greatly reduce the maximum value of the expected average payoff to the adversaries via provisioning sufficient defensive resources, which is reflected by setting a proper penalty factor against

Towards an Iterated Game Model with Multiple Adversaries in Smart-World Systems.

Science.gov (United States)

He, Xiaofei; Yang, Xinyu; Yu, Wei; Lin, Jie; Yang, Qingyu

2018-02-24

Diverse and varied cyber-attacks challenge the operation of the smart-world system that is supported by Internet-of-Things (IoT) (smart cities, smart grid, smart transportation, etc.) and must be carefully and thoughtfully addressed before widespread adoption of the smart-world system can be fully realized. Although a number of research efforts have been devoted to defending against these threats, a majority of existing schemes focus on the development of a specific defensive strategy to deal with specific, often singular threats. In this paper, we address the issue of coalitional attacks, which can be launched by multiple adversaries cooperatively against the smart-world system such as smart cities. Particularly, we propose a game-theory based model to capture the interaction among multiple adversaries, and quantify the capacity of the defender based on the extended Iterated Public Goods Game (IPGG) model. In the formalized game model, in each round of the attack, a participant can either cooperate by participating in the coalitional attack, or defect by standing aside. In our work, we consider the generic defensive strategy that has a probability to detect the coalitional attack. When the coalitional attack is detected, all participating adversaries are penalized. The expected payoff of each participant is derived through the equalizer strategy that provides participants with competitive benefits. The multiple adversaries with the collusive strategy are also considered. Via a combination of theoretical analysis and experimentation, our results show that no matter which strategies the adversaries choose (random strategy, win-stay-lose-shift strategy, or even the adaptive equalizer strategy), our formalized game model is capable of enabling the defender to greatly reduce the maximum value of the expected average payoff to the adversaries via provisioning sufficient defensive resources, which is reflected by setting a proper penalty factor against the adversaries

Design and economic investigation of shell and tube heat exchangers using Improved Intelligent Tuned Harmony Search algorithm

Directory of Open Access Journals (Sweden)

Oguz Emrah Turgut

2014-12-01

Full Text Available This study explores the thermal design of shell and tube heat exchangers by using Improved Intelligent Tuned Harmony Search (I-ITHS algorithm. Intelligent Tuned Harmony Search (ITHS is an upgraded version of harmony search algorithm which has an advantage of deciding intensification and diversification processes by applying proper pitch adjusting strategy. In this study, we aim to improve the search capacity of ITHS algorithm by utilizing chaotic sequences instead of uniformly distributed random numbers and applying alternative search strategies inspired by Artificial Bee Colony algorithm and Opposition Based Learning on promising areas (best solutions. Design variables including baffle spacing, shell diameter, tube outer diameter and number of tube passes are used to minimize total cost of heat exchanger that incorporates capital investment and the sum of discounted annual energy expenditures related to pumping and heat exchanger area. Results show that I-ITHS can be utilized in optimizing shell and tube heat exchangers.

An Extended Chemical Plant Environmental Protection Game on Addressing Uncertainties of Human Adversaries

Science.gov (United States)

Wang, Rongxiao; Chen, Feiran; Wang, Yiping; Qiu, Xiaogang

2018-01-01

Chemical production activities in industrial districts pose great threats to the surrounding atmospheric environment and human health. Therefore, developing appropriate and intelligent pollution controlling strategies for the management team to monitor chemical production processes is significantly essential in a chemical industrial district. The literature shows that playing a chemical plant environmental protection (CPEP) game can force the chemical plants to be more compliant with environmental protection authorities and reduce the potential risks of hazardous gas dispersion accidents. However, results of the current literature strictly rely on several perfect assumptions which rarely hold in real-world domains, especially when dealing with human adversaries. To address bounded rationality and limited observability in human cognition, the CPEP game is extended to generate robust schedules of inspection resources for inspection agencies. The present paper is innovative on the following contributions: (i) The CPEP model is extended by taking observation frequency and observation cost of adversaries into account, and thus better reflects the industrial reality; (ii) Uncertainties such as attackers with bounded rationality, attackers with limited observation and incomplete information (i.e., the attacker’s parameters) are integrated into the extended CPEP model; (iii) Learning curve theory is employed to determine the attacker’s observability in the game solver. Results in the case study imply that this work improves the decision-making process for environmental protection authorities in practical fields by bringing more rewards to the inspection agencies and by acquiring more compliance from chemical plants. PMID:29584679

An Extended Chemical Plant Environmental Protection Game on Addressing Uncertainties of Human Adversaries.

Science.gov (United States)

Zhu, Zhengqiu; Chen, Bin; Qiu, Sihang; Wang, Rongxiao; Chen, Feiran; Wang, Yiping; Qiu, Xiaogang

2018-03-27

Chemical production activities in industrial districts pose great threats to the surrounding atmospheric environment and human health. Therefore, developing appropriate and intelligent pollution controlling strategies for the management team to monitor chemical production processes is significantly essential in a chemical industrial district. The literature shows that playing a chemical plant environmental protection (CPEP) game can force the chemical plants to be more compliant with environmental protection authorities and reduce the potential risks of hazardous gas dispersion accidents. However, results of the current literature strictly rely on several perfect assumptions which rarely hold in real-world domains, especially when dealing with human adversaries. To address bounded rationality and limited observability in human cognition, the CPEP game is extended to generate robust schedules of inspection resources for inspection agencies. The present paper is innovative on the following contributions: (i) The CPEP model is extended by taking observation frequency and observation cost of adversaries into account, and thus better reflects the industrial reality; (ii) Uncertainties such as attackers with bounded rationality, attackers with limited observation and incomplete information (i.e., the attacker's parameters) are integrated into the extended CPEP model; (iii) Learning curve theory is employed to determine the attacker's observability in the game solver. Results in the case study imply that this work improves the decision-making process for environmental protection authorities in practical fields by bringing more rewards to the inspection agencies and by acquiring more compliance from chemical plants.

An Extended Chemical Plant Environmental Protection Game on Addressing Uncertainties of Human Adversaries

Directory of Open Access Journals (Sweden)

Zhengqiu Zhu

2018-03-01

Full Text Available Chemical production activities in industrial districts pose great threats to the surrounding atmospheric environment and human health. Therefore, developing appropriate and intelligent pollution controlling strategies for the management team to monitor chemical production processes is significantly essential in a chemical industrial district. The literature shows that playing a chemical plant environmental protection (CPEP game can force the chemical plants to be more compliant with environmental protection authorities and reduce the potential risks of hazardous gas dispersion accidents. However, results of the current literature strictly rely on several perfect assumptions which rarely hold in real-world domains, especially when dealing with human adversaries. To address bounded rationality and limited observability in human cognition, the CPEP game is extended to generate robust schedules of inspection resources for inspection agencies. The present paper is innovative on the following contributions: (i The CPEP model is extended by taking observation frequency and observation cost of adversaries into account, and thus better reflects the industrial reality; (ii Uncertainties such as attackers with bounded rationality, attackers with limited observation and incomplete information (i.e., the attacker’s parameters are integrated into the extended CPEP model; (iii Learning curve theory is employed to determine the attacker’s observability in the game solver. Results in the case study imply that this work improves the decision-making process for environmental protection authorities in practical fields by bringing more rewards to the inspection agencies and by acquiring more compliance from chemical plants.

Assessing risk from intelligent attacks: A perspective on approaches

International Nuclear Information System (INIS)

Guikema, Seth D.; Aven, Terje

2010-01-01

Assessing the uncertainties in and severity of the consequences of intelligent attacks are fundamentally different from risk assessment for accidental events and other phenomena with inherently random failures. Intelligent attacks against a system involve adaptation on the part of the adversary. The probabilities of the initiating events depend on the risk management actions taken, and they may be more difficult to assess due to high degrees of epistemic uncertainty about the motivations and future actions of adversaries. Several fundamentally different frameworks have been proposed for assessing risk from intelligent attacks. These include basing risk assessment and management on game theoretic modelling of attacker actions, using a probabilistic risk analysis (PRA) approach based on eliciting probabilities of different initiating events from appropriate experts, assessing uncertainties beyond probabilities and expected values, and ignoring the probabilities of the attacks and choosing to protect highest valued targets. In this paper we discuss and compare the fundamental assumptions that underlie each of these approaches. We then suggest a new framework that makes the fundamental assumptions underlying the approaches clear to decision makers and presents them with a suite of results from conditional risk analysis methods. Each of the conditional methods presents the risk from a specified set of fundamental assumptions, allowing the decision maker to see the impacts of these assumptions on the risk management strategies considered and to weight the different conditional results with their assessments of the relative likelihood of the different sets of assumptions.

Deep Learning and Music Adversaries

DEFF Research Database (Denmark)

Kereliuk, Corey Mose; Sturm, Bob L.; Larsen, Jan

2015-01-01

the minimal perturbation of the input image such that the system misclassifies it with high confidence. We adapt this approach to construct and deploy an adversary of deep learning systems applied to music content analysis. In our case, however, the system inputs are magnitude spectral frames, which require...

Modelling adversary actions against a nuclear material accounting system

International Nuclear Information System (INIS)

Lim, J.J.; Huebel, J.G.

1979-01-01

A typical nuclear material accounting system employing double-entry bookkeeping is described. A logic diagram is used to model the interactions of the accounting system and the adversary when he attempts to thwart it. Boolean equations are derived from the logic diagram; solution of these equations yields the accounts and records through which the adversary may disguise a SSNM theft and the collusion requirements needed to accomplish this feat. Some technical highlights of the logic diagram are also discussed

Recent advances in intelligent image search and video retrieval

CERN Document Server

2017-01-01

This book initially reviews the major feature representation and extraction methods and effective learning and recognition approaches, which have broad applications in the context of intelligent image search and video retrieval. It subsequently presents novel methods, such as improved soft assignment coding, Inheritable Color Space (InCS) and the Generalized InCS framework, the sparse kernel manifold learner method, the efficient Support Vector Machine (eSVM), and the Scale-Invariant Feature Transform (SIFT) features in multiple color spaces. Lastly, the book presents clothing analysis for subject identification and retrieval, and performance evaluation methods of video analytics for traffic monitoring. Digital images and videos are proliferating at an amazing speed in the fields of science, engineering and technology, media and entertainment. With the huge accumulation of such data, keyword searches and manual annotation schemes may no longer be able to meet the practical demand for retrieving relevant conte...

Towards an Iterated Game Model with Multiple Adversaries in Smart-World Systems †

Science.gov (United States)

Yang, Xinyu; Yu, Wei; Lin, Jie; Yang, Qingyu

2018-01-01

Diverse and varied cyber-attacks challenge the operation of the smart-world system that is supported by Internet-of-Things (IoT) (smart cities, smart grid, smart transportation, etc.) and must be carefully and thoughtfully addressed before widespread adoption of the smart-world system can be fully realized. Although a number of research efforts have been devoted to defending against these threats, a majority of existing schemes focus on the development of a specific defensive strategy to deal with specific, often singular threats. In this paper, we address the issue of coalitional attacks, which can be launched by multiple adversaries cooperatively against the smart-world system such as smart cities. Particularly, we propose a game-theory based model to capture the interaction among multiple adversaries, and quantify the capacity of the defender based on the extended Iterated Public Goods Game (IPGG) model. In the formalized game model, in each round of the attack, a participant can either cooperate by participating in the coalitional attack, or defect by standing aside. In our work, we consider the generic defensive strategy that has a probability to detect the coalitional attack. When the coalitional attack is detected, all participating adversaries are penalized. The expected payoff of each participant is derived through the equalizer strategy that provides participants with competitive benefits. The multiple adversaries with the collusive strategy are also considered. Via a combination of theoretical analysis and experimentation, our results show that no matter which strategies the adversaries choose (random strategy, win-stay-lose-shift strategy, or even the adaptive equalizer strategy), our formalized game model is capable of enabling the defender to greatly reduce the maximum value of the expected average payoff to the adversaries via provisioning sufficient defensive resources, which is reflected by setting a proper penalty factor against the adversaries

A swarm intelligence framework for reconstructing gene networks: searching for biologically plausible architectures.

Science.gov (United States)

Kentzoglanakis, Kyriakos; Poole, Matthew

2012-01-01

In this paper, we investigate the problem of reverse engineering the topology of gene regulatory networks from temporal gene expression data. We adopt a computational intelligence approach comprising swarm intelligence techniques, namely particle swarm optimization (PSO) and ant colony optimization (ACO). In addition, the recurrent neural network (RNN) formalism is employed for modeling the dynamical behavior of gene regulatory systems. More specifically, ACO is used for searching the discrete space of network architectures and PSO for searching the corresponding continuous space of RNN model parameters. We propose a novel solution construction process in the context of ACO for generating biologically plausible candidate architectures. The objective is to concentrate the search effort into areas of the structure space that contain architectures which are feasible in terms of their topological resemblance to real-world networks. The proposed framework is initially applied to the reconstruction of a small artificial network that has previously been studied in the context of gene network reverse engineering. Subsequently, we consider an artificial data set with added noise for reconstructing a subnetwork of the genetic interaction network of S. cerevisiae (yeast). Finally, the framework is applied to a real-world data set for reverse engineering the SOS response system of the bacterium Escherichia coli. Results demonstrate the relative advantage of utilizing problem-specific knowledge regarding biologically plausible structural properties of gene networks over conducting a problem-agnostic search in the vast space of network architectures.

Artificial intelligence search techniques for optimization of the cold source geometry

International Nuclear Information System (INIS)

Azmy, Y.Y.

1988-01-01

Most optimization studies of cold neutron sources have concentrated on the numerical prediction or experimental measurement of the cold moderator optimum thickness which produces the largest cold neutron leakage for a given thermal neutron source. Optimizing the geometrical shape of the cold source, however, is a more difficult problem because the optimized quantity, the cold neutron leakage, is an implicit function of the shape which is the unknown in such a study. We draw an analogy between this problem and a state space search, then we use a simple Artificial Intelligence (AI) search technique to determine the optimum cold source shape based on a two-group, r-z diffusion model. We implemented this AI design concept in the computer program AID which consists of two modules, a physical model module and a search module, which can be independently modified, improved, or made more sophisticated. 7 refs., 1 fig

Artificial intelligence search techniques for the optimization of cold source geometry

International Nuclear Information System (INIS)

Azmy, Y.Y.

1988-01-01

Most optimization studies of cold neutron sources have concentrated on the numerical prediction or experimental measurement of the cold moderator optimum thickness that produces the largest cold neutron leakage for a given thermal neutron source. Optimizing the geometric shape of the cold source, however, is a more difficult problem because the optimized quantity, the cold neutron leakage, is an implicit function of the shape, which is the unknown in such a study. An analogy is drawn between this problem and a state space search, then a simple artificial intelligence (AI) search technique is used to determine the optimum cold source shape based on a two-group, r-z diffusion model. This AI design concept was implemented in the computer program AID, which consists of two modules, a physical model module, and a search module, which can be independently modified, improved, or made more sophisticated

A framework for intelligent data acquisition and real-time database searching for shotgun proteomics.

Science.gov (United States)

Graumann, Johannes; Scheltema, Richard A; Zhang, Yong; Cox, Jürgen; Mann, Matthias

2012-03-01

In the analysis of complex peptide mixtures by MS-based proteomics, many more peptides elute at any given time than can be identified and quantified by the mass spectrometer. This makes it desirable to optimally allocate peptide sequencing and narrow mass range quantification events. In computer science, intelligent agents are frequently used to make autonomous decisions in complex environments. Here we develop and describe a framework for intelligent data acquisition and real-time database searching and showcase selected examples. The intelligent agent is implemented in the MaxQuant computational proteomics environment, termed MaxQuant Real-Time. It analyzes data as it is acquired on the mass spectrometer, constructs isotope patterns and SILAC pair information as well as controls MS and tandem MS events based on real-time and prior MS data or external knowledge. Re-implementing a top10 method in the intelligent agent yields similar performance to the data dependent methods running on the mass spectrometer itself. We demonstrate the capabilities of MaxQuant Real-Time by creating a real-time search engine capable of identifying peptides "on-the-fly" within 30 ms, well within the time constraints of a shotgun fragmentation "topN" method. The agent can focus sequencing events onto peptides of specific interest, such as those originating from a specific gene ontology (GO) term, or peptides that are likely modified versions of already identified peptides. Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra. MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition. Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available.

C-RNN-GAN: Continuous recurrent neural networks with adversarial training

OpenAIRE

Mogren, Olof

2016-01-01

Generative adversarial networks have been proposed as a way of efficiently training deep generative neural networks. We propose a generative adversarial model that works on continuous sequential data, and apply it by training it on a collection of classical music. We conclude that it generates music that sounds better and better as the model is trained, report statistics on generated music, and let the reader judge the quality by downloading the generated songs.

Are We Alone? GAVRT Search for Extra Terrestrial Intelligence (SETI) Project

Science.gov (United States)

Bensel, Holly; Cool, Ian; St. Mary's High School Astronomy Club; St. Mary's Middle School Astronomy Club

2017-01-01

The Goldstone Apple Valley Radio Telescope Program (GAVRT) is a partnership between NASA’s Jet Propulsion Laboratory and the Lewis Center for Educational Research. The program is an authentic science investigation program for students in grades K through 12 and offers them the ability to learn how to be a part of a science team while they are making a real contribution to scientific knowledge.Using the internet from their classroom, students take control of a 34-meter decommissioned NASA radio telescope located at the Goldstone Deep Space Network complex in California. Students collect data on strong radio sources and work in collaboration with professional radio astronomers to analyze the data.Throughout history man has wondered if we were alone in the Universe. SETI - or the Search for Extra Terrestrial Intelligence - is one of the programs offered through GAVRT that is designed to help answer that question. By participating in SETI, students learn about science by doing real science and maybe, if they get very lucky, they might make the most important discovery of our lifetime: Intelligent life beyond Earth!At St. Mary’s School, students in grades 6-12 have participated in the project since its inception. The St. Mary’s Middle School Astronomy Club is leading the way in their relentless search for ET and radio telescope studies. Students use the radio telescope to select a very small portion of the Milky Way Galaxy - or galactic plane - and scan across it over and over in the hopes of finding a signal that is not coming from humans or radio interference. The possibility of being the first to discover an alien signal has kept some students searching for the past three years. For them to discover something of this magnitude is like winning the lottery: small chance of winning - big payoff. To that end, the club is focusing on several portions of the Milky Way where they have detected a strong candidate in the past. The hope is to pick it up a second and

End-to-End Adversarial Retinal Image Synthesis.

Science.gov (United States)

Costa, Pedro; Galdran, Adrian; Meyer, Maria Ines; Niemeijer, Meindert; Abramoff, Michael; Mendonca, Ana Maria; Campilho, Aurelio

2018-03-01

In medical image analysis applications, the availability of the large amounts of annotated data is becoming increasingly critical. However, annotated medical data is often scarce and costly to obtain. In this paper, we address the problem of synthesizing retinal color images by applying recent techniques based on adversarial learning. In this setting, a generative model is trained to maximize a loss function provided by a second model attempting to classify its output into real or synthetic. In particular, we propose to implement an adversarial autoencoder for the task of retinal vessel network synthesis. We use the generated vessel trees as an intermediate stage for the generation of color retinal images, which is accomplished with a generative adversarial network. Both models require the optimization of almost everywhere differentiable loss functions, which allows us to train them jointly. The resulting model offers an end-to-end retinal image synthesis system capable of generating as many retinal images as the user requires, with their corresponding vessel networks, by sampling from a simple probability distribution that we impose to the associated latent space. We show that the learned latent space contains a well-defined semantic structure, implying that we can perform calculations in the space of retinal images, e.g., smoothly interpolating new data points between two retinal images. Visual and quantitative results demonstrate that the synthesized images are substantially different from those in the training set, while being also anatomically consistent and displaying a reasonable visual quality.

GANViz: A Visual Analytics Approach to Understand the Adversarial Game.

Science.gov (United States)

Wang, Junpeng; Gou, Liang; Yang, Hao; Shen, Han-Wei

2018-06-01

Generative models bear promising implications to learn data representations in an unsupervised fashion with deep learning. Generative Adversarial Nets (GAN) is one of the most popular frameworks in this arena. Despite the promising results from different types of GANs, in-depth understanding on the adversarial training process of the models remains a challenge to domain experts. The complexity and the potential long-time training process of the models make it hard to evaluate, interpret, and optimize them. In this work, guided by practical needs from domain experts, we design and develop a visual analytics system, GANViz, aiming to help experts understand the adversarial process of GANs in-depth. Specifically, GANViz evaluates the model performance of two subnetworks of GANs, provides evidence and interpretations of the models' performance, and empowers comparative analysis with the evidence. Through our case studies with two real-world datasets, we demonstrate that GANViz can provide useful insight into helping domain experts understand, interpret, evaluate, and potentially improve GAN models.

Intelligible Artificial Intelligence

OpenAIRE

Weld, Daniel S.; Bansal, Gagan

2018-01-01

Since Artificial Intelligence (AI) software uses techniques like deep lookahead search and stochastic optimization of huge neural networks to fit mammoth datasets, it often results in complex behavior that is difficult for people to understand. Yet organizations are deploying AI algorithms in many mission-critical settings. In order to trust their behavior, we must make it intelligible --- either by using inherently interpretable models or by developing methods for explaining otherwise overwh...

Scientific method, adversarial system, and technology assessment

Science.gov (United States)

Mayo, L. H.

1975-01-01

A basic framework is provided for the consideration of the purposes and techniques of scientific method and adversarial systems. Similarities and differences in these two techniques of inquiry are considered with reference to their relevance in the performance of assessments.

Gender Identity and Adversarial Sexual Beliefs as Predictors of Attitudes toward Sexual Harassment.

Science.gov (United States)

Murrell, Audrey J.; Dietz-Uhler, Beth L.

1993-01-01

Examines impact of gender identity and adversarial sexual beliefs as predictors of attitudes toward sexual harassment for 52 female and 55 male college students. Adversarial beliefs and experience with sexual harassment predict less tolerant attitudes toward harassment for males, whereas strong gender group identity and experience with harassment…

Cascading Generative Adversarial Networks for Targeted

KAUST Repository

Hamdi, Abdullah

2018-01-01

Abundance of labelled data played a crucial role in the recent developments in computer vision, but that faces problems like scalability and transferability to the wild. One alternative approach is to utilize the data without labels, i.e. unsupervised learning, in learning valuable information and put it in use to tackle vision problems. Generative Adversarial Networks (GANs) have gained momentum for their ability to model image distributions in unsupervised manner. They learn to emulate the training set and that enables sampling from that domain and using the knowledge learned for useful applications. Several methods proposed enhancing GANs, including regularizing the loss with some feature matching. We seek to push GANs beyond the data in the training and try to explore unseen territory in the image manifold. We first propose a new regularizer for GAN based on K-Nearest Neighbor (K-NN) selective feature matching to a target set Y in high-level feature space, during the adversarial training of GAN on the base set X, and we call this novel model K-GAN. We show that minimizing the added term follows from cross-entropy minimization between the distributions of GAN and set Y. Then, we introduce a cascaded framework for GANs that try to address the task of imagining a new distribution that combines the base set X and target set Y by cascading sampling GANs with translation GANs, and we dub the cascade of such GANs as the Imaginative Adversarial Network (IAN). Several cascades are trained on a collected dataset Zoo-Faces and generated innovative samples are shown, including from K-GAN cascade. We conduct an objective and subjective evaluation for different IAN setups in the addressed task of generating innovative samples and we show the effect of regularizing GAN on different scores. We conclude with some useful applications for these IANs, like multi-domain manifold traversing.

Cascading Generative Adversarial Networks for Targeted

KAUST Repository

Hamdi, Abdullah

2018-04-09

Abundance of labelled data played a crucial role in the recent developments in computer vision, but that faces problems like scalability and transferability to the wild. One alternative approach is to utilize the data without labels, i.e. unsupervised learning, in learning valuable information and put it in use to tackle vision problems. Generative Adversarial Networks (GANs) have gained momentum for their ability to model image distributions in unsupervised manner. They learn to emulate the training set and that enables sampling from that domain and using the knowledge learned for useful applications. Several methods proposed enhancing GANs, including regularizing the loss with some feature matching. We seek to push GANs beyond the data in the training and try to explore unseen territory in the image manifold. We first propose a new regularizer for GAN based on K-Nearest Neighbor (K-NN) selective feature matching to a target set Y in high-level feature space, during the adversarial training of GAN on the base set X, and we call this novel model K-GAN. We show that minimizing the added term follows from cross-entropy minimization between the distributions of GAN and set Y. Then, we introduce a cascaded framework for GANs that try to address the task of imagining a new distribution that combines the base set X and target set Y by cascading sampling GANs with translation GANs, and we dub the cascade of such GANs as the Imaginative Adversarial Network (IAN). Several cascades are trained on a collected dataset Zoo-Faces and generated innovative samples are shown, including from K-GAN cascade. We conduct an objective and subjective evaluation for different IAN setups in the addressed task of generating innovative samples and we show the effect of regularizing GAN on different scores. We conclude with some useful applications for these IANs, like multi-domain manifold traversing.

Intelligent bioinformatics : the application of artificial intelligence techniques to bioinformatics problems

National Research Council Canada - National Science Library

Keedwell, Edward

2005-01-01

... Intelligence and Computer Science 3.1 Introduction to search 3.2 Search algorithms 3.3 Heuristic search methods 3.4 Optimal search strategies 3.5 Problems with search techniques 3.6 Complexity of...

Consensus of discrete-time multi-agent systems with adversaries and time delays

Science.gov (United States)

Wu, Yiming; He, Xiongxiong; Liu, Shuai; Xie, Lihua

2014-05-01

This paper studies the resilient asymptotic consensus problem for discrete-time multi-agent systems in the presence of adversaries and transmission delays. The network is assumed to have ? loyal agents and ? adversarial agents, and each loyal agent in the network has no knowledge of the network topology other than an upper bound on the number of adversarial agents in its neighborhood. For the considered networked system, only locally delayed information is available for each loyal agent, and also the information flow is directed and a control protocol using only local information is designed to guarantee the realization of consensus with respect to communication graph, which satisfies a featured network robustness. Numerical examples are finally given to demonstrate the effectiveness of theoretical results.

Vulnerability assessment: Determining probabilities of neutralization of adversaries

International Nuclear Information System (INIS)

Graves, B.R.

1987-01-01

The Security Manager charged with the responsibility of designing Safeguards and Security Systems at Department of Energy facilities must take many factors into consideration. There must be a clear understanding, supported by documented guidance, of the level of threat to be addressed; the nature of the facility to be protected, and the funds available to design, implement, and maintain the Safeguards and Security System. Armed with these prerequisites, the Security Manager may then determine the characteristics of the Safeguards measures and security forces necessary to protect the facility. Security forces selection and training programs may then be established based on realistic facility needs. The next step is to attempt to determine the probability of security forces winning in a confrontation with adversaries. To determine the probability of success the Security Manager must consider the characteristics of the facility and surrounding area; the characteristics of the security forces and safeguards system at the facility; the response time and capabilities of the augmentation forces and the characteristics and capabilities of the adversary threat level to be addressed. Obviously, the Safeguards and Security Systems must initially address ''worst case'' scenarios consistent with stated guidelines. Validation of the assessment of the Safeguards and Security Systems must then be determined by simulation testing of the capabilities of the response forces against the capabilities of the adversary

Modeling documents with Generative Adversarial Networks

OpenAIRE

Glover, John

2016-01-01

This paper describes a method for using Generative Adversarial Networks to learn distributed representations of natural language documents. We propose a model that is based on the recently proposed Energy-Based GAN, but instead uses a Denoising Autoencoder as the discriminator network. Document representations are extracted from the hidden layer of the discriminator and evaluated both quantitatively and qualitatively.

Adding Robustness to Support Vector Machines Against Adversarial Reverse Engineering

KAUST Repository

Alabdulmohsin, Ibrahim

2014-01-01

Many classification algorithms have been successfully deployed in security-sensitive applications including spam filters and intrusion detection systems. Under such adversarial environments, adversaries can generate exploratory attacks against the defender such as evasion and reverse engineering. In this paper, we discuss why reverse engineering attacks can be carried out quite efficiently against fixed classifiers, and investigate the use of randomization as a suitable strategy for mitigating their risk. In particular, we derive a semidefinite programming (SDP) formulation for learning a distribution of classifiers subject to the constraint that any single classifier picked at random from such distribution provides reliable predictions with a high probability. We analyze the tradeoff between variance of the distribution and its predictive accuracy, and establish that one can almost always incorporate randomization with large variance without incurring a loss in accuracy. In other words, the conventional approach of using a fixed classifier in adversarial environments is generally Pareto suboptimal. Finally, we validate such conclusions on both synthetic and real-world classification problems. Copyright 2014 ACM.

The role of social media in the intelligence cycle

Science.gov (United States)

Forrester, Bruce; den Hollander, Kees

2016-05-01

Social Media (SM) is a relatively new phenomenon. Intelligence agencies have been struggling to understand how to exploit the social pulse that flows from this source. The paper starts with a brief overview of SM with some examples of how it is being used by adversaries and how we might be able to exploit this usage. Often treated as another form of open source intelligence (OSINT), we look at some of the differences with traditional OSINT compared to SM then outline the possible uses by military intelligence. The next section looks at how SM fits into the different phases of the intelligence cycle: Direction, Collection, Processing and Dissemination. For the first phase, Direction, a number of questions are identified that can be answered typically by SM. For the second phase, the Collection, it is explained how SM, as an asset, transfers questions into methods and the use of different SM resources (e.g. marketer, cognitive behavioral psychologist) and sources to seek the required information. SM is exploited as a multi-intelligence capability. For the Processing phase some aspects are described in how to deal with this capacity (e.g. enabling other intelligence sources) and also which techniques are used to be able to validate the SM sources used.

Are Forensic Experts Already Biased before Adversarial Legal Parties Hire Them?

Directory of Open Access Journals (Sweden)

Tess M S Neal

Full Text Available This survey of 206 forensic psychologists tested the "filtering" effects of preexisting expert attitudes in adversarial proceedings. Results confirmed the hypothesis that evaluator attitudes toward capital punishment influence willingness to accept capital case referrals from particular adversarial parties. Stronger death penalty opposition was associated with higher willingness to conduct evaluations for the defense and higher likelihood of rejecting referrals from all sources. Conversely, stronger support was associated with higher willingness to be involved in capital cases generally, regardless of referral source. The findings raise the specter of skewed evaluator involvement in capital evaluations, where evaluators willing to do capital casework may have stronger capital punishment support than evaluators who opt out, and evaluators with strong opposition may work selectively for the defense. The results may provide a partial explanation for the "allegiance effect" in adversarial legal settings such that preexisting attitudes may contribute to partisan participation through a self-selection process.

Are Forensic Experts Already Biased before Adversarial Legal Parties Hire Them?

Science.gov (United States)

2016-01-01

This survey of 206 forensic psychologists tested the “filtering” effects of preexisting expert attitudes in adversarial proceedings. Results confirmed the hypothesis that evaluator attitudes toward capital punishment influence willingness to accept capital case referrals from particular adversarial parties. Stronger death penalty opposition was associated with higher willingness to conduct evaluations for the defense and higher likelihood of rejecting referrals from all sources. Conversely, stronger support was associated with higher willingness to be involved in capital cases generally, regardless of referral source. The findings raise the specter of skewed evaluator involvement in capital evaluations, where evaluators willing to do capital casework may have stronger capital punishment support than evaluators who opt out, and evaluators with strong opposition may work selectively for the defense. The results may provide a partial explanation for the “allegiance effect” in adversarial legal settings such that preexisting attitudes may contribute to partisan participation through a self-selection process. PMID:27124416

Intelligent systems for urban search and rescue: challenges and lessons learned

Science.gov (United States)

Jacoff, Adam; Messina, Elena; Weiss, Brian A.

2003-09-01

Urban search and rescue (USAR) is one of the most dangerous and time-critical non-wartime activities. Researchers have been developing hardware and software to enable robots to perform some search and rescue functions so as to minimize the exposure of human rescue personnel to danger and maximize the survival of victims. Significant progress has been achieved, but much work remains. USAR demands a blending of numerous specialized technologies. An effective USAR robot must be endowed with key competencies, such as being able to negotiate collapsed structures, find victims and assess their condition, identify potential hazards, generate maps of the structure and victim locations, and communicate with rescue personnel. These competencies bring to bear work in numerous sub-disciplines of intelligent systems (or artificial intelligence) such as sensory processing, world modeling, behavior generation, path planning, and human-robot interaction, in addition to work in communications, mechanism design and advanced sensors. In an attempt to stimulate progress in the field, reference USAR challenges are being developed and propagated worldwide. In order to make efficient use of finite research resources, the robotic USAR community must share a common understanding of what is required, technologically, to attain each competency, and have a rigorous measure of the current level of effectiveness of various technologies. NIST is working with partner organizations to measure the performance of robotic USAR competencies and technologies. In this paper, we describe the reference test arenas for USAR robots, assess the current challenges within the field, and discuss experiences thus far in the testing effort.

How to define and build an effective cyber threat intelligence capability how to understand, justify and implement a new approach to security

CERN Document Server

Dalziel, Henry; Carnall, James

2014-01-01

Intelligence-Led Security: How to Understand, Justify and Implement a New Approach to Security is a concise review of the concept of Intelligence-Led Security. Protecting a business, including its information and intellectual property, physical infrastructure, employees, and reputation, has become increasingly difficult. Online threats come from all sides: internal leaks and external adversaries; domestic hacktivists and overseas cybercrime syndicates; targeted threats and mass attacks. And these threats run the gamut from targeted to indiscriminate to entirely accidental. Amo

Coupled generative adversarial stacked Auto-encoder: CoGASA.

Science.gov (United States)

Kiasari, Mohammad Ahangar; Moirangthem, Dennis Singh; Lee, Minho

2018-04-01

Coupled Generative Adversarial Network (CoGAN) was recently introduced in order to model a joint distribution of a multi modal dataset. The CoGAN model lacks the capability to handle noisy data as well as it is computationally expensive and inefficient for practical applications such as cross-domain image transformation. In this paper, we propose a new method, named the Coupled Generative Adversarial Stacked Auto-encoder (CoGASA), to directly transfer data from one domain to another domain with robustness to noise in the input data as well to as reduce the computation time. We evaluate the proposed model using MNIST and the Large-scale CelebFaces Attributes (CelebA) datasets, and the results demonstrate a highly competitive performance. Our proposed models can easily transfer images into the target domain with minimal effort. Copyright © 2018 Elsevier Ltd. All rights reserved.

Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining.

Science.gov (United States)

Salehi, Mojtaba; Bahreininejad, Ardeshir

2011-08-01

Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously.

Computationally Secure Pattern Matching in the Presence of Malicious Adversaries

DEFF Research Database (Denmark)

Hazay, Carmit; Toft, Tomas

2014-01-01

for important variations of the secure pattern matching problem that are significantly more efficient than the current state of art solutions: First, we deal with secure pattern matching with wildcards. In this variant the pattern may contain wildcards that match both 0 and 1. Our protocol requires O......We propose a protocol for the problem of secure two-party pattern matching, where Alice holds a text t∈{0,1}∗ of length n, while Bob has a pattern p∈{0,1}∗ of length m. The goal is for Bob to (only) learn where his pattern occurs in Alice’s text, while Alice learns nothing. Private pattern matching...... is an important problem that has many applications in the area of DNA search, computational biology and more. Our construction guarantees full simulation in the presence of malicious, polynomial-time adversaries (assuming the hardness of DDH assumption) and exhibits computation and communication costs of O...

Security intelligence a practitioner's guide to solving enterprise security challenges

CERN Document Server

Li, Qing

2015-01-01

Identify, deploy, and secure your enterprise Security Intelligence, A Practitioner's Guide to Solving Enterprise Security Challenges is a handbook for security in modern times, against modern adversaries. As leaders in the design and creation of security products that are deployed globally across a range of industries and market sectors, authors Qing Li and Gregory Clark deliver unparalleled insight into the development of comprehensive and focused enterprise security solutions. They walk you through the process of translating your security goals into specific security technology domains, fo

Adversarial risks in social experiments with new technologies

NARCIS (Netherlands)

Pieters, Wolter; Dechesne, Francien; van der Poel, Ibo; Asveld, Lotte; Mehos, Donna C.

2017-01-01

Studies that approach the deployment of new technologies as social experiments have mostly focused on unintentional effects, notably safety. We argue for the inclusion of adversarial risks or security aspects that are the result of intentional, strategic behavior of actors, who aim at using the

Adversarial Reinforcement Learning in a Cyber Security Simulation}

NARCIS (Netherlands)

Elderman, Richard; Pater, Leon; Thie, Albert; Drugan, Madalina; Wiering, Marco

2017-01-01

This paper focuses on cyber-security simulations in networks modeled as a Markov game with incomplete information and stochastic elements. The resulting game is an adversarial sequential decision making problem played with two agents, the attacker and defender. The two agents pit one reinforcement

Modeling urbanization patterns with generative adversarial networks

OpenAIRE

Albert, Adrian; Strano, Emanuele; Kaur, Jasleen; Gonzalez, Marta

2018-01-01

In this study we propose a new method to simulate hyper-realistic urban patterns using Generative Adversarial Networks trained with a global urban land-use inventory. We generated a synthetic urban "universe" that qualitatively reproduces the complex spatial organization observed in global urban patterns, while being able to quantitatively recover certain key high-level urban spatial metrics.

Adversarial risk analysis with incomplete information: a level-k approach.

Science.gov (United States)

Rothschild, Casey; McLay, Laura; Guikema, Seth

2012-07-01

This article proposes, develops, and illustrates the application of level-k game theory to adversarial risk analysis. Level-k reasoning, which assumes that players play strategically but have bounded rationality, is useful for operationalizing a Bayesian approach to adversarial risk analysis. It can be applied in a broad class of settings, including settings with asynchronous play and partial but incomplete revelation of early moves. Its computational and elicitation requirements are modest. We illustrate the approach with an application to a simple defend-attack model in which the defender's countermeasures are revealed with a probability less than one to the attacker before he decides on how or whether to attack. © 2011 Society for Risk Analysis.

An adversarial queueing model for online server routing

NARCIS (Netherlands)

Bonifaci, V.

2007-01-01

In an online server routing problem, a vehicle or server moves in a network in order to process incoming requests at the nodes. Online server routing problems have been thoroughly studied using competitive analysis. We propose a new model for online server routing, based on adversarial queueing

Vulnerability of classifiers to evolutionary generated adversarial examples

Czech Academy of Sciences Publication Activity Database

Vidnerová, Petra; Neruda, Roman

submitted 14.1. 2017 (2018) ISSN 0941-0643 R&D Projects: GA ČR GA15-18108S Institutional support: RVO:67985807 Keywords : supervised learning * neural networks * kernel methods * genetic algorithm s * adversarial examples Subject RIV: IN - Informatics, Computer Science Impact factor: 2.505, year: 2016

Adversary modeling: an analysis of criminal activities analogous to potential threats to nuclear safeguard systems

International Nuclear Information System (INIS)

Heineke, J.M.

1978-01-01

This study examines and analyzes several classes of incidents in which decision makers are confronted with adversaries. The classes are analogous to adversaries in a material control system in a nuclear facility. Both internal threats (bank frauds and embezzlements) and external threats (aircraft hijackings and hostage-type terrorist events were analyzed

The Breakthrough Listen Search for Intelligent Life

Science.gov (United States)

Croft, Steve; Siemion, Andrew; De Boer, David; Enriquez, J. Emilio; Foster, Griffin; Gajjar, Vishal; Hellbourg, Greg; Hickish, Jack; Isaacson, Howard; Lebofsky, Matt; MacMahon, David; Price, Daniel; Werthimer, Dan

2018-01-01

The $100M, 10-year philanthropic "Breakthrough Listen" project is driving an unprecedented expansion of the search for intelligent life beyond Earth. Modern instruments allow ever larger regions of parameter space (luminosity function, duty cycle, beaming fraction, frequency coverage) to be explored, which is enabling us to place meaningful physical limits on the prevalence of transmitting civilizations. Data volumes are huge, and preclude long-term storage of the raw data products, so real-time and machine learning processing techniques must be employed to identify candidate signals as well as simultaneously classifying interfering sources. However, the Galaxy is now known to be a target-rich environment, teeming with habitable planets.Data from Breakthrough Listen can also be used by researchers in other areas of astronomy to study pulsars, fast radio bursts, and a range of other science targets. Breakthrough Listen is already underway in the optical and radio bands, and is also engaging with facilities across the world, including Square Kilometer Array precursors and pathfinders. I will give an overview of the technology, science goals, data products, and roadmap of Breakthrough Listen, as we attempt to answer one of humanity's oldest questions: Are we alone?

A Privacy-Preserving Intelligent Medical Diagnosis System Based on Oblivious Keyword Search

Directory of Open Access Journals (Sweden)

Zhaowen Lin

2017-01-01

Full Text Available One of the concerns people have is how to get the diagnosis online without privacy being jeopardized. In this paper, we propose a privacy-preserving intelligent medical diagnosis system (IMDS, which can efficiently solve the problem. In IMDS, users submit their health examination parameters to the server in a protected form; this submitting process is based on Paillier cryptosystem and will not reveal any information about their data. And then the server retrieves the most likely disease (or multiple diseases from the database and returns it to the users. In the above search process, we use the oblivious keyword search (OKS as a basic framework, which makes the server maintain the computational ability but cannot learn any personal information over the data of users. Besides, this paper also provides a preprocessing method for data stored in the server, to make our protocol more efficient.

Adversary modeling: an analysis of criminal activities analogous to potential threats to nuclear safeguard systems

Energy Technology Data Exchange (ETDEWEB)

Heineke, J.M.

1978-12-20

This study examines and analyzes several classes of incidents in which decision makers are confronted with adversaries. The classes are analogous to adversaries in a material control system in a nuclear facility. Both internal threats (bank frauds and embezzlements) and external threats (aircraft hijackings and hostage-type terrorist events were analyzed. (DLC)

The Search for Extraterrestrial Intelligence in the 1960s: Science in Popular Culture

Science.gov (United States)

Smith, Sierra

2012-01-01

Building upon the advancement of technology during the Second World War and the important scientific discoveries which have been made about the structure and components of the universe, scientists, especially in radio astronomy and physics, began seriously addressing the possibility of extraterrestrial intelligence in the 1960s. The Search for Extraterrestrial Intelligence (SETI) quickly became one of the most controversial scientific issues in the post Second World War period. The controversy played out, not only in scientific and technical journals, but in newspapers and in popular literature. Proponents for SETI, including Frank Drake, Carl Sagan, and Philip Morrison, actively used a strategy of engagement with the public by using popular media to lobby for exposure and funding. This paper will examine the use of popular media by scientists interested in SETI to popularize and heighten public awareness and also to examine the effects of popularization on SETI's early development. My research has been generously supported by the National Radio Astronomy Observatory.

Adversarial training and dilated convolutions for brain MRI segmentation

NARCIS (Netherlands)

Moeskops, P.; Veta, M.; Lafarge, M.W.; Eppenhof, K.A.J.; Pluim, J.P.W.

2017-01-01

Convolutional neural networks (CNNs) have been applied to various automatic image segmentation tasks in medical image analysis, including brain MRI segmentation. Generative adversarial networks have recently gained popularity because of their power in generating images that are difficult to

Inference-Based Similarity Search in Randomized Montgomery Domains for Privacy-Preserving Biometric Identification.

Science.gov (United States)

Wang, Yi; Wan, Jianwu; Guo, Jun; Cheung, Yiu-Ming; C Yuen, Pong

2017-07-14

Similarity search is essential to many important applications and often involves searching at scale on high-dimensional data based on their similarity to a query. In biometric applications, recent vulnerability studies have shown that adversarial machine learning can compromise biometric recognition systems by exploiting the biometric similarity information. Existing methods for biometric privacy protection are in general based on pairwise matching of secured biometric templates and have inherent limitations in search efficiency and scalability. In this paper, we propose an inference-based framework for privacy-preserving similarity search in Hamming space. Our approach builds on an obfuscated distance measure that can conceal Hamming distance in a dynamic interval. Such a mechanism enables us to systematically design statistically reliable methods for retrieving most likely candidates without knowing the exact distance values. We further propose to apply Montgomery multiplication for generating search indexes that can withstand adversarial similarity analysis, and show that information leakage in randomized Montgomery domains can be made negligibly small. Our experiments on public biometric datasets demonstrate that the inference-based approach can achieve a search accuracy close to the best performance possible with secure computation methods, but the associated cost is reduced by orders of magnitude compared to cryptographic primitives.

Intelligence Ethics:

DEFF Research Database (Denmark)

Rønn, Kira Vrist

2016-01-01

Questions concerning what constitutes a morally justified conduct of intelligence activities have received increased attention in recent decades. However, intelligence ethics is not yet homogeneous or embedded as a solid research field. The aim of this article is to sketch the state of the art...... of intelligence ethics and point out subjects for further scrutiny in future research. The review clusters the literature on intelligence ethics into two groups: respectively, contributions on external topics (i.e., the accountability of and the public trust in intelligence agencies) and internal topics (i.......e., the search for an ideal ethical framework for intelligence actions). The article concludes that there are many holes to fill for future studies on intelligence ethics both in external and internal discussions. Thus, the article is an invitation – especially, to moral philosophers and political theorists...

Application of Generative Adversarial Networks (GANs) to jet images

CERN Multimedia

CERN. Geneva

2017-01-01

https://arxiv.org/abs/1701.05927 We provide a bridge between generative modeling in the Machine Learning community and simulated physical processes in High Energy Particle Physics by applying a novel Generative Adversarial Network (GAN) architecture to the production of jet images -- 2D representations of energy depositions from particles interacting with a calorimeter. We propose a simple architecture, the Location-Aware Generative Adversarial Network, that learns to produce realistic radiation patterns from simulated high energy particle collisions. The pixel intensities of GAN-generated images faithfully span over many orders of magnitude and exhibit the desired low-dimensional physical properties (i.e., jet mass, n-subjettiness, etc.). We shed light on limitations, and provide a novel empirical validation of image quality and validity of GAN-produced simulations of the natural world. This work provides a base for further explorations of GANs for use in faster simulation in High Energy Particle Physics.

Feminized Power and Adversarial Advocacy: Levelling Arguments or Analyzing Them?

Science.gov (United States)

Condit, Celeste Michelle

1989-01-01

Examines the journalistic analysis of the 1988 Presidential Debates from a feminist perspective in order to identify the revisions needed in the debate process. Provides historical background of feminized power and adversarial advocacy. (MM)

Searching for Extraterrestrial Intelligence SETI Past, Present, and Future

CERN Document Server

Shuch, H Paul

2011-01-01

This book is a collection of essays written by the very scientists and engineers who have led, and continue to lead, the scientific quest known as SETI, the search for extraterrestrial intelligence. Divided into three parts, the first section, ‘The Spirit of SETI Past’, written by the surviving pioneers of this then emerging discipline, reviews the major projects undertaken during the first 50 years of SETI science and the results of that research. In the second section, ‘The Spirit of SETI Present’, the present-day science and technology is discussed in detail, providing the technical background to contemporary SETI instruments, experiments, and analytical techniques, including the processing of the received signals to extract potential alien communications. In the third and final section, ‘The Spirit of SETI Future’, the book looks ahead to the possible directions that SETI will take in the next 50 years, addressing such important topics as interstellar message construction, the risks and assump...

Generative adversarial networks for anomaly detection in images

OpenAIRE

Batiste Ros, Guillem

2018-01-01

Anomaly detection is used to identify abnormal observations that don t follow a normal pattern. Inthis work, we use the power of Generative Adversarial Networks in sampling from image distributionsto perform anomaly detection with images and to identify local anomalous segments within thisimages. Also, we explore potential application of this method to support pathological analysis ofbiological tissues

On-line diagnosis and recovery of adversary attack using logic flowgraph methodology simulation

International Nuclear Information System (INIS)

Guarro, S.B.

1986-01-01

The Logic Flowgraph Methodology (LFM) allows the construction of special graph models for simulation of complex processes of causality, including feedback loops and sequential effects. Among the most notable features of LFM is the formal inclusion in its models of causality conditioning by logic switches imbedded in the modeled process, such as faults or modes of operation. The LFM model of a process is a graph structure that captures, in one synthetic representation, the relevant success and fault space characterization of that process. LFM is very similar to an artificial intelligence expert system shell. To illustrate the utilization of LFM, an application to the assessment and on-line monitoring of a material control facility is presented. The LFM models are used to model adversary action and control response, and to generate mini-diagnostic and recovery trees in real time, as well as reliability tress for off-line evaluation. Although the case study presented is for an imaginary facility, most of the conceptual elements that would be present in a real application have been retained in order to highlight the features and capabilities of the methodology

Generative Adversarial Networks: An Overview

Science.gov (United States)

Creswell, Antonia; White, Tom; Dumoulin, Vincent; Arulkumaran, Kai; Sengupta, Biswa; Bharath, Anil A.

2018-01-01

Generative adversarial networks (GANs) provide a way to learn deep representations without extensively annotated training data. They achieve this through deriving backpropagation signals through a competitive process involving a pair of networks. The representations that can be learned by GANs may be used in a variety of applications, including image synthesis, semantic image editing, style transfer, image super-resolution and classification. The aim of this review paper is to provide an overview of GANs for the signal processing community, drawing on familiar analogies and concepts where possible. In addition to identifying different methods for training and constructing GANs, we also point to remaining challenges in their theory and application.

Generative Adversarial Networks for Improving Face Classification

OpenAIRE

Natten, Jonas

2017-01-01

Master's thesis Information- and communication technology IKT590 - University of Agder 2017 Facial recognition can be applied in a wide variety of cases, including entertainment purposes and biometric security. In this thesis we take a look at improving the results of an existing facial recognition approach by utilizing generative adversarial networks to improve the existing dataset. The training data was taken from the LFW dataset[4] and was preprocessed using OpenCV[2] for...

Smart Collision Avoidance and Hazard Routing Mechanism for Intelligent Transport Network

Science.gov (United States)

Singh, Gurpreet; Gupta, Pooja; Wahab, Mohd Helmy Abd

2017-08-01

The smart vehicular ad-hoc network is the network that consists of vehicles for smooth movement and better management of the vehicular connectivity across the given network. This research paper aims to propose a set of solution for the VANETs consisting of the automatic driven vehicles, also called as the autonomous car. Such vehicular networks are always prone to collision due to the natural or un-natural reasons which must be solved before the large-scale deployment of the autonomous transport systems. The newly designed intelligent transport movement control mechanism is based upon the intelligent data propagation along with the vehicle collision and traffic jam prevention schema [8], which may help the future designs of smart cities to become more robust and less error-prone. In the proposed model, the focus is on designing a new dynamic and robust hazard routing protocol for intelligent vehicular networks for improvement of the overall performance in various aspects. It is expected to improve the overall transmission delay as well as the number of collisions or adversaries across the vehicular network zone.

A5: Automated Analysis of Adversarial Android Applications

Science.gov (United States)

2014-06-03

A5: Automated Analysis of Adversarial Android Applications Timothy Vidas, Jiaqi Tan, Jay Nahata, Chaur Lih Tan, Nicolas Christin...detecting, on the device itself, that an application is malicious is much more complex without elevated privileges . In other words, given the...interface via website. Blasing et al. [7] describe another dynamic analysis system for Android . Their system focuses on classifying input applications as

Meta-Search Utilizing Evolitionary Recommendation: A Web Search Architecture Proposal

Czech Academy of Sciences Publication Activity Database

Húsek, Dušan; Keyhanipour, A.; Krömer, P.; Moshiri, B.; Owais, S.; Snášel, V.

2008-01-01

Roč. 33, - (2008), s. 189-200 ISSN 1870-4069 Institutional research plan: CEZ:AV0Z10300504 Keywords : web search * meta-search engine * intelligent re-ranking * ordered weighted averaging * Boolean search queries optimizing Subject RIV: IN - Informatics, Computer Science

RETHINKING THE ROLE OF SMALL-GROUP COLLABORATORS AND ADVERSARIES IN THE LONDON KLEINIAN DEVELOPMENT (1914-1968).

Science.gov (United States)

Aguayo, Joseph; Regeczkey, Agnes

2016-07-01

The authors historically situate the London Kleinian development in terms of the small-group collaborations and adversaries that arose during the course of Melanie Klein's career. Some collaborations later became personally adversarial (e.g., those Klein had with Glover and Schmideberg); other adversarial relationships forever remained that way (with A. Freud); while still other long-term collaborations became theoretically contentious (such as with Winnicott and Heimann). After the Controversial Discussions in 1944, Klein marginalized one group of supporters (Heimann, Winnicott, and Riviere) in favor of another group (Rosenfeld, Segal, and Bion). After Klein's death in 1960, Bion maintained loyalty to Klein's ideas while quietly distancing his work from the London Klein group, immigrating to the United States in 1968. © 2016 The Psychoanalytic Quarterly, Inc.

The ontology supported intelligent system for experiment search in the scientific Research center

Directory of Open Access Journals (Sweden)

Cvjetković Vladimir

2014-01-01

Full Text Available Ontologies and corresponding knowledge bases can be quite successfully used for many tasks that rely on domain knowledge and semantic structures, which should be available for machine processing and sharing. Using SPARQL queries for retrieval of required elements from ontologies and knowledge bases, can significantly simplify modeling of arbitrary structures of concepts and data, and implementation of required functionalities. This paper describes developed ontology for support of Research Centre for testing of active substances that conducts scientific experiments. According to created ontology corresponding knowledge base was made and populated with real experimental data. Developed ontology and knowledge base are directly used for an intelligent system of experiment search which is based on many criteria from ontology. Proposed system gets the desired search result, which is actually an experiment in the form of a written report. Presented solution and implementation are very flexible and adaptable, and can be used as kind of a template by similar information system dealing with biological or similar complex system.

Online Evolution for Multi-Action Adversarial Games

OpenAIRE

Justesen, Niels; Mahlmann, Tobias; Togelius, Julian

2016-01-01

We present Online Evolution, a novel method for playing turn-based multi-action adversarial games. Such games, which include most strategy games, have extremely high branching factors due to each turn having multiple actions. In Online Evolution, an evolutionary algorithm is used to evolve the combination of atomic actions that make up a single move, with a state evaluation function used for fitness. We implement Online Evolution for the turn-based multi-action game Hero Academy and compare i...

Comparing Generative Adversarial Network Techniques for Image Creation and Modification

NARCIS (Netherlands)

Pieters, Mathijs; Wiering, Marco

2018-01-01

Generative adversarial networks (GANs) have demonstrated to be successful at generating realistic real-world images. In this paper we compare various GAN techniques, both supervised and unsupervised. The effects on training stability of different objective functions are compared. We add an encoder

Adversarial reasoning and resource allocation: the LG approach

Science.gov (United States)

Stilman, Boris; Yakhnis, Vladimir; Umanskiy, Oleg; Boyd, Ron

2005-05-01

Many existing automated tools purporting to model the intelligent enemy utilize a fixed battle plan for the enemy while using flexible decisions of human players for the friendly side. According to the Naval Studies Board, "It is an open secret and a point of distress ... that too much of the substantive content of such M&S has its origin in anecdote, ..., or a narrow construction tied to stereotypical current practices of 'doctrinally correct behavior.'" Clearly, such runs lack objectivity by being heavily skewed in favor of the friendly forces. Presently, the military branches employ a variety of game-based simulators and synthetic environments, with manual (i.e., user-based) decision-making, for training and other purposes. However, without an ability to automatically generate the best strategies, tactics, and COA, the games serve mostly to display the current situation rather than form a basis for automated decision-making and effective training. We solve the problem of adversarial reasoning as a gaming problem employing Linguistic Geometry (LG), a new type of game theory demonstrating significant increase in size in gaming problems solvable in real and near-real time. It appears to be a viable approach for solving such practical problems as mission planning and battle management. Essentially, LG may be structured into two layers: game construction and game solving. Game construction includes construction of a game called an LG hypergame based on a hierarchy of Abstract Board Games (ABG). Game solving includes resource allocation for constructing an advantageous initial game state and strategy generation to reach a desirable final game state in the course of the game.

Evaluation of risk from acts of terrorism :the adversary/defender model using belief and fuzzy sets.

Energy Technology Data Exchange (ETDEWEB)

Darby, John L.

2006-09-01

Risk from an act of terrorism is a combination of the likelihood of an attack, the likelihood of success of the attack, and the consequences of the attack. The considerable epistemic uncertainty in each of these three factors can be addressed using the belief/plausibility measure of uncertainty from the Dempster/Shafer theory of evidence. The adversary determines the likelihood of the attack. The success of the attack and the consequences of the attack are determined by the security system and mitigation measures put in place by the defender. This report documents a process for evaluating risk of terrorist acts using an adversary/defender model with belief/plausibility as the measure of uncertainty. Also, the adversary model is a linguistic model that applies belief/plausibility to fuzzy sets used in an approximate reasoning rule base.

Durham Zoo: Powering a Search-&-Innovation Engine with Collective Intelligence

Directory of Open Access Journals (Sweden)

Richard Absalom

2015-02-01

Full Text Available Purpose – Durham Zoo (hereinafter – DZ is a project to design and operate a concept search engine for science and technology. In DZ, a concept includes a solution to a problem in a particular context.Design – Concept searching is rendered complex by the fuzzy nature of a concept, the many possible implementations of the same concept, and the many more ways that the many implementations can be expressed in natural language. An additional complexity is the diversity of languages and formats, in which the concepts can be disclosed.Humans understand language, inference, implication and abstraction and, hence, concepts much better than computers, that in turn are much better at storing and processing vast amounts of data.We are 7 billion on the planet and we have the Internet as the backbone for Collective Intelligence. So, our concept search engine uses humans to store concepts via a shorthand that can be stored, processed and searched by computers: so, humans IN and computers OUT.The shorthand is classification: metadata in a structure that can define the content of a disclosure. The classification is designed to be powerful in terms of defining and searching concepts, whilst suited to a crowdsourcing effort. It is simple and intuitive to use. Most importantly, it is adapted to restrict ambiguity, which is the poison of classification, without imposing a restrictive centralised management.In the classification scheme, each entity is shown together in a graphical representation with related entities. The entities are arranged on a sliding scale of similarity. This sliding scale is effectively fuzzy classification.Findings – The authors of the paper have been developing a first classification scheme for the technology of traffic cones, this in preparation for a trial of a working system. The process has enabled the authors to further explore the practicalities of concept classification. The CmapTools knowledge modelling kit to develop the

Computationally Secure Pattern Matching in the Presence of Malicious Adversaries

DEFF Research Database (Denmark)

Hazay, Carmit; Toft, Tomas

2010-01-01

simulation in the presence of malicious, polynomial-time adversaries (assuming that ElGamal encryption is semantically secure) and exhibits computation and communication costs of O(n + m) in a constant round complexity. In addition to the above, we propose a collection of protocols for variations...

Secure Learning and Learning for Security: Research in the Intersection

OpenAIRE

Rubinstein, Benjamin

2010-01-01

Statistical Machine Learning is used in many real-world systems, such as web search, network and power management, online advertising, finance and health services, in which adversaries are incentivized to attack the learner, motivating the urgent need for a better understanding of the security vulnerabilities of adaptive systems. Conversely, research in Computer Security stands to reap great benefits by leveraging learning for building adaptive defenses and even designing intelligent attacks ...

Adversarial Reinforcement Learning in a Cyber Security Simulation}

OpenAIRE

Elderman, Richard; Pater, Leon; Thie, Albert; Drugan, Madalina; Wiering, Marco

2017-01-01

This paper focuses on cyber-security simulations in networks modeled as a Markov game with incomplete information and stochastic elements. The resulting game is an adversarial sequential decision making problem played with two agents, the attacker and defender. The two agents pit one reinforcement learning technique, like neural networks, Monte Carlo learning and Q-learning, against each other and examine their effectiveness against learning opponents. The results showed that Monte Carlo lear...

Cognitive-Emotional Conflict: Adversary Will and Social Resilience

Science.gov (United States)

2017-12-21

effectively with skilled adversaries in the realm of social media . This admit- tedly is a complex problem for any open, democratic society that does not... social media of the targeted populations. Rather than inciting a population to take a particular action, as the leak of the Zimmerman telegram did in...produced by the 24/7 news cycle, amplified and accelerated by social media . National Level Most Americans do not recognize the threats posed by

Are the advocates of nuclear power and the adversaries listening to each other? Does Dialogue have a chance? Introductory remarks by John A. Macpherson[Roundtable discussion on whether the advocates of nuclear power and the adversaries are listening to each other

Energy Technology Data Exchange (ETDEWEB)

Macpherson, John A [Atomic Energy of Canada Ltd., Mississauga, ON (Canada)

1989-07-01

Are the advocates of nuclear power and the adversaries listening to each other? Does dialogue have a chance? My short answer to both questions posed as the title for this discussion is 'no'. And I would add: There is no point in trying to bring opposite poles together, it requires too much investment for too little return. A nuclear dialogue will have a chance only it a distinction can be shown between physics and metaphysics, between chemistry and alchemy, and if the gap can be bridged between the polarized views of the world's societal needs which, incidentally, create the nuclear issue in the first place. This is a daunting task Movements in search of a cause have a passion for preaching rather than a love for listening.

Budget constraints and optimization in sponsored search auctions

CERN Document Server

Yang, Yanwu

2013-01-01

The Intelligent Systems Series publishes reference works and handbooks in three core sub-topic areas: Intelligent Automation, Intelligent Transportation Systems, and Intelligent Computing. They include theoretical studies, design methods, and real-world implementations and applications. The series' readership is broad, but focuses on engineering, electronics, and computer science. Budget constraints and optimization in sponsored search auctions takes into account consideration of the entire life cycle of campaigns for researchers and developers working on search systems and ROI maximization

On the Runtime of Randomized Local Search and Simple Evolutionary Algorithms for Dynamic Makespan Scheduling

DEFF Research Database (Denmark)

Neumann, Frank; Witt, Carsten

2015-01-01

combinatorial optimization problem, namely makespan scheduling. We study the model of a strong adversary which is allowed to change one job at regular intervals. Furthermore, we investigate the setting of random changes. Our results show that randomized local search and a simple evolutionary algorithm are very...

Cooperative Control of Distributed Autonomous Vehicles in Adversarial Environments

Science.gov (United States)

2006-08-14

COOPERATIVE CONTROL OF DISTRIBUTED AUTONOMOUS VEHICLES IN ADVERSARIAL ENVIRONMENTS Grant #F49620–01–1–0361 Final Report Jeff Shamma Department of...CONTRACT NUMBER F49620-01-1-0361 5b. GRANT NUMBER 4. TITLE AND SUBTITLE COOPERATIVE CONTROL OF DISTRIBUTED AUTONOMOUS VEHICLES IN...single dominant language or a distribution of languages. A relation to multivehicle systems is understanding how highly autonomous vehicles on extended

The internet and intelligent machines: search engines, agents and robots; Radiologische Informationssuche im Internet: Datenbanken, Suchmaschinen und intelligente Agenten

Energy Technology Data Exchange (ETDEWEB)

Achenbach, S; Alfke, H [Marburg Univ. (Germany). Abt. fuer Strahlendiagnostik

2000-04-01

The internet plays an important role in a growing number of medical applications. Finding relevant information is not always easy as the amount of available information on the Web is rising quickly. Even the best Search Engines can only collect links to a fraction of all existing Web pages. In addition, many of these indexed documents have been changed or deleted. The vast majority of information on the Web is not searchable with conventional methods. New search strategies, technologies and standards are combined in Intelligent Search Agents (ISA) an Robots, which can retrieve desired information in a specific approach. Conclusion: The article describes differences between ISAs and conventional Search Engines and how communication between Agents improves their ability to find information. Examples of existing ISAs are given and the possible influences on the current and future work in radiology is discussed. (orig.) [German] Das Internet findet zunehmend in medizinischen Anwendungen Verbreitung, jedoch ist das Auffinden relevanter Informationen nicht immer leicht. Die Anzahl der verfuegbaren Dokumente im World wide web nimmt so schnell zu, dass die Suche zunehmend Probleme bereitet: Auch gute Suchmaschinen erfassen nur einige Prozent der vorhandenen Seiten in Ihren Datenbanken. Zusaetzlich sorgen staendige Veraenderungen dafuer, dass nur ein Teil dieser durchsuchbaren Dokumente ueberhaupt noch existiert. Der Grossteil des Internets ist daher mit konventionellen Methoden nicht zu erschliessen. Neue Standards, Suchstrategien und Technologien vereinen sich in den Suchagenten und Robots, die gezielter und intelligenter Inhalte ermitteln koennen. Schlussfolgerung: Der Artikel stellt dar, wie sich ein Intelligent search agent (ISA) von einer Suchmaschine unterscheidet und durch Kooperation mit anderen Agenten die Anforderungen der Benutzer besser erfuellen kann. Neben den Grundlagen werden exemplarische Anwendungen gezeigt, die heute im Netz existieren, und ein Ausblick

Intelligent methods for data retrieval in fusion databases

International Nuclear Information System (INIS)

Vega, J.

2008-01-01

The plasma behaviour is identified through the recognition of patterns inside signals. The search for patterns is usually a manual and tedious procedure in which signals need to be examined individually. A breakthrough in data retrieval for fusion databases is the development of intelligent methods to search for patterns. A pattern (in the broadest sense) could be a single segment of a waveform, a set of pixels within an image or even a heterogeneous set of features made up of waveforms, images and any kind of experimental data. Intelligent methods will allow searching for data according to technical, scientific and structural criteria instead of an identifiable time interval or pulse number. Such search algorithms should be intelligent enough to avoid passing over the entire database. Benefits of such access methods are discussed and several available techniques are reviewed. In addition, the applicability of the methods from general purpose searching systems to ad hoc developments is covered

GalaxyGAN: Generative Adversarial Networks for recovery of galaxy features

Science.gov (United States)

Schawinski, Kevin; Zhang, Ce; Zhang, Hantian; Fowler, Lucas; Krishnan Santhanam, Gokula

2017-02-01

GalaxyGAN uses Generative Adversarial Networks to reliably recover features in images of galaxies. The package uses machine learning to train on higher quality data and learns to recover detailed features such as galaxy morphology by effectively building priors. This method opens up the possibility of recovering more information from existing and future imaging data.

Intelligence Is What the Intelligence Test Measures. Seriously

Directory of Open Access Journals (Sweden)

Han L. J. van der Maas

2014-02-01

Full Text Available The mutualism model, an alternative for the g-factor model of intelligence, implies a formative measurement model in which “g” is an index variable without a causal role. If this model is accurate, the search for a genetic of brain instantiation of “g” is deemed useless. This also implies that the (weighted sum score of items of an intelligence test is just what it is: a weighted sum score. Preference for one index above the other is a pragmatic issue that rests mainly on predictive value.

Intelligent System Design Using Hyper-Heuristics

Directory of Open Access Journals (Sweden)

Nelishia Pillay

2015-07-01

Full Text Available Determining the most appropriate search method or artificial intelligence technique to solve a problem is not always evident and usually requires implementation of the different approaches to ascertain this. In some instances a single approach may not be sufficient and hybridization of methods may be needed to find a solution. This process can be time consuming. The paper proposes the use of hyper-heuristics as a means of identifying which method or combination of approaches is needed to solve a problem. The research presented forms part of a larger initiative aimed at using hyper-heuristics to develop intelligent hybrid systems. As an initial step in this direction, this paper investigates this for classical artificial intelligence uninformed and informed search methods, namely depth first search, breadth first search, best first search, hill-climbing and the A* algorithm. The hyper-heuristic determines the search or combination of searches to use to solve the problem. An evolutionary algorithm hyper-heuristic is implemented for this purpose and its performance is evaluated in solving the 8-Puzzle, Towers of Hanoi and Blocks World problems. The hyper-heuristic employs a generational evolutionary algorithm which iteratively refines an initial population using tournament selection to select parents, which the mutation and crossover operators are applied to for regeneration. The hyper-heuristic was able to identify a search or combination of searches to produce solutions for the twenty 8-Puzzle, five Towers of Hanoi and five Blocks World problems. Furthermore, admissible solutions were produced for all problem instances.

High-speed data search

Science.gov (United States)

Driscoll, James N.

1994-01-01

The high-speed data search system developed for KSC incorporates existing and emerging information retrieval technology to help a user intelligently and rapidly locate information found in large textual databases. This technology includes: natural language input; statistical ranking of retrieved information; an artificial intelligence concept called semantics, where 'surface level' knowledge found in text is used to improve the ranking of retrieved information; and relevance feedback, where user judgements about viewed information are used to automatically modify the search for further information. Semantics and relevance feedback are features of the system which are not available commercially. The system further demonstrates focus on paragraphs of information to decide relevance; and it can be used (without modification) to intelligently search all kinds of document collections, such as collections of legal documents medical documents, news stories, patents, and so forth. The purpose of this paper is to demonstrate the usefulness of statistical ranking, our semantic improvement, and relevance feedback.

The Search for Extraterrestrial Intelligence (SETI) and Whether to send 'Messages' (METI): A Case for Conversation, Patience and Due Diligence

Science.gov (United States)

Brin, D.

Understanding the controversy over "Messages to Extra Terrestrial Intelligence" or METI requires a grounding in the history and rationale of SETI (Search for ETI). Insights since the turn of the century have changed SETI's scientific basis. Continued null results from the radio search do not invalidate continuing effort, but they do raise questions about long-held assumptions. Modified search strategies are discussed. The Great Silence or Fermi Paradox is appraised, along with the disruptive plausibility of interstellar travel. Psychological motivations for METI are considered. With this underpinning, we consider why a small cadre of SETI-ist radio astronomers have resisted the notion of international consultations before humanity takes a brash and irreversible step into METI, shouting our presence into the cosmos.

Methodology for characterizing potential adversaries of Nuclear Material Safeguards Systems

International Nuclear Information System (INIS)

Kirkwood, C.W.; Pollock, S.M.

1978-11-01

The results are described of a study by Woodward--Clyde Consultants to assist the University of California Lawrence Livermore Laboratory in the development of methods to analyze and evaluate Nuclear Material Safeguards (NMS) Systems. The study concentrated on developing a methodology to assist experts in describing, in quantitative form, their judgments about the characteristics of potential adversaries of NMS Systems

Methodology for characterizing potential adversaries of Nuclear Material Safeguards Systems

Energy Technology Data Exchange (ETDEWEB)

Kirkwood, C.W.; Pollock, S.M.

1978-11-01

The results are described of a study by Woodward--Clyde Consultants to assist the University of California Lawrence Livermore Laboratory in the development of methods to analyze and evaluate Nuclear Material Safeguards (NMS) Systems. The study concentrated on developing a methodology to assist experts in describing, in quantitative form, their judgments about the characteristics of potential adversaries of NMS Systems.

Speech-Driven Facial Reenactment Using Conditional Generative Adversarial Networks

OpenAIRE

Jalalifar, Seyed Ali; Hasani, Hosein; Aghajan, Hamid

2018-01-01

We present a novel approach to generating photo-realistic images of a face with accurate lip sync, given an audio input. By using a recurrent neural network, we achieved mouth landmarks based on audio features. We exploited the power of conditional generative adversarial networks to produce highly-realistic face conditioned on a set of landmarks. These two networks together are capable of producing a sequence of natural faces in sync with an input audio track.

Bring a gun to a gunfight: armed adversaries and violence across nations.

Science.gov (United States)

Felson, Richard B; Berg, Mark T; Rogers, Meghan L

2014-09-01

We use homicide data and the International Crime Victimization Survey to examine the role of firearms in explaining cross-national variation in violence. We suggest that while gun violence begets gun violence, it inhibits the tendency to engage in violence without guns. We attribute the patterns to adversary effects-i.e., the tendency of offenders to take into account the threat posed by their adversaries. Multi-level analyses of victimization data support the hypothesis that living in countries with high rates of gun violence lowers an individual's risk of an unarmed assault and assaults with less lethal weapons. Analyses of aggregate data show that homicide rates and gun violence rates load on a separate underlying factor than other types of violence. The results suggest that a country's homicide rate reflects, to a large extent, the tendency of its offenders to use firearms. Copyright © 2014 Elsevier Inc. All rights reserved.

Challenging problems and solutions in intelligent systems

CERN Document Server

Grzegorzewski, Przemysław; Kacprzyk, Janusz; Owsiński, Jan; Penczek, Wojciech; Zadrożny, Sławomir

2016-01-01

This volume presents recent research, challenging problems and solutions in Intelligent Systems– covering the following disciplines: artificial and computational intelligence, fuzzy logic and other non-classic logics, intelligent database systems, information retrieval, information fusion, intelligent search (engines), data mining, cluster analysis, unsupervised learning, machine learning, intelligent data analysis, (group) decision support systems, intelligent agents and multi-agent systems, knowledge-based systems, imprecision and uncertainty handling, electronic commerce, distributed systems, etc. The book defines a common ground for sometimes seemingly disparate problems and addresses them by using the paradigm of broadly perceived intelligent systems. It presents a broad panorama of a multitude of theoretical and practical problems which have been successfully dealt with using the paradigm of intelligent computing.

Cooperation and punishment in an adversarial game: How defectors pave the way to a peaceful society

Science.gov (United States)

Short, M. B.; Brantingham, P. J.; D'Orsogna, M. R.

2010-12-01

The evolution of human cooperation has been the subject of much research, especially within the framework of evolutionary public goods games, where several mechanisms have been proposed to account for persistent cooperation. Yet, in addressing this issue, little attention has been given to games of a more adversarial nature, in which defecting players, rather than simply free riding, actively seek to harm others. Here, we develop an adversarial evolutionary game using the specific example of criminal activity, recasting the familiar public goods strategies of punishers, cooperators, and defectors in this light. We then introduce a strategy—the informant—with no clear analog in public goods games and show that individuals employing this strategy are a key to the emergence of systems where cooperation dominates. We also find that a defection-dominated regime may be transitioned to one that is cooperation-dominated by converting an optimal number of players into informants. We discuss these findings, the role of informants, and possible intervention strategies in extreme adversarial societies, such as those marred by wars and insurgencies.

Psycholinguistics and the Search for Extraterrestrial Intelligence

Directory of Open Access Journals (Sweden)

Lidija Krotenko

2017-09-01

Full Text Available The author of the article reveals the possibilities of psycholinguistics in the identifi cation and interpretation of languages and texts of Alien Civilizations. The author combines modern interdisciplinary research in psycholinguistics with the theory “Evolving Matter” proposed by Oleg Bazaluk and concludes that the identifi cation of languages and texts of Alien Civilizations, as well as the communication of terrestrial civilization with Extraterrestrial Intelligence, is in principle possible. To that end, it is necessary to achieve the required level of the modeling of neurophilosophy and to include these achievements of modern psycholinguistics studies: а language acquisition; b language comprehension; c language production; d second language acquisition. On the one hand, the possibilities of neurophilosophy to accumulate and model advanced neuroscience research; on the other hand, highly specialized psycholinguistic studies in language evolution are able to provide the communication of terrestrial civilization with Extraterrestrial Intelligence.

Probabilistic Characterization of Adversary Behavior in Cyber Security

Energy Technology Data Exchange (ETDEWEB)

Meyers, C A; Powers, S S; Faissol, D M

2009-10-08

The objective of this SMS effort is to provide a probabilistic characterization of adversary behavior in cyber security. This includes both quantitative (data analysis) and qualitative (literature review) components. A set of real LLNL email data was obtained for this study, consisting of several years worth of unfiltered traffic sent to a selection of addresses at ciac.org. The email data was subjected to three interrelated analyses: a textual study of the header data and subject matter, an examination of threats present in message attachments, and a characterization of the maliciousness of embedded URLs.

Semantic policy and adversarial modeling for cyber threat identification and avoidance

Science.gov (United States)

DeFrancesco, Anton; McQueary, Bruce

2009-05-01

Today's enterprise networks undergo a relentless barrage of attacks from foreign and domestic adversaries. These attacks may be perpetrated with little to no funding, but may wreck incalculable damage upon the enterprises security, network infrastructure, and services. As more services come online, systems that were once in isolation now provide information that may be combined dynamically with information from other systems to create new meaning on the fly. Security issues are compounded by the potential to aggregate individual pieces of information and infer knowledge at a higher classification than any of its constituent parts. To help alleviate these challenges, in this paper we introduce the notion of semantic policy and discuss how it's use is evolving from a robust approach to access control to preempting and combating attacks in the cyber domain, The introduction of semantic policy and adversarial modeling to network security aims to ask 'where is the network most vulnerable', 'how is the network being attacked', and 'why is the network being attacked'. The first aspect of our approach is integration of semantic policy into enterprise security to augment traditional network security with an overall awareness of policy access and violations. This awareness allows the semantic policy to look at the big picture - analyzing trends and identifying critical relations in system wide data access. The second aspect of our approach is to couple adversarial modeling with semantic policy to move beyond reactive security measures and into a proactive identification of system weaknesses and areas of vulnerability. By utilizing Bayesian-based methodologies, the enterprise wide meaning of data and semantic policy is applied to probability and high-level risk identification. This risk identification will help mitigate potential harm to enterprise networks by enabling resources to proactively isolate, lock-down, and secure systems that are most vulnerable.

Managing Quality, Identity and Adversaries in Public Discourse with Machine Learning

Science.gov (United States)

Brennan, Michael

2012-01-01

Automation can mitigate issues when scaling and managing quality and identity in public discourse on the web. Discourse needs to be curated and filtered. Anonymous speech has to be supported while handling adversaries. Reliance on human curators or analysts does not scale and content can be missed. These scaling and management issues include the…

Artificial intelligence in medicine.

OpenAIRE

Ramesh, A. N.; Kambhampati, C.; Monson, J. R. T.; Drew, P. J.

2004-01-01

INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of ...

Information theory, animal communication, and the search for extraterrestrial intelligence

Science.gov (United States)

Doyle, Laurance R.; McCowan, Brenda; Johnston, Simon; Hanser, Sean F.

2011-02-01

We present ongoing research in the application of information theory to animal communication systems with the goal of developing additional detectors and estimators for possible extraterrestrial intelligent signals. Regardless of the species, for intelligence (i.e., complex knowledge) to be transmitted certain rules of information theory must still be obeyed. We demonstrate some preliminary results of applying information theory to socially complex marine mammal species (bottlenose dolphins and humpback whales) as well as arboreal squirrel monkeys, because they almost exclusively rely on vocal signals for their communications, producing signals which can be readily characterized by signal analysis. Metrics such as Zipf's Law and higher-order information-entropic structure are emerging as indicators of the communicative complexity characteristic of an "intelligent message" content within these animals' signals, perhaps not surprising given these species' social complexity. In addition to human languages, for comparison we also apply these metrics to pulsar signals—perhaps (arguably) the most "organized" of stellar systems—as an example of astrophysical systems that would have to be distinguished from an extraterrestrial intelligence message by such information theoretic filters. We also look at a message transmitted from Earth (Arecibo Observatory) that contains a lot of meaning but little information in the mathematical sense we define it here. We conclude that the study of non-human communication systems on our own planet can make a valuable contribution to the detection of extraterrestrial intelligence by providing quantitative general measures of communicative complexity. Studying the complex communication systems of other intelligent species on our own planet may also be one of the best ways to deprovincialize our thinking about extraterrestrial communication systems in general.

Intelligent Systems For Aerospace Engineering: An Overview

Science.gov (United States)

KrishnaKumar, K.

2003-01-01

Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become extremely important for advancing the current trends in information technology. Artificially intelligent systems currently utilize computers to emulate various faculties of human intelligence and biological metaphors. They use a combination of symbolic and sub-symbolic systems capable of evolving human cognitive skills and intelligence, not just systems capable of doing things humans do not do well. Intelligent systems are ideally suited for tasks such as search and optimization, pattern recognition and matching, planning, uncertainty management, control, and adaptation. In this paper, the intelligent system technologies and their application potential are highlighted via several examples.

Search for microorganisms on Europa and Mars in relation with the evolution of intelligent behavior on other worlds

International Nuclear Information System (INIS)

Chela-Flores, Julian

2001-11-01

Within the context of how to search for life in the Solar System, we discuss the need to consider universal evolutionary biomarkers, in addition to those of biochemical nature that have already been selected for in the biology experiments of the old Viking and future Beagle-2 landers. For the wider problem of the evolution of intelligent behavior on other worlds (the SETI program), the type of experiments suggested below aim at establishing a direct connection between Solar System exploration and the first steps along the pathway toward the evolution of intelligent behavior. The two leading sites for the implementation of the proposed first whole-cell experiments would be, firstly, Europa after the Europa-Orbiter mission, either on the ice-crust, or in the ocean itself by means of a submersible; secondly, such experiments could be implemented once isolated liquid water oases are identified in the Martian substratum. (author)

Automatic figure ranking and user interfacing for intelligent figure search.

Directory of Open Access Journals (Sweden)

Hong Yu

2010-10-01

Full Text Available Figures are important experimental results that are typically reported in full-text bioscience articles. Bioscience researchers need to access figures to validate research facts and to formulate or to test novel research hypotheses. On the other hand, the sheer volume of bioscience literature has made it difficult to access figures. Therefore, we are developing an intelligent figure search engine (http://figuresearch.askhermes.org. Existing research in figure search treats each figure equally, but we introduce a novel concept of "figure ranking": figures appearing in a full-text biomedical article can be ranked by their contribution to the knowledge discovery.We empirically validated the hypothesis of figure ranking with over 100 bioscience researchers, and then developed unsupervised natural language processing (NLP approaches to automatically rank figures. Evaluating on a collection of 202 full-text articles in which authors have ranked the figures based on importance, our best system achieved a weighted error rate of 0.2, which is significantly better than several other baseline systems we explored. We further explored a user interfacing application in which we built novel user interfaces (UIs incorporating figure ranking, allowing bioscience researchers to efficiently access important figures. Our evaluation results show that 92% of the bioscience researchers prefer as the top two choices the user interfaces in which the most important figures are enlarged. With our automatic figure ranking NLP system, bioscience researchers preferred the UIs in which the most important figures were predicted by our NLP system than the UIs in which the most important figures were randomly assigned. In addition, our results show that there was no statistical difference in bioscience researchers' preference in the UIs generated by automatic figure ranking and UIs by human ranking annotation.The evaluation results conclude that automatic figure ranking and user

Artificial Intelligence in Civil Engineering

Directory of Open Access Journals (Sweden)

Pengzhen Lu

2012-01-01

Full Text Available Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applications of artificial intelligence in civil engineering, including evolutionary computation, neural networks, fuzzy systems, expert system, reasoning, classification, and learning, as well as others like chaos theory, cuckoo search, firefly algorithm, knowledge-based engineering, and simulated annealing. The main research trends are also pointed out in the end. The paper provides an overview of the advances of artificial intelligence applied in civil engineering.

Evaluating late detection capability against diverse insider adversaries

International Nuclear Information System (INIS)

Sicherman, A.

1987-01-01

This paper describes a model for evaluating the late (after-the-fact) detection capability of material control and accountability (MCandA) systems against insider theft or diversion of special nuclear material. Potential insider cover-up strategies to defeat activities providing detection (e.g., inventories) are addressed by the model in a tractable manner. For each potential adversary and detection activity, two probabilities are assessed and used to fit the model. The model then computes the probability of detection for activities occurring periodically over time. The model provides insight into MCandA effectiveness and helps identify areas for safeguards improvement. 4 refs., 4 tabs

Protecting Privacy in Shared Photos via Adversarial Examples Based Stealth

Directory of Open Access Journals (Sweden)

Yujia Liu

2017-01-01

Full Text Available Online image sharing in social platforms can lead to undesired privacy disclosure. For example, some enterprises may detect these large volumes of uploaded images to do users’ in-depth preference analysis for commercial purposes. And their technology might be today’s most powerful learning model, deep neural network (DNN. To just elude these automatic DNN detectors without affecting visual quality of human eyes, we design and implement a novel Stealth algorithm, which makes the automatic detector blind to the existence of objects in an image, by crafting a kind of adversarial examples. It is just like all objects disappear after wearing an “invisible cloak” from the view of the detector. Then we evaluate the effectiveness of Stealth algorithm through our newly defined measurement, named privacy insurance. The results indicate that our scheme has considerable success rate to guarantee privacy compared with other methods, such as mosaic, blur, and noise. Better still, Stealth algorithm has the smallest impact on image visual quality. Meanwhile, we set a user adjustable parameter called cloak thickness for regulating the perturbation intensity. Furthermore, we find that the processed images have transferability property; that is, the adversarial images generated for one particular DNN will influence the others as well.

Intelligent Search Optimization using Artificial Fuzzy Logics

OpenAIRE

Manral, Jai

2015-01-01

Information on the web is prodigious; searching relevant information is difficult making web users to rely on search engines for finding relevant information on the web. Search engines index and categorize web pages according to their contents using crawlers and rank them accordingly. For given user query they retrieve millions of webpages and display them to users according to web-page rank. Every search engine has their own algorithms based on certain parameters for ranking web-pages. Searc...

Code-Based Cryptography: New Security Solutions Against a Quantum Adversary

OpenAIRE

Sendrier , Nicolas; Tillich , Jean-Pierre

2016-01-01

International audience; Cryptography is one of the key tools for providing security in our quickly evolving technological society. An adversary with the ability to use a quantum computer would defeat most of the cryptographic solutions that are deployed today to secure our communications. We do not know when quantum computing will become available, but nevertheless, the cryptographic research community must get ready for it now. Code-based cryptography is among the few cryptographic technique...

Quantum capacity under adversarial quantum noise: arbitrarily varying quantum channels

OpenAIRE

Ahlswede, Rudolf; Bjelakovic, Igor; Boche, Holger; Noetzel, Janis

2010-01-01

We investigate entanglement transmission over an unknown channel in the presence of a third party (called the adversary), which is enabled to choose the channel from a given set of memoryless but non-stationary channels without informing the legitimate sender and receiver about the particular choice that he made. This channel model is called arbitrarily varying quantum channel (AVQC). We derive a quantum version of Ahlswede's dichotomy for classical arbitrarily varying channels. This includes...

Generative adversarial network based telecom fraud detection at the receiving bank.

Science.gov (United States)

Zheng, Yu-Jun; Zhou, Xiao-Han; Sheng, Wei-Guo; Xue, Yu; Chen, Sheng-Yong

2018-06-01

Recently telecom fraud has become a serious problem especially in developing countries such as China. At present, it can be very difficult to coordinate different agencies to prevent fraud completely. In this paper we study how to detect large transfers that are sent from victims deceived by fraudsters at the receiving bank. We propose a new generative adversarial network (GAN) based model to calculate for each large transfer a probability that it is fraudulent, such that the bank can take appropriate measures to prevent potential fraudsters to take the money if the probability exceeds a threshold. The inference model uses a deep denoising autoencoder to effectively learn the complex probabilistic relationship among the input features, and employs adversarial training that establishes a minimax game between a discriminator and a generator to accurately discriminate between positive samples and negative samples in the data distribution. We show that the model outperforms a set of well-known classification methods in experiments, and its applications in two commercial banks have reduced losses of about 10 million RMB in twelve weeks and significantly improved their business reputation. Copyright © 2018 Elsevier Ltd. All rights reserved.

Translation-aware semantic segmentation via conditional least-square generative adversarial networks

Science.gov (United States)

Zhang, Mi; Hu, Xiangyun; Zhao, Like; Pang, Shiyan; Gong, Jinqi; Luo, Min

2017-10-01

Semantic segmentation has recently made rapid progress in the field of remote sensing and computer vision. However, many leading approaches cannot simultaneously translate label maps to possible source images with a limited number of training images. The core issue is insufficient adversarial information to interpret the inverse process and proper objective loss function to overcome the vanishing gradient problem. We propose the use of conditional least squares generative adversarial networks (CLS-GAN) to delineate visual objects and solve these problems. We trained the CLS-GAN network for semantic segmentation to discriminate dense prediction information either from training images or generative networks. We show that the optimal objective function of CLS-GAN is a special class of f-divergence and yields a generator that lies on the decision boundary of discriminator that reduces possible vanished gradient. We also demonstrate the effectiveness of the proposed architecture at translating images from label maps in the learning process. Experiments on a limited number of high resolution images, including close-range and remote sensing datasets, indicate that the proposed method leads to the improved semantic segmentation accuracy and can simultaneously generate high quality images from label maps.

The adversarial system and the best interests of the child in divorce ...

African Journals Online (AJOL)

In this contribution it is argued that the adversarial system of litigation does not serve the best interests of children upon divorce. After a brief analysis of the system it is concluded that other less aggressive means of litigation should be considered underupon divorce. Collaborative Law is suggested as a means to bear in ...

Computational Intelligence in a Human Brain Model

Directory of Open Access Journals (Sweden)

Viorel Gaftea

2016-06-01

Full Text Available This paper focuses on the current trends in brain research domain and the current stage of development of research for software and hardware solutions, communication capabilities between: human beings and machines, new technologies, nano-science and Internet of Things (IoT devices. The proposed model for Human Brain assumes main similitude between human intelligence and the chess game thinking process. Tactical & strategic reasoning and the need to follow the rules of the chess game, all are very similar with the activities of the human brain. The main objective for a living being and the chess game player are the same: securing a position, surviving and eliminating the adversaries. The brain resolves these goals, and more, the being movement, actions and speech are sustained by the vital five senses and equilibrium. The chess game strategy helps us understand the human brain better and easier replicate in the proposed ‘Software and Hardware’ SAH Model.

Internet-based intelligent information processing systems

CERN Document Server

Tonfoni, G; Ichalkaranje, N S

2003-01-01

The Internet/WWW has made it possible to easily access quantities of information never available before. However, both the amount of information and the variation in quality pose obstacles to the efficient use of the medium. Artificial intelligence techniques can be useful tools in this context. Intelligent systems can be applied to searching the Internet and data-mining, interpreting Internet-derived material, the human-Web interface, remote condition monitoring and many other areas. This volume presents the latest research on the interaction between intelligent systems (neural networks, adap

Extraterrestrial Intelligence: What Would it Mean?

Science.gov (United States)

Impey, Chris

2015-04-01

Results from NASA's Kepler mission imply a hundred million Earth-like habitable worlds in the Milky Way galaxy, many of which formed billions of years before the Earth. Each of these worlds is likely to have all of the ingredients needed for biology. The real estate of time and space for the evolution of intelligent life is formidable, begging the question of whether or not we are alone in the universe. The implications of making contact have been explored extensively in science fiction and the popular culture, but less frequently in the serious scientific literature. Astronomers have carried out searches for extraterrestrial intelligence for over half a century, with no success so far. In practice, it is easier to search for alien technology than to discern intelligence of unknown function and form. In this talk, the modes of technology that can currently be detected are summarized, along with the implications of a timing argument than any detected civilization is likely to be much more advanced than ours. Fermi's famous question ``Where Are They?'' is as well posed now as it was sixty years ago. The existence of extraterrestrial intelligence would have profound practical, cultural, and religious implications for humanity.

Source Anonymity in WSNs against Global Adversary Utilizing Low Transmission Rates with Delay Constraints

Directory of Open Access Journals (Sweden)

Anas Bushnag

2016-06-01

Full Text Available Wireless sensor networks (WSN are deployed for many applications such as tracking and monitoring of endangered species, military applications, etc. which require anonymity of the origin, known as Source Location Privacy (SLP. The aim in SLP is to prevent unauthorized observers from tracing the source of a real event by analyzing the traffic in the network. Previous approaches to SLP such as Fortified Anonymous Communication Protocol (FACP employ transmission of real or fake packets in every time slot, which is inefficient. To overcome this shortcoming, we developed three different techniques presented in this paper. Dummy Uniform Distribution (DUD, Dummy Adaptive Distribution (DAD and Controlled Dummy Adaptive Distribution (CAD were developed to overcome the anonymity problem against a global adversary (which has the capability of analyzing and monitoring the entire network. Most of the current techniques try to prevent the adversary from perceiving the location and time of the real event whereas our proposed techniques confuse the adversary about the existence of the real event by introducing low rate fake messages, which subsequently lead to location and time privacy. Simulation results demonstrate that the proposed techniques provide reasonable delivery ratio, delay, and overhead of a real event's packets while keeping a high level of anonymity. Three different analysis models are conducted to verify the performance of our techniques. A visualization of the simulation data is performed to confirm anonymity. Further, neural network models are developed to ensure that the introduced techniques preserve SLP. Finally, a steganography model based on probability is implemented to prove the anonymity of the techniques.

AN OPPORTUNISTIC SEARCH FOR EXTRATERRESTRIAL INTELLIGENCE (SETI) WITH THE MURCHISON WIDEFIELD ARRAY

Energy Technology Data Exchange (ETDEWEB)

Tingay, S. J.; Tremblay, C.; Walsh, A.; Urquhart, R. [International Centre for Radio Astronomy Research (ICRAR), Curtin University, Bentley, WA 6102 (Australia)

2016-08-20

A spectral line image cube generated from 115 minutes of MWA data that covers a field of view of 400 sq, deg. around the Galactic Center is used to perform the first Search for ExtraTerrestrial Intelligence (SETI) with the Murchison Widefield Array (MWA). Our work constitutes the first modern SETI experiment at low radio frequencies, here between 103 and 133 MHz, paving the way for large-scale searches with the MWA and, in the future, the low-frequency Square Kilometre Array. Limits of a few hundred mJy beam{sup −1} for narrowband emission (10 kHz) are derived from our data, across our 400 sq. deg. field of view. Within this field, 45 exoplanets in 38 planetary systems are known. We extract spectra at the locations of these systems from our image cube to place limits on the presence of narrow line emission from these systems. We then derive minimum isotropic transmitter powers for these exoplanets; a small handful of the closest objects (10 s of pc) yield our best limits of order 10{sup 14} W (Equivalent Isotropic Radiated Power). These limits lie above the highest power directional transmitters near these frequencies currently operational on Earth. A SETI experiment with the MWA covering the full accessible sky and its full frequency range would require approximately one month of observing time. The MWA frequency range, its southern hemisphere location on an extraordinarily radio quiet site, its very large field of view, and its high sensitivity make it a unique facility for SETI.

Identifying quantum phase transitions with adversarial neural networks

Science.gov (United States)

Huembeli, Patrick; Dauphin, Alexandre; Wittek, Peter

2018-04-01

The identification of phases of matter is a challenging task, especially in quantum mechanics, where the complexity of the ground state appears to grow exponentially with the size of the system. Traditionally, physicists have to identify the relevant order parameters for the classification of the different phases. We here follow a radically different approach: we address this problem with a state-of-the-art deep learning technique, adversarial domain adaptation. We derive the phase diagram of the whole parameter space starting from a fixed and known subspace using unsupervised learning. This method has the advantage that the input of the algorithm can be directly the ground state without any ad hoc feature engineering. Furthermore, the dimension of the parameter space is unrestricted. More specifically, the input data set contains both labeled and unlabeled data instances. The first kind is a system that admits an accurate analytical or numerical solution, and one can recover its phase diagram. The second type is the physical system with an unknown phase diagram. Adversarial domain adaptation uses both types of data to create invariant feature extracting layers in a deep learning architecture. Once these layers are trained, we can attach an unsupervised learner to the network to find phase transitions. We show the success of this technique by applying it on several paradigmatic models: the Ising model with different temperatures, the Bose-Hubbard model, and the Su-Schrieffer-Heeger model with disorder. The method finds unknown transitions successfully and predicts transition points in close agreement with standard methods. This study opens the door to the classification of physical systems where the phase boundaries are complex such as the many-body localization problem or the Bose glass phase.

TRANSITION FROM ADVERSARIAL TO COOPERATIVE STRATEGIC INTERACTION; FINAL

International Nuclear Information System (INIS)

G.H. CANAVAN

2001-01-01

This note extends the game theoretic analysis of strategic conflicts begun in earlier Seminars on Planetary Emergencies to interactions with and without defenses between two or more adversaries with more realistic target structures. It reviews the essentials of game theory as applied to the analysis of strategic decisions, the application of first and second strike costs as payoffs, and solution optimization, which resolves several inconsistencies seen with earlier metrics. The stability of the current bilateral offensive configuration is shown to be high and insensitive to deep reductions in offensive forces, the deployment of limited defenses, and the exchange of significant offensive forces for defenses. The transition from adversarial to cooperative interaction is represented by the progressive reduction of the parameters representing each side's preference for damaging or deterring the other, which monotonically improves stability. Estimates of strike incentives in bilateral and trilateral configurations are reduced by the inclusion of high value targets in both sides' force allocations, which dominates the details of offensive and defensive forces. The shift to high value targets stabilizes trilateral offensive configurations, a result that differs with that from analyses based on military costs only. When defenses are included, they lead to a balance between a large defended side and small undefended side that resembles the balance between two large sides. Including the large side's preference for defense of high value targets in the analyses reduces its strike incentives and thus the small side's incentive to preempt. However, it also removes the large sides' ability to deter, so the stability of multi-polar configurations continues to be controlled by the least stable dyad, which places constraints on the size of defenses that can be deployed stably that could be more stringent than those from the bilateral balance

iPixel: a visual content-based and semantic search engine for retrieving digitized mammograms by using collective intelligence.

Science.gov (United States)

Alor-Hernández, Giner; Pérez-Gallardo, Yuliana; Posada-Gómez, Rubén; Cortes-Robles, Guillermo; Rodríguez-González, Alejandro; Aguilar-Laserre, Alberto A

2012-09-01

Nowadays, traditional search engines such as Google, Yahoo and Bing facilitate the retrieval of information in the format of images, but the results are not always useful for the users. This is mainly due to two problems: (1) the semantic keywords are not taken into consideration and (2) it is not always possible to establish a query using the image features. This issue has been covered in different domains in order to develop content-based image retrieval (CBIR) systems. The expert community has focussed their attention on the healthcare domain, where a lot of visual information for medical analysis is available. This paper provides a solution called iPixel Visual Search Engine, which involves semantics and content issues in order to search for digitized mammograms. iPixel offers the possibility of retrieving mammogram features using collective intelligence and implementing a CBIR algorithm. Our proposal compares not only features with similar semantic meaning, but also visual features. In this sense, the comparisons are made in different ways: by the number of regions per image, by maximum and minimum size of regions per image and by average intensity level of each region. iPixel Visual Search Engine supports the medical community in differential diagnoses related to the diseases of the breast. The iPixel Visual Search Engine has been validated by experts in the healthcare domain, such as radiologists, in addition to experts in digital image analysis.

Show, Adapt and Tell: Adversarial Training of Cross-domain Image Captioner

OpenAIRE

Chen, Tseng-Hung; Liao, Yuan-Hong; Chuang, Ching-Yao; Hsu, Wan-Ting; Fu, Jianlong; Sun, Min

2017-01-01

Impressive image captioning results are achieved in domains with plenty of training image and sentence pairs (e.g., MSCOCO). However, transferring to a target domain with significant domain shifts but no paired training data (referred to as cross-domain image captioning) remains largely unexplored. We propose a novel adversarial training procedure to leverage unpaired data in the target domain. Two critic networks are introduced to guide the captioner, namely domain critic and multi-modal cri...

The Foreign Intelligence Surveillance Act: An Overview of the Statutory Framework and U.S. Foreign Intelligence Surveillance Court and U.S. Foreign Intelligence Surveillance Court of Review Decisions

National Research Council Canada - National Science Library

Bazan, Elizabeth B

2007-01-01

.... Subsequent legislation expanded federal laws dealing with foreign intelligence gathering to address physical searches, pen registers and trap and trace devices, and access to certain business records...

The Breakthrough Listen Search for Intelligent Life: 1.1-1.9 GHz Observations of 692 Nearby Stars

Science.gov (United States)

Enriquez, J. Emilio; Siemion, Andrew; Foster, Griffin; Gajjar, Vishal; Hellbourg, Greg; Hickish, Jack; Isaacson, Howard; Price, Danny C.; Croft, Steve; DeBoer, David; Lebofsky, Matt; MacMahon, David H. E.; Werthimer, Dan

2017-11-01

We report on a search for engineered signals from a sample of 692 nearby stars using the Robert C. Byrd Green Bank Telescope, undertaken as part of the Breakthrough Listen Initiative search for extraterrestrial intelligence. Observations were made over 1.1-1.9 GHz (L band), with three sets of five-minute observations of the 692 primary targets, interspersed with five-minute observations of secondary targets. By comparing the “ON” and “OFF” observations, we are able to identify terrestrial interference and place limits on the presence of engineered signals from putative extraterrestrial civilizations inhabiting the environs of the target stars. During the analysis, 11 events passed our thresholding algorithm, but a detailed analysis of their properties indicates that they are consistent with known examples of anthropogenic radio-frequency interference. We conclude that, at the time of our observations, none of the observed systems host high-duty-cycle radio transmitters emitting between 1.1 and 1.9 GHz with an Equivalent Isotropic Radiated Power of ˜1013 W, which is readily achievable by our own civilization. Our results suggest that fewer than ˜0.1% of the stellar systems within 50 pc possess the type of transmitters searched in this survey.

The Adversarial Principle in Prima Facie Judgments of the Legal Thesis Firmed in the Trial of Repetitive Cases

Directory of Open Access Journals (Sweden)

Juliana Provedel Cardoso

2016-10-01

Full Text Available The present articles objective is to analyse the highly effective adversarial principle from the Constitutional Democratic State of Law and the cooperative process structure. In this sense, an analysis of the repetitive cases model is made with special relevance to the Civil Procedure Codice 2015, put in evidence the preliminary injunction, the repetitive appeals and the resolution incident repetitive demands. With the establishment of the premises, an analysis of the adversarial principle is made on prima facie judgments of the legal thesis firmed in the trial of repetitive cases, in view of the motivation of the court decision (speech of the case and law (speech of the precedents.

When does familiarity promote versus undermine interpersonal attraction? A proposed integrative model from erstwhile adversaries

NARCIS (Netherlands)

Frost, J.H.; Finkel, E.J.; Norton, M.I.; Ariely, D.; Caprariello, P.A.; Eastwick, P.W.

2015-01-01

This article began as an adversarial collaboration between two groups of researchers with competing views on a longstanding question: Does familiarity promote or undermine interpersonal attraction? As we explored our respective positions, it became clear that the limitations of our

Applications of artificial intelligence 1993: Knowledge-based systems in aerospace and industry; Proceedings of the Meeting, Orlando, FL, Apr. 13-15, 1993

Science.gov (United States)

Fayyad, Usama M. (Editor); Uthurusamy, Ramasamy (Editor)

1993-01-01

The present volume on applications of artificial intelligence with regard to knowledge-based systems in aerospace and industry discusses machine learning and clustering, expert systems and optimization techniques, monitoring and diagnosis, and automated design and expert systems. Attention is given to the integration of AI reasoning systems and hardware description languages, care-based reasoning, knowledge, retrieval, and training systems, and scheduling and planning. Topics addressed include the preprocessing of remotely sensed data for efficient analysis and classification, autonomous agents as air combat simulation adversaries, intelligent data presentation for real-time spacecraft monitoring, and an integrated reasoner for diagnosis in satellite control. Also discussed are a knowledge-based system for the design of heat exchangers, reuse of design information for model-based diagnosis, automatic compilation of expert systems, and a case-based approach to handling aircraft malfunctions.

Polyphase-discrete Fourier transform spectrum analysis for the Search for Extraterrestrial Intelligence sky survey

Science.gov (United States)

Zimmerman, G. A.; Gulkis, S.

1991-01-01

The sensitivity of a matched filter-detection system to a finite-duration continuous wave (CW) tone is compared with the sensitivities of a windowed discrete Fourier transform (DFT) system and an ideal bandpass filter-bank system. These comparisons are made in the context of the NASA Search for Extraterrestrial Intelligence (SETI) microwave observing project (MOP) sky survey. A review of the theory of polyphase-DFT filter banks and its relationship to the well-known windowed-DFT process is presented. The polyphase-DFT system approximates the ideal bandpass filter bank by using as few as eight filter taps per polyphase branch. An improvement in sensitivity of approx. 3 dB over a windowed-DFT system can be obtained by using the polyphase-DFT approach. Sidelobe rejection of the polyphase-DFT system is vastly superior to the windowed-DFT system, thereby improving its performance in the presence of radio frequency interference (RFI).

Data Driven Exploratory Attacks on Black Box Classifiers in Adversarial Domains

OpenAIRE

Sethi, Tegjyot Singh; Kantardzic, Mehmed

2017-01-01

While modern day web applications aim to create impact at the civilization level, they have become vulnerable to adversarial activity, where the next cyber-attack can take any shape and can originate from anywhere. The increasing scale and sophistication of attacks, has prompted the need for a data driven solution, with machine learning forming the core of many cybersecurity systems. Machine learning was not designed with security in mind, and the essential assumption of stationarity, requiri...

Emotional intelligence as a crucial component to medical education.

Science.gov (United States)

Johnson, Debbi R

2015-12-06

The primary focus of this review was to discover what is already known about Emotional Intelligence (EI) and the role it plays within social relationships, as well as its importance in the fields of health care and health care education. This article analyzes the importance of EI in the field of health care and recommends various ways that this important skill can be built into medical programs. Information was gathered using various database searches including EBSCOHOST, Academic Search Premier and ERIC. The search was conducted in English language journals from the last ten years. Descriptors include: Emotional Intelligence, medical students and communication skills, graduate medical education, Emotional Intelligence and graduate medical education, Emotional Intelligence training programs, program evaluation and development. Results of the study show a direct correlation between medical education and emotional intelligence competencies, which makes the field of medical education an ideal one in which to integrate further EI training. The definition of EI as an ability-based skill allows for training in specific competencies that can be directly applied to a specialized field. When EI is conceptualized as an ability that can be taught, learned, and changed, it may be used to address the specific aspects of the clinician-patient relationship that are not working well. For this reason, teaching EI should be a priority in the field of medical education in order to better facilitate this relationship in the future.

Intelligence-Augmented Rat Cyborgs in Maze Solving.

Directory of Open Access Journals (Sweden)

Yipeng Yu

Full Text Available Cyborg intelligence is an emerging kind of intelligence paradigm. It aims to deeply integrate machine intelligence with biological intelligence by connecting machines and living beings via neural interfaces, enhancing strength by combining the biological cognition capability with the machine computational capability. Cyborg intelligence is considered to be a new way to augment living beings with machine intelligence. In this paper, we build rat cyborgs to demonstrate how they can expedite the maze escape task with integration of machine intelligence. We compare the performance of maze solving by computer, by individual rats, and by computer-aided rats (i.e. rat cyborgs. They were asked to find their way from a constant entrance to a constant exit in fourteen diverse mazes. Performance of maze solving was measured by steps, coverage rates, and time spent. The experimental results with six rats and their intelligence-augmented rat cyborgs show that rat cyborgs have the best performance in escaping from mazes. These results provide a proof-of-principle demonstration for cyborg intelligence. In addition, our novel cyborg intelligent system (rat cyborg has great potential in various applications, such as search and rescue in complex terrains.

Intelligence-Augmented Rat Cyborgs in Maze Solving.

Science.gov (United States)

Yu, Yipeng; Pan, Gang; Gong, Yongyue; Xu, Kedi; Zheng, Nenggan; Hua, Weidong; Zheng, Xiaoxiang; Wu, Zhaohui

2016-01-01

Cyborg intelligence is an emerging kind of intelligence paradigm. It aims to deeply integrate machine intelligence with biological intelligence by connecting machines and living beings via neural interfaces, enhancing strength by combining the biological cognition capability with the machine computational capability. Cyborg intelligence is considered to be a new way to augment living beings with machine intelligence. In this paper, we build rat cyborgs to demonstrate how they can expedite the maze escape task with integration of machine intelligence. We compare the performance of maze solving by computer, by individual rats, and by computer-aided rats (i.e. rat cyborgs). They were asked to find their way from a constant entrance to a constant exit in fourteen diverse mazes. Performance of maze solving was measured by steps, coverage rates, and time spent. The experimental results with six rats and their intelligence-augmented rat cyborgs show that rat cyborgs have the best performance in escaping from mazes. These results provide a proof-of-principle demonstration for cyborg intelligence. In addition, our novel cyborg intelligent system (rat cyborg) has great potential in various applications, such as search and rescue in complex terrains.

Are the advocates of nuclear power and the adversaries listening to each other? Does Dialogue have a chance? Introductory remarks by John A. Macpherson

International Nuclear Information System (INIS)

Macpherson, John A.

1989-01-01

Are the advocates of nuclear power and the adversaries listening to each other? Does dialogue have a chance? My short answer to both questions posed as the title for this discussion is 'no'. And I would add: There is no point in trying to bring opposite poles together, it requires too much investment for too little return. A nuclear dialogue will have a chance only it a distinction can be shown between physics and metaphysics, between chemistry and alchemy, and if the gap can be bridged between the polarized views of the world's societal needs which, incidentally, create the nuclear issue in the first place. This is a daunting task Movements in search of a cause have a passion for preaching rather than a love for listening

Intelligent Search on XML Data

NARCIS (Netherlands)

Blanken, Henk; Grabs, T.; Schek, H-J.; Schenkel, R.; Weikum, G.; Unknown, [Unknown

2003-01-01

Recently, we have seen a steep increase in the popularity and adoption of XML, in areas such as traditional databases, e-business, the scientific environment, and on the web. Querying XML documents and data efficiently is a challenging issue; this book approaches search on XML data by combining

Saliency detection by conditional generative adversarial network

Science.gov (United States)

Cai, Xiaoxu; Yu, Hui

2018-04-01

Detecting salient objects in images has been a fundamental problem in computer vision. In recent years, deep learning has shown its impressive performance in dealing with many kinds of vision tasks. In this paper, we propose a new method to detect salient objects by using Conditional Generative Adversarial Network (GAN). This type of network not only learns the mapping from RGB images to salient regions, but also learns a loss function for training the mapping. To the best of our knowledge, this is the first time that Conditional GAN has been used in salient object detection. We evaluate our saliency detection method on 2 large publicly available datasets with pixel accurate annotations. The experimental results have shown the significant and consistent improvements over the state-of-the-art method on a challenging dataset, and the testing speed is much faster.

Heuristic Search Theory and Applications

CERN Document Server

Edelkamp, Stefan

2011-01-01

Search has been vital to artificial intelligence from the very beginning as a core technique in problem solving. The authors present a thorough overview of heuristic search with a balance of discussion between theoretical analysis and efficient implementation and application to real-world problems. Current developments in search such as pattern databases and search with efficient use of external memory and parallel processing units on main boards and graphics cards are detailed. Heuristic search as a problem solving tool is demonstrated in applications for puzzle solving, game playing, constra

Application of adversarial risk analysis model in pricing strategies with remanufacturing

Directory of Open Access Journals (Sweden)

Liurui Deng

2015-01-01

Full Text Available Purpose: Purpose: This paper mainly focus on the application of adversarial risk analysis (ARA in pricing strategy with remanufacturing. We hope to obtain more realistic results than classical model. Moreover, we also wish that our research improve the development of ARA in pricing strategy of manufacturing or remanufacturing. Approach: In order to gain more actual research, combining adversarial risk analysis, we explore the pricing strategy with remanufacturing based on Stackelberg model. Especially, we build OEM’s 1-order ARA model and further study on manufacturers and remanufacturers’ pricing strategy. Findings: We find the OEM’s 1-order ARA model for the OEM’s product cost C. Besides, we get according manufacturers and remanufacturers’ pricing strategies. Besides, the pricing strategies based on 1-order ARA model have advantage over than the classical model regardless of OEMs and remanufacturers. Research implications: The research on application of ARA imply that we can get more actual results with this kind of modern risk analysis method and ARA can be extensively in pricing strategies of supply chain. Value: Our research improves the application of ARA in remanufacturing industry. Meanwhile, inspired by this analysis, we can also create different ARA models for different parameters. Furthermore, some results and analysis methods can be applied to other pricing strategies of supply chain.

Artificial intelligence techniques in Prolog

CERN Document Server

Shoham, Yoav

1993-01-01

Artificial Intelligence Techniques in Prolog introduces the reader to the use of well-established algorithmic techniques in the field of artificial intelligence (AI), with Prolog as the implementation language. The techniques considered cover general areas such as search, rule-based systems, and truth maintenance, as well as constraint satisfaction and uncertainty management. Specific application domains such as temporal reasoning, machine learning, and natural language are also discussed.Comprised of 10 chapters, this book begins with an overview of Prolog, paying particular attention to Prol

The Nigerian health care system: Need for integrating adequate medical intelligence and surveillance systems

Directory of Open Access Journals (Sweden)

Menizibeya Osain Welcome

2011-01-01

Full Text Available Objectives : As an important element of national security, public health not only functions to provide adequate and timely medical care but also track, monitor, and control disease outbreak. The Nigerian health care had suffered several infectious disease outbreaks year after year. Hence, there is need to tackle the problem. This study aims to review the state of the Nigerian health care system and to provide possible recommendations to the worsening state of health care in the country. To give up-to-date recommendations for the Nigerian health care system, this study also aims at reviewing the dynamics of health care in the United States, Britain, and Europe with regards to methods of medical intelligence/surveillance. Materials and Methods : Databases were searched for relevant literatures using the following keywords: Nigerian health care, Nigerian health care system, and Nigerian primary health care system. Additional keywords used in the search were as follows: United States (OR Europe health care dynamics, Medical Intelligence, Medical Intelligence systems, Public health surveillance systems, Nigerian medical intelligence, Nigerian surveillance systems, and Nigerian health information system. Literatures were searched in scientific databases Pubmed and African Journals OnLine. Internet searches were based on Google and Search Nigeria. Results : Medical intelligence and surveillance represent a very useful component in the health care system and control diseases outbreak, bioattack, etc. There is increasing role of automated-based medical intelligence and surveillance systems, in addition to the traditional manual pattern of document retrieval in advanced medical setting such as those in western and European countries. Conclusion : The Nigerian health care system is poorly developed. No adequate and functional surveillance systems are developed. To achieve success in health care in this modern era, a system well grounded in routine

The Adversarial Principle and the5º Paragraph of the Article 307 of the TCE-ES Res. 261/2013

Directory of Open Access Journals (Sweden)

Rafael Ambrósio Gava

2015-12-01

Full Text Available This paper aims to analyze the implications of the adversarial principle in the administrative process that are judged by the TCE-ES under summary rite. More specifically, we examine if it is possible to judge the process merit without the accused's subpoena. Throughout the study, the characteristics of the Courts of Accounts are explained, according to the doctrine and jurisprudence, as well their prerogative of precautionary action, recognized by the theory of implied powers. In addition, the systematic of the summary procedure, by which develop the processes in which there are precautionary action, is studied, from the specific legislation. At last, the summary procedure is analyzed, specifically with respect to the art. 307, §5º, Res. TCE-ES 261/2013, from the perspective of the adversarial principle, understood, based on the doctrine teaching and according to the New Code of Civil Procedure, as the right of knowledge and of influence the debate. We demonstrated, based on literature and through a deductive argumentative reasoning, that the TEC -ES cannot do disregard the adversarial principle, otherwise there would be violation of this fundamental right.

Database in Artificial Intelligence.

Science.gov (United States)

Wilkinson, Julia

1986-01-01

Describes a specialist bibliographic database of literature in the field of artificial intelligence created by the Turing Institute (Glasgow, Scotland) using the BRS/Search information retrieval software. The subscription method for end-users--i.e., annual fee entitles user to unlimited access to database, document provision, and printed awareness…

Translating agency reform through durable rhetorical styles: comparing official agency talk across consensus and adversarial contexts

NARCIS (Netherlands)

Smullen, A.

2010-01-01

This article directs attention to the role of ideational variables in shaping public management reform initiatives. It considers the contribution of both endogenous rhetorical styles and exogenous international fashions in explaining official agency talk in consensus and adversarial contexts.

SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation.

Science.gov (United States)

Xue, Yuan; Xu, Tao; Zhang, Han; Long, L Rodney; Huang, Xiaolei

2018-05-03

Inspired by classic Generative Adversarial Networks (GANs), we propose a novel end-to-end adversarial neural network, called SegAN, for the task of medical image segmentation. Since image segmentation requires dense, pixel-level labeling, the single scalar real/fake output of a classic GAN's discriminator may be ineffective in producing stable and sufficient gradient feedback to the networks. Instead, we use a fully convolutional neural network as the segmentor to generate segmentation label maps, and propose a novel adversarial critic network with a multi-scale L 1 loss function to force the critic and segmentor to learn both global and local features that capture long- and short-range spatial relationships between pixels. In our SegAN framework, the segmentor and critic networks are trained in an alternating fashion in a min-max game: The critic is trained by maximizing a multi-scale loss function, while the segmentor is trained with only gradients passed along by the critic, with the aim to minimize the multi-scale loss function. We show that such a SegAN framework is more effective and stable for the segmentation task, and it leads to better performance than the state-of-the-art U-net segmentation method. We tested our SegAN method using datasets from the MICCAI BRATS brain tumor segmentation challenge. Extensive experimental results demonstrate the effectiveness of the proposed SegAN with multi-scale loss: on BRATS 2013 SegAN gives performance comparable to the state-of-the-art for whole tumor and tumor core segmentation while achieves better precision and sensitivity for Gd-enhance tumor core segmentation; on BRATS 2015 SegAN achieves better performance than the state-of-the-art in both dice score and precision.

Synthetic aperture radar ship discrimination, generation and latent variable extraction using information maximizing generative adversarial networks

CSIR Research Space (South Africa)

Schwegmann, Colin P

2017-07-01

Full Text Available such as Synthetic Aperture Radar imagery. To aid in the creation of improved machine learning-based ship detection and discrimination methods this paper applies a type of neural network known as an Information Maximizing Generative Adversarial Network. Generative...

A Graphical Adversarial Risk Analysis Model for Oil and Gas Drilling Cybersecurity

OpenAIRE

Vieira, Aitor Couce; Houmb, Siv Hilde; Insua, David Rios

2014-01-01

Oil and gas drilling is based, increasingly, on operational technology, whose cybersecurity is complicated by several challenges. We propose a graphical model for cybersecurity risk assessment based on Adversarial Risk Analysis to face those challenges. We also provide an example of the model in the context of an offshore drilling rig. The proposed model provides a more formal and comprehensive analysis of risks, still using the standard business language based on decisions, risks, and value.

Competitive Intelligence on the Internet-Going for the Gold.

Science.gov (United States)

Kassler, Helene

2000-01-01

Discussion of competitive intelligence (CI) focuses on recent Web sties and several search techniques that provide valuable CI information. Highlights include links that display business relationships; information from vendors; general business sites; search engine strategies; local business newspapers; job postings; patent and trademark…

Searching for South Asian intelligence: psychometry in British India, 1919-1940.

Science.gov (United States)

Setlur, Shivrang

2014-01-01

This paper describes the introduction and development of intelligence testing in British India. Between 1919 and 1940 experimenters such as C. Herbert Rice, Prasanta Chandra Mahalanobis, and Venkatrao Vithal Kamat imported a number of intelligence tests, adapting them to suit a variety of South Asian languages and contexts. Charting South Asian psychometry's gradual move from American missionary efforts toward the state, this paper argues that political reforms in the 1920s and 1930s affected how psychometry was "indigenized" in South Asia. Describing how approaches to race and caste shifted across instruments and over time, this paper charts the gradual recession, within South Asian psychometry, of a "race" theory of caste. Describing some of the ways in which this "late colonial" period affected the postcolonial landscape, the paper concludes by suggesting potential lines for further inquiry into the later career of intelligence testing in India and Pakistan. © 2014 Wiley Periodicals, Inc.

SEAPATH: A microcomputer code for evaluating physical security effectiveness using adversary sequence diagrams

International Nuclear Information System (INIS)

Darby, J.L.

1986-01-01

The Adversary Sequence Diagram (ASD) concept was developed by Sandia National Laboratories (SNL) to examine physical security system effectiveness. Sandia also developed a mainframe computer code, PANL, to analyze the ASD. The authors have developed a microcomputer code, SEAPATH, which also analyzes ASD's. The Authors are supporting SNL in software development of the SAVI code; SAVI utilizes the SEAPATH algorithm to identify and quantify paths

Creativity Styles and Emotional Intelligence of Filipino Student Teachers: A Search for Congruity

Directory of Open Access Journals (Sweden)

Gilbert C. Magulod Jr.

2017-02-01

Full Text Available The purpose of this study is to determine the congruity between the creativity styles and emotional intelligence of Filipino student teachers. Descriptive correlational research design was employed. The participants of the study were the 76 fourth year students of Bachelor in Elementary Education (BEED and Bachelor in Secondary Education (BSED in one state university in the Philippines. Data of the study were obtained using two standardized instruments relating to creativity styles and emotional intelligence. Findings of the study revealed that the student teachers espoused themselves to have high creative capacity while they assessed themselves to have high creativity styles along belief in unconscious processes, use of techniques, use of other people and final product orientation. With regards to their emotional intelligence, they assessed themselves to have high attributes on self-awareness, management of emotions, self-motivation, empathy and social skills. Significantly, this study also revealed that gender, birth order, course and scholastic standing in high school spelled differences on the creativity styles of Filipino student teachers. Moreover, test of difference also showed that scholastic standing in high school and family income defined differences along emotional intelligence. Finally, it was also revealed in the study that there is a significant relationship between creativity styles and emotional intelligence of Filipino student teachers. Implications of the congruity between emotional intelligence and creativity styles would help Teacher Education Institutions (TEIs to implement curriculum enhancement which is vital to the preparation of twenty-first century teachers.

Intelligent Chatter Bot for Regulation Search

Science.gov (United States)

De Luise, María Daniela López; Pascal, Andrés; Saad, Ben; Álvarez, Claudia; Pescio, Pablo; Carrilero, Patricio; Malgor, Rafael; Díaz, Joaquín

2016-01-01

This communication presents a functional prototype, named PTAH, implementing a linguistic model focused on regulations in Spanish. Its global architecture, the reasoning model and short statistics are provided for the prototype. It is mainly a conversational robot linked to an Expert System by a module with many intelligent linguistic filters, implementing the reasoning model of an expert. It is focused on bylaws, regulations, jurisprudence and customized background representing entity mission, vision and profile. This Structure and model are generic enough to self-adapt to any regulatory environment, but as a first step, it was limited to an academic field. This way it is possible to limit the slang and data numbers. The foundations of the linguistic model are also outlined and the way the architecture implements the key features of the behavior.

With God on our side: Religious primes reduce the envisioned physical formidability of a menacing adversary.

Science.gov (United States)

Holbrook, Colin; Fessler, Daniel M T; Pollack, Jeremy

2016-01-01

The imagined support of benevolent supernatural agents attenuates anxiety and risk perception. Here, we extend these findings to judgments of the threat posed by a potentially violent adversary. Conceptual representations of bodily size and strength summarize factors that determine the relative threat posed by foes. The proximity of allies moderates the envisioned physical formidability of adversaries, suggesting that cues of access to supernatural allies will reduce the envisioned physical formidability of a threatening target. Across two studies, subtle cues of both supernatural and earthly social support reduced the envisioned physical formidability of a violent criminal. These manipulations had no effect on the perceived likelihood of encountering non-conflictual physical danger, raising the possibility that imagined supernatural support leads participants to view themselves not as shielded from encountering perilous situations, but as protected should perils arise. Copyright © 2015 Elsevier B.V. All rights reserved.

Ambient intelligence : visualising the future

NARCIS (Netherlands)

Aarts, E.H.L.

2005-01-01

Ambient Intelligence systems are aimed at making user-system interaction and content consumption a truly positive experience. The endless search for nifty information visualisation mechanism to squeeze yet one more piece of information onto a visual display is surpassed by the challenge to embed

A Survey of Intelligent Car Parking System

OpenAIRE

Faheem; S.A. Mahmud; G.M. Khan; M. Rahman; H. Zafar

2013-01-01

The industrialization of the world, increase in population, slow paced city development and mismanagement of the available parking space has resulted in parking related problems. There is a dire need for a secure, intelligent, efficient and reliable system which can be used for searching the unoccupied parking facility, guidance towards the parking facility, negotiation of the parking fee, along with the proper management of the parking facility. Intelligent Parking Service is a part of Intel...

A Graphical Adversarial Risk Analysis Model for Oil and Gas Drilling Cybersecurity

Directory of Open Access Journals (Sweden)

Aitor Couce Vieira

2014-04-01

Full Text Available Oil and gas drilling is based, increasingly, on operational technology, whose cybersecurity is complicated by several challenges. We propose a graphical model for cybersecurity risk assessment based on Adversarial Risk Analysis to face those challenges. We also provide an example of the model in the context of an offshore drilling rig. The proposed model provides a more formal and comprehensive analysis of risks, still using the standard business language based on decisions, risks, and value.

Intelligent interaction based on holographic personalized portal

Directory of Open Access Journals (Sweden)

Yadong Huang

2017-06-01

Full Text Available Purpose – The purpose of this paper is to study the architecture of holographic personalized portal, user modeling, commodity modeling and intelligent interaction. Design/methodology/approach – In this paper, the authors propose crowd-science industrial ecological system based on holographic personalized portal and its interaction. The holographic personality portal is based on holographic enterprises, commodities and consumers, and the personalized portal consists of accurate ontology, reliable supply, intelligent demand and smart cyberspace. Findings – The personalized portal can realize the information acquisition, characteristic analysis and holographic presentation. Then, the intelligent interaction, e.g. demand decomposition, personalized search, personalized presentation and demand prediction, will be implemented within the personalized portal. Originality/value – The authors believe that their work on intelligent interaction based on holographic personalized portal, which has been first proposed in this paper, is innovation focusing on the interaction between intelligence and convenience.

Intelligent environmental data warehouse

International Nuclear Information System (INIS)

Ekechukwu, B.

1998-01-01

Making quick and effective decisions in environment management are based on multiple and complex parameters, a data warehouse is a powerful tool for the over all management of massive environmental information. Selecting the right data from a warehouse is an important factor consideration for end-users. This paper proposed an intelligent environmental data warehouse system. It consists of data warehouse to feed an environmental researchers and managers with desire environmental information needs to their research studies and decision in form of geometric and attribute data for study area, and a metadata for the other sources of environmental information. In addition, the proposed intelligent search engine works according to a set of rule, which enables the system to be aware of the environmental data wanted by the end-user. The system development process passes through four stages. These are data preparation, warehouse development, intelligent engine development and internet platform system development. (author)

The Breakthrough Listen Search for Intelligent Life: the first SETI results and other future science.

Science.gov (United States)

Enriquez, J. Emilio; Breakthrough Listen Team

2018-01-01

The Breakthrough Listen (BL) Initiative is the largest campaign in human history on the search for extraterrestrial intelligence. The work presented here is the first BL search for engineered signals. This comprises a sample of 692 nearby stars within 50 pc. We used the Green Bank Telescope (GBT) to conduct observations over 1.1-1.9 GHz (L-band). Our observing strategy allows us to reject most of the detected signals as terrestrial interference. During the analysis, eleven stars show events that passed our thresholding algorithm, but detailed analysis of their properties indicates they are consistent with known examples of anthropogenic radio frequency interference. This small number of false positives and their understood properties give confidence on the techniques used for this search. We conclude that, at the time of our observations none of the observed systems host high-duty-cycle radio transmitters emitting at the observed frequencies with an EIRP of 10^13 W, readily achievable by our own civilization.We can place limits on the presence of engineered signals from putative extraterrestrial civilizations inhabiting the environs of the target stars. Our results suggest that fewer than ~0.1% of the stellar systems within 50 pc possess the type of transmitters searched in this survey. This work provides the most stringent limit on the number of low power radio transmitters around nearby stars to date. We explored several metics to compare our results to previous SETI efforts. We developed a new figure-of-merit that can encompass a wider set of parameters and can be used on future SETI experiments for a meaningful comparison.We note that the current BL state-of-the-art digital backend installed at the Green Bank Observatory is the fastest ever used for a SETI experiment by a factor of a few. Here we will describe the potential use of the BL backend by other groups on complementary science, as well as a mention the ongoing and potential collaborations focused in

Basic study on intelligent materialization of glass; Glass no intelligent ko zairyoka ni kansuru kenkyu

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-10-31

This is the report No. 98 issued by the Inorganic Material Research Institute. An intelligent material is a substance and/or material which responds intelligently to environmental conditions and exhibits functions. One of the features of amorphous materials including amorphous glass is a large freedom in chemical composition. These materials maintain order in short distance, but have as a whole the turbulent and specific atom orientation. Therefore, high tolerability in selecting the composition, and diverse synthesizing methods are available. A wide range of utilization may be conceived, such as introduction of the state of electrons having different valences in a structure, and the diverse chemical combinations. Patterns of existence of polyhedrons having different orientations, and how they are connected correlate closely with an external environment. Intelligent materials have high freedom against change in the external environment and are suitable to exhibit intelligent functions. Setting heat and light as the external conditions, attempts have been made on search and creation of intelligent materials based on state change induced by interactions between the two factors. Fundamental studies have been made on synthesis of different environment responding glasses and films, and on factors and phenomena for exhibition of the intelligence. 62 refs., 91 figs., 8 tabs.

Intelligent Robot-assisted Humanitarian Search and Rescue System

Directory of Open Access Journals (Sweden)

Henry Y. K. Lau

2009-11-01

Full Text Available The unprecedented scale and number of natural and man-made disasters in the past decade has urged international emergency search and rescue communities to seek for novel technology to enhance operation efficiency. Tele-operated search and rescue robots that can navigate deep into rubble to search for victims and to transfer critical field data back to the control console has gained much interest among emergency response institutions. In response to this need, a low-cost autonomous mini robot equipped with thermal sensor, accelerometer, sonar, pin-hole camera, microphone, ultra-bright LED and wireless communication module is developed to study the control of a group of decentralized mini search and rescue robots. The robot can navigate autonomously between voids to look for living body heat and can send back audio and video information to allow the operator to determine if the found object is a living human. This paper introduces the design and control of a low-cost robotic search and rescue system based on an immuno control framework developed for controlling decentralized systems. Design and development of the physical prototype and the immunity-based control system are described in this paper.

Intelligent Robot-Assisted Humanitarian Search and Rescue System

Directory of Open Access Journals (Sweden)

Albert W. Y. Ko

2009-06-01

Full Text Available The unprecedented scale and number of natural and man-made disasters in the past decade has urged international emergency search and rescue communities to seek for novel technology to enhance operation efficiency. Tele-operated search and rescue robots that can navigate deep into rubble to search for victims and to transfer critical field data back to the control console has gained much interest among emergency response institutions. In response to this need, a low-cost autonomous mini robot equipped with thermal sensor, accelerometer, sonar, pin-hole camera, microphone, ultra-bright LED and wireless communication module is developed to study the control of a group of decentralized mini search and rescue robots. The robot can navigate autonomously between voids to look for living body heat and can send back audio and video information to allow the operator to determine if the found object is a living human. This paper introduces the design and control of a low-cost robotic search and rescue system based on an immuno control framework developed for controlling decentralized systems. Design and development of the physical prototype and the immunity-based control system are described in this paper.

Search techniques in intelligent classification systems

CERN Document Server

Savchenko, Andrey V

2016-01-01

A unified methodology for categorizing various complex objects is presented in this book. Through probability theory, novel asymptotically minimax criteria suitable for practical applications in imaging and data analysis are examined including the special cases such as the Jensen-Shannon divergence and the probabilistic neural network. An optimal approximate nearest neighbor search algorithm, which allows faster classification of databases is featured. Rough set theory, sequential analysis and granular computing are used to improve performance of the hierarchical classifiers. Practical examples in face identification (including deep neural networks), isolated commands recognition in voice control system and classification of visemes captured by the Kinect depth camera are included. This approach creates fast and accurate search procedures by using exact probability densities of applied dissimilarity measures. This book can be used as a guide for independent study and as supplementary material for a technicall...

Artificial intelligence applications in information and communication technologies

CERN Document Server

Bouguila, Nizar

2015-01-01

This book presents various recent applications of Artificial Intelligence in Information and Communication Technologies such as Search and Optimization methods, Machine Learning, Data Representation and Ontologies, and Multi-agent Systems. The main aim of this book is to help Information and Communication Technologies (ICT) practitioners in managing efficiently their platforms using AI tools and methods and to provide them with sufficient Artificial Intelligence background to deal with real-life problems.  .

Algorithms and architectures of artificial intelligence

CERN Document Server

Tyugu, E

2007-01-01

This book gives an overview of methods developed in artificial intelligence for search, learning, problem solving and decision-making. It gives an overview of algorithms and architectures of artificial intelligence that have reached the degree of maturity when a method can be presented as an algorithm, or when a well-defined architecture is known, e.g. in neural nets and intelligent agents. It can be used as a handbook for a wide audience of application developers who are interested in using artificial intelligence methods in their software products. Parts of the text are rather independent, so that one can look into the index and go directly to a description of a method presented in the form of an abstract algorithm or an architectural solution. The book can be used also as a textbook for a course in applied artificial intelligence. Exercises on the subject are added at the end of each chapter. Neither programming skills nor specific knowledge in computer science are expected from the reader. However, some p...

Artificial Intelligence: Applications in Education.

Science.gov (United States)

Thorkildsen, Ron J.; And Others

1986-01-01

Artificial intelligence techniques are used in computer programs to search out rapidly and retrieve information from very large databases. Programing advances have also led to the development of systems that provide expert consultation (expert systems). These systems, as applied to education, are the primary emphasis of this article. (LMO)

Emotionally intelligent nurse leadership: a literature review study.

Science.gov (United States)

Akerjordet, Kristin; Severinsson, Elisabeth

2008-07-01

To establish a synthesis of the literature on the theoretical and empirical basis of emotional intelligence and it's linkage to nurse leadership, focusing on subjective well-being and professional development. Emotional intelligence has been acknowledged in the literature as supporting nurse leadership that fosters a healthy work environment, creating inspiring relationships based on mutual trust. Nurse leaders who exhibit characteristics of emotional intelligence enhance organizational, staff and patient outcomes. A literature search was undertaken using international data bases covering the period January 1997 to December 2007. Eighteen articles were included in this integrative review and were thoroughly reviewed by both authors. Emotional intelligence was associated with positive empowerment processes as well as positive organizational outcomes. Emotionally intelligent nurse leadership characterized by self-awareness and supervisory skills highlights positive empowerment processes, creating a favourable work climate characterized by resilience, innovation and change. Emotional intelligence cannot be considered a general panacea, but it may offer new ways of thinking and being for nurse leaders, as it takes the intelligence of feelings more seriously by continually reflecting, evaluating and improving leadership and supervisory skills.

Anti-Makeup: Learning A Bi-Level Adversarial Network for Makeup-Invariant Face Verification

OpenAIRE

Li, Yi; Song, Lingxiao; Wu, Xiang; He, Ran; Tan, Tieniu

2017-01-01

Makeup is widely used to improve facial attractiveness and is well accepted by the public. However, different makeup styles will result in significant facial appearance changes. It remains a challenging problem to match makeup and non-makeup face images. This paper proposes a learning from generation approach for makeup-invariant face verification by introducing a bi-level adversarial network (BLAN). To alleviate the negative effects from makeup, we first generate non-makeup images from makeu...

Reconstruction of three-dimensional porous media using generative adversarial neural networks

Science.gov (United States)

Mosser, Lukas; Dubrule, Olivier; Blunt, Martin J.

2017-10-01

To evaluate the variability of multiphase flow properties of porous media at the pore scale, it is necessary to acquire a number of representative samples of the void-solid structure. While modern x-ray computer tomography has made it possible to extract three-dimensional images of the pore space, assessment of the variability in the inherent material properties is often experimentally not feasible. We present a method to reconstruct the solid-void structure of porous media by applying a generative neural network that allows an implicit description of the probability distribution represented by three-dimensional image data sets. We show, by using an adversarial learning approach for neural networks, that this method of unsupervised learning is able to generate representative samples of porous media that honor their statistics. We successfully compare measures of pore morphology, such as the Euler characteristic, two-point statistics, and directional single-phase permeability of synthetic realizations with the calculated properties of a bead pack, Berea sandstone, and Ketton limestone. Results show that generative adversarial networks can be used to reconstruct high-resolution three-dimensional images of porous media at different scales that are representative of the morphology of the images used to train the neural network. The fully convolutional nature of the trained neural network allows the generation of large samples while maintaining computational efficiency. Compared to classical stochastic methods of image reconstruction, the implicit representation of the learned data distribution can be stored and reused to generate multiple realizations of the pore structure very rapidly.

Developing Realistic Behaviors in Adversarial Agents for Air Combat Simulation

Science.gov (United States)

1993-12-01

34Building Symbolic Primitives with Continuous Control Rou- tines." Proceedings of the 1st International Conference on Aritificial Intelligence Planning...shortcoming is the minimal Air Force participation in this field. 1-1 Some of the artificial intelligence (AI) personnel at the Air Force Institute of... intelligent system that operates in a moderately complex or unpredictable environment must be reactive. In being reactive the intelligent system must

CaloGAN: Simulating 3D high energy particle showers in multilayer electromagnetic calorimeters with generative adversarial networks

Science.gov (United States)

Paganini, Michela; de Oliveira, Luke; Nachman, Benjamin

2018-01-01

The precise modeling of subatomic particle interactions and propagation through matter is paramount for the advancement of nuclear and particle physics searches and precision measurements. The most computationally expensive step in the simulation pipeline of a typical experiment at the Large Hadron Collider (LHC) is the detailed modeling of the full complexity of physics processes that govern the motion and evolution of particle showers inside calorimeters. We introduce CaloGAN, a new fast simulation technique based on generative adversarial networks (GANs). We apply these neural networks to the modeling of electromagnetic showers in a longitudinally segmented calorimeter and achieve speedup factors comparable to or better than existing full simulation techniques on CPU (100 ×-1000 × ) and even faster on GPU (up to ˜105× ). There are still challenges for achieving precision across the entire phase space, but our solution can reproduce a variety of geometric shower shape properties of photons, positrons, and charged pions. This represents a significant stepping stone toward a full neural network-based detector simulation that could save significant computing time and enable many analyses now and in the future.

Learning to Solve Problems by Searching for Macro-Operators

Science.gov (United States)

1983-07-01

executing generalized robot plans. Aritificial Intelligence 3:25 1-288, 1972. [Frey 821 Frey, Alexander Ii. Jr., and David Singmaster. Handbook of Cubik...and that searching for macros may be a useful general learning paradigm. 1.1. Introduction One view of die die field of artificial intelligence is that... intelligence literature [Schofield 67, Gaschnig 79, Ericsson 761 and provides one of the simplest examples of the operation of the Macro Problem Solver. It

Emotional intelligence education in pre-registration nursing programmes: an integrative review.

Science.gov (United States)

Foster, Kim; McCloughen, Andrea; Delgado, Cynthia; Kefalas, Claudia; Harkness, Emily

2015-03-01

To investigate the state of knowledge on emotional intelligence (EI) education in pre-registration nursing programmes. Integrative literature review. CINAHL, Medline, Scopus, ERIC, and Web of Knowledge electronic databases were searched for abstracts published in English between 1992-2014. Data extraction and constant comparative analysis of 17 articles. Three categories were identified: Constructs of emotional intelligence; emotional intelligence curricula components; and strategies for emotional intelligence education. A wide range of emotional intelligence constructs were found, with a predominance of trait-based constructs. A variety of strategies to enhance students' emotional intelligence skills were identified, but limited curricula components and frameworks reported in the literature. An ability-based model for curricula and learning and teaching approaches is recommended. Copyright © 2014. Published by Elsevier Ltd.

Intelligent techniques in engineering management theory and applications

CERN Document Server

Onar, Sezi

2015-01-01

This book presents recently developed intelligent techniques with applications and theory in the area of engineering management. The involved applications of intelligent techniques such as neural networks, fuzzy sets, Tabu search, genetic algorithms, etc. will be useful for engineering managers, postgraduate students, researchers, and lecturers. The book has been written considering the contents of a classical engineering management book but intelligent techniques are used for handling the engineering management problem areas. This comprehensive characteristics of the book makes it an excellent reference for the solution of complex problems of engineering management. The authors of the chapters are well-known researchers with their previous works in the area of engineering management.

Generalizing Backtrack-Free Search: A Framework for Search-Free Constraint Satisfaction

Science.gov (United States)

Jonsson, Ari K.; Frank, Jeremy

2000-01-01

Tractable classes of constraint satisfaction problems are of great importance in artificial intelligence. Identifying and taking advantage of such classes can significantly speed up constraint problem solving. In addition, tractable classes are utilized in applications where strict worst-case performance guarantees are required, such as constraint-based plan execution. In this work, we present a formal framework for search-free (backtrack-free) constraint satisfaction. The framework is based on general procedures, rather than specific propagation techniques, and thus generalizes existing techniques in this area. We also relate search-free problem solving to the notion of decision sets and use the result to provide a constructive criterion that is sufficient to guarantee search-free problem solving.

Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation

OpenAIRE

Peng, Xi; Tang, Zhiqiang; Yang, Fei; Feris, Rogerio; Metaxas, Dimitris

2018-01-01

Random data augmentation is a critical technique to avoid overfitting in training deep neural network models. However, data augmentation and network training are usually treated as two isolated processes, limiting the effectiveness of network training. Why not jointly optimize the two? We propose adversarial data augmentation to address this limitation. The main idea is to design an augmentation network (generator) that competes against a target network (discriminator) by generating `hard' au...

Cognitive Targeting: A Coercive Air Power Theory for Conventional Escalation Control Against Nuclear Armed Adversaries

Science.gov (United States)

2016-06-01

strategic,” in the cognitive targeting paradigm , are those that directly disable - in the strategic audience’s mind – the attractiveness or...This study analyses the applicability of three operational targeting paradigms to coerce a nuclear-armed adversary in a regional crisis, while...principles and elements of war and understand the coercive ability of utility targeting (a capabilities-based targeting paradigm , CBTP), axiological

Teaching Planetary Science as Part of the Search for Extraterrestrial Intelligence (SETI)

Science.gov (United States)

Margot, Jean-Luc; Greenberg, Adam H.

2017-10-01

In Spring 2016 and 2017, UCLA offered a course titled "EPSS C179/279 - Search for Extraterrestrial Intelligence: Theory and Applications". The course is designed for advanced undergraduate students and graduate students in the science, technical, engineering, and mathematical fields. Each year, students designed an observing sequence for the Green Bank telescope, observed known planetary systems remotely, wrote a sophisticated and modular data processing pipeline, analyzed the data, and presented their results. In 2016, 15 students participated in the course (9U, 5G; 11M, 3F) and observed 14 planetary systems in the Kepler field. In 2017, 17 students participated (15U, 2G; 10M, 7F) and observed 10 planetary systems in the Kepler field, TRAPPIST-1, and LHS 1140. In order to select suitable targets, students learned about planetary systems, planetary habitability, and planetary dynamics. In addition to planetary science fundamentals, students learned radio astronomy fundamentals, collaborative software development, signal processing techniques, and statistics. Evaluations indicate that the course is challenging but that students are eager to learn because of the engrossing nature of SETI. Students particularly value the teamwork approach, the observing experience, and working with their own data. The next offering of the course will be in Spring 2018. Additional information about our SETI work is available at seti.ucla.edu.

Are the advocates of nuclear power and the adversaries listening to each other?

International Nuclear Information System (INIS)

Bernard, Jean-Francois

1989-01-01

It's obvious that one cannot answer the question from the title with simple 'yes' or 'no'. If it seems that the nuclear advocates globaly, have the same point of view, and an homegeneous argumentation, it is not the same for the opponents to Nuclear Energy. We can classify these adversaries in 4 categories, according to the nature of their opposition: ideological, economical, political, that includes ideological, mystical. In reality, these 4 types of opposition are not equally represented in France. From 1974 to the present moment, the EDF, has tried to have a dialogue with them. Various resultswere achieved with the Ecologists, 'Economical opponents', 'political adversaries'. Theer was no dialogue with the 'mystical opponents', for a very simple reason 'Nuclear people' are the Devil himself and they did not wish to have anything to do with him. There can be no end to the discussion about the sex of angels. To conclude, it is believed that there has been a discussion in France. It did not lead to any sort of complete consensus, but there are some true positive results. Only one, the well-known opponent to nuclear energy, in the seventies, the President of 'The Friends of the Earth' he is, now, French 'Environment Vice-Minister' and he considers that, among the energy industries, the nuclear energy is, without doubt, the less polluting

Are the advocates of nuclear power and the adversaries listening to each other?

Energy Technology Data Exchange (ETDEWEB)

Bernard, Jean-Francois [Electricite de France, Engineering and Construction Division, Sites-Environment-Information Branch, 22-30, avenue de Wagram, 75008, Paris (France)

1989-07-01

It's obvious that one cannot answer the question from the title with simple 'yes' or 'no'. If it seems that the nuclear advocates globaly, have the same point of view, and an homegeneous argumentation, it is not the same for the opponents to Nuclear Energy. We can classify these adversaries in 4 categories, according to the nature of their opposition: ideological, economical, political, that includes ideological, mystical. In reality, these 4 types of opposition are not equally represented in France. From 1974 to the present moment, the EDF, has tried to have a dialogue with them. Various resultswere achieved with the Ecologists, 'Economical opponents', 'political adversaries'. Theer was no dialogue with the 'mystical opponents', for a very simple reason 'Nuclear people' are the Devil himself and they did not wish to have anything to do with him. There can be no end to the discussion about the sex of angels. To conclude, it is believed that there has been a discussion in France. It did not lead to any sort of complete consensus, but there are some true positive results. Only one, the well-known opponent to nuclear energy, in the seventies, the President of 'The Friends of the Earth' he is, now, French 'Environment Vice-Minister' and he considers that, among the energy industries, the nuclear energy is, without doubt, the less polluting.

Computer-Assisted Search Of Large Textual Data Bases

Science.gov (United States)

Driscoll, James R.

1995-01-01

"QA" denotes high-speed computer system for searching diverse collections of documents including (but not limited to) technical reference manuals, legal documents, medical documents, news releases, and patents. Incorporates previously available and emerging information-retrieval technology to help user intelligently and rapidly locate information found in large textual data bases. Technology includes provision for inquiries in natural language; statistical ranking of retrieved information; artificial-intelligence implementation of semantics, in which "surface level" knowledge found in text used to improve ranking of retrieved information; and relevance feedback, in which user's judgements of relevance of some retrieved documents used automatically to modify search for further information.

Guidance of visual search by memory and knowledge.

Science.gov (United States)

Hollingworth, Andrew

2012-01-01

To behave intelligently in the world, humans must be able to find objects efficiently within the complex environments they inhabit. A growing proportion of the literature on visual search is devoted to understanding this type of natural search. In the present chapter, I review the literature on visual search through natural scenes, focusing on the role of memory and knowledge in guiding attention to task-relevant objects.

E-learning environment as intelligent tutoring system

Science.gov (United States)

Nagyová, Ingrid

2017-07-01

The development of computers and artificial intelligence theory allow their application in the field of education. Intelligent tutoring systems reflect student learning styles and adapt the curriculum according to their individual needs. The building of intelligent tutoring systems requires not only the creation of suitable software, but especially the search and application of the rules enabling ICT to individually adapt the curriculum. The main idea of this paper is to attempt to specify the rules for dividing the students to systematically working students and more practically or pragmatically inclined students. The paper shows that monitoring the work of students in e-learning environment, analysis of various approaches to educational materials and correspondence assignments show different results for the defined groups of students.

Assessing Mission Impact of Cyberattacks: Report of the NATO IST-128 Workshop

Science.gov (United States)

2015-12-01

simulation) perspective. This would be natural, considering that the cybersecurity problem is highly adversarial in nature. Because it involves intelligent ...be formulated as a partial information game; artificial intelligence techniques might help here. Yet another style of problem formulation that...computational information processing for weapons, intelligence , communication, and logistics systems continues to increase the vulnerability of

Competitive Intelligence: Finding the Clues Online.

Science.gov (United States)

Combs, Richard; Moorhead, John

1990-01-01

Defines and discusses competitive intelligence for business decision making and suggests the use of online databases to start looking for relevant information. The best databases to use are described, designing the search strategy is explained, reviewing and editing results are discussed, and the presentation of results is considered. (LRW)

Intelligent Agent Based Semantic Web in Cloud Computing Environment

OpenAIRE

Mukhopadhyay, Debajyoti; Sharma, Manoj; Joshi, Gajanan; Pagare, Trupti; Palwe, Adarsha

2013-01-01

Considering today's web scenario, there is a need of effective and meaningful search over the web which is provided by Semantic Web. Existing search engines are keyword based. They are vulnerable in answering intelligent queries from the user due to the dependence of their results on information available in web pages. While semantic search engines provides efficient and relevant results as the semantic web is an extension of the current web in which information is given well defined meaning....

Interactive analysis of geodata based intelligence

Science.gov (United States)

Wagner, Boris; Eck, Ralf; Unmüessig, Gabriel; Peinsipp-Byma, Elisabeth

2016-05-01

When a spatiotemporal events happens, multi-source intelligence data is gathered to understand the problem, and strategies for solving the problem are investigated. The difficulties arising from handling spatial and temporal intelligence data represent the main problem. The map might be the bridge to visualize the data and to get the most understand model for all stakeholders. For the analysis of geodata based intelligence data, a software was developed as a working environment that combines geodata with optimized ergonomics. The interaction with the common operational picture (COP) is so essentially facilitated. The composition of the COP is based on geodata services, which are normalized by international standards of the Open Geospatial Consortium (OGC). The basic geodata are combined with intelligence data from images (IMINT) and humans (HUMINT), stored in a NATO Coalition Shared Data Server (CSD). These intelligence data can be combined with further information sources, i.e., live sensors. As a result a COP is generated and an interaction suitable for the specific workspace is added. This allows the users to work interactively with the COP, i.e., searching with an on board CSD client for suitable intelligence data and integrate them into the COP. Furthermore, users can enrich the scenario with findings out of the data of interactive live sensors and add data from other sources. This allows intelligence services to contribute effectively to the process by what military and disaster management are organized.

An Innovative Approach for online Meta Search Engine Optimization

OpenAIRE

Manral, Jai; Hossain, Mohammed Alamgir

2015-01-01

This paper presents an approach to identify efficient techniques used in Web Search Engine Optimization (SEO). Understanding SEO factors which can influence page ranking in search engine is significant for webmasters who wish to attract large number of users to their website. Different from previous relevant research, in this study we developed an intelligent Meta search engine which aggregates results from various search engines and ranks them based on several important SEO parameters. The r...

Learning Search Algorithms: An Educational View

Directory of Open Access Journals (Sweden)

Ales Janota

2014-12-01

Full Text Available Artificial intelligence methods find their practical usage in many applications including maritime industry. The paper concentrates on the methods of uninformed and informed search, potentially usable in solving of complex problems based on the state space representation. The problem of introducing the search algorithms to newcomers has its technical and psychological dimensions. The authors show how it is possible to cope with both of them through design and use of specialized authoring systems. A typical example of searching a path through the maze is used to demonstrate how to test, observe and compare properties of various search strategies. Performance of search methods is evaluated based on the common criteria.

Recent advances in swarm intelligence and evolutionary computation

CERN Document Server

2015-01-01

This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms and applications with the emphasis on swarm intelligence and bio-inspired computation. Topics include the analysis and overview of swarm intelligence and evolutionary computation, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search as well as convergent hybridization. Application case studies have focused on the dehydration of fruits and vegetables by the firefly algorithm and goal programming, feature selection by the binary flower pollination algorithm, job shop scheduling, single row facility layout optimization, training of feed-forward neural networks, damage and stiffness identification, synthesis of cross-ambiguity functions by the bat algorithm, web document clustering, truss analysis, water distribution networks, sustainable building designs and others. As a timely review, this book can serve as an ideal reference f...

Deep Convolutional Generative Adversarial Network for Procedural 3D Landscape Generation Based on DEM

OpenAIRE

Wulff-Jensen, Andreas; Rant, Niclas Nerup; Møller, Tobias Nordvig; Billeskov, Jonas Aksel

2018-01-01

This paper proposes a novel framework for improving procedural generation of 3D landscapes using machine learning. We utilized a Deep Convolutional Generative Adversarial Network (DC-GAN) to generate heightmaps. The network was trained on a dataset consisting of Digital Elevation Maps (DEM) of the alps. During map generation, the batch size and learning rate were optimized for the most efficient and satisfying map production. The diversity of the final output was tested against Perlin noise u...

Occluded object reconstruction for first responders with augmented reality glasses using conditional generative adversarial networks

OpenAIRE

Yun, Kyongsik; Lu, Thomas; Chow, Edward

2018-01-01

Firefighters suffer a variety of life-threatening risks, including line-of-duty deaths, injuries, and exposures to hazardous substances. Support for reducing these risks is important. We built a partially occluded object reconstruction method on augmented reality glasses for first responders. We used a deep learning based on conditional generative adversarial networks to train associations between the various images of flammable and hazardous objects and their partially occluded counterparts....

Category Theory Approach to Solution Searching Based on Photoexcitation Transfer Dynamics

Directory of Open Access Journals (Sweden)

Makoto Naruse

2017-07-01

Full Text Available Solution searching that accompanies combinatorial explosion is one of the most important issues in the age of artificial intelligence. Natural intelligence, which exploits natural processes for intelligent functions, is expected to help resolve or alleviate the difficulties of conventional computing paradigms and technologies. In fact, we have shown that a single-celled organism such as an amoeba can solve constraint satisfaction problems and related optimization problems as well as demonstrate experimental systems based on non-organic systems such as optical energy transfer involving near-field interactions. However, the fundamental mechanisms and limitations behind solution searching based on natural processes have not yet been understood. Herein, we present a theoretical background of solution searching based on optical excitation transfer from a category-theoretic standpoint. One important indication inspired by the category theory is that the satisfaction of short exact sequences is critical for an adequate computational operation that determines the flow of time for the system and is termed as “short-exact-sequence-based time.” In addition, the octahedral and braid structures known in triangulated categories provide a clear understanding of the underlying mechanisms, including a quantitative indication of the difficulties of obtaining solutions based on homology dimension. This study contributes to providing a fundamental background of natural intelligence.

The future of active and intelligent packaging industry

Directory of Open Access Journals (Sweden)

Renata Dobrucka

2013-06-01

Full Text Available Background: Innovation in food and beverage packaging is mostly driven by consumer needs and demands influenced by changing global trends, such as increased life expectancy, fewer organizations investing in food production and distribution. Food industry has seen great advances in the packaging sector since its inception in the 18th century with most active and intelligent innovations occurring during the past century. These advances have led to improved food quality and safety. Active and intelligent packaging is new and exciting area of technology  which efficient contemporary consumer response. Materials and methods: On the basis of broad review of the current state of the art in world literature, the market active and intelligent packaging is discussed. Results: This paper shows present innovation in the market active and intelligent packaging. Conclusion: Research and development in the field of active and intelligent packaging materials is very dynamic and develops in relation with the search for environment friendly packaging solutions. Besides, active and intelligent packaging is becoming more and more widely used for food products. The future of this type of packaging system seems to be very interesting.

PubData: search engine for bioinformatics databases worldwide

OpenAIRE

Vand, Kasra; Wahlestedt, Thor; Khomtchouk, Kelly; Sayed, Mohammed; Wahlestedt, Claes; Khomtchouk, Bohdan

2016-01-01

We propose a search engine and file retrieval system for all bioinformatics databases worldwide. PubData searches biomedical data in a user-friendly fashion similar to how PubMed searches biomedical literature. PubData is built on novel network programming, natural language processing, and artificial intelligence algorithms that can patch into the file transfer protocol servers of any user-specified bioinformatics database, query its contents, retrieve files for download, and adapt to the use...

Intelligence and Its Role in Protecting Against Terrorism

Directory of Open Access Journals (Sweden)

Don Githens

2010-01-01

Full Text Available The art and science of gathering critical operational intelligence has been defined in many ways and is beyond our needs for this writing. Throughout the course of history, many wars have been fought depending heavily on various forms of intelligence. During our most recent actions in the War on Terror, intelligence analysis has played a critical role in both offensive and defensive operations in Iraq and Afghanistan. With such varying fact-finding techniques available and utilized in the defense of our country, it has become an arduous task to collect, decipher, package, prioritize, disseminate, and act upon everything that comes down the pipe.Intelligence is even more important in homeland defense and security. Our society is suspicious of intrusions on personal liberties. Mandated identity cards, restricted vehicle access and random searches of airline passengers are generally not well received. That makes it especially important to prevent terrorist attacks by interdicting the terrorists and their resources before they can reach their targets. The primary means of accomplishing this is through a combination of intelligence and law enforcement work.

Adversarial life testing: A Bayesian negotiation model

International Nuclear Information System (INIS)

Rufo, M.J.; Martín, J.; Pérez, C.J.

2014-01-01

Life testing is a procedure intended for facilitating the process of making decisions in the context of industrial reliability. On the other hand, negotiation is a process of making joint decisions that has one of its main foundations in decision theory. A Bayesian sequential model of negotiation in the context of adversarial life testing is proposed. This model considers a general setting for which a manufacturer offers a product batch to a consumer. It is assumed that the reliability of the product is measured in terms of its lifetime. Furthermore, both the manufacturer and the consumer have to use their own information with respect to the quality of the product. Under these assumptions, two situations can be analyzed. For both of them, the main aim is to accept or reject the product batch based on the product reliability. This topic is related to a reliability demonstration problem. The procedure is applied to a class of distributions that belong to the exponential family. Thus, a unified framework addressing the main topics in the considered Bayesian model is presented. An illustrative example shows that the proposed technique can be easily applied in practice

Sharpness-Aware Low-Dose CT Denoising Using Conditional Generative Adversarial Network.

Science.gov (United States)

Yi, Xin; Babyn, Paul

2018-02-20

Low-dose computed tomography (LDCT) has offered tremendous benefits in radiation-restricted applications, but the quantum noise as resulted by the insufficient number of photons could potentially harm the diagnostic performance. Current image-based denoising methods tend to produce a blur effect on the final reconstructed results especially in high noise levels. In this paper, a deep learning-based approach was proposed to mitigate this problem. An adversarially trained network and a sharpness detection network were trained to guide the training process. Experiments on both simulated and real dataset show that the results of the proposed method have very small resolution loss and achieves better performance relative to state-of-the-art methods both quantitatively and visually.

Fine-Tuning Neural Patient Question Retrieval Model with Generative Adversarial Networks.

Science.gov (United States)

Tang, Guoyu; Ni, Yuan; Wang, Keqiang; Yong, Qin

2018-01-01

The online patient question and answering (Q&A) system attracts an increasing amount of users in China. Patient will post their questions and wait for doctors' response. To avoid the lag time involved with the waiting and to reduce the workload on the doctors, a better method is to automatically retrieve the semantically equivalent question from the archive. We present a Generative Adversarial Networks (GAN) based approach to automatically retrieve patient question. We apply supervised deep learning based approaches to determine the similarity between patient questions. Then a GAN framework is used to fine-tune the pre-trained deep learning models. The experiment results show that fine-tuning by GAN can improve the performance.

Federated Search Tools in Fusion Centers: Bridging Databases in the Information Sharing Environment

Science.gov (United States)

2012-09-01

Suspicious Activity Reporting Initiative ODNI Office of the Director of National Intelligence OSINT Open Source Intelligence PERF Police Executive...Fusion centers are encouraged to explore all available information sources to enhance the intelligence analysis process. It follows then that fusion...WSIC also utilizes ACCURINT, a web-based, subscription service. ACCURINT searches open source information and is able to collect and collate

druGAN: An Advanced Generative Adversarial Autoencoder Model for de Novo Generation of New Molecules with Desired Molecular Properties in Silico.

Science.gov (United States)

Kadurin, Artur; Nikolenko, Sergey; Khrabrov, Kuzma; Aliper, Alex; Zhavoronkov, Alex

2017-09-05

Deep generative adversarial networks (GANs) are the emerging technology in drug discovery and biomarker development. In our recent work, we demonstrated a proof-of-concept of implementing deep generative adversarial autoencoder (AAE) to identify new molecular fingerprints with predefined anticancer properties. Another popular generative model is the variational autoencoder (VAE), which is based on deep neural architectures. In this work, we developed an advanced AAE model for molecular feature extraction problems, and demonstrated its advantages compared to VAE in terms of (a) adjustability in generating molecular fingerprints; (b) capacity of processing very large molecular data sets; and (c) efficiency in unsupervised pretraining for regression model. Our results suggest that the proposed AAE model significantly enhances the capacity and efficiency of development of the new molecules with specific anticancer properties using the deep generative models.

Intelligence in Artificial Intelligence

OpenAIRE

Datta, Shoumen Palit Austin

2016-01-01

The elusive quest for intelligence in artificial intelligence prompts us to consider that instituting human-level intelligence in systems may be (still) in the realm of utopia. In about a quarter century, we have witnessed the winter of AI (1990) being transformed and transported to the zenith of tabloid fodder about AI (2015). The discussion at hand is about the elements that constitute the canonical idea of intelligence. The delivery of intelligence as a pay-per-use-service, popping out of ...

Defending Tor from Network Adversaries: A Case Study of Network Path Prediction

Directory of Open Access Journals (Sweden)

Juen Joshua

2015-06-01

Full Text Available The Tor anonymity network has been shown vulnerable to traffic analysis attacks by autonomous systems (ASes and Internet exchanges (IXes, which can observe different overlay hops belonging to the same circuit. We evaluate whether network path prediction techniques provide an accurate picture of the threat from such adversaries, and whether they can be used to avoid this threat. We perform a measurement study by collecting 17.2 million traceroutes from Tor relays to destinations around the Internet. We compare the collected traceroute paths to predicted paths using state-of-the-art path inference techniques. We find that traceroutes present a very different picture, with the set of ASes seen in the traceroute path differing from the predicted path 80% of the time. We also consider the impact that prediction errors have on Tor security. Using a simulator to choose paths over a week, our traceroutes indicate a user has nearly a 100% chance of at least one compromise in a week with 11% of total paths containing an AS compromise and less than 1% containing an IX compromise when using default Tor selection. We find modifying the path selection to choose paths predicted to be safe lowers total paths with an AS compromise to 0.14% but still presents a 5–11% chance of at least one compromise in a week while making 5% of paths fail, with 96% of failures due to false positives in path inferences. Our results demonstrate more measurement and better path prediction is necessary to mitigate the risk of AS and IX adversaries to Tor.

Post-Westgate SWAT : C4ISTAR Architectural Framework for Autonomous Network Integrated Multifaceted Warfighting Solutions Version 1.0 : A Peer-Reviewed Monograph

OpenAIRE

Nyagudi, Nyagudi Musandu

2013-01-01

Nations are today challenged with multiple constraints such as declining population and financial austerity, these inevitably reduce military/security forces preparedness. Faced with well resourced adversaries or those of the asymmetric type, only a Nation that arms itself "intelligently" and fights "smart" attains advantages in the world's ever more complex and restrictive battle-spaces. Police SWAT teams and Military Special Forces face mounting pressure and challenges from adversaries that...

The National Counterintelligence Strategy of the United States of America

National Research Council Canada - National Science Library

McConnell, J. M

2007-01-01

.... Our adversaries -- foreign intelligence services, terrorists, foreign criminal enterprises and cyber intruders -- use overt, covert, and clandestine activities to exploit and undermine US national security interests...

Creating Turbulent Flow Realizations with Generative Adversarial Networks

Science.gov (United States)

King, Ryan; Graf, Peter; Chertkov, Michael

2017-11-01

Generating valid inflow conditions is a crucial, yet computationally expensive, step in unsteady turbulent flow simulations. We demonstrate a new technique for rapid generation of turbulent inflow realizations that leverages recent advances in machine learning for image generation using a deep convolutional generative adversarial network (DCGAN). The DCGAN is an unsupervised machine learning technique consisting of two competing neural networks that are trained against each other using backpropagation. One network, the generator, tries to produce samples from the true distribution of states, while the discriminator tries to distinguish between true and synthetic samples. We present results from a fully-trained DCGAN that is able to rapidly draw random samples from the full distribution of possible inflow states without needing to solve the Navier-Stokes equations, eliminating the costly process of spinning up inflow turbulence. This suggests a new paradigm in physics informed machine learning where the turbulence physics can be encoded in either the discriminator or generator. Finally, we also propose additional applications such as feature identification and subgrid scale modeling.

Intelligent Information Systems for Web Product Search

NARCIS (Netherlands)

D. Vandic (Damir)

2017-01-01

markdownabstractOver the last few years, we have experienced an increase in online shopping. Consequently, there is a need for efficient and effective product search engines. The rapid growth of e-commerce, however, has also introduced some challenges. Studies show that users can get overwhelmed by

An introduction to harmony search optimization method

CERN Document Server

Wang, Xiaolei; Zenger, Kai

2014-01-01

This brief provides a detailed introduction, discussion and bibliographic review of the nature1-inspired optimization algorithm called Harmony Search. It uses a large number of simulation results to demonstrate the advantages of Harmony Search and its variants and also their drawbacks. The authors show how weaknesses can be amended by hybridization with other optimization methods. The Harmony Search Method with Applications will be of value to researchers in computational intelligence in demonstrating the state of the art of research on an algorithm of current interest. It also helps researche

An improved parametrization and analysis of the EXP3++ algorithm for stochastic and adversarial bandits

DEFF Research Database (Denmark)

Seldin, Yevgeny; Lugosi, Gábor

We present a new strategy for gap estimation in randomized algorithms for multiarmed bandits and combine it with the EXP3++ algorithm of Seldin and Slivkins (2014). In the stochastic regime the strategy reduces dependence of regret on a time horizon from $(ln t)^3$ to $(ln t)^2$ and eliminates an...... an additive factor of order $\\Delta e^{\\Delta^2}$, where $\\Delta$ is the minimal gap of a problem instance. In the adversarial regime regret guarantee remains unchanged....

An improved parametrization and analysis of the EXP3++ algorithm for stochastic and adversarial bandits

DEFF Research Database (Denmark)

Seldin, Yevgeny; Lugosi, Gábor

2017-01-01

We present a new strategy for gap estimation in randomized algorithms for multiarmed bandits and combine it with the EXP3++ algorithm of Seldin and Slivkins (2014). In the stochastic regime the strategy reduces dependence of regret on a time horizon from $(ln t)^3$ to $(ln t)^2$ and eliminates...... an additive factor of order $\\Delta e^{\\Delta^2}$, where $\\Delta$ is the minimal gap of a problem instance. In the adversarial regime regret guarantee remains unchanged....

Material control study: a directed graph and fault tree procedure for adversary event set generation

International Nuclear Information System (INIS)

Lambert, H.E.; Lim, J.J.; Gilman, F.M.

1978-01-01

In work for the United States Nuclear Regulatory Commission, Lawrence Livermore Laboratory is developing an assessment procedure to evaluate the effectiveness of a potential nuclear facility licensee's material control (MC) system. The purpose of an MC system is to prevent the theft of special nuclear material such as plutonium and highly enriched uranium. The key in the assessment procedure is the generation and analysis of the adversary event sets by a directed graph and fault-tree methodology

Search and Tracking of an Unknown Number of Targets by a Team of Autonomous Agents Utilizing Time-evolving Partition Classification

OpenAIRE

Wood, Jared Gregory

2011-01-01

The advancement of computing technology has enabled the practical development of intelligent autonomous systems. Intelligent autonomous systems can be used to perform difficult sensing tasks. One such sensing task is to search for and track targets over large geographic areas. Searching for and tracking targets over geographic areas has important applications. These applications include search and rescue, boarder patrol, and reconnaissance. Inherent in applications such as these is the need ...

Emotional Intelligence Research within Human Resource Development Scholarship

Science.gov (United States)

Farnia, Forouzan; Nafukho, Fredrick Muyia

2016-01-01

Purpose: The purpose of this study is to review and synthesize pertinent emotional intelligence (EI) research within the human resource development (HRD) scholarship. Design/methodology/approach: An integrative review of literature was conducted and multiple electronic databases were searched to find the relevant resources. Using the content…

Artificial Intelligence and Moral intelligence

OpenAIRE

Laura Pana

2008-01-01

We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined,...

Roles of Cognitive Status and Intelligibility in Everyday Communication in People with Parkinson's Disease: A Systematic Review.

Science.gov (United States)

Barnish, Maxwell S; Whibley, Daniel; Horton, Simon M C; Butterfint, Zoe R; Deane, Katherine H O

2016-03-16

Communication is fundamental to human interaction and the development and maintenance of human relationships and is frequently affected in Parkinson's disease (PD). However, research and clinical practice have both tended to focus on impairment rather than participation aspects of communicative deficit in PD. In contrast, people with PD have reported that it is these participation aspects of communication that are of greatest concern to them rather than physical speech impairment. To systematically review the existing body of evidence regarding the association between cognitive status and/or intelligibility and everyday communication in PD. Five online databases were systematically searched in May 2015 (Medline Ovid, EMBASE, AMED, PsycINFO and CINAHL) and supplementary searches were also conducted. Two reviewers independently evaluated retrieved records for inclusion and then performed data extraction and quality assessment using standardised forms. Articles were eligible for inclusion if they were English-language original peer-reviewed research articles, book chapters or doctoral theses investigating the associations between at least one of cognitive status and level of intelligibility impairment and an everyday communication outcome in human participants with PD. 4816 unique records were identified through database searches with 16 additional records identified through supplementary searches. 41 articles were suitable for full-text screening and 15 articles (12 studies) met the eligibility criteria. 10 studies assessed the role of cognitive status and 9 found that participants with greater cognitive impairment had greater everyday communication difficulties. 4 studies assessed the role of intelligibility and all found that participants with greater intelligibility impairment had greater everyday communication difficulties, although effects were often weak and not consistent. Both cognitive status and intelligibility may be associated with everyday communicative

Intelligent decision-making models for production and retail operations

CERN Document Server

Guo, Zhaoxia

2016-01-01

This book provides an overview of intelligent decision-making techniques and discusses their application in production and retail operations. Manufacturing and retail enterprises have stringent standards for using advanced and reliable techniques to improve decision-making processes, since these processes have significant effects on the performance of relevant operations and the entire supply chain. In recent years, researchers have been increasingly focusing attention on using intelligent techniques to solve various decision-making problems. The opening chapters provide an introduction to several commonly used intelligent techniques, such as genetic algorithm, harmony search, neural network and extreme learning machine. The book then explores the use of these techniques for handling various production and retail decision-making problems, such as production planning and scheduling, assembly line balancing, and sales forecasting.

Intelligence Reach for Expertise (IREx)

Science.gov (United States)

Hadley, Christina; Schoening, James R.; Schreiber, Yonatan

2015-05-01

IREx is a search engine for next-generation analysts to find collaborators. U.S. Army Field Manual 2.0 (Intelligence) calls for collaboration within and outside the area of operations, but finding the best collaborator for a given task can be challenging. IREx will be demonstrated as part of Actionable Intelligence Technology Enabled Capability Demonstration (AI-TECD) at the E15 field exercises at Ft. Dix in July 2015. It includes a Task Model for describing a task and its prerequisite competencies, plus a User Model (i.e., a user profile) for individuals to assert their capabilities and other relevant data. These models use a canonical suite of ontologies as a foundation for these models, which enables robust queries and also keeps the models logically consistent. IREx also supports learning validation, where a learner who has completed a course module can search and find a suitable task to practice and demonstrate that their new knowledge can be used in the real world for its intended purpose. The IREx models are in the initial phase of a process to develop them as an IEEE standard. This initiative is currently an approved IEEE Study Group, after which follows a standards working group, then a balloting group, and if all goes well, an IEEE standard.

Intelligence Naturelle et Intelligence Artificielle

OpenAIRE

Dubois, Daniel

2011-01-01

Cet article présente une approche systémique du concept d’intelligence naturelle en ayant pour objectif de créer une intelligence artificielle. Ainsi, l’intelligence naturelle, humaine et animale non-humaine, est une fonction composée de facultés permettant de connaître et de comprendre. De plus, l'intelligence naturelle reste indissociable de la structure, à savoir les organes du cerveau et du corps. La tentation est grande de doter les systèmes informatiques d’une intelligence artificielle ...

Substring Position Search over Encrypted Cloud Data Supporting Efficient Multi-User Setup

Directory of Open Access Journals (Sweden)

Mikhail Strizhov

2016-07-01

Full Text Available Existing Searchable Encryption (SE solutions are able to handle simple Boolean search queries, such as single or multi-keyword queries, but cannot handle substring search queries over encrypted data that also involve identifying the position of the substring within the document. These types of queries are relevant in areas such as searching DNA data. In this paper, we propose a tree-based Substring Position Searchable Symmetric Encryption (SSP-SSE to overcome the existing gap. Our solution efficiently finds occurrences of a given substring over encrypted cloud data. Specifically, our construction uses the position heap tree data structure and achieves asymptotic efficiency comparable to that of an unencrypted position heap tree. Our encryption takes O ( k n time, and the resulting ciphertext is of size O ( k n , where k is a security parameter and n is the size of stored data. The search takes O ( m 2 + o c c time and three rounds of communication, where m is the length of the queried substring and o c c is the number of occurrences of the substring in the document collection. We prove that the proposed scheme is secure against chosen-query attacks that involve an adaptive adversary. Finally, we extend SSP-SSE to the multi-user setting where an arbitrary group of cloud users can submit substring queries to search the encrypted data.

Coupling artificial intelligence and numerical computation for engineering design (Invited paper)

Science.gov (United States)

Tong, S. S.

1986-01-01

The possibility of combining artificial intelligence (AI) systems and numerical computation methods for engineering designs is considered. Attention is given to three possible areas of application involving fan design, controlled vortex design of turbine stage blade angles, and preliminary design of turbine cascade profiles. Among the AI techniques discussed are: knowledge-based systems; intelligent search; and pattern recognition systems. The potential cost and performance advantages of an AI-based design-generation system are discussed in detail.

Learning Physics-based Models in Hydrology under the Framework of Generative Adversarial Networks

Science.gov (United States)

Karpatne, A.; Kumar, V.

2017-12-01

Generative adversarial networks (GANs), that have been highly successful in a number of applications involving large volumes of labeled and unlabeled data such as computer vision, offer huge potential for modeling the dynamics of physical processes that have been traditionally studied using simulations of physics-based models. While conventional physics-based models use labeled samples of input/output variables for model calibration (estimating the right parametric forms of relationships between variables) or data assimilation (identifying the most likely sequence of system states in dynamical systems), there is a greater opportunity to explore the full power of machine learning (ML) methods (e.g, GANs) for studying physical processes currently suffering from large knowledge gaps, e.g. ground-water flow. However, success in this endeavor requires a principled way of combining the strengths of ML methods with physics-based numerical models that are founded on a wealth of scientific knowledge. This is especially important in scientific domains like hydrology where the number of data samples is small (relative to Internet-scale applications such as image recognition where machine learning methods has found great success), and the physical relationships are complex (high-dimensional) and non-stationary. We will present a series of methods for guiding the learning of GANs using physics-based models, e.g., by using the outputs of physics-based models as input data to the generator-learner framework, and by using physics-based models as generators trained using validation data in the adversarial learning framework. These methods are being developed under the broad paradigm of theory-guided data science that we are developing to integrate scientific knowledge with data science methods for accelerating scientific discovery.

Institutionalizing dissent: a proposal for an adversarial system of pharmaceutical research.

Science.gov (United States)

Biddle, Justin

2013-12-01

There are serious problems with the way in which pharmaceutical research is currently practiced, many of which can be traced to the influence of commercial interests on research. One of the most significant is inadequate dissent, or organized skepticism. In order to ameliorate this problem, I develop a proposal that I call the "Adversarial Proceedings for the Evaluation of Pharmaceuticals," to be instituted within a regulatory agency such as the Food and Drug Administration for the evaluation of controversial new drugs and controversial drugs already in the market. This proposal is an organizational one based upon the "science court" proposal by Arthur Kantrowitz in the 1960s and 1970s. The primary benefit of this system is its ability to institutionalize dissent, thereby ensuring that one set of interests does not dominate all others.

Artificial Intelligence and the Future of Defense

DEFF Research Database (Denmark)

De Spiegeleire, Stephan; Maas, Matthijs Michiel; Sweijs, Tim

Artificial intelligence (AI) is on everybody’s minds these days. Most of the world’s leading companies are making massive investments in it. Governments are scrambling to catch up. Every single one of us who uses Google Search or any of the new digital assistants on our smartphones has witnessed...... suggests that the advent of artificial super-intelligence (i.e. AI that is superior across the board to human intelligence), which many experts now put firmly within the longer-term planning horizons of our DSOs, presents us with unprecedented risks but also opportunities that we have to start to explore....... The report contains an overview of the role that ‘intelligence’ - the computational part of the ability to achieve goals in the world - has played in defense and security throughout human history; a primer on AI (what it is, where it comes from and where it stands today - in both civilian and military...

Sampling the Radio Transient Universe: Studies of Pulsars and the Search for Extraterrestrial Intelligence

Science.gov (United States)

Chennamangalam, Jayanth

The transient radio universe is a relatively unexplored area of astronomy, offering a variety of phenomena, from solar and Jovian bursts, to flare stars, pulsars, and bursts of Galactic and potentially even cosmological origin. Among these, perhaps the most widely studied radio transients, pulsars are fast-spinning neutron stars that emit radio beams from their magnetic poles. In spite of over 40 years of research on pulsars, we have more questions than answers on these exotic compact objects, chief among them the nature of their emission mechanism. Nevertheless, the wealth of phenomena exhibited by pulsars make them one of the most useful astrophysical tools. With their high densities, pulsars are probes of the nature of ultra-dense matter. Characterized by their high timing stability, pulsars can be used to verify the predictions of general relativity, discover planets around them, study bodies in the solar system, and even serve as an interplanetary (and possibly some day, interstellar) navigation aid. Pulsars are also used to study the nature of the interstellar medium, much like a flashlight illuminating airborne dust in a dark room. Studies of pulsars in the Galactic center can help answer questions about the massive black hole in the region and the star formation history in its vicinity. Millisecond pulsars in globular clusters are long-lived tracers of their progenitors, low-mass X-ray binaries, and can be used to study the dynamical history of those clusters. Another source of interest in radio transient astronomy is the hitherto undetected engineered signal from extraterrestrial intelligence. The Search for Extraterrestrial Intelligence (SETI) is an ongoing attempt at discovering the presence of technological life elsewhere in the Galaxy. In this work, I present my forays into two aspects of the study of the radio transient universe---pulsars and SETI. Firstly, I describe my work on the luminosity function and population size of pulsars in the globular

OFFSETTING TOMORROW’S ADVERSARY IN A CONTESTED ENVIRONMENT: DEFENDING EXPEDITIONARY ADVANCE BASES IN 2025 AND BEYOND

Science.gov (United States)

2017-04-06

EABs enable the dispersal of key assets to cloud adversary targeting process while 8 providing the joint force proximity to the area of...environment, the denial of ISR capabilities is critical to maintaining an adversary’s uncertainty and cloud his situational awareness. To this task...James E. 2014. "Expeditionary Force 21." Expeditionary Force 21, Forward and Ready: Now and in the Future. Washington, DC: HQ USMC, March 4. Board

Search for design intelligence: A field study on the role of emotional intelligence in architectural design studios

OpenAIRE

Nazidizaji, Sajjad; Tomé, Ana; Regateiro, Francisco

2017-01-01

The design studio is the core of the architecture curriculum. Interpersonal interactions have a key role during the processes of design and critique. The influence of emotional intelligence (EQ) on interpersonal communication skills has been widely proven. This study examines the correlation between EQ and architectural design competence. To achieve this, 78 architecture students were selected via a simple random sampling method and tested using an EQ test questionnaire developed by Bradbury ...

Antenna concepts for interstellar search systems

International Nuclear Information System (INIS)

Basler, R.P.; Johnson, G.L.; Vondrak, R.R.

1977-01-01

An evaluation is made of microwave receiving systems designed to search for signals from extraterrestrial intelligence. Specific design concepts are analyzed parametrically to determine whether the optimum antenna system location is on earth, in space, or on the moon. Parameters considered include the hypothesized number of transmitting civilizations, the number of stars that must be searched to give any desired probability of receiving a signal, the antenna collecting area, the search time, the search range, and the cost. This analysis suggests that search systems based on the moon are not cost-competitive, if the search is extended only a few hundred light years from the earth, a Cyclops-type array on earth may be the most cost-effective system, for a search extending to 500 light years or more, a substantial cost and search-time advantage can be achieved with a large spherical reflector in space with multiple feeds, radio frequency interference shields can be provided for space systems, and cost can range from a few hundred million to tens of billions of dollars, depending on the parameter values assumed

Adversarial Allegiance: The Devil is in the Evidence Details, Not Just on the Witness Stand

Science.gov (United States)

McAuliff, Bradley D.; Arter, Jeana L.

2016-01-01

This study examined the potential influence of adversarial allegiance on expert testimony in a simulated child sexual abuse case. A national sample of 100 witness suggestibility experts reviewed a police interview of an alleged 5 year-old female victim. Retaining party (prosecution, defense) and interview suggestibility (low, high) varied across experts. Experts were very willing to testify, but more so for the prosecution than the defense when interview suggestibility was low and vice versa when interview suggestibility was high. Experts' anticipated testimony focused more on pro-defense aspects of the police interview and child's memory overall (negativity bias), but favored retaining party only when interview suggestibility was low. Unlike prosecution-retained experts who shifted their focus from pro-defense aspects of the case in the high suggestibility interview to pro-prosecution aspects in the low suggestibility interview, defense experts did not. Blind raters' perceptions of expert focus mirrored those findings. Despite an initial bias toward retaining party, experts' evaluations of child victim accuracy and interview quality were lower in the high versus low interview suggestibility condition only. Our data suggest that adversarial allegiance exists, that it can (but not always) influence how experts process evidence, and that it may be more likely in cases involving evidence that is not blatantly flawed. Defense experts may evaluate this type of evidence more negatively than prosecution experts due to negativity bias and positive testing strategies associated with confirmation bias. PMID:27243362

Adversarial allegiance: The devil is in the evidence details, not just on the witness stand.

Science.gov (United States)

McAuliff, Bradley D; Arter, Jeana L

2016-10-01

This study examined the potential influence of adversarial allegiance on expert testimony in a simulated child sexual abuse case. A national sample of 100 witness suggestibility experts reviewed a police interview of an alleged 5-year-old female victim. Retaining party (prosecution, defense) and interview suggestibility (low, high) varied across experts. Experts were very willing to testify, but more so for the prosecution than the defense when interview suggestibility was low and vice versa when interview suggestibility was high. Experts' anticipated testimony focused more on prodefense aspects of the police interview and child's memory overall (negativity bias), but favored retaining party only when interview suggestibility was low. Prosecution-retained experts shifted their focus from prodefense aspects of the case in the high suggestibility interview to proprosecution aspects in the low suggestibility interview; defense experts did not. Blind raters' perceptions of expert focus mirrored those findings. Despite an initial bias toward retaining party, experts' evaluations of child victim accuracy and police interview quality were lower in the high versus low interview suggestibility condition only. Our data suggest that adversarial allegiance exists, that it can (but not always) influence how experts process evidence, and that it may be more likely in cases involving evidence that is not blatantly flawed. Defense experts may evaluate this type of evidence more negatively than prosecution experts because of negativity bias and positive testing strategies associated with confirmation bias. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

OAST Space Theme Workshop. Volume 2: Theme summary. 3: Search for extraterrestrial intelligence (no. 9). A: Theme statement. B. 26 April 1976 presentation. C. Summary. D. Newer initiatives (form 4). E. Initiative actions (form 5)

Science.gov (United States)

1976-01-01

Preliminary (1977-1983), intermediate (1982-1988), and long term (1989+) phases of the search for extraterrestrial intelligence (SETI) program are examined as well as the benefits to be derived in radioastronomy and the problems to be surmounted in radio frequency interference. The priorities, intrinsic value, criteria, and strategy for the search are discussed for both terrestrial and lunar-based CYCLOPS and for a space SETI system located at lunar liberation point L4. New initiatives related to antenna independent technology, multichannel analyzers, and radio frequency interference shielding are listed. Projected SETI program costs are included.

Stock Market Prediction on High-Frequency Data Using Generative Adversarial Nets

Directory of Open Access Journals (Sweden)

Xingyu Zhou

2018-01-01

Full Text Available Stock price prediction is an important issue in the financial world, as it contributes to the development of effective strategies for stock exchange transactions. In this paper, we propose a generic framework employing Long Short-Term Memory (LSTM and convolutional neural network (CNN for adversarial training to forecast high-frequency stock market. This model takes the publicly available index provided by trading software as input to avoid complex financial theory research and difficult technical analysis, which provides the convenience for the ordinary trader of nonfinancial specialty. Our study simulates the trading mode of the actual trader and uses the method of rolling partition training set and testing set to analyze the effect of the model update cycle on the prediction performance. Extensive experiments show that our proposed approach can effectively improve stock price direction prediction accuracy and reduce forecast error.

Competitive intelligence as an enabler for firm competitiveness: An overview

Directory of Open Access Journals (Sweden)

Alexander Maune

2014-06-01

Full Text Available The purpose of this article is to provide an overview, from literature, about how competitive intelligence can be an enabler towards a firm’s competitiveness. This overview is done under the background of intense global competition that firms are currently experiencing. This paper used a qualitative content analysis as a data collection methodology on all identified journal articles on competitive intelligence and firm competitiveness. To identify relevant literature, academic databases and search engines were used. Moreover, a review of references in related studies led to more relevant sources, the references of which were further reviewed and analysed. To ensure reliability and trustworthiness, peer-reviewed journal articles and triangulation were used. The paper found that competitive intelligence is an important enabler of firm competitiveness. The findings from this paper will assist business managers to understand and improve their outlook of competitive intelligence as an enabler of firm competitiveness and will be of great academic value.

Patient behavior and the benefits of artificial intelligence: the perils of "dangerous" literacy and illusory patient empowerment.

Science.gov (United States)

Schulz, Peter J; Nakamoto, Kent

2013-08-01

Artificial intelligence can provide important support of patient health. However, limits to realized benefits can arise as patients assume an active role in their health decisions. Distinguishing the concepts of health literacy and patient empowerment, we analyze conditions that bias patient use of the Internet and limit access to and impact of artificial intelligence. Improving health literacy in the face of the Internet requires significant guidance. Patients must be directed toward the appropriate tools and also provided with key background knowledge enabling them to use the tools and capitalize on the artificial intelligence technology. Benefits of tools employing artificial intelligence to promote health cannot be realized without recognizing and addressing the patients' desires, expectations, and limitations that impact their Internet behavior. In order to benefit from artificial intelligence, patients need a substantial level of background knowledge and skill in information use-i.e., health literacy. It is critical that health professionals respond to patient search for information on the Internet, first by guiding their search to relevant, authoritative, and responsive sources, and second by educating patients about how to interpret the information they are likely to encounter. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A Systematic Review of Physician Leadership and Emotional Intelligence

Science.gov (United States)

Mintz, Laura Janine; Stoller, James K.

2014-01-01

Objective This review evaluates the current understanding of emotional intelligence (EI) and physician leadership, exploring key themes and areas for future research. Literature Search We searched the literature using PubMed, Google Scholar, and Business Source Complete for articles published between 1990 and 2012. Search terms included physician and leadership, emotional intelligence, organizational behavior, and organizational development. All abstracts were reviewed. Full articles were evaluated if they addressed the connection between EI and physician leadership. Articles were included if they focused on physicians or physicians-in-training and discussed interventions or recommendations. Appraisal and Synthesis We assessed articles for conceptual rigor, study design, and measurement quality. A thematic analysis categorized the main themes and findings of the articles. Results The search produced 3713 abstracts, of which 437 full articles were read and 144 were included in this review. Three themes were identified: (1) EI is broadly endorsed as a leadership development strategy across providers and settings; (2) models of EI and leadership development practices vary widely; and (3) EI is considered relevant throughout medical education and practice. Limitations of the literature were that most reports were expert opinion or observational and studies used several different tools for measuring EI. Conclusions EI is widely endorsed as a component of curricula for developing physician leaders. Research comparing practice models and measurement tools will critically advance understanding about how to develop and nurture EI to enhance leadership skills in physicians throughout their careers. PMID:24701306

Protecting Clock Synchronization: Adversary Detection through Network Monitoring

Directory of Open Access Journals (Sweden)

Elena Lisova

2016-01-01

Full Text Available Nowadays, industrial networks are often used for safety-critical applications with real-time requirements. Such applications usually have a time-triggered nature with message scheduling as a core property. Scheduling requires nodes to share the same notion of time, that is, to be synchronized. Therefore, clock synchronization is a fundamental asset in real-time networks. However, since typical standards for clock synchronization, for example, IEEE 1588, do not provide the required level of security, it raises the question of clock synchronization protection. In this paper, we identify a way to break synchronization based on the IEEE 1588 standard, by conducting a man-in-the-middle (MIM attack followed by a delay attack. A MIM attack can be accomplished through, for example, Address Resolution Protocol (ARP poisoning. Using the AVISPA tool, we evaluate the potential to perform a delay attack using ARP poisoning and analyze its consequences showing both that the attack can, indeed, break clock synchronization and that some design choices, such as a relaxed synchronization condition mode, delay bounding, and using knowledge of environmental conditions, can make the network more robust/resilient against these kinds of attacks. Lastly, a Configuration Agent is proposed to monitor and detect anomalies introduced by an adversary performing attacks targeting clock synchronization.

Web Search Services in 1998: Trends and Challenges.

Science.gov (United States)

Feldman, Susan

1998-01-01

Charts the trends and challenges that 1998 has brought to popular search engines such as AltaVista, Excite, HotBot, Infoseek, Lycos, and Northern Light. Highlights testing strategies used, use of real (not artificial) intelligence, innovations, online market pressures, barriers to use, and tips and recommendations. (AEF)

Generative adversarial networks for brain lesion detection

Science.gov (United States)

Alex, Varghese; Safwan, K. P. Mohammed; Chennamsetty, Sai Saketh; Krishnamurthi, Ganapathy

2017-02-01

Manual segmentation of brain lesions from Magnetic Resonance Images (MRI) is cumbersome and introduces errors due to inter-rater variability. This paper introduces a semi-supervised technique for detection of brain lesion from MRI using Generative Adversarial Networks (GANs). GANs comprises of a Generator network and a Discriminator network which are trained simultaneously with the objective of one bettering the other. The networks were trained using non lesion patches (n=13,000) from 4 different MR sequences. The network was trained on BraTS dataset and patches were extracted from regions excluding tumor region. The Generator network generates data by modeling the underlying probability distribution of the training data, (PData). The Discriminator learns the posterior probability P (Label Data) by classifying training data and generated data as "Real" or "Fake" respectively. The Generator upon learning the joint distribution, produces images/patches such that the performance of the Discriminator on them are random, i.e. P (Label Data = GeneratedData) = 0.5. During testing, the Discriminator assigns posterior probability values close to 0.5 for patches from non lesion regions, while patches centered on lesion arise from a different distribution (PLesion) and hence are assigned lower posterior probability value by the Discriminator. On the test set (n=14), the proposed technique achieves whole tumor dice score of 0.69, sensitivity of 91% and specificity of 59%. Additionally the generator network was capable of generating non lesion patches from various MR sequences.

The security analyzer, a security analyzer program written in Prolog

International Nuclear Information System (INIS)

Zimmerman, B.D.; Densley, P.J.; Carlson, R.L.

1987-01-01

A technique has been developed to characterize a nuclear facility and measure the strengths and weaknesses of the physical protection system. It utilizes the artificial intelligence capabilities available in the prolog programming language to probe a facility's defenses and find potential attack paths that meet designated search criteria. As sensors or barriers become inactive due to maintenance, failure, or inclement weather conditions, the protection system can rapidly be reanalyzed to discover weaknesses that would need to be strengthened by alternative means. Conversely, proposed upgrades and enhancements can be easily entered into the database and their effect measured against a variety of potential adversary attacks. Thus the security analyzer is a tool that aids the protection planner as well as the protection operations staff

An Integrated Conceptual Environment based on Collective Intelligence and Distributed Artificial Intelligence for Connecting People on Problem Solving

Directory of Open Access Journals (Sweden)

Vasile MAZILESCU

2012-12-01

Full Text Available This paper aims to analyze the different forms of intelligence within organizations in a systemic and inclusive vision, in order to conceptualize an integrated environment based on Distributed Artificial Intelligence (DAI and Collective Intelligence (CI. In this way we effectively shift the classical approaches of connecting people with people using collaboration tools (which allow people to work together, such as videoconferencing or email, groupware in virtual space, forums, workflow, of connecting people with a series of content management knowledge (taxonomies and documents classification, ontologies or thesauri, search engines, portals, to the current approaches of connecting people on the use (automatic of operational knowledge to solve problems and make decisions based on intellectual cooperation. The best way to use collective intelligence is based on knowledge mobilization and semantic technologies. We must not let computers to imitate people but to support people think and develop their ideas within a group. CI helps people to think together, while DAI tries to support people so as to limit human error. Within an organization, to manage CI is to combine instruments like Semantic Technologies (STs, knowledge mobilization methods for developing Knowledge Management (KM strategies, and the processes that promote connection and collaboration between individual minds in order to achieve collective objectives, to perform a task or to solve increasingly economic complex problems.

Intelligence as the efficiency of cue-driven retrieval from secondary memory.

Science.gov (United States)

Liesefeld, Heinrich René; Hoffmann, Eugenia; Wentura, Dirk

2016-01-01

Complex-span (working-memory-capacity) tasks are among the most successful predictors of intelligence. One important contributor to this relationship is the ability to efficiently employ cues for the retrieval from secondary memory. Presumably, intelligent individuals can considerably restrict their memory search sets by using such cues and can thereby improve recall performance. We here test this assumption by experimentally manipulating the validity of retrieval cues. When memoranda are drawn from the same semantic category on two successive trials of a verbal complex-span task, the category is a very strong retrieval cue on its first occurrence (strong-cue trial) but loses some of its validity on its second occurrence (weak-cue trial). If intelligent individuals make better use of semantic categories as retrieval cues, their recall accuracy suffers more from this loss of cue validity. Accordingly, our results show that less variance in intelligence is explained by recall accuracy on weak-cue compared with strong-cue trials.

Intelligence after traumatic brain injury: meta-analysis of outcomes and prognosis.

Science.gov (United States)

Königs, M; Engenhorst, P J; Oosterlaan, J

2016-01-01

Worldwide, 54-60 million individuals sustain traumatic brain injury (TBI) each year. This meta-analysis aimed to quantify intelligence impairments after TBI and to determine the value of age and injury severity in the prognosis of TBI. An electronic database search identified 81 relevant peer-reviewed articles encompassing 3890 patients. Full-scale IQ (FSIQ), performance IQ (PIQ) and verbal IQ (VIQ) impairments were quantified (Cohen's d) for patients with mild, moderate and severe TBI in the subacute phase of recovery and the chronic phase. Meta-regressions explored prognostic values of age and injury severity measures for intelligence impairments. The results showed that, in the subacute phase, FSIQ impairments were absent for patients with mild TBI, medium-sized for patients with moderate TBI (d = -0.61, P intelligence impairments, where children may have better recovery from mild TBI and poorer recovery from severe TBI than adults. Injury severity measures predict intelligence impairments and do not outperform one another. © 2015 EAN.

Towards an Intelligent Tutor for Mathematical Proofs

Directory of Open Access Journals (Sweden)

Serge Autexier

2012-02-01

Full Text Available Computer-supported learning is an increasingly important form of study since it allows for independent learning and individualized instruction. In this paper, we discuss a novel approach to developing an intelligent tutoring system for teaching textbook-style mathematical proofs. We characterize the particularities of the domain and discuss common ITS design models. Our approach is motivated by phenomena found in a corpus of tutorial dialogs that were collected in a Wizard-of-Oz experiment. We show how an intelligent tutor for textbook-style mathematical proofs can be built on top of an adapted assertion-level proof assistant by reusing representations and proof search strategies originally developed for automated and interactive theorem proving. The resulting prototype was successfully evaluated on a corpus of tutorial dialogs and yields good results.

What it feels like to be me: Linking emotional intelligence, identity, and intimacy.

Science.gov (United States)

Maher, Hemali; Winston, Christine N; S, Usha Rani

2017-04-01

The search for the self and for an intimate other are the normative tasks of adolescence and early adulthood. The role of emotions in the resolution of these developmental tasks, however, remains largely under-studied, especially in non-western cultures. The objective of the present study, therefore, was to examine the relationships between emotional intelligence, identity, and intimacy, among Indian adolescents. Differences across genders (boys vs. girls) and types of school (gender segregated vs. integrated) were also explored. A sample of 486 adolescents completed measures of emotional intelligence, identity, and intimacy. Girls scored higher than boys on intimacy, and those from segregated schools scored higher, than those from integrated schools, on emotional intelligence. Significant relationships emerged between emotional intelligence, and identity and intimacy, and were invariant across the groups. These findings underscore the pivotal role that emotional intelligence plays in healthy adolescent development, irrespective of personal and environmental variables. Copyright © 2017 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Intelligent cognitive radio jamming - a game-theoretical approach

Science.gov (United States)

Dabcevic, Kresimir; Betancourt, Alejandro; Marcenaro, Lucio; Regazzoni, Carlo S.

2014-12-01

Cognitive radio (CR) promises to be a solution for the spectrum underutilization problems. However, security issues pertaining to cognitive radio technology are still an understudied topic. One of the prevailing such issues are intelligent radio frequency (RF) jamming attacks, where adversaries are able to exploit on-the-fly reconfigurability potentials and learning mechanisms of cognitive radios in order to devise and deploy advanced jamming tactics. In this paper, we use a game-theoretical approach to analyze jamming/anti-jamming behavior between cognitive radio systems. A non-zero-sum game with incomplete information on an opponent's strategy and payoff is modelled as an extension of Markov decision process (MDP). Learning algorithms based on adaptive payoff play and fictitious play are considered. A combination of frequency hopping and power alteration is deployed as an anti-jamming scheme. A real-life software-defined radio (SDR) platform is used in order to perform measurements useful for quantifying the jamming impacts, as well as to infer relevant hardware-related properties. Results of these measurements are then used as parameters for the modelled jamming/anti-jamming game and are compared to the Nash equilibrium of the game. Simulation results indicate, among other, the benefit provided to the jammer when it is employed with the spectrum sensing algorithm in proactive frequency hopping and power alteration schemes.

Categorization of web pages - Performance enhancement to search engine

Digital Repository Service at National Institute of Oceanography (India)

Lakshminarayana, S.

of Artificial Intelligence, Volume III. Los Altos, CA.: William Kaufmann. pp 1-74. 18. Brin, S. & Page, L. (1998). The anatomy of a large scale hyper-textual web search engine. In Proceedings of the seventh World Wide Web conference, Brisbane, Australia. 19...

The Foreign Intelligence Surveillance Act: An Overview of the Statutory Framework and Recent Judicial Decisions

National Research Council Canada - National Science Library

Bazan, Elizabeth B

2004-01-01

.... Subsequent legislation expanded federal laws dealing with foreign intelligence gathering to address physical searches, pen registers and trap and trace devices, and access to certain business records...

The Foreign Intelligence Surveillance Act: An Overview of the Statutory Framework and Recent Judicial Decisions

National Research Council Canada - National Science Library

Bazan, Elizabeth B

2005-01-01

.... Subsequent legislation expanded federal laws dealing with foreign intelligence gathering to address physical searches, pen registers and trap and trace devices, and access to certain business records...

How to Improve the ROK and U.S. Military Alliance Against North Korea’s Threats to Cyberspace: Lessons From NATO’s Defense Cooperation

Science.gov (United States)

2017-12-01

North Korea’s policy. For instance, North Korea has been interested in developing technology like Artificial Intelligence (AI) and has made efforts to...No. 8 NPT Nuclear Proliferation Treaty OSINT Open Source intelligence RGB Reconnaissance General Bureau (of North Korea) ROK Republic of Korea... Cybersecurity is linked directly to national security in the ROK. Although challenging for the military, as the primary target of adversaries, the

A New Dimension of Business Intelligence: Location-based Intelligence

OpenAIRE

Zeljko Panian

2012-01-01

Through the course of this paper we define Locationbased Intelligence (LBI) which is outgrowing from process of amalgamation of geolocation and Business Intelligence. Amalgamating geolocation with traditional Business Intelligence (BI) results in a new dimension of BI named Location-based Intelligence. LBI is defined as leveraging unified location information for business intelligence. Collectively, enterprises can transform location data into business intelligence applic...

Intelligence analysis – the royal discipline of Competitive Intelligence

Directory of Open Access Journals (Sweden)

František Bartes

2011-01-01

Full Text Available The aim of this article is to propose work methodology for Competitive Intelligence teams in one of the intelligence cycle’s specific area, in the so-called “Intelligence Analysis”. Intelligence Analysis is one of the stages of the Intelligence Cycle in which data from both the primary and secondary research are analyzed. The main result of the effort is the creation of added value for the information collected. Company Competiitve Intelligence, correctly understood and implemented in business practice, is the “forecasting of the future”. That is forecasting about the future, which forms the basis for strategic decisions made by the company’s top management. To implement that requirement in corporate practice, the author perceives Competitive Intelligence as a systemic application discipline. This approach allows him to propose a “Work Plan” for Competitive Intelligence as a fundamental standardized document to steer Competitive Intelligence team activities. The author divides the Competitive Intelligence team work plan into five basic parts. Those parts are derived from the five-stage model of the intelligence cycle, which, in the author’s opinion, is more appropriate for complicated cases of Competitive Intelligence.

Spiritual Intelligence, Emotional Intelligence and Auditor’s Performance

OpenAIRE

Hanafi, Rustam

2010-01-01

The objective of this research was to investigate empirical evidence about influence audi-tor spiritual intelligence on the performance with emotional intelligence as a mediator variable. Linear regression models are developed to examine the hypothesis and path analysis. The de-pendent variable of each model is auditor performance, whereas the independent variable of model 1 is spiritual intelligence, of model 2 are emotional intelligence and spiritual intelligence. The parameters were estima...

Mothers' power assertion; children's negative, adversarial orientation; and future behavior problems in low-income families: early maternal responsiveness as a moderator of the developmental cascade.

Science.gov (United States)

Kim, Sanghag; Kochanska, Grazyna

2015-02-01

Parental power assertion, a key dimension of family environment, generally sets in motion detrimental developmental cascades; however, evidence suggests that other qualities of parenting, such as responsiveness, can significantly moderate those processes. Mechanisms that account for such moderating effects are not fully understood. We propose a conceptual model of processes linking parental power assertion, parental responsiveness, children's negative, adversarial, rejecting orientation toward the parent, and behavior problems. We test that model in a short-term longitudinal design involving 186 low-income, ethnically diverse mothers and their toddlers. When children were 30 months, the dyads were observed in multiple, lengthy, naturalistic laboratory interactions to assess behaviorally mothers' responsiveness and their power-assertive control style. At 33 months, we observed behavioral indicators of children's negative, adversarial, rejecting orientation toward the mothers in several naturalistic and standardized paradigms. At 40 months, mothers rated children's behavior problems. The proposed moderated mediation sequence, tested using a new approach, PROCESS (Hayes, 2013), was supported. The indirect effect from maternal power assertion to children's negative, adversarial orientation to future behavior problems was present when mothers' responsiveness was either low or average but absent when mothers were highly responsive. This study elucidates a potential process that may link parental power assertion with behavior problems and highlights how positive aspects of parenting can moderate this process and defuse maladaptive developmental cascades. It also suggests possible targets for parenting intervention and prevention efforts. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Cutting out the middleman: physicians can contract directly with employers--a viable alternative to adversarial managed care agreements.

Science.gov (United States)

Lester, Howard

2002-01-01

HMOs, PPOs, and other managed care "middlemen" control the means by which most physicians do business with employers. As physicians face dwindling reimbursements, greater practice restrictions, and increased pressure to sign adversarial middleman contracts, interest in direct contracting has grown. This article introduces direct contracting as an important alternative to commercial managed care agreements; cites the key advantages and process of direct contracting; and offers practical recommendations for helping physician practices successfully negotiate direct physician/employer agreements.

Convergence Analysis of a Class of Computational Intelligence Approaches

Directory of Open Access Journals (Sweden)

Junfeng Chen

2013-01-01

Full Text Available Computational intelligence approaches is a relatively new interdisciplinary field of research with many promising application areas. Although the computational intelligence approaches have gained huge popularity, it is difficult to analyze the convergence. In this paper, a computational model is built up for a class of computational intelligence approaches represented by the canonical forms of generic algorithms, ant colony optimization, and particle swarm optimization in order to describe the common features of these algorithms. And then, two quantification indices, that is, the variation rate and the progress rate, are defined, respectively, to indicate the variety and the optimality of the solution sets generated in the search process of the model. Moreover, we give four types of probabilistic convergence for the solution set updating sequences, and their relations are discussed. Finally, the sufficient conditions are derived for the almost sure weak convergence and the almost sure strong convergence of the model by introducing the martingale theory into the Markov chain analysis.

Search-based model identification of smart-structure damage

Science.gov (United States)

Glass, B. J.; Macalou, A.

1991-01-01

This paper describes the use of a combined model and parameter identification approach, based on modal analysis and artificial intelligence (AI) techniques, for identifying damage or flaws in a rotating truss structure incorporating embedded piezoceramic sensors. This smart structure example is representative of a class of structures commonly found in aerospace systems and next generation space structures. Artificial intelligence techniques of classification, heuristic search, and an object-oriented knowledge base are used in an AI-based model identification approach. A finite model space is classified into a search tree, over which a variant of best-first search is used to identify the model whose stored response most closely matches that of the input. Newly-encountered models can be incorporated into the model space. This adaptativeness demonstrates the potential for learning control. Following this output-error model identification, numerical parameter identification is used to further refine the identified model. Given the rotating truss example in this paper, noisy data corresponding to various damage configurations are input to both this approach and a conventional parameter identification method. The combination of the AI-based model identification with parameter identification is shown to lead to smaller parameter corrections than required by the use of parameter identification alone.

An intelligent sales assistant for configurable products

OpenAIRE

Molina, Martin

2001-01-01

Some of the recent proposals of web-based applications are oriented to provide advanced search services through virtual shops. Within this context, this paper proposes an advanced type of software application that simulates how a sales assistant dialogues with a consumer to dynamically configure a product according to particular needs. The paper presents the general knowl- edge model that uses artificial intelligence and knowledge-based techniques to simulate the configuration process. Finall...

Intelligence analysis – the royal discipline of Competitive Intelligence

OpenAIRE

František Bartes

2011-01-01

The aim of this article is to propose work methodology for Competitive Intelligence teams in one of the intelligence cycle’s specific area, in the so-called “Intelligence Analysis”. Intelligence Analysis is one of the stages of the Intelligence Cycle in which data from both the primary and secondary research are analyzed. The main result of the effort is the creation of added value for the information collected. Company Competiitve Intelligence, correctly understood and implemented in busines...

An FMRI-compatible Symbol Search task.

Science.gov (United States)

Liebel, Spencer W; Clark, Uraina S; Xu, Xiaomeng; Riskin-Jones, Hannah H; Hawkshead, Brittany E; Schwarz, Nicolette F; Labbe, Donald; Jerskey, Beth A; Sweet, Lawrence H

2015-03-01

Our objective was to determine whether a Symbol Search paradigm developed for functional magnetic resonance imaging (FMRI) is a reliable and valid measure of cognitive processing speed (CPS) in healthy older adults. As all older adults are expected to experience cognitive declines due to aging, and CPS is one of the domains most affected by age, establishing a reliable and valid measure of CPS that can be administered inside an MR scanner may prove invaluable in future clinical and research settings. We evaluated the reliability and construct validity of a newly developed FMRI Symbol Search task by comparing participants' performance in and outside of the scanner and to the widely used and standardized Symbol Search subtest of the Wechsler Adult Intelligence Scale (WAIS). A brief battery of neuropsychological measures was also administered to assess the convergent and discriminant validity of the FMRI Symbol Search task. The FMRI Symbol Search task demonstrated high test-retest reliability when compared to performance on the same task administered out of the scanner (r=.791; pSymbol Search (r=.717; pSymbol Search task were also observed. The FMRI Symbol Search task is a reliable and valid measure of CPS in healthy older adults and exhibits expected sensitivity to the effects of age on CPS performance.

A World Wide Web Region-Based Image Search Engine

DEFF Research Database (Denmark)

Kompatsiaris, Ioannis; Triantafyllou, Evangelia; Strintzis, Michael G.

2001-01-01

In this paper the development of an intelligent image content-based search engine for the World Wide Web is presented. This system will offer a new form of media representation and access of content available in WWW. Information Web Crawlers continuously traverse the Internet and collect images...

A Functional Programming Approach to AI Search Algorithms

Science.gov (United States)

Panovics, Janos

2012-01-01

The theory and practice of search algorithms related to state-space represented problems form the major part of the introductory course of Artificial Intelligence at most of the universities and colleges offering a degree in the area of computer science. Students usually meet these algorithms only in some imperative or object-oriented language…

Constructing an Intelligent Patent Network Analysis Method

Directory of Open Access Journals (Sweden)

Chao-Chan Wu

2012-11-01

Full Text Available Patent network analysis, an advanced method of patent analysis, is a useful tool for technology management. This method visually displays all the relationships among the patents and enables the analysts to intuitively comprehend the overview of a set of patents in the field of the technology being studied. Although patent network analysis possesses relative advantages different from traditional methods of patent analysis, it is subject to several crucial limitations. To overcome the drawbacks of the current method, this study proposes a novel patent analysis method, called the intelligent patent network analysis method, to make a visual network with great precision. Based on artificial intelligence techniques, the proposed method provides an automated procedure for searching patent documents, extracting patent keywords, and determining the weight of each patent keyword in order to generate a sophisticated visualization of the patent network. This study proposes a detailed procedure for generating an intelligent patent network that is helpful for improving the efficiency and quality of patent analysis. Furthermore, patents in the field of Carbon Nanotube Backlight Unit (CNT-BLU were analyzed to verify the utility of the proposed method.

A computer model for identifying security system upgrades

International Nuclear Information System (INIS)

Lamont, A.

1988-01-01

This paper describes a prototype safeguards analysis tool that automatically identifies system weaknesses against an insider adversary and suggest possible upgrades to improve the probability that the adversary will be detected. The tool is based on this premise: as the adversary acts, he or she creates a set of facts that can be detected by safeguards components. Whenever an adversary's planned set of actions create a set of facts which the security personnel would consider irregular or unusual, we can improve the security system by implementing safeguards that detect those facts. Therefore, an intelligent computer program can suggest upgrades to the facility if we construct a knowledge base that contains information about: (1) the facts created by each possible adversary action, (2) the facts that each possible safeguard can detect, and (3) groups of facts which will be considered irregular whenever they occur together. The authors describe the structure of the knowledge base and show how the above information can be represented in it. They also describe the procedures that a computer program can use to identify missing or weak safeguards and to suggest upgrades

Combined semantic and similarity search in medical image databases

Science.gov (United States)

Seifert, Sascha; Thoma, Marisa; Stegmaier, Florian; Hammon, Matthias; Kramer, Martin; Huber, Martin; Kriegel, Hans-Peter; Cavallaro, Alexander; Comaniciu, Dorin

2011-03-01

The current diagnostic process at hospitals is mainly based on reviewing and comparing images coming from multiple time points and modalities in order to monitor disease progression over a period of time. However, for ambiguous cases the radiologist deeply relies on reference literature or second opinion. Although there is a vast amount of acquired images stored in PACS systems which could be reused for decision support, these data sets suffer from weak search capabilities. Thus, we present a search methodology which enables the physician to fulfill intelligent search scenarios on medical image databases combining ontology-based semantic and appearance-based similarity search. It enabled the elimination of 12% of the top ten hits which would arise without taking the semantic context into account.

Mothers’ Power Assertion, Children’s Negative, Adversarial Orientation, and Future Behavior Problems in Low-Income Families: Early Maternal Responsiveness as a Moderator of the Developmental Cascade

Science.gov (United States)

Kim, Sanghag; Kochanska, Grazyna

2014-01-01

Parental power assertion, a key dimension of family environment, generally sets in motion detrimental developmental cascades; however, evidence suggests that other qualities of parenting, such as responsiveness, can significantly moderate those processes. Mechanisms that account for such moderating effects are not fully understood. We propose a conceptual model of processes linking parental power assertion, parental responsiveness, children’s negative, adversarial, rejecting orientation toward the parent, and behavior problems. We test that model in a short-term longitudinal design involving 186 low-income, ethnically diverse mothers and their toddlers. When children were 30 months, the dyads were observed in multiple, lengthy, naturalistic laboratory interactions to assess behaviorally mothers’ responsiveness and their power-assertive control style. At 33 months, we observed behavioral indicators of children’s negative, adversarial, rejecting orientation toward the mothers in several naturalistic and standardized paradigms. At 40 months, mothers rated children’s behavior problems. The proposed moderated mediation sequence, tested using a new approach, PROCESS (Hayes, 2013), was supported. The indirect effect from maternal power assertion to children’s negative, adversarial orientation to future behavior problems was present when mothers’ responsiveness was either low or average but absent when mothers were highly responsive. This study elucidates a potential process that may link parental power assertion with behavior problems and highlights how positive aspects of parenting can moderate this process and defuse maladaptive developmental cascades. It also suggests possible targets for parenting intervention and prevention efforts. PMID:25401483

Approaches to the study of intelligence

Science.gov (United States)

Norman, Donald A.

1991-01-01

A survey and an evaluation are conducted for the Rosenbloom et al. (1991) 'SOAR' model of intelligence, both as found in humans and in prospective AI systems, which views it as a representational system for goal-oriented symbolic activity based on a physical symbol system. Attention is given to SOAR's implications for semantic and episodic memory, symbol processing, and search within a uniform problem space; also noted are the relationships of SOAR to competing AI schemes, and its potential usefulness as a theoretical tool for cognitive psychology.

Intelligent video surveillance systems and technology

CERN Document Server

Ma, Yunqian

2009-01-01

From the streets of London to subway stations in New York City, hundreds of thousands of surveillance cameras ubiquitously collect hundreds of thousands of videos, often running 24/7. How can such vast volumes of video data be stored, analyzed, indexed, and searched? How can advanced video analysis and systems autonomously recognize people and detect targeted activities real-time? Collating and presenting the latest information Intelligent Video Surveillance: Systems and Technology explores these issues, from fundamentals principle to algorithmic design and system implementation.An Integrated

How People Interact with Technology based on Natural and Artificial Intelligence

Directory of Open Access Journals (Sweden)

Vasile MAZILESCU

2017-04-01

Full Text Available This paper aims to analyse the different forms of intelligence within organizations in a systemic and inclusive vision, in order to design an integrated environment based on Artificial Intelligence (AI and Collective Intelligence (CI. This way we effectively shift the classical approaches of connecting people with people using collaboration tools (which allow people to work together, such as videoconferencing or email, groupware in virtual space, forums, workflow, of connecting people with a series of content management knowledge (taxonomies and documents classification, ontologies or thesauri, search engines, portals, to the current approaches of connecting people on the use (automatic of operational knowledge to solve problems and make decisions based on intellectual cooperation. Few technologies have the big potential to review how we live, move, and work. Artificial intelligence (AI is nowdays equivalent of electricity and the Internet. AI is expected to bring massive shifts in how people perceive and interact with technology, with machines performing a wider range of tasks, in many cases doing a better job than humans.

Web Intelligence and Artificial Intelligence in Education

Science.gov (United States)

Devedzic, Vladan

2004-01-01

This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

Artificial Intelligence and Moral intelligence

Directory of Open Access Journals (Sweden)

Laura Pana

2008-07-01

Full Text Available We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined, even unpredictable conduct, 2- entities endowed with diverse or even multiple intelligence forms, like moral intelligence, 3- open and, even, free-conduct performing systems (with specific, flexible and heuristic mechanisms and procedures of decision, 4 – systems which are open to education, not just to instruction, 5- entities with “lifegraphy”, not just “stategraphy”, 6- equipped not just with automatisms but with beliefs (cognitive and affective complexes, 7- capable even of reflection (“moral life” is a form of spiritual, not just of conscious activity, 8 – elements/members of some real (corporal or virtual community, 9 – cultural beings: free conduct gives cultural value to the action of a ”natural” or artificial being. Implementation of such characteristics does not necessarily suppose efforts to design, construct and educate machines like human beings. The human moral code is irremediably imperfect: it is a morality of preference, of accountability (not of responsibility and a morality of non-liberty, which cannot be remedied by the invention of ethical systems, by the circulation of ideal values and by ethical (even computing education. But such an imperfect morality needs perfect instruments for its implementation: applications of special logic fields; efficient psychological (theoretical and technical attainments to endow the machine not just with intelligence, but with conscience and even spirit; comprehensive technical

Towards a universal competitive intelligence process model

Directory of Open Access Journals (Sweden)

Rene Pellissier

2013-08-01

Full Text Available Background: Competitive intelligence (CI provides actionable intelligence, which provides a competitive edge in enterprises. However, without proper process, it is difficult to develop actionable intelligence. There are disagreements about how the CI process should be structured. For CI professionals to focus on producing actionable intelligence, and to do so with simplicity, they need a common CI process model.Objectives: The purpose of this research is to review the current literature on CI, to look at the aims of identifying and analysing CI process models, and finally to propose a universal CI process model.Method: The study was qualitative in nature and content analysis was conducted on all identified sources establishing and analysing CI process models. To identify relevant literature, academic databases and search engines were used. Moreover, a review of references in related studies led to more relevant sources, the references of which were further reviewed and analysed. To ensure reliability, only peer-reviewed articles were used.Results: The findings reveal that the majority of scholars view the CI process as a cycle of interrelated phases. The output of one phase is the input of the next phase.Conclusion: The CI process is a cycle of interrelated phases. The output of one phase is the input of the next phase. These phases are influenced by the following factors: decision makers, process and structure, organisational awareness and culture, and feedback.

Naturalist Intelligence Among the Other Multiple Intelligences [In Bulgarian

Directory of Open Access Journals (Sweden)

R. Genkov

2007-09-01

Full Text Available The theory of multiple intelligences was presented by Gardner in 1983. The theory was revised later (1999 and among the other intelligences a naturalist intelligence was added. The criteria for distinguishing of the different types of intelligences are considered. While Gardner restricted the analysis of the naturalist intelligence with examples from the living nature only, the present paper considered this problem on wider background including objects and persons of the natural sciences.

VAR control in distribution systems by using artificial intelligence techniques

Energy Technology Data Exchange (ETDEWEB)

Golkar, M.A. [Curtin Univ. of Technology, Sarawak (Malaysia). School of Engineering and Science

2005-07-01

This paper reviewed artificial intelligence techniques used in VAR control systems. Reactive power controls in distribution systems were also reviewed. While artificial intelligence methods are widely used in power control systems, the techniques require extensive human knowledge bases and experiences in order to operate correctly. Expert systems use knowledge and interface procedures to solve problems that often require human expertise. Expert systems often cause knowledge bottlenecks as they are unable to learn or adopt to new situations. While neural networks possess learning ability, they are computationally expensive. However, test results in recent neural network studies have demonstrated that they work well in a variety of loading conditions. Fuzzy logic techniques are used to accurately represent the operational constraints of power systems. Fuzzy logic has an advantage over other artificial intelligence techniques as it is able to remedy uncertainties in data. Evolutionary computing algorithms use probabilistic transition rules which can search complicated data to determine optimal constraints and parameters. Over 95 per cent of all papers published on power systems use genetic algorithms. It was concluded that hybrid systems using various artificial intelligence techniques are now being used by researchers. 69 refs.

Innovative issues in intelligent systems

CERN Document Server

Yager, Ronald; Kacprzyk, Janusz; Jotsov, Vladimir

2016-01-01

This book presents a broad variety of different contemporary IT methods and applications in Intelligent Systems is displayed. Every book chapter represents a detailed, specific, far reaching and original re-search in a respective scientific and practical field. However, all of the chapters share the common point of strong similarity in a sense of being innovative, applicable and mutually compatible with each other. In other words, the methods from the different chapters can be viewed as bricks for building the next generation “thinking machines” as well as for other futuristic logical applications that are rapidly changing our world nowadays.

Artificial Intelligence and Expert Systems Research and Their Possible Impact on Information Science.

Science.gov (United States)

Borko, Harold

1985-01-01

Defines artificial intelligence (AI) and expert systems; describes library applications utilizing AI to automate creation of document representations, request formulations, and design and modify search strategies for information retrieval systems; discusses expert system development for information services; and reviews impact of these…

Prediction of Compressional, Shear, and Stoneley Wave Velocities from Conventional Well Log Data Using a Committee Machine with Intelligent Systems

Science.gov (United States)

Asoodeh, Mojtaba; Bagheripour, Parisa

2012-01-01

Measurement of compressional, shear, and Stoneley wave velocities, carried out by dipole sonic imager (DSI) logs, provides invaluable data in geophysical interpretation, geomechanical studies and hydrocarbon reservoir characterization. The presented study proposes an improved methodology for making a quantitative formulation between conventional well logs and sonic wave velocities. First, sonic wave velocities were predicted from conventional well logs using artificial neural network, fuzzy logic, and neuro-fuzzy algorithms. Subsequently, a committee machine with intelligent systems was constructed by virtue of hybrid genetic algorithm-pattern search technique while outputs of artificial neural network, fuzzy logic and neuro-fuzzy models were used as inputs of the committee machine. It is capable of improving the accuracy of final prediction through integrating the outputs of aforementioned intelligent systems. The hybrid genetic algorithm-pattern search tool, embodied in the structure of committee machine, assigns a weight factor to each individual intelligent system, indicating its involvement in overall prediction of DSI parameters. This methodology was implemented in Asmari formation, which is the major carbonate reservoir rock of Iranian oil field. A group of 1,640 data points was used to construct the intelligent model, and a group of 800 data points was employed to assess the reliability of the proposed model. The results showed that the committee machine with intelligent systems performed more effectively compared with individual intelligent systems performing alone.

The design of intelligent support systems for nuclear reactor operators

International Nuclear Information System (INIS)

Bernard, J.A.

1992-01-01

This paper identifies factors relevant to the design of intelligent support systems and their use for the provision of real-time diagnostic information. As such, it constitutes a followup to the state-of-the-art review that was previously published by Bernard and Washio on the utilization of expert systems within the nuclear industry. Some major differences between intelligent-support tools and conventional expert systems are enumerated. In summary, conventional expert systems that encode experimental knowledge in production rules are not suitable vehicle for the creation of operator support systems. The principal difficulty is the need for real-time operation. This in turn means that intelligent support systems will have knowledge bases derived from temporally accurate plant models, inference engines that permit revisions in the search process to accommodate revised data, and man-machine interfaces that do not require any human input. Such systems will be heavily instrumented, and the associated knowledge bases will require a hierarchical organization to emulate human approaches to analysis

Eliminating Adversary Weapons of Mass Destruction: What's at Stake?

National Research Council Canada - National Science Library

Hersman, Rebecca K

2004-01-01

.... Unfortunately, the current preoccupation with intelligence might mask other issues and shortcomings in the American ability to eliminate the threat posed by weapons of mass destruction in the hands of its enemies...

Artificial intelligence

CERN Document Server

Hunt, Earl B

1975-01-01

Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet

#%Applications of artificial intelligence in intelligent manufacturing: a review

Institute of Scientific and Technical Information of China (English)

#

2017-01-01

#%Based on research into the applications of artificial intelligence (AI) technology in the manufacturing industry in recent years, we analyze the rapid development of core technologies in the new era of 'Internet plus AI', which is triggering a great change in the models, means, and ecosystems of the manufacturing industry, as well as in the development of AI. We then propose new models, means, and forms of intelligent manufacturing, intelligent manufacturing system architecture, and intelligent man-ufacturing technology system, based on the integration of AI technology with information communications, manufacturing, and related product technology. Moreover, from the perspectives of intelligent manufacturing application technology, industry, and application demonstration, the current development in intelligent manufacturing is discussed. Finally, suggestions for the appli-cation of AI in intelligent manufacturing in China are presented.

Using agent technology to build a real-world training application

NARCIS (Netherlands)

Cap, M.; Heuvelink, A.; Bosch, K. van den; Doesburg, W. van

2011-01-01

Using staff personnel for playing roles in simulation-based training (e.g. team mates, adversaries) elevates costs, and imposes organizational constraints on delivery of training. One solution to this problem is to use intelligent software agents that play the required roles autonomously. BDI

When is Information Sufficient for Action Search with Unreliable Yet Informative Intelligence

Science.gov (United States)

2016-03-30

specificity. Math . Methods Oper. Res. 68(3): 539–549. Lange R-J (2012) Brownian motion and multidimensional decision making. Unpublished doctoral...intelligence assets, political ramifications, etc. We describe the problem in §2 and formulate the mathe - matical model in §3. The cases of n= 2 and n...boundary problem in n dimensions. When n> 2 cells, our problem relates to the family of multinomial selection problems (Kim and Nelson 2006) in which an

Interface Design Concepts in the Development of ELSA, an Intelligent Electronic Library Search Assistant.

Science.gov (United States)

Denning, Rebecca; Smith, Philip J.

1994-01-01

Describes issues and advances in the design of appropriate inference engines and knowledge structures needed by commercially feasible intelligent intermediary systems for information retrieval. Issues associated with the design of interfaces to such functions are discussed in detail. Design principles for guiding implementation of these interfaces…

Searching for exoplanets using artificial intelligence

Science.gov (United States)

Pearson, Kyle A.; Palafox, Leon; Griffith, Caitlin A.

2018-02-01

In the last decade, over a million stars were monitored to detect transiting planets. Manual interpretation of potential exoplanet candidates is labor intensive and subject to human error, the results of which are difficult to quantify. Here we present a new method of detecting exoplanet candidates in large planetary search projects which, unlike current methods uses a neural network. Neural networks, also called "deep learning" or "deep nets" are designed to give a computer perception into a specific problem by training it to recognize patterns. Unlike past transit detection algorithms deep nets learn to recognize planet features instead of relying on hand-coded metrics that humans perceive as the most representative. Our convolutional neural network is capable of detecting Earth-like exoplanets in noisy time-series data with a greater accuracy than a least-squares method. Deep nets are highly generalizable allowing data to be evaluated from different time series after interpolation without compromising performance. As validated by our deep net analysis of Kepler light curves, we detect periodic transits consistent with the true period without any model fitting. Our study indicates that machine learning will facilitate the characterization of exoplanets in future analysis of large astronomy data sets.

Social intelligence, human intelligence and niche construction.

Science.gov (United States)

Sterelny, Kim

2007-04-29

This paper is about the evolution of hominin intelligence. I agree with defenders of the social intelligence hypothesis in thinking that externalist models of hominin intelligence are not plausible: such models cannot explain the unique cognition and cooperation explosion in our lineage, for changes in the external environment (e.g. increasing environmental unpredictability) affect many lineages. Both the social intelligence hypothesis and the social intelligence-ecological complexity hybrid I outline here are niche construction models. Hominin evolution is hominin response to selective environments that earlier hominins have made. In contrast to social intelligence models, I argue that hominins have both created and responded to a unique foraging mode; a mode that is both social in itself and which has further effects on hominin social environments. In contrast to some social intelligence models, on this view, hominin encounters with their ecological environments continue to have profound selective effects. However, though the ecological environment selects, it does not select on its own. Accidents and their consequences, differential success and failure, result from the combination of the ecological environment an agent faces and the social features that enhance some opportunities and suppress others and that exacerbate some dangers and lessen others. Individuals do not face the ecological filters on their environment alone, but with others, and with the technology, information and misinformation that their social world provides.

Trends in ambient intelligent systems the role of computational intelligence

CERN Document Server

Khan, Mohammad; Abraham, Ajith

2016-01-01

This book demonstrates the success of Ambient Intelligence in providing possible solutions for the daily needs of humans. The book addresses implications of ambient intelligence in areas of domestic living, elderly care, robotics, communication, philosophy and others. The objective of this edited volume is to show that Ambient Intelligence is a boon to humanity with conceptual, philosophical, methodical and applicative understanding. The book also aims to schematically demonstrate developments in the direction of augmented sensors, embedded systems and behavioral intelligence towards Ambient Intelligent Networks or Smart Living Technology. It contains chapters in the field of Ambient Intelligent Networks, which received highly positive feedback during the review process. The book contains research work, with in-depth state of the art from augmented sensors, embedded technology and artificial intelligence along with cutting-edge research and development of technologies and applications of Ambient Intelligent N...

Multi-Intelligence Analytics for Next Generation Analysts (MIAGA)

Science.gov (United States)

Blasch, Erik; Waltz, Ed

2016-05-01

Current analysts are inundated with large volumes of data from which extraction, exploitation, and indexing are required. A future need for next-generation analysts is an appropriate balance between machine analytics from raw data and the ability of the user to interact with information through automation. Many quantitative intelligence tools and techniques have been developed which are examined towards matching analyst opportunities with recent technical trends such as big data, access to information, and visualization. The concepts and techniques summarized are derived from discussions with real analysts, documented trends of technical developments, and methods to engage future analysts with multiintelligence services. For example, qualitative techniques should be matched against physical, cognitive, and contextual quantitative analytics for intelligence reporting. Future trends include enabling knowledge search, collaborative situational sharing, and agile support for empirical decision-making and analytical reasoning.

Artificial Intelligence Based Selection of Optimal Cutting Tool and Process Parameters for Effective Turning and Milling Operations

Science.gov (United States)

Saranya, Kunaparaju; John Rozario Jegaraj, J.; Ramesh Kumar, Katta; Venkateshwara Rao, Ghanta

2016-06-01

With the increased trend in automation of modern manufacturing industry, the human intervention in routine, repetitive and data specific activities of manufacturing is greatly reduced. In this paper, an attempt has been made to reduce the human intervention in selection of optimal cutting tool and process parameters for metal cutting applications, using Artificial Intelligence techniques. Generally, the selection of appropriate cutting tool and parameters in metal cutting is carried out by experienced technician/cutting tool expert based on his knowledge base or extensive search from huge cutting tool database. The present proposed approach replaces the existing practice of physical search for tools from the databooks/tool catalogues with intelligent knowledge-based selection system. This system employs artificial intelligence based techniques such as artificial neural networks, fuzzy logic and genetic algorithm for decision making and optimization. This intelligence based optimal tool selection strategy is developed using Mathworks Matlab Version 7.11.0 and implemented. The cutting tool database was obtained from the tool catalogues of different tool manufacturers. This paper discusses in detail, the methodology and strategies employed for selection of appropriate cutting tool and optimization of process parameters based on multi-objective optimization criteria considering material removal rate, tool life and tool cost.

Does emotional intelligence influence success during medical school admissions and program matriculation?: a systematic review.

Science.gov (United States)

Cook, Christian Jaeger; Cook, Chad E; Hilton, Tiffany N

2016-01-01

It aimed at determining whether emotional intelligence is a predictor for success in a medical school program and whether the emotional intelligence construct correlated with other markers for admission into medical school. Three databases (PubMed, CINAHL, and ERIC) were searched up to and including July 2016, using relevant terms. Studies written in English were selected if they included emotional intelligence as a predictor for success in medical school, markers of success such as examination scores and grade point average and association with success defined through traditional medical school admission criteria and failures, and details about the sample. Data extraction included the study authors and year, population description, emotional intelligence I tool, outcome variables, and results. Associations between emotional intelligence scores and reported data were extracted and recorded. Six manuscripts were included. Overall, study quality was high. Four of the manuscripts examined emotional intelligence as a predictor for success while in medical school. Three of these four studies supported a weak positive relationship between emotional intelligence scores and success during matriculation. Two of manuscripts examined the relationship of emotional intelligence to medical school admissions. There were no significant relevant correlations between emotional intelligence and medical school admission selection. Emotional intelligence was correlated with some, but not all, measures of success during medical school matriculation and none of the measures associated with medical school admissions. Variability in success measures across studies likely explains the variable findings.

Does emotional intelligence influence success during medical school admissions and program matriculation?: a systematic review

Directory of Open Access Journals (Sweden)

Christian Jaeger Cook

2016-11-01

Full Text Available Purpose It aimed at determining whether emotional intelligence is a predictor for success in a medical school program and whether the emotional intelligence construct correlated with other markers for admission into medical school. Methods Three databases (PubMed, CINAHL, and ERIC were searched up to and including July 2016, using relevant terms. Studies written in English were selected if they included emotional intelligence as a predictor for success in medical school, markers of success such as examination scores and grade point average and association with success defined through traditional medical school admission criteria and failures, and details about the sample. Data extraction included the study authors and year, population description, emotional intelligence I tool, outcome variables, and results. Associations between emotional intelligence scores and reported data were extracted and recorded. Results Six manuscripts were included. Overall, study quality was high. Four of the manuscripts examined emotional intelligence as a predictor for success while in medical school. Three of these four studies supported a weak positive relationship between emotional intelligence scores and success during matriculation. Two of manuscripts examined the relationship of emotional intelligence to medical school admissions. There were no significant relevant correlations between emotional intelligence and medical school admission selection. Conclusion Emotional intelligence was correlated with some, but not all, measures of success during medical school matriculation and none of the measures associated with medical school admissions. Variability in success measures across studies likely explains the variable findings.

The 2P1/2 → 2P3/2 laser transition in atomic iodine and the problem of search for signals from extraterrestrial intelligence

International Nuclear Information System (INIS)

Kutaev, Yu F; Mankevich, S K; Nosach, O Yu; Orlov, E P

2007-01-01

It is proposed to search for signals from extraterrestrial intelligence (ETI) at a wavelength of 1.315 μm of the laser 2 P 1/2 → 2 P 3/2 transition in the atomic iodine, which can be used for this purpose as the natural frequency reference. The search at this wavelength is promising because active quantum filters (AQFs) with the quantum sensitivity limit have been developed for this wavelength, which are capable of receiving laser signals, consisting of only a few photons, against the background of emission from a star under study. In addition, high-power iodine lasers emitting diffraction-limited radiation at 1.315 μm have been created, which highly developed ETI also can have. If a ETI sends in our direction a diffraction-limited 10-ns, 1-kJ laser pulse with the beam diameter of 10 m, a receiver with an AQF mounted on a ten-meter extra-atmospheric optical telescope can detect this signal at a distance of up to 300 light years, irrespective of the ETI position on the celestial sphere. The realisation of the projects for manufacturing optical telescopes of diameter 30 m will increase the research range up to 2700 light years. A weak absorption of the 1.315-μm radiation in the Earth atmosphere (the signal is attenuated by less than 20%) allows the search for ETI signals by using ground telescopes equipped with adaptive optical systems. (laser applications and other topics in quantum electronics)

Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

Directory of Open Access Journals (Sweden)

Yongcheng Li

Full Text Available Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

Application of Hierarchical Dissociated Neural Network in Closed-Loop Hybrid System Integrating Biological and Mechanical Intelligence

Science.gov (United States)

Zhang, Bin; Wang, Yuechao; Li, Hongyi

2015-01-01

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including ‘random’ and ‘4Q’ (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the ‘4Q’ cultures presented absolutely different activities, and the robot controlled by the ‘4Q’ network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems. PMID:25992579

Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

Science.gov (United States)

Li, Yongcheng; Sun, Rong; Zhang, Bin; Wang, Yuechao; Li, Hongyi

2015-01-01

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

Carl Sagan and Joseph Shklovsky: Intelligent Life in the Universe

Science.gov (United States)

Kurt, Vladimir

J. S. Shklovsky and Carl Sagan played an outstanding role in modern astronomy. Their names are well known not only to professional astronomers, but also to millions of educated people in many countries, which are interested in modern state of science research. Among these trends of modern science, which are difficult to define, are such problems, as the creation of Solar system, the origin of life on Earth, the evolution of living organisms on Earth from the simplest viruses to Homo Sapiens, the evolution of intelligence and technology. Finally, both outstanding scientists were deeply interested in the problem of SETI (Search Extraterrestrial Intelligence), i.e. search of extraterrestrial civilizations and methods of making contacts with them. And both scientists were high professionals in their fields. Joseph Shklovsky was a theoretical astronomer in all fields of modern astronomy (geophysics and physics of the upper atmosphere of the Earth, Sun and Solar Corona, Interplanetary Medium and Solar Wind, Interstellar Medium, Supernova and their remnants, the Galaxy and galaxies, Quasars and Cosmology). There is hardly a field in modern astrophysics (except perhaps the theory of the interior structure of stars), where Joseph Shklovsky has not l a bright stamp of his talent…

Intelligent agents: adaptation of autonomous bimodal microsystems

Science.gov (United States)

Smith, Patrice; Terry, Theodore B.

2014-03-01

Autonomous bimodal microsystems exhibiting survivability behaviors and characteristics are able to adapt dynamically in any given environment. Equipped with a background blending exoskeleton it will have the capability to stealthily detect and observe a self-chosen viewing area while exercising some measurable form of selfpreservation by either flying or crawling away from a potential adversary. The robotic agent in this capacity activates a walk-fly algorithm, which uses a built in multi-sensor processing and navigation subsystem or algorithm for visual guidance and best walk-fly path trajectory to evade capture or annihilation. The research detailed in this paper describes the theoretical walk-fly algorithm, which broadens the scope of spatial and temporal learning, locomotion, and navigational performances based on optical flow signals necessary for flight dynamics and walking stabilities. By observing a fly's travel and avoidance behaviors; and, understanding the reverse bioengineering research efforts of others, we were able to conceptualize an algorithm, which works in conjunction with decisionmaking functions, sensory processing, and sensorimotor integration. Our findings suggest that this highly complex decentralized algorithm promotes inflight or terrain travel mobile stability which is highly suitable for nonaggressive micro platforms supporting search and rescue (SAR), and chemical and explosive detection (CED) purposes; a necessity in turbulent, non-violent structured or unstructured environments.

Advanced intelligent systems

CERN Document Server

Ryoo, Young; Jang, Moon-soo; Bae, Young-Chul

2014-01-01

Intelligent systems have been initiated with the attempt to imitate the human brain. People wish to let machines perform intelligent works. Many techniques of intelligent systems are based on artificial intelligence. According to changing and novel requirements, the advanced intelligent systems cover a wide spectrum: big data processing, intelligent control, advanced robotics, artificial intelligence and machine learning. This book focuses on coordinating intelligent systems with highly integrated and foundationally functional components. The book consists of 19 contributions that features social network-based recommender systems, application of fuzzy enforcement, energy visualization, ultrasonic muscular thickness measurement, regional analysis and predictive modeling, analysis of 3D polygon data, blood pressure estimation system, fuzzy human model, fuzzy ultrasonic imaging method, ultrasonic mobile smart technology, pseudo-normal image synthesis, subspace classifier, mobile object tracking, standing-up moti...

A Framework for the Systematic Collection of Open Source Intelligence

Energy Technology Data Exchange (ETDEWEB)

Pouchard, Line Catherine [ORNL; Trien, Joseph P [ORNL; Dobson, Jonathan D [ORNL

2009-01-01

Following legislative directions, the Intelligence Community has been mandated to make greater use of Open Source Intelligence (OSINT). Efforts are underway to increase the use of OSINT but there are many obstacles. One of these obstacles is the lack of tools helping to manage the volume of available data and ascertain its credibility. We propose a unique system for selecting, collecting and storing Open Source data from the Web and the Open Source Center. Some data management tasks are automated, document source is retained, and metadata containing geographical coordinates are added to the documents. Analysts are thus empowered to search, view, store, and analyze Web data within a single tool. We present ORCAT I and ORCAT II, two implementations of the system.

Street Smarts and a Scalpel: Emotional Intelligence in Surgical Education.

Science.gov (United States)

Erdman, Mary Kate; Bonaroti, Alisha; Provenzano, Gina; Appelbaum, Rachel; Browne, Marybeth

To evaluate trends of emotional intelligence (EI) in surgical education and to compare the incorporation of EI in surgical education to other fields of graduate medical education. A MEDLINE search was performed for publications containing both "surgery" and "emotional intelligence" with at least one term present in the title. Articles were included if the authors deemed EI in surgical education to be a significant focus. A separate series of MEDLINE searches were performed with the phrase "emotional intelligence" in any field and either "surg*," "internal medicine," "pediatric," "neurology," "obstetric," "gynecology," "OBGYN," "emergency," or "psychiat*" in the title. Articles were included if they discussed resident education as the primary subject. Next, a qualitative analysis of the articles was performed, with important themes from each article noted. Lehigh Valley Health Network in Allentown, PA. Eight articles addressed surgical resident education and satisfied inclusion criteria with 0, 1, and 7 articles published between 2001 and 2005, 2005 and 2010, and 2010 and 2015, respectively. The comparative data for articles on EI and resident education showed the following : 8 in surgery, 2 in internal medicine, 2 in pediatrics, 0 in neurology, 0 in OBGYN, 1 in emergency medicine, and 3 in psychiatry. Integration of EI principles is a growing trend within surgical education. A prominent theme is quantitative assessment of EI in residents and residency applicants. Further study is warranted on the integration process of EI in surgical education and its effect on patient outcomes and long-term job satisfaction. Copyright © 2017 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Competitive Intelligence.

Science.gov (United States)

Bergeron, Pierrette; Hiller, Christine A.

2002-01-01

Reviews the evolution of competitive intelligence since 1994, including terminology and definitions and analytical techniques. Addresses the issue of ethics; explores how information technology supports the competitive intelligence process; and discusses education and training opportunities for competitive intelligence, including core competencies…

Application of artificial intelligence to search ground-state geometry of clusters

International Nuclear Information System (INIS)

Lemes, Mauricio Ruv; Marim, L.R.; Dal Pino, A. Jr.

2002-01-01

We introduce a global optimization procedure, the neural-assisted genetic algorithm (NAGA). It combines the power of an artificial neural network (ANN) with the versatility of the genetic algorithm. This method is suitable to solve optimization problems that depend on some kind of heuristics to limit the search space. If a reasonable amount of data is available, the ANN can 'understand' the problem and provide the genetic algorithm with a selected population of elements that will speed up the search for the optimum solution. We tested the method in a search for the ground-state geometry of silicon clusters. We trained the ANN with information about the geometry and energetics of small silicon clusters. Next, the ANN learned how to restrict the configurational space for larger silicon clusters. For Si 10 and Si 20 , we noticed that the NAGA is at least three times faster than the 'pure' genetic algorithm. As the size of the cluster increases, it is expected that the gain in terms of time will increase as well

Starry messages: Searching for signatures of interstellar archaeology

Energy Technology Data Exchange (ETDEWEB)

Carrigan, Richard A., Jr.; /Fermilab

2009-12-01

Searching for signatures of cosmic-scale archaeological artifacts such as Dyson spheres or Kardashev civilizations is an interesting alternative to conventional SETI. Uncovering such an artifact does not require the intentional transmission of a signal on the part of the original civilization. This type of search is called interstellar archaeology or sometimes cosmic archaeology. The detection of intelligence elsewhere in the Universe with interstellar archaeology or SETI would have broad implications for science. For example, the constraints of the anthropic principle would have to be loosened if a different type of intelligence was discovered elsewhere. A variety of interstellar archaeology signatures are discussed including non-natural planetary atmospheric constituents, stellar doping with isotopes of nuclear wastes, Dyson spheres, as well as signatures of stellar and galactic-scale engineering. The concept of a Fermi bubble due to interstellar migration is introduced in the discussion of galactic signatures. These potential interstellar archaeological signatures are classified using the Kardashev scale. A modified Drake equation is used to evaluate the relative challenges of finding various sources. With few exceptions interstellar archaeological signatures are clouded and beyond current technological capabilities. However SETI for so-called cultural transmissions and planetary atmosphere signatures are within reach.

Simulation to Support Local Search in Trajectory Optimization Planning

Science.gov (United States)

Morris, Robert A.; Venable, K. Brent; Lindsey, James

2012-01-01

NASA and the international community are investing in the development of a commercial transportation infrastructure that includes the increased use of rotorcraft, specifically helicopters and civil tilt rotors. However, there is significant concern over the impact of noise on the communities surrounding the transportation facilities. One way to address the rotorcraft noise problem is by exploiting powerful search techniques coming from artificial intelligence coupled with simulation and field tests to design low-noise flight profiles which can be tested in simulation or through field tests. This paper investigates the use of simulation based on predictive physical models to facilitate the search for low-noise trajectories using a class of automated search algorithms called local search. A novel feature of this approach is the ability to incorporate constraints directly into the problem formulation that addresses passenger safety and comfort.

The Complexity of Threats to Nuclear Strategic Deterrence Posture

Science.gov (United States)

2017-02-07

India and Pakistan, and concludes “…South Asian nuclear adversaries are believed to make each of the four dangers of inadvertent use of nuclear...directed energy, unmanned systems, and artificial intelligence ( AI ).”50 Ultimately, the promulgation of either of these technologies in a mature or

[An encounter with extraterrestrial intelligence].

Science.gov (United States)

Hisabayashi, Hisashi

2003-12-01

It is much easier to find extraterrestrial intelligence than to detect simple organisms living on other planets. However, it is hard to communicate with such intelligence without the mutual understanding of inter-stellar communication protocol. The radio SETI (The Search for Extra-Terrestrial Intelligence) was initiated with the pioneering work of F. Drake in 1960, one year after the historical SETI paper by Cocconi and Morrison. This talk explains that SETI evolves with two bases of science; the understanding of our universe and the development of technology. Since SETI has had strong connection with radio astronomy from its early beginning, the impacts of radio astronomical findings and technological breakthrough can be seen in many aspects of the SETI history. Topics of this talk include the detection of microwave 3 K background radiation in the universe. Interstellar atomic and molecular lines found in radio-wave spectra provide the evidence of pre-biotic chemical evolution in such region. Radio telescope imaging and spectral technique are closely associated with methodology of SETI. Topics of the talk extend to new Allen Telescope Array and projected Square Kilometer Array. Recent optical SETI and the discoveries of extra solar planets are also explained. In the end, the recent understanding of our universe is briefly introduced in terms of matter, dark matter and dark energy. Even our understanding of the universe has been evolutionarily revolved and accumulated after 1960, we must recognize that our universe is still poorly understood and that astronomy and SETI are required to proceed hand in hand.

Privacy for Key-Trees with Adaptive Adversaries

NARCIS (Netherlands)

Beye, M.; Veugen, P.J.M.

2011-01-01

Hash-lock authentication protocols for Radio Frequency IDentification (RFID) tags incur heavy search on the server. Key-trees have been proposed as a way to reduce search times, but because partial keys in such trees are shared, key compromise affects several tags. Butty´an [3] and Beye and Veugen

Anonymity for key-trees with adaptive adversaries

NARCIS (Netherlands)

Beye, M.; Veugen, P.J.M.

2012-01-01

Hash-lock authentication protocols for Radio Frequency IDentification (RFID) tags incur heavy search on the server. Key-trees have been proposed as a way to reduce search times, but because partial keys in such trees are shared, key compromise affects several tags. Buttyán [4] and Beye and Veugen

Using the Web for Competitive Intelligence (CI) Gathering

Science.gov (United States)

Rocker, JoAnne; Roncaglia, George

2002-01-01

Businesses use the Internet as a way to communicate company information as a way of engaging their customers. As the use of the Web for business transactions and advertising grows, so too, does the amount of useful information for practitioners of competitive intelligence (CI). CI is the legal and ethical practice of information gathering about competitors and the marketplace. Information sources like company webpages, online newspapers and news organizations, electronic journal articles and reports, and Internet search engines allow CI practitioners analyze company strengths and weaknesses for their customers. More company and marketplace information than ever is available on the Internet and a lot of it is free. Companies should view the Web not only as a business tool but also as a source of competitive intelligence. In a highly competitive marketplace can any organization afford to ignore information about the other players and customers in that same marketplace?

Modelling traffic flows with intelligent cars and intelligent roads

NARCIS (Netherlands)

van Arem, Bart; Tampere, Chris M.J.; Malone, Kerry

2003-01-01

This paper addresses the modeling of traffic flows with intelligent cars and intelligent roads. It will describe the modeling approach MIXIC and review the results for different ADA systems: Adaptive Cruise Control, a special lane for Intelligent Vehicles, cooperative following and external speed

Fuzzy Search Method for Hi Education Information Security

Directory of Open Access Journals (Sweden)

Grigory Grigorevich Novikov

2016-03-01

Full Text Available The main reason of the research is how to use fuzzy search method for information security of Hi Education or some similar purposes. So many sensitive information leaks are through non SUMMARY 149 classified documents legal publishing. That’s why many intelligence services so love to use the «mosaic» information collection method. This article is about how to prevent it.

Sistema penal acusatorio en Veracruz/Adversarial criminal system in Veracruz

Directory of Open Access Journals (Sweden)

Jorge Alberto Pérez Tolentino (México

2014-01-01

Full Text Available El estudio y comprensión del nuevo Código de Procedimientos Penales de Veracruz resulta ineludible, en virtud de las nítidas diferencias existentes entre las figuras jurídicas que contiene el actual ordenamiento, en comparación con el anterior. Es preciso sistematizar, describir y analizar la estructura del sistema penal acusatorio, a efecto de estar en condiciones de evaluar y, en su caso, proponer las mejoras al sistema en cuestión. El contenido esquemático y sustancial del código, la visión y recepción que del mismo tienen los operadores jurídicos y la sociedad en general, son aspectos que cubre el presente documento. The study and understanding of the new Code of Criminal Procedure of Veracruz is unavoidable, by reason of the sharp differences between the legal concepts that contains the actual order, compared with the previous. Needs to be systematized, describe and analyze the structure of the adversarial criminal system, in order to be able to evaluate and, if necessary, propose improvements to the system in question. The schematic and substantial content of the code, viewing and welcome that the same have the legal practitioners and society in general, are aspects covered by herein.

Intelligence.

Science.gov (United States)

Sternberg, Robert J

2012-03-01

Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.

Intelligence

Science.gov (United States)

Sternberg, Robert J.

2012-01-01

Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain—especially with regard to the functioning in the prefrontal cortex—and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301

Issues regarding the design and acceptance of intelligent support systems for reactor operators

International Nuclear Information System (INIS)

Bernard, J.A.

1992-01-01

In this paper, factors relevant to the design and acceptance of intelligent support systems for the operation of nuclear power plants are enumerated and discussed. The central premise is that conventional expert systems which encode experiential knowledge in production rules are not a suitable vehicle for the creation of practical operator support systems. The principal difficulty is the need for real-time operation. This in turn means that intelligent support systems will have knowledge bases derived from temporally accurate plant models, inference engines that permit revisions in the search process so as to accommodate revised or new data, and man-machine interfaces that do not require any human input. Such systems will have to be heavily instrumented and the associated knowledge bases will require a hierarchical organization so as to emulate human approaches to analysis. Issues related to operator acceptance of intelligent support tools are then reviewed. Possible applications are described and the relative merits of the machine- and human-centered approaches to the implementation of intelligent support systems are enumerated. The paper concludes with a plea for additional experimental evaluations

Visual search and attention in five-year-old very preterm/very low birth weight children.

Science.gov (United States)

Geldof, Christiaan J A; de Kieviet, Jorrit F; Dik, Marjolein; Kok, Joke H; van Wassenaer-Leemhuis, Aleid G; Oosterlaan, Jaap

2013-12-01

This study aimed to establish visual search performance and attention functioning in very preterm/very low birth weight (VP/VLBW) children using novel and well established measures, and to study their contribution to intellectual functioning. Visual search and attention network efficiency were assessed in 108 VP/VLBW children and 72 age matched term controls at 5.5 years corrected age. Visual search performance was investigated with a newly developed paradigm manipulating stimulus density and stimulus organization. Attention functioning was studied using the Attention Network Test (ANT). Intellectual functioning was measured by a short form of the Wechsler Preschool and Primary Scale of Intelligence. Data were analyzed using ANOVAs and multiple regression analyses. Visual search was less efficient in VP/VLBW children as compared to term controls, as indicated by increased search time (0.31 SD, p = .04) and increased error rate (0.36 SD, p = .02). In addition, VP/VLBW children demonstrated poorer executive attention as indicated by lower accuracy for the executive attention measure of the ANT (0.61 SD, p attention measures (0.13 SD, p = .42). Visual search time and error rate, and executive attention, collectively, accounted for 14% explained variance in full scale IQ (R(2) = .14, p attention. Visual attention dysfunctions contributed to intelligence, suggesting the opportunity to improve intellectual functioning by using interventions programs that may enhance attention capacities. © 2013.

Combined Intelligent Control (CIC an Intelligent Decision Making Algorithm

Directory of Open Access Journals (Sweden)

Moteaal Asadi Shirzi

2007-03-01

Full Text Available The focus of this research is to introduce the concept of combined intelligent control (CIC as an effective architecture for decision-making and control of intelligent agents and multi-robot sets. Basically, the CIC is a combination of various architectures and methods from fields such as artificial intelligence, Distributed Artificial Intelligence (DAI, control and biological computing. Although any intelligent architecture may be very effective for some specific applications, it could be less for others. Therefore, CIC combines and arranges them in a way that the strengths of any approach cover the weaknesses of others. In this paper first, we introduce some intelligent architectures from a new aspect. Afterward, we offer the CIC by combining them. CIC has been executed in a multi-agent set. In this set, robots must cooperate to perform some various tasks in a complex and nondeterministic environment with a low sensory feedback and relationship. In order to investigate, improve, and correct the combined intelligent control method, simulation software has been designed which will be presented and considered. To show the ability of the CIC algorithm as a distributed architecture, a central algorithm is designed and compared with the CIC.

A Search Engine That's Aware of Your Needs

Science.gov (United States)

2005-01-01

Internet research can be compared to trying to drink from a firehose. Such a wealth of information is available that even the simplest inquiry can sometimes generate tens of thousands of leads, more information than most people can handle, and more burdensome than most can endure. Like everyone else, NASA scientists rely on the Internet as a primary search tool. Unlike the average user, though, NASA scientists perform some pretty sophisticated, involved research. To help manage the Internet and to allow researchers at NASA to gain better, more efficient access to the wealth of information, the Agency needed a search tool that was more refined and intelligent than the typical search engine. Partnership NASA funded Stottler Henke, Inc., of San Mateo, California, a cutting-edge software company, with a Small Business Innovation Research (SBIR) contract to develop the Aware software for searching through the vast stores of knowledge quickly and efficiently. The partnership was through NASA s Ames Research Center.

Intelligence and negotiating

International Nuclear Information System (INIS)

George, D.G.

1990-01-01

This paper discusses the role of US intelligence during arms control negotiations between 1982 and 1987. It also covers : the orchestration of intelligence projects; an evaluation of the performance of intelligence activities; the effect intelligence work had on actual arms negotiations; and suggestions for improvements in the future

32 CFR Appendix A to Part 292 - Uniform Agency Fees for Search and Duplication Under the Freedom of Information Act (as Amended)

Science.gov (United States)

2010-07-01

... PROGRAM DEFENSE INTELLIGENCE AGENCY (DIA) FREEDOM OF INFORMATION ACT Pt. 292, App. A Appendix A to Part... search site, conducting the search and return may be charged as FOIA search costs. General Pre-Printed material, per printed page .02 Office copy, per page .15 Microfiche, per page .25 Aerial Photography...

Intelligence and childlessness.

Science.gov (United States)

Kanazawa, Satoshi

2014-11-01

Demographers debate why people have children in advanced industrial societies where children are net economic costs. From an evolutionary perspective, however, the important question is why some individuals choose not to have children. Recent theoretical developments in evolutionary psychology suggest that more intelligent individuals may be more likely to prefer to remain childless than less intelligent individuals. Analyses of the National Child Development Study show that more intelligent men and women express preference to remain childless early in their reproductive careers, but only more intelligent women (not more intelligent men) are more likely to remain childless by the end of their reproductive careers. Controlling for education and earnings does not at all attenuate the association between childhood general intelligence and lifetime childlessness among women. One-standard-deviation increase in childhood general intelligence (15 IQ points) decreases women's odds of parenthood by 21-25%. Because women have a greater impact on the average intelligence of future generations, the dysgenic fertility among women is predicted to lead to a decline in the average intelligence of the population in advanced industrial nations. Copyright © 2014 Elsevier Inc. All rights reserved.

Perceived intelligence is associated with measured intelligence in men but not women.

Science.gov (United States)

Kleisner, Karel; Chvátalová, Veronika; Flegr, Jaroslav

2014-01-01

The ability to accurately assess the intelligence of other persons finds its place in everyday social interaction and should have important evolutionary consequences. We used static facial photographs of 40 men and 40 women to test the relationship between measured IQ, perceived intelligence, and facial shape. Both men and women were able to accurately evaluate the intelligence of men by viewing facial photographs. In addition to general intelligence, figural and fluid intelligence showed a significant relationship with perceived intelligence, but again, only in men. No relationship between perceived intelligence and IQ was found for women. We used geometric morphometrics to determine which facial traits are associated with the perception of intelligence, as well as with intelligence as measured by IQ testing. Faces that are perceived as highly intelligent are rather prolonged with a broader distance between the eyes, a larger nose, a slight upturn to the corners of the mouth, and a sharper, pointing, less rounded chin. By contrast, the perception of lower intelligence is associated with broader, more rounded faces with eyes closer to each other, a shorter nose, declining corners of the mouth, and a rounded and massive chin. By contrast, we found no correlation between morphological traits and real intelligence measured with IQ test, either in men or women. These results suggest that a perceiver can accurately gauge the real intelligence of men, but not women, by viewing their faces in photographs; however, this estimation is possibly not based on facial shape. Our study revealed no relation between intelligence and either attractiveness or face shape.

What Friends Are For: Collaborative Intelligence Analysis and Search

Science.gov (United States)

2014-06-01

preferences, then the similarity measure could then be some type of vector angularity measurement. Regardless of how similarity is computed, once 26 the...III. In addition to implementing the model, the software supports analysis of search performance. The program is written in Java and Python and...profiles within the profile database are encoded in XML format, as seen in Figure 13. Profiler is written in both Java and Python and is dependent upon

Artificial Intelligence.

Science.gov (United States)

Information Technology Quarterly, 1985

1985-01-01

This issue of "Information Technology Quarterly" is devoted to the theme of "Artificial Intelligence." It contains two major articles: (1) Artificial Intelligence and Law" (D. Peter O'Neill and George D. Wood); (2) "Artificial Intelligence: A Long and Winding Road" (John J. Simon, Jr.). In addition, it contains two sidebars: (1) "Calculating and…

The Effects of Sacred Value Networks Within an Evolutionary, Adversarial Game

Science.gov (United States)

McCalla, Scott G.; Short, Martin B.; Brantingham, P. Jeffrey

2013-05-01

The effects of personal relationships and shared ideologies on levels of crime and the formation of criminal coalitions are studied within the context of an adversarial, evolutionary game first introduced in Short et al. (Phys. Rev. E 82:066114, 2010). Here, we interpret these relationships as connections on a graph of N players. These connections are then used in a variety of ways to define each player's "sacred value network"—groups of individuals that are subject to special consideration or treatment by that player. We explore the effects on the dynamics of the system that these networks introduce, through various forms of protection from both victimization and punishment. Under local protection, these networks introduce a new fixed point within the game dynamics, which we find through a continuum approximation of the discrete game. Under more complicated, extended protection, we numerically observe the emergence of criminal coalitions, or "gangs". We also find that a high-crime steady state is much more frequent in the context of extended protection networks, in both the case of Erdős-Rényi and small world random graphs.

Incorporating Emotional Intelligence in Legal Education: A Theoretical Perspective

Science.gov (United States)

Douglas, Susan

2015-01-01

"Thinking like a lawyer" is traditionally associated with rational-analytical problem solving and an adversarial approach to conflict. These features have been correlated with problems of psychological, or emotional, distress amongst lawyers and law students. These problems provide a strong argument for incorporating a consideration of…

Moral intelligence and its position in nursing profession

Directory of Open Access Journals (Sweden)

Pooneh Yousefi

2015-10-01

Full Text Available Introduction: Moral intelligence is one of the aspects of intelligence which can provide a framework for proper performance of the humans, which is known as a forecaster factor of behavior. MI is a vital intelligence for humans owing to guidance of other shapes of intelligence toward valuable tasks . It is  a combination of knowledge, interest and resolve, also includes the method of thinking, feeding and acting. The role and importance of MI is outstanding because of making balance and improvement in individual's interactions and social terms, especially in occupations related to medical and nursing field which directly deals with people's life. The goal of this study is the definition and identification of MI and its application in medical science, especially nursing. Methods: This research is a retrospective article in which other researchers' study has been investigated and analyzed. Therefore, three main keywords; intelligence, morality, MI, has been searched in different nursing field databases such as SID, CVID, PUBMED, CINAHL, SCIENCE, MAGIRAN DIRECT, GOOGLE SCHOLAR and SCOPUS. Hence, based on these criteria, published articles from 2000  up to the present has been found and abstracted or editors interpretation ones eliminated. Only full text articles have been used. Definitions and applications of MI in nursing, presented in articles has been organized and revised in this article. Results: The results showed that MI education is a revolution and essential requirement in nursing, since changing to a descent nurse not only depends on theoretical knowledge and clinical skills but also needs applying moral knowledge and responsibility. Following moral criterion in nurse's performance is more important than other care issues as moral behavior accompany nurses' responsibility can be an effective factor in patients' remission and recovery. Conclusion: Achievement of MI skills leads to nursing profession advancement by basic changes in nurse

The U.S. Army Functional Concept for Intelligence 2020-2040

Science.gov (United States)

2017-02-01

importance of open source intelligence ( OSINT ) and the Internet of things adds to the volume and diversity of data. Access to the vast amounts of data...U.S. interests. OSINT collection may be the driving source of information, particularly in large urban centers. TRADOC Pamphlet 525-2-1 22...private and public security and traffic systems. (2) OSINT provides insight into human terrain, including social media, search-engines, databases

Self-Assessing of the Emotional Intelligence and Organizational Intelligence in Schools

Science.gov (United States)

Dagiene, Valentina; Juškeviciene, Anita; Carneiro, Roberto; Child, Camilla; Cullen, Joe

2015-01-01

The paper presents the results of an evaluation of the Emotional Intelligence (EI) and Organisational Intelligence (OI) competences self-assessment tools developed and applied by the IGUANA project. In the paper Emotional Intelligence and Organisational Intelligence competences are discussed, their use in action research experiments to assess and…

3D conditional generative adversarial networks for high-quality PET image estimation at low dose.

Science.gov (United States)

Wang, Yan; Yu, Biting; Wang, Lei; Zu, Chen; Lalush, David S; Lin, Weili; Wu, Xi; Zhou, Jiliu; Shen, Dinggang; Zhou, Luping

2018-07-01

Positron emission tomography (PET) is a widely used imaging modality, providing insight into both the biochemical and physiological processes of human body. Usually, a full dose radioactive tracer is required to obtain high-quality PET images for clinical needs. This inevitably raises concerns about potential health hazards. On the other hand, dose reduction may cause the increased noise in the reconstructed PET images, which impacts the image quality to a certain extent. In this paper, in order to reduce the radiation exposure while maintaining the high quality of PET images, we propose a novel method based on 3D conditional generative adversarial networks (3D c-GANs) to estimate the high-quality full-dose PET images from low-dose ones. Generative adversarial networks (GANs) include a generator network and a discriminator network which are trained simultaneously with the goal of one beating the other. Similar to GANs, in the proposed 3D c-GANs, we condition the model on an input low-dose PET image and generate a corresponding output full-dose PET image. Specifically, to render the same underlying information between the low-dose and full-dose PET images, a 3D U-net-like deep architecture which can combine hierarchical features by using skip connection is designed as the generator network to synthesize the full-dose image. In order to guarantee the synthesized PET image to be close to the real one, we take into account of the estimation error loss in addition to the discriminator feedback to train the generator network. Furthermore, a concatenated 3D c-GANs based progressive refinement scheme is also proposed to further improve the quality of estimated images. Validation was done on a real human brain dataset including both the normal subjects and the subjects diagnosed as mild cognitive impairment (MCI). Experimental results show that our proposed 3D c-GANs method outperforms the benchmark methods and achieves much better performance than the state

Perceived Intelligence Is Associated with Measured Intelligence in Men but Not Women

Science.gov (United States)

Kleisner, Karel; Chvátalová, Veronika; Flegr, Jaroslav

2014-01-01

Background The ability to accurately assess the intelligence of other persons finds its place in everyday social interaction and should have important evolutionary consequences. Methodology/Principal Findings We used static facial photographs of 40 men and 40 women to test the relationship between measured IQ, perceived intelligence, and facial shape. Both men and women were able to accurately evaluate the intelligence of men by viewing facial photographs. In addition to general intelligence, figural and fluid intelligence showed a significant relationship with perceived intelligence, but again, only in men. No relationship between perceived intelligence and IQ was found for women. We used geometric morphometrics to determine which facial traits are associated with the perception of intelligence, as well as with intelligence as measured by IQ testing. Faces that are perceived as highly intelligent are rather prolonged with a broader distance between the eyes, a larger nose, a slight upturn to the corners of the mouth, and a sharper, pointing, less rounded chin. By contrast, the perception of lower intelligence is associated with broader, more rounded faces with eyes closer to each other, a shorter nose, declining corners of the mouth, and a rounded and massive chin. By contrast, we found no correlation between morphological traits and real intelligence measured with IQ test, either in men or women. Conclusions These results suggest that a perceiver can accurately gauge the real intelligence of men, but not women, by viewing their faces in photographs; however, this estimation is possibly not based on facial shape. Our study revealed no relation between intelligence and either attractiveness or face shape. PMID:24651120

Nexus between Intelligence Education and Intelligence Training: A South African Perspective

Directory of Open Access Journals (Sweden)

M. A. van den Berg

2015-10-01

Full Text Available This paper examines the nexus of intelligence education and training from a South African perspective with the focus on current practices in light of the country’s transition towards democracy. A brief overview is provided on the history and development of the South African intelligence community with specific focus on the civilian intelligence services from the period prior 1994 to date (2015. The main focus, however, is on intelligence education that is currently available from training institutions and universities in South Africa as registered with the Department of Higher Education as well as private training institutions on the one hand, and the intelligence training practices within the statutory intelligence environment on the other. To this extent, the relations between academic institutions and the intelligence structures in terms of education and training within South Africa are perused against other practices within the African continent and internationally. The approaches to the study of intelligence are also addressed within this paper. Likewise, the how, what as well as to whom – pertaining to intelligence education and training availability and accessibility to students and practitioners within South Africa, is reviewed and analysed with the focus on making recommendations for the enhancement and improvement thereof to enable a focus on preparing the next generation of professional intelligence officers.

Open Access Intellectual Property Systems: A Comparison to Commercial Solutions in Competitive Intelligence

Directory of Open Access Journals (Sweden)

Jan Cerny

2016-07-01

Full Text Available ICT/IS management plays an important role within the framework of innovation management, and one of the key elements of this role is the support of Competitive Intelligence in the context of innovation processes. The strategic information needs of innovation management are also directed towards different kinds of intellectual property (IP information entities and commercialization. The purpose of this paper is to define these entities and IP information systems as an important part of a company’s Competitive Intelligence Unit for competitor analysis and technology trends. The open access IP information systems will be analysed together with commercial solutions.. The aim of this paper is to underline the importance of open access IP systems compared to added value commercial solutions for competitive intelligence purposes for SMEs. The comparison will be carried out using examples of patent searches within a concrete dataset.

Emotional intelligence in professional nursing practice: A concept review using Rodgers's evolutionary analysis approach

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Angelina E. Raghubir

2018-04-01

Full Text Available Background: Knowledge around emotional intelligence originated in the 1990s from research regarding thoughts, emotions and abilities. The concept of emotional intelligence has evolved over the last 25 years; however, the understanding and use is still unclear. Despite this, emotional intelligence has been a widely-considered concept within professions such as business, management, education, and within the last 10 years has gained traction within nursing practice. Aims and objectives: The aim of this concept review is to clarify the understanding of the concept emotional intelligence, what attributes signify emotional intelligence, what are its antecedents, consequences, related terms and implications to advance nursing practice. Method: A computerized search was guided by Rodger's evolutional concept analysis. Data courses included: CINAHL, PyschINFO, Scopus, EMBASE and ProQuest, focusing on articles published in Canada and the United Stated during 1990–2017. Results: A total of 23 articles from various bodies of disciplines were included in this integrative concept review. The analysis reveals that there are many inconsistencies regarding the description of emotional intelligence, however, four common attributes were discovered: self-awareness, self-management, social awareness and social/relationship management. These attributes facilitate the emotional well-being among advance practice nurses and enhances the ability to practice in a way that will benefit patients, families, colleagues and advance practice nurses as working professionals and as individuals. Conclusion: The integration of emotional intelligence is supported within several disciplines as there is consensus on the impact that emotional intelligence has on job satisfaction, stress level, burnout and helps to facilitate a positive environment. Explicit to advance practice nursing, emotional intelligence is a concept that may be central to nursing practice as it has the

VIGAN: Missing View Imputation with Generative Adversarial Networks.

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Shang, Chao; Palmer, Aaron; Sun, Jiangwen; Chen, Ko-Shin; Lu, Jin; Bi, Jinbo

2017-01-01

In an era when big data are becoming the norm, there is less concern with the quantity but more with the quality and completeness of the data. In many disciplines, data are collected from heterogeneous sources, resulting in multi-view or multi-modal datasets. The missing data problem has been challenging to address in multi-view data analysis. Especially, when certain samples miss an entire view of data, it creates the missing view problem. Classic multiple imputations or matrix completion methods are hardly effective here when no information can be based on in the specific view to impute data for such samples. The commonly-used simple method of removing samples with a missing view can dramatically reduce sample size, thus diminishing the statistical power of a subsequent analysis. In this paper, we propose a novel approach for view imputation via generative adversarial networks (GANs), which we name by VIGAN. This approach first treats each view as a separate domain and identifies domain-to-domain mappings via a GAN using randomly-sampled data from each view, and then employs a multi-modal denoising autoencoder (DAE) to reconstruct the missing view from the GAN outputs based on paired data across the views. Then, by optimizing the GAN and DAE jointly, our model enables the knowledge integration for domain mappings and view correspondences to effectively recover the missing view. Empirical results on benchmark datasets validate the VIGAN approach by comparing against the state of the art. The evaluation of VIGAN in a genetic study of substance use disorders further proves the effectiveness and usability of this approach in life science.

SOLVING ENGINEERING OPTIMIZATION PROBLEMS WITH THE SWARM INTELLIGENCE METHODS

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V. Panteleev Andrei

2017-01-01

Full Text Available An important stage in problem solving process for aerospace and aerostructures designing is calculating their main charac- teristics optimization. The results of the four constrained optimization problems related to the design of various technical systems: such as determining the best parameters of welded beams, pressure vessel, gear, spring are presented. The purpose of each task is to minimize the cost and weight of the construction. The object functions in optimization practical problem are nonlinear functions with a lot of variables and a complex layer surface indentations. That is why using classical approach for extremum seeking is not efficient. Here comes the necessity of using such methods of optimization that allow to find a near optimal solution in acceptable amount of time with the minimum waste of computer power. Such methods include the methods of Swarm Intelligence: spiral dy- namics algorithm, stochastic diffusion search, hybrid seeker optimization algorithm. The Swarm Intelligence methods are designed in such a way that a swarm consisting of agents carries out the search for extremum. In search for the point of extremum, the parti- cles exchange information and consider their experience as well as the experience of population leader and the neighbors in some area. To solve the listed problems there has been designed a program complex, which efficiency is illustrated by the solutions of four applied problems. Each of the considered applied optimization problems is solved with all the three chosen methods. The ob- tained numerical results can be compared with the ones found in a swarm with a particle method. The author gives recommenda- tions on how to choose methods parameters and penalty function value, which consider inequality constraints.

The relationship of Emotional Intelligence with Academic Intelligence and the Big Five

NARCIS (Netherlands)

Van der Zee, K.I.; Thijs, Melanie; Schakel, Lolle

The present study examines the relationship of self- and other ratings of emotional intelligence with academic intelligence and personality, as well as the incremental validity of emotional intelligence beyond academic intelligence and personality in predicting academic and social success. A sample

The relationship of emotional intelligence with academic intelligence and the Big Five

NARCIS (Netherlands)

van der Zee, K; Thijs, M; Schakel, L

2002-01-01

The present study examines the relationship of self- and other ratings of emotional intelligence with academic intelligence and personality, as well as the incremental validity of emotional intelligence beyond academic intelligence and personality in predicting academic and social success. A sample

Search for design intelligence: A field study on the role of emotional intelligence in architectural design studios

Directory of Open Access Journals (Sweden)

Sajjad Nazidizaji

2014-12-01

Full Text Available The design studio is the core of the architecture curriculum. Interpersonal interactions have a key role during the processes of design and critique. The influence of emotional intelligence (EQ on interpersonal communication skills has been widely proven. This study examines the correlation between EQ and architectural design competence. To achieve this, 78 architecture students were selected via a simple random sampling method and tested using an EQ test questionnaire developed by Bradbury and Greaves (2006. The scores of five architectural design studio courses (ADS-1, ADS-2, ADS-3, ADS-4, and ADS-5 were used as indicators of the progress in design of the students. Descriptive and inferential statistics methods were both employed to analyze the research data. The methods included correlation analysis, mean comparison t-test for independent samples, and single sample t-test. Findings showed no significant relationship between EQ and any of the indicators.

An Educational System for Learning Search Algorithms and Automatically Assessing Student Performance

Science.gov (United States)

Grivokostopoulou, Foteini; Perikos, Isidoros; Hatzilygeroudis, Ioannis

2017-01-01

In this paper, first we present an educational system that assists students in learning and tutors in teaching search algorithms, an artificial intelligence topic. Learning is achieved through a wide range of learning activities. Algorithm visualizations demonstrate the operational functionality of algorithms according to the principles of active…

Intelligence in youth and all-cause-mortality: systematic review with meta-analysis.

Science.gov (United States)

Calvin, Catherine M; Deary, Ian J; Fenton, Candida; Roberts, Beverly A; Der, Geoff; Leckenby, Nicola; Batty, G David

2011-06-01

A number of prospective cohort studies have examined the association between intelligence in childhood or youth and life expectancy in adulthood; however, the effect size of this association is yet to be quantified and previous reviews require updating. The systematic review included an electronic search of EMBASE, MEDLINE and PSYCHINFO databases. This yielded 16 unrelated studies that met inclusion criteria, comprising 22,453 deaths among 1,107,022 participants. Heterogeneity was assessed, and fixed effects models were applied to the aggregate data. Publication bias was evaluated, and sensitivity analyses were conducted. A 1-standard deviation (SD) advantage in cognitive test scores was associated with a 24% (95% confidence interval 23-25) lower risk of death, during a 17- to 69-year follow-up. There was little evidence of publication bias (Egger's intercept = 0.10, P = 0.81), and the intelligence-mortality association was similar for men and women. Adjustment for childhood socio-economic status (SES) in the nine studies containing these data had almost no impact on this relationship, suggesting that this is not a confounder of the intelligence-mortality association. Controlling for adult SES in five studies and for education in six studies attenuated the intelligence-mortality hazard ratios by 34 and 54%, respectively. Future investigations should address the extent to which attenuation of the intelligence-mortality link by adult SES indicators is due to mediation, over-adjustment and/or confounding. The explanation(s) for association between higher early-life intelligence and lower risk of adult mortality require further elucidation.

Graphics-based intelligent search and abstracting using Data Modeling

Science.gov (United States)

Jaenisch, Holger M.; Handley, James W.; Case, Carl T.; Songy, Claude G.

2002-11-01

This paper presents an autonomous text and context-mining algorithm that converts text documents into point clouds for visual search cues. This algorithm is applied to the task of data-mining a scriptural database comprised of the Old and New Testaments from the Bible and the Book of Mormon, Doctrine and Covenants, and the Pearl of Great Price. Results are generated which graphically show the scripture that represents the average concept of the database and the mining of the documents down to the verse level.

Extended-Search, Bézier Curve-Based Lane Detection and Reconstruction System for an Intelligent Vehicle

Directory of Open Access Journals (Sweden)

Xiaoyun Huang

2015-09-01

Full Text Available To improve the real-time performance and detection rate of a Lane Detection and Reconstruction (LDR system, an extended-search-based lane detection method and a Bézier curve-based lane reconstruction algorithm are proposed in this paper. The extended-search-based lane detection method is designed to search boundary blocks from the initial position, in an upwards direction and along the lane, with small search areas including continuous search, discontinuous search and bending search in order to detect different lane boundaries. The Bézier curve-based lane reconstruction algorithm is employed to describe a wide range of lane boundary forms with comparatively simple expressions. In addition, two Bézier curves are adopted to reconstruct the lanes' outer boundaries with large curvature variation. The lane detection and reconstruction algorithm — including initial-blocks' determining, extended search, binarization processing and lane boundaries' fitting in different scenarios — is verified in road tests. The results show that this algorithm is robust against different shadows and illumination variations; the average processing time per frame is 13 ms. Significantly, it presents an 88.6% high-detection rate on curved lanes with large or variable curvatures, where the accident rate is higher than that of straight lanes.

Artificial Intelligence Project

Science.gov (United States)

1990-01-01

Symposium on Aritificial Intelligence and Software Engineering Working Notes, March 1989. Blumenthal, Brad, "An Architecture for Automating...Artificial Intelligence Project Final Technical Report ARO Contract: DAAG29-84-K-OGO Artificial Intelligence LaboratO"ry The University of Texas at...Austin N>.. ~ ~ JA 1/I 1991 n~~~ Austin, Texas 78712 ________k A,.tificial Intelligence Project i Final Technical Report ARO Contract: DAAG29-84-K-0060

Quantum Capacity under Adversarial Quantum Noise: Arbitrarily Varying Quantum Channels

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Ahlswede, Rudolf; Bjelaković, Igor; Boche, Holger; Nötzel, Janis

2013-01-01

We investigate entanglement transmission over an unknown channel in the presence of a third party (called the adversary), which is enabled to choose the channel from a given set of memoryless but non-stationary channels without informing the legitimate sender and receiver about the particular choice that he made. This channel model is called an arbitrarily varying quantum channel (AVQC). We derive a quantum version of Ahlswede's dichotomy for classical arbitrarily varying channels. This includes a regularized formula for the common randomness-assisted capacity for entanglement transmission of an AVQC. Quite surprisingly and in contrast to the classical analog of the problem involving the maximal and average error probability, we find that the capacity for entanglement transmission of an AVQC always equals its strong subspace transmission capacity. These results are accompanied by different notions of symmetrizability (zero-capacity conditions) as well as by conditions for an AVQC to have a capacity described by a single-letter formula. In the final part of the paper the capacity of the erasure-AVQC is computed and some light shed on the connection between AVQCs and zero-error capacities. Additionally, we show by entirely elementary and operational arguments motivated by the theory of AVQCs that the quantum, classical, and entanglement-assisted zero-error capacities of quantum channels are generically zero and are discontinuous at every positivity point.

The Ĝ Infrared Search for Extraterrestrial Civilizations with Large Energy Supplies. I. Background and Justification

Science.gov (United States)

Wright, J. T.; Mullan, B.; Sigurdsson, S.; Povich, M. S.

2014-09-01

We motivate the Ĝ infrared search for extraterrestrial civilizations with large energy supplies. We discuss some philosophical difficulties of the search for extraterrestrial intelligence (SETI), and how communication SETI circumvents them. We review "Dysonian SETI," the search for artifacts of alien civilizations, and find that it is highly complementary to traditional communication SETI; the two together might succeed where either one alone has not. We discuss the argument of Hart that spacefaring life in the Milky Way should be either galaxy-spanning or non-existent, and examine a portion of his argument that we call the "monocultural fallacy." We discuss some rebuttals to Hart that invoke sustainability and predict long Galaxy colonization timescales. We find that the maximum Galaxy colonization timescale is actually much shorter than previous work has found (energy supplies and argue that detectably large energy supplies can plausibly be expected to exist because life has the potential for exponential growth until checked by resources or other limitations, and intelligence implies the ability to overcome such limitations. As such, if Hart's thesis is correct, then searches for large alien civilizations in other galaxies may be fruitful; if it is incorrect, then searches for civilizations within the Milky Way are more likely to succeed than Hart argued. We review some past Dysonian SETI efforts and discuss the promise of new mid-infrared surveys, such as that of WISE.

Searching for alien artifacts on the moon

Science.gov (United States)

Davies, P. C. W.; Wagner, R. V.

2013-08-01

The Search for Extraterrestrial Intelligence (SETI) has a low probability of success, but it would have a high impact if successful. Therefore it makes sense to widen the search as much as possible within the confines of the modest budget and limited resources currently available. To date, SETI has been dominated by the paradigm of seeking deliberately beamed radio messages. However, indirect evidence for extraterrestrial intelligence could come from any incontrovertible signatures of non-human technology. Existing searchable databases from astronomy, biology, earth and planetary sciences all offer low-cost opportunities to seek a footprint of extraterrestrial technology. In this paper we take as a case study one particular new and rapidly-expanding database: the photographic mapping of the Moon's surface by the Lunar Reconnaissance Orbiter (LRO) to 0.5 m resolution. Although there is only a tiny probability that alien technology would have left traces on the moon in the form of an artifact or surface modification of lunar features, this location has the virtue of being close, and of preserving traces for an immense duration. Systematic scrutiny of the LRO photographic images is being routinely conducted anyway for planetary science purposes, and this program could readily be expanded and outsourced at little extra cost to accommodate SETI goals, after the fashion of the SETI@home and Galaxy Zoo projects.

A Retrospective and Prospective View of Information Retrieval and Artificial Intelligence in the 21st Century.

Science.gov (United States)

Garfield, Eugene

2001-01-01

Traces the development of information retrieval/services and suggests that the creation of large digital libraries seems inevitable. Examines possibilities for increasing electronic access and the role of artificial intelligence. Highlights include: searching full text; sending full texts; selective dissemination of information (SDI) profiling and…

Design of an intelligent materials data base for the IFR

International Nuclear Information System (INIS)

Mikaili, R.; Lambert, J.D.B.; Orth, T.D.

1992-01-01

In the development of the integral fast reactor (IFR) concept, there is a consensus that materials considerations are an important part of the reactor design, operation, and maintenance and that materials performance is central to liquid-metal reactor reliability and safety. In the design of the IRF materials data base, artificial intelligence techniques are being used to ensure efficient control of information. Intelligent control will provide for the selection of menus to be displayed, efficient data-base searches, and application-dependent guidance through the data base. The development of the IRF data base has progressed to the point of (a) completing the design of the data-base architecture and tables, (b) installing computer hardware for storing large amounts of data, (c) outlining strategies for data transferal, and (d) identifying ways to validate and secure the integrity of data

Routledge companion to intelligence studies

CERN Document Server

Dover, Robert; Hillebrand, Claudia

2013-01-01

The Routledge Companion to Intelligence Studies provides a broad overview of the growing field of intelligence studies. The recent growth of interest in intelligence and security studies has led to an increased demand for popular depictions of intelligence and reference works to explain the architecture and underpinnings of intelligence activity. Divided into five comprehensive sections, this Companion provides a strong survey of the cutting-edge research in the field of intelligence studies: Part I: The evolution of intelligence studies; Part II: Abstract approaches to intelligence; Part III: Historical approaches to intelligence; Part IV: Systems of intelligence; Part V: Contemporary challenges. With a broad focus on the origins, practices and nature of intelligence, the book not only addresses classical issues, but also examines topics of recent interest in security studies. The overarching aim is to reveal the rich tapestry of intelligence studies in both a sophisticated and accessible way. This Companion...

Systematic review of dermoscopy and digital dermoscopy/ artificial intelligence for the diagnosis of melanoma.

Science.gov (United States)

Rajpara, S M; Botello, A P; Townend, J; Ormerod, A D

2009-09-01

Dermoscopy improves diagnostic accuracy of the unaided eye for melanoma, and digital dermoscopy with artificial intelligence or computer diagnosis has also been shown useful for the diagnosis of melanoma. At present there is no clear evidence regarding the diagnostic accuracy of dermoscopy compared with artificial intelligence. To evaluate the diagnostic accuracy of dermoscopy and digital dermoscopy/artificial intelligence for melanoma diagnosis and to compare the diagnostic accuracy of the different dermoscopic algorithms with each other and with digital dermoscopy/artificial intelligence for the detection of melanoma. A literature search on dermoscopy and digital dermoscopy/artificial intelligence for melanoma diagnosis was performed using several databases. Titles and abstracts of the retrieved articles were screened using a literature evaluation form. A quality assessment form was developed to assess the quality of the included studies. Heterogeneity among the studies was assessed. Pooled data were analysed using meta-analytical methods and comparisons between different algorithms were performed. Of 765 articles retrieved, 30 studies were eligible for meta-analysis. Pooled sensitivity for artificial intelligence was slightly higher than for dermoscopy (91% vs. 88%; P = 0.076). Pooled specificity for dermoscopy was significantly better than artificial intelligence (86% vs. 79%; P artificial intelligence, which were not significantly different (P = 0.783). There were no significance differences in diagnostic odds ratio among the different dermoscopic diagnostic algorithms. Dermoscopy and artificial intelligence performed equally well for diagnosis of melanocytic skin lesions. There was no significant difference in the diagnostic performance of various dermoscopy algorithms. The three-point checklist, the seven-point checklist and Menzies score had better diagnostic odds ratios than the others; however, these results need to be confirmed by a large-scale high

78 FR 90 - Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting

Science.gov (United States)

2013-01-02

... DEPARTMENT OF DEFENSE Office of the Secretary Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting AGENCY: National Intelligence University, Defense Intelligence... hereby given that a closed meeting of the National Intelligence University Board of Visitors has been...

When does familiarity promote versus undermine interpersonal attraction? A proposed integrative model from erstwhile adversaries.

Science.gov (United States)

Finkel, Eli J; Norton, Michael I; Reis, Harry T; Ariely, Dan; Caprariello, Peter A; Eastwick, Paul W; Frost, Jeana H; Maniaci, Michael R

2015-01-01

This article began as an adversarial collaboration between two groups of researchers with competing views on a longstanding question: Does familiarity promote or undermine interpersonal attraction? As we explored our respective positions, it became clear that the limitations of our conceptualizations of the familiarity-attraction link, as well as the limitations of prior research, were masking a set of higher order principles capable of integrating these diverse conceptualizations. This realization led us to adopt a broader perspective, which focuses on three distinct relationship stages-awareness, surface contact, and mutuality-and suggests that the influence of familiarity on attraction depends on both the nature and the stage of the relationship between perceivers and targets. This article introduces the framework that emerged from our discussions and suggests directions for research to investigate its validity. © The Author(s) 2014.

Extending Galactic Habitable Zone Modeling to Include the Emergence of Intelligent Life.

Science.gov (United States)

Morrison, Ian S; Gowanlock, Michael G

2015-08-01

Previous studies of the galactic habitable zone have been concerned with identifying those regions of the Galaxy that may favor the emergence of complex life. A planet is deemed habitable if it meets a set of assumed criteria for supporting the emergence of such complex life. In this work, we extend the assessment of habitability to consider the potential for life to further evolve to the point of intelligence--termed the propensity for the emergence of intelligent life, φI. We assume φI is strongly influenced by the time durations available for evolutionary processes to proceed undisturbed by the sterilizing effects of nearby supernovae. The times between supernova events provide windows of opportunity for the evolution of intelligence. We developed a model that allows us to analyze these window times to generate a metric for φI, and we examine here the spatial and temporal variation of this metric. Even under the assumption that long time durations are required between sterilizations to allow for the emergence of intelligence, our model suggests that the inner Galaxy provides the greatest number of opportunities for intelligence to arise. This is due to the substantially higher number density of habitable planets in this region, which outweighs the effects of a higher supernova rate in the region. Our model also shows that φI is increasing with time. Intelligent life emerged at approximately the present time at Earth's galactocentric radius, but a similar level of evolutionary opportunity was available in the inner Galaxy more than 2 Gyr ago. Our findings suggest that the inner Galaxy should logically be a prime target region for searches for extraterrestrial intelligence and that any civilizations that may have emerged there are potentially much older than our own.

Breastfeeding and intelligence: a systematic review and meta-analysis.

Science.gov (United States)

Horta, Bernardo L; Loret de Mola, Christian; Victora, Cesar G

2015-12-01

This study was aimed at systematically reviewing evidence of the association between breastfeeding and performance in intelligence tests. Two independent searches were carried out using Medline, LILACS, SCIELO and Web of Science. Studies restricted to infants and those where estimates were not adjusted for stimulation or interaction at home were excluded. Fixed- and random-effects models were used to pool the effect estimates, and a random-effects regression was used to assess potential sources of heterogeneity. We included 17 studies with 18 estimates of the relationship between breastfeeding and performance in intelligence tests. In a random-effects model, breastfed subjects achieved a higher IQ [mean difference: 3.44 points (95% confidence interval: 2.30; 4.58)]. We found no evidence of publication bias. Studies that controlled for maternal IQ showed a smaller benefit from breastfeeding [mean difference 2.62 points (95% confidence interval: 1.25; 3.98)]. In the meta-regression, none of the study characteristics explained the heterogeneity among the studies. Breastfeeding is related to improved performance in intelligence tests. A positive effect of breastfeeding on cognition was also observed in a randomised trial. This suggests that the association is causal. ©2015 The Authors. Acta Paediatrica published by John Wiley & Sons Ltd on behalf of Foundation Acta Paediatrica.

Intelligent products : A survey

NARCIS (Netherlands)

Meyer, G.G.; Främling, K.; Holmström, J.

This paper presents an overview of the field of Intelligent Products. As Intelligent Products have many facets, this paper is mainly focused on the concept behind Intelligent Products, the technical foundations, and the achievable practical goals of Intelligent Products. A novel classification of

Benefits of collective intelligence: Swarm intelligent foraging, an ethnographic research

Directory of Open Access Journals (Sweden)

Sivave Mashingaidze

2014-12-01

Full Text Available Wisdom of crowds; bees, colonies of ants, schools of fish, flocks of birds, and fireflies flashing synchronously are all examples of highly coordinated behaviors that emerge from collective, decentralized intelligence. This article is an ethnographic study of swarm intelligence foraging of swarms and the benefits derived from collective decision making. The author used using secondary data analysis to look at the benefits of swarm intelligence in decision making to achieve intended goals. Concepts like combined decision making and consensus were discussed and four principles of swarm intelligence were also discussed viz; coordination, cooperation, deliberation and collaboration. The research found out that collective decision making in swarms is the touchstone of achieving their goals. The research further recommended corporate to adopt collective intelligence for business sustainability.

Intelligence: Real or artificial?

OpenAIRE

Schlinger, Henry D.

1992-01-01

Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally r...

A cognitive robotic system based on the Soar cognitive architecture for mobile robot navigation, search, and mapping missions

Science.gov (United States)

Hanford, Scott D.

Most unmanned vehicles used for civilian and military applications are remotely operated or are designed for specific applications. As these vehicles are used to perform more difficult missions or a larger number of missions in remote environments, there will be a great need for these vehicles to behave intelligently and autonomously. Cognitive architectures, computer programs that define mechanisms that are important for modeling and generating domain-independent intelligent behavior, have the potential for generating intelligent and autonomous behavior in unmanned vehicles. The research described in this presentation explored the use of the Soar cognitive architecture for cognitive robotics. The Cognitive Robotic System (CRS) has been developed to integrate software systems for motor control and sensor processing with Soar for unmanned vehicle control. The CRS has been tested using two mobile robot missions: outdoor navigation and search in an indoor environment. The use of the CRS for the outdoor navigation mission demonstrated that a Soar agent could autonomously navigate to a specified location while avoiding obstacles, including cul-de-sacs, with only a minimal amount of knowledge about the environment. While most systems use information from maps or long-range perceptual capabilities to avoid cul-de-sacs, a Soar agent in the CRS was able to recognize when a simple approach to avoiding obstacles was unsuccessful and switch to a different strategy for avoiding complex obstacles. During the indoor search mission, the CRS autonomously and intelligently searches a building for an object of interest and common intersection types. While searching the building, the Soar agent builds a topological map of the environment using information about the intersections the CRS detects. The agent uses this topological model (along with Soar's reasoning, planning, and learning mechanisms) to make intelligent decisions about how to effectively search the building. Once the

Colloquium paper: adaptive specializations, social exchange, and the evolution of human intelligence.

Science.gov (United States)

Cosmides, Leda; Barrett, H Clark; Tooby, John

2010-05-11

Blank-slate theories of human intelligence propose that reasoning is carried out by general-purpose operations applied uniformly across contents. An evolutionary approach implies a radically different model of human intelligence. The task demands of different adaptive problems select for functionally specialized problem-solving strategies, unleashing massive increases in problem-solving power for ancestrally recurrent adaptive problems. Because exchange can evolve only if cooperators can detect cheaters, we hypothesized that the human mind would be equipped with a neurocognitive system specialized for reasoning about social exchange. Whereas humans perform poorly when asked to detect violations of most conditional rules, we predicted and found a dramatic spike in performance when the rule specifies an exchange and violations correspond to cheating. According to critics, people's uncanny accuracy at detecting violations of social exchange rules does not reflect a cheater detection mechanism, but extends instead to all rules regulating when actions are permitted (deontic conditionals). Here we report experimental tests that falsify these theories by demonstrating that deontic rules as a class do not elicit the search for violations. We show that the cheater detection system functions with pinpoint accuracy, searching for violations of social exchange rules only when these are likely to reveal the presence of someone who intends to cheat. It does not search for violations of social exchange rules when these are accidental, when they do not benefit the violator, or when the situation would make cheating difficult.

Artificial intelligence, expert systems, computer vision, and natural language processing

Science.gov (United States)

Gevarter, W. B.

1984-01-01

An overview of artificial intelligence (AI), its core ingredients, and its applications is presented. The knowledge representation, logic, problem solving approaches, languages, and computers pertaining to AI are examined, and the state of the art in AI is reviewed. The use of AI in expert systems, computer vision, natural language processing, speech recognition and understanding, speech synthesis, problem solving, and planning is examined. Basic AI topics, including automation, search-oriented problem solving, knowledge representation, and computational logic, are discussed.

Searching for a WISC-R Profile for Learning Disabled Children: An Inappropriate Task?

Science.gov (United States)

Ryckman, David B.

1981-01-01

Although indexes of scatter on the Wechsler Intelligence Scale for Children-Revised computed for 100 learning disabled (LD) elementary children were significantly greater than values previously reported for the normal standardized sample, the substantial overlap suggests the inadvisability of continuing the search for a characteristic LD profile.…

Quality control of intelligence research

International Nuclear Information System (INIS)

Lu Yan; Xin Pingping; Wu Jian

2014-01-01

Quality control of intelligence research is the core issue of intelligence management, is a problem in study of information science This paper focuses on the performance of intelligence to explain the significance of intelligence research quality control. In summing up the results of the study on the basis of the analysis, discusses quality control methods in intelligence research, introduces the experience of foreign intelligence research quality control, proposes some recommendations to improve quality control in intelligence research. (authors)

Intelligence Issues for Congress

Science.gov (United States)

2013-04-23

open source information— osint (newspapers...by user agencies. Section 1052 of the Intelligence Reform Act expressed the sense of Congress that there should be an open source intelligence ...center to coordinate the collection, analysis, production, and dissemination of open source intelligence to other intelligence agencies. An Open Source

Orchestrating Multiple Intelligences

Science.gov (United States)

Moran, Seana; Kornhaber, Mindy; Gardner, Howard

2006-01-01

Education policymakers often go astray when they attempt to integrate multiple intelligences theory into schools, according to the originator of the theory, Howard Gardner, and his colleagues. The greatest potential of a multiple intelligences approach to education grows from the concept of a profile of intelligences. Each learner's intelligence…

Semantic Business Intelligence - a New Generation of Business Intelligence

Directory of Open Access Journals (Sweden)

Dinu AIRINEI

2012-01-01

Full Text Available Business Intelligence Solutions represents applications used by companies to manage process and analyze data to provide substantiated decision. In the context of Semantic Web develop-ment trend is to integrate semantic unstructured data, making business intelligence solutions to be redesigned in such a manner that can analyze, process and synthesize, in addition to traditional data and data integrated with semantic another form and structure. This invariably leads appearance of new BI solution, called Semantic Business Intelligence.

Research of Classical and Intelligent Information System Solutions for Criminal Intelligence Analysis

OpenAIRE

Šimović, Vladimir

2001-01-01

The objective of this study is to present research on classical and intelligent information system solutions used in criminal intelligence analysis in Croatian security system theory. The study analyses objective and classical methods of information science, including artificial intelligence and other scientific methods. The intelligence and classical software solutions researched, proposed, and presented in this study were used in developing the integrated information system for the Croatian...

Improving multivariate Horner schemes with Monte Carlo tree search

Science.gov (United States)

Kuipers, J.; Plaat, A.; Vermaseren, J. A. M.; van den Herik, H. J.

2013-11-01

Optimizing the cost of evaluating a polynomial is a classic problem in computer science. For polynomials in one variable, Horner's method provides a scheme for producing a computationally efficient form. For multivariate polynomials it is possible to generalize Horner's method, but this leaves freedom in the order of the variables. Traditionally, greedy schemes like most-occurring variable first are used. This simple textbook algorithm has given remarkably efficient results. Finding better algorithms has proved difficult. In trying to improve upon the greedy scheme we have implemented Monte Carlo tree search, a recent search method from the field of artificial intelligence. This results in better Horner schemes and reduces the cost of evaluating polynomials, sometimes by factors up to two.

Searching for Exoplanets using Artificial Intelligence

Science.gov (United States)

Pearson, Kyle Alexander; Palafox, Leon; Griffith, Caitlin Ann

2017-10-01

In the last decade, over a million stars were monitored to detect transiting planets. The large volume of data obtained from current and future missions (e.g. Kepler, K2, TESS and LSST) requires automated methods to detect the signature of a planet. Manual interpretation of potential exoplanet candidates is labor intensive and subject to human error, the results of which are difficult to quantify. Here we present a new method of detecting exoplanet candidates in large planetary search projects which, unlike current methods uses a neural network. Neural networks, also called ``deep learning'' or ``deep nets'', are a state of the art machine learning technique designed to give a computer perception into a specific problem by training it to recognize patterns. Unlike past transit detection algorithms, the deep net learns to characterize the data instead of relying on hand-coded metrics that humans perceive as the most representative. Exoplanet transits have different shapes, as a result of, e.g. the planet's and stellar atmosphere and transit geometry. Thus, a simple template does not suffice to capture the subtle details, especially if the signal is below the noise or strong systematics are present. Current false-positive rates from the Kepler data are estimated around 12.3% for Earth-like planets and there has been no study of the false negative rates. It is therefore important to ask how the properties of current algorithms exactly affect the results of the Kepler mission and, future missions such as TESS, which flies next year. These uncertainties affect the fundamental research derived from missions, such as the discovery of habitable planets, estimates of their occurrence rates and our understanding about the nature and evolution of planetary systems.

Geometrical Fuzzy Search Method for the Business Information Security Systems

Directory of Open Access Journals (Sweden)

Grigory Grigorievich Novikov

2014-12-01

Full Text Available The main reason of the article is how to use one of new fuzzy search method for information security of business or some other purposes. So many sensitive information leaks are through non-classified documents legal publishing. That’s why many intelligence services like to use the “mosaic” information collection method so much: This article is about how to prevent it.

Artificial Consciousness or Artificial Intelligence

OpenAIRE

Spanache Florin

2017-01-01

Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus a...

Intelligent mechatronics; Intelligent mechatronics

Energy Technology Data Exchange (ETDEWEB)

Hashimoto, H. [The University of Tokyo, Tokyo (Japan). Institute of Industrial Science

1995-10-01

Intelligent mechatronics (IM) was explained as follows: a study of IM essentially targets realization of a robot namely, but in the present stage the target is a creation of new values by intellectualization of machine, that is, a combination of the information infrastructure and the intelligent machine system. IM is also thought to be constituted of computers positively used and micromechatronics. The paper next introduces examples of IM study, mainly those the author is concerned with as shown below: sensor gloves, robot hands, robot eyes, tele operation, three-dimensional object recognition, mobile robot, magnetic bearing, construction of remote controlled unmanned dam, robot network, sensitivity communication using neuro baby, etc. 27 figs.

Paradigms of forensic science and legal process: a critical diagnosis.

Science.gov (United States)

Roberts, Paul

2015-08-05

This article reconsiders the relationship between criminal adjudication and forensic expertise in the light of 'new paradigms' of forensic practice and recent law reform. It briefly summarizes conventional wisdom on the typical shortcomings of forensic science and other expert evidence, as a springboard for a more searching critical diagnosis of longstanding maladies. The fundamentally jurisdictional nature of law is emphasized, and some implications for expert testimony noted. English law's traditionally adversarial model of criminal procedure is then reassessed, taking account of a proper understanding of its normative structure and modern development, and drawing on comparative legal research and theorizing to obtain a more rounded second opinion. In conclusion, some avenues for intelligent prescription are canvassed, highlighting the importance of promoting and facilitating effective communication between experts, lawyers and courts, and prioritizing modest practical remedies over radical surgery. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Brain Intelligence: Go Beyond Artificial Intelligence

OpenAIRE

Lu, Huimin; Li, Yujie; Chen, Min; Kim, Hyoungseop; Serikawa, Seiichi

2017-01-01

Artificial intelligence (AI) is an important technology that supports daily social life and economic activities. It contributes greatly to the sustainable growth of Japan's economy and solves various social problems. In recent years, AI has attracted attention as a key for growth in developed countries such as Europe and the United States and developing countries such as China and India. The attention has been focused mainly on developing new artificial intelligence information communication ...

Business Intelligence Systems

Directory of Open Access Journals (Sweden)

Bogdan NEDELCU

2014-02-01

Full Text Available The aim of this article is to show the importance of business intelligence and its growing influence. It also shows when the concept of business intelligence was used for the first time and how it evolved over time. The paper discusses the utility of a business intelligence system in any organization and its contribution to daily activities. Furthermore, we highlight the role and the objectives of business intelligence systems inside an organization and the needs to grow the incomes and reduce the costs, to manage the complexity of the business environment and to cut IT costs so that the organization survives in the current competitive climate. The article contains information about architectural principles of a business intelligence system and how such a system can be achieved.

Geometrical shape optimization of a cold neutron source using artificial intelligence strategies

International Nuclear Information System (INIS)

Azmy, Y.Y.

1989-01-01

A new approach is developed for optimizing the geometrical shape of a cold neutron source to maximize its cold neutron outward leakage. An analogy is drawn between the shape optimization problem and a state space search, which is the fundamental problem in Artificial Intelligence applications. The new optimization concept is implemented in the computer code DAIT in which the physical model is represented by a two group, r-z geometry nodal diffusion method, and the state space search is conducted via the Nearest Neighbor algorithm. The accuracy of the nodal diffusion method solution is established on meshes of interest, and is shown to behave qualitatively the same as transport theory solutions. The dependence of the optimum shape and its value on several physical and search parameters is examined via numerical experimentation. 10 refs., 6 figs., 2 tabs

Professionalizing Intelligence Analysis

Directory of Open Access Journals (Sweden)

James B. Bruce

2015-09-01

Full Text Available This article examines the current state of professionalism in national security intelligence analysis in the U.S. Government. Since the introduction of major intelligence reforms directed by the Intelligence Reform and Terrorism Prevention Act (IRTPA in December, 2004, we have seen notable strides in many aspects of intelligence professionalization, including in analysis. But progress is halting, uneven, and by no means permanent. To consolidate its gains, and if it is to continue improving, the U.S. intelligence community (IC should commit itself to accomplishing a new program of further professionalization of analysis to ensure that it will develop an analytic cadre that is fully prepared to deal with the complexities of an emerging multipolar and highly dynamic world that the IC itself is forecasting. Some recent reforms in intelligence analysis can be assessed against established standards of more fully developed professions; these may well fall short of moving the IC closer to the more fully professionalized analytical capability required for producing the kind of analysis needed now by the United States.

Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction

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Jianzhou Wang

2014-01-01

Full Text Available Swarm intelligence (SI is widely and successfully applied in the engineering field to solve practical optimization problems because various hybrid models, which are based on the SI algorithm and statistical models, are developed to further improve the predictive abilities. In this paper, hybrid intelligent forecasting models based on the cuckoo search (CS as well as the singular spectrum analysis (SSA, time series, and machine learning methods are proposed to conduct short-term power load prediction. The forecasting performance of the proposed models is augmented by a rolling multistep strategy over the prediction horizon. The test results are representative of the out-performance of the SSA and CS in tuning the seasonal autoregressive integrated moving average (SARIMA and support vector regression (SVR in improving load forecasting, which indicates that both the SSA-based data denoising and SI-based intelligent optimization strategy can effectively improve the model’s predictive performance. Additionally, the proposed CS-SSA-SARIMA and CS-SSA-SVR models provide very impressive forecasting results, demonstrating their strong robustness and universal forecasting capacities in terms of short-term power load prediction 24 hours in advance.

Revolutionary Intelligence: The Expanding Intelligence Role of the Iranian Revolutionary Guard Corps

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Udit Banerjea

2015-09-01

Full Text Available The Iranian Revolutionary Guard Corps (IRGC is a military and paramilitary organization that is meant to defend the ideals of the Iranian Islamic Revolution in 1979. Since its formation, the IRGC has grown in influence and its intelligence role has expanded. This paper examines the role of the IRGC in Iran’s intelligence system through a comprehensive analysis of the organization of the IRGC’s intelligence arm, along with its operations and capabilities. In doing so, the scope, objectives, resources, customers, and sponsors of the IRGC’s intelligence activities are also analyzed. Additionally, this paper explores how the IRGC interacts with the government of Iran, the Ministry of Intelligence and Security (MOIS, other key internal stakeholders, and foreign client organizations. A key focus of this analysis is the evolution of the relationship between the IRGC and the MOIS and the growing influence of the IRGC in Iran’s intelligence community over the last decade. The paper concludes that the IRGC has now eclipsed the MOIS within Iran’s intelligence community and is one of the most powerful institutions in Iranian politics today, using its intelligence activities as its key means of maintaining power and influence within the country.

77 FR 32952 - Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting

Science.gov (United States)

2012-06-04

... DEPARTMENT OF DEFENSE Office of the Secretary Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting AGENCY: Department of Defense, Defense Intelligence Agency, National Intelligence University. ACTION: Notice of closed meeting. SUMMARY: Pursuant to the provisions of...

Intelligent playgrounds

DEFF Research Database (Denmark)

Larsen, Lasse Juel

2009-01-01

This paper examines play, gaming and learning in regard to intelligent playware developed for outdoor use. The key questions are how does these novel artefacts influence the concept of play, gaming and learning. Up until now play and game have been understood as different activities. This paper...... examines if the sharp differentiation between the two can be uphold in regard to intelligent playware for outdoor use. Play and game activities will be analysed and viewed in conjunction with learning contexts. This paper will stipulate that intelligent playware facilitates rapid shifts in contexts...

Artificial intelligence

CERN Document Server

Ennals, J R

1987-01-01

Artificial Intelligence: State of the Art Report is a two-part report consisting of the invited papers and the analysis. The editor first gives an introduction to the invited papers before presenting each paper and the analysis, and then concludes with the list of references related to the study. The invited papers explore the various aspects of artificial intelligence. The analysis part assesses the major advances in artificial intelligence and provides a balanced analysis of the state of the art in this field. The Bibliography compiles the most important published material on the subject of

Advanced intelligence and mechanism approach

Institute of Scientific and Technical Information of China (English)

ZHONG Yixin

2007-01-01

Advanced intelligence will feature the intelligence research in next 50 years.An understanding of the concept of advanced intelligence as well as its importance will be provided first,and detailed analysis on an approach,the mechanism approach.suitable to the advanced intelligence research will then be flolowed.And the mutual relationship among mechanism approach,traditional approaches existed in artificial intelligence research,and the cognitive informatics will be discussed.It is interesting to discover that mechanism approach is a good one to the Advanced Intelligence research and a tmified form of the existed approaches to artificial intelligence.

iHelp: an intelligent online helpdesk system.

Science.gov (United States)

Wang, Dingding; Li, Tao; Zhu, Shenghuo; Gong, Yihong

2011-02-01

Due to the importance of high-quality customer service, many companies use intelligent helpdesk systems (e.g., case-based systems) to improve customer service quality. However, these systems face two challenges: 1) Case retrieval measures: most case-based systems use traditional keyword-matching-based ranking schemes for case retrieval and have difficulty to capture the semantic meanings of cases and 2) result representation: most case-based systems return a list of past cases ranked by their relevance to a new request, and customers have to go through the list and examine the cases one by one to identify their desired cases. To address these challenges, we develop iHelp, an intelligent online helpdesk system, to automatically find problem-solution patterns from the past customer-representative interactions. When a new customer request arrives, iHelp searches and ranks the past cases based on their semantic relevance to the request, groups the relevant cases into different clusters using a mixture language model and symmetric matrix factorization, and summarizes each case cluster to generate recommended solutions. Case and user studies have been conducted to show the full functionality and the effectiveness of iHelp.

A review of the scientific rationale and methods used in the search for other planetary systems

Science.gov (United States)

Black, D. C.

1985-01-01

Planetary systems appear to be one of the crucial links in the chain leading from simple molecules to living systems, particularly complex (intelligent?) living systems. Although there is currently no observational proof of the existence of any planetary system other than our own, techniques are now being developed which will permit a comprehensive search for other planetary systems. The scientific rationale for and methods used in such a search effort are reviewed here.

Computational Intelligence in Intelligent Data Analysis

CERN Document Server

Nürnberger, Andreas

2013-01-01

Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intell...

Improved Multiobjective Harmony Search Algorithm with Application to Placement and Sizing of Distributed Generation

Directory of Open Access Journals (Sweden)

Wanxing Sheng

2014-01-01

Full Text Available To solve the comprehensive multiobjective optimization problem, this study proposes an improved metaheuristic searching algorithm with combination of harmony search and the fast nondominated sorting approach. This is a kind of the novel intelligent optimization algorithm for multiobjective harmony search (MOHS. The detailed description and the algorithm formulating are discussed. Taking the optimal placement and sizing issue of distributed generation (DG in distributed power system as one example, the solving procedure of the proposed method is given. Simulation result on modified IEEE 33-bus test system and comparison with NSGA-II algorithm has proved that the proposed MOHS can get promising results for engineering application.

Before and Beyond Anticipatory Intelligence: Assessing the Potential for Crowdsourcing and Intelligence Studies

Directory of Open Access Journals (Sweden)

Alexander Halman

2015-10-01

Full Text Available Crowdsourcing is a new tool for businesses, academics, and now intelligence analysts. Enabled by recent technology, crowdsourcing allows researchers to harness the wisdom of crowds and provide recommendations and insight into complex problems. This paper examines the potential benefits and limitations of crowdsourcing for intelligence analysis and the intelligence community beyond its primary use: anticipatory intelligence. The author constructs a model and compares it to existing crowdsourcing theories in business, information science, and public policy. Finally, he offers advice for intelligence analysis and public policy.

Intelligent Information Retrieval: Diagnosing Information Need. Part II. Uncertainty Expansion in a Prototype of a Diagnostic IR Tool.

Science.gov (United States)

Cole, Charles; Cantero, Pablo; Sauve, Diane

1998-01-01

Outlines a prototype of an intelligent information-retrieval tool to facilitate information access for an undergraduate seeking information for a term paper. Topics include diagnosing the information need, Kuhlthau's information-search-process model, Shannon's mathematical theory of communication, and principles of uncertainty expansion and…

2015 Chinese Intelligent Systems Conference

CERN Document Server

Du, Junping; Li, Hongbo; Zhang, Weicun; CISC’15

2016-01-01

This book presents selected research papers from the 2015 Chinese Intelligent Systems Conference (CISC’15), held in Yangzhou, China. The topics covered include multi-agent systems, evolutionary computation, artificial intelligence, complex systems, computation intelligence and soft computing, intelligent control, advanced control technology, robotics and applications, intelligent information processing, iterative learning control, and machine learning. Engineers and researchers from academia, industry and the government can gain valuable insights into solutions combining ideas from multiple disciplines in the field of intelligent systems.

Intelligence and the machinery of government: conceptualizing the intelligence community

OpenAIRE

Davies, PHJ

2010-01-01

This article argues that the failure to address intelligence agencies as public organizations part and parcel with the overt machinery of government constitutes a significant lacuna both in the specialist study of intelligence and the broader discipline of public administration studies. The role and status of intelligence institutions as aspects of the machinery of central government is examined, along with the prospects of certain key paradigms in the field for understanding those institutio...

Hybrid Artificial Bee Colony Algorithm and Particle Swarm Search for Global Optimization

Directory of Open Access Journals (Sweden)

Wang Chun-Feng

2014-01-01

Full Text Available Artificial bee colony (ABC algorithm is one of the most recent swarm intelligence based algorithms, which has been shown to be competitive to other population-based algorithms. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. To overcome this problem, we propose a novel artificial bee colony algorithm based on particle swarm search mechanism. In this algorithm, for improving the convergence speed, the initial population is generated by using good point set theory rather than random selection firstly. Secondly, in order to enhance the exploitation ability, the employed bee, onlookers, and scouts utilize the mechanism of PSO to search new candidate solutions. Finally, for further improving the searching ability, the chaotic search operator is adopted in the best solution of the current iteration. Our algorithm is tested on some well-known benchmark functions and compared with other algorithms. Results show that our algorithm has good performance.

Secular gains in fluid intelligence: evidence from the Culture-Fair intelligence test.

Science.gov (United States)

Colom, Roberto; García-López, Oscar

2003-01-01

There is no doubt about the reality of the secular increase in cognitive test scores. However, there is disagreement about a key issue: does the observed increase reflect a genuine upward trend in intelligence? Evidence from the Raven test is clear, although there are some doubts about its adequacy as a fine-grained measure of fluid intelligence. Evidence from the so-called 'method of correlated vectors' is much less clear. When a crystallized battery is considered, the results leave little doubt: the increase does not reflect gains in general intelligence. However, when a fluid battery is analysed, the increase does reflect gains in general intelligence. The present study uses one of the best available measures of fluid intelligence (the Culture-Fair intelligence test) to provide new evidence for the secular increase in fluid intelligence, beyond the findings from the Raven test and the method of correlated vectors. A total of 4498 Spanish high school students and high school graduates were tested within a time interval of 20 and 23 years, respectively. The results show that there is a clear upward trend in intelligence. Moreover, students show an average increase equivalent to 6 IQ points, while graduates show an average increase of 4 IQ points. Therefore, more selected people (graduates) show a smaller increase than less selected people (students). Some implications are discussed.

Dual-mode nested search method for categorical uncertain multi-objective optimization

Science.gov (United States)

Tang, Long; Wang, Hu

2016-10-01

Categorical multi-objective optimization is an important issue involved in many matching design problems. Non-numerical variables and their uncertainty are the major challenges of such optimizations. Therefore, this article proposes a dual-mode nested search (DMNS) method. In the outer layer, kriging metamodels are established using standard regular simplex mapping (SRSM) from categorical candidates to numerical values. Assisted by the metamodels, a k-cluster-based intelligent sampling strategy is developed to search Pareto frontier points. The inner layer uses an interval number method to model the uncertainty of categorical candidates. To improve the efficiency, a multi-feature convergent optimization via most-promising-area stochastic search (MFCOMPASS) is proposed to determine the bounds of objectives. Finally, typical numerical examples are employed to demonstrate the effectiveness of the proposed DMNS method.

Scholastic Success: Fluid Intelligence, Personality, and Emotional Intelligence

Science.gov (United States)

Downey, Luke A.; Lomas, Justine; Billings, Clare; Hansen, Karen; Stough, Con

2014-01-01

The aim of the current study was to examine the role of fluid intelligence, personality traits, and emotional intelligence (EI) in predicting female Year 9 students' grade point average (GPA) and to determine whether any differences in scholastic performance were related to differences in EI or Personality. Two-hundred and forty-three female…

Perceived emotional intelligence, general intelligence and early professional success: predictive and incremental validity

Directory of Open Access Journals (Sweden)

José-Manuel de Haro

2014-05-01

Full Text Available Although the study of factors affecting career success has shown connections between biographical and other aspects related to ability, knowledge and personality, few studies have examined the relationship between emotional intelligence and professional success at the initial career stage. When these studies were carried out, the results showed significant relationships between the dimensions of emotional intelligence (emotional self-awareness, self-regulation, social awareness or social skills and the level of professional competence. In this paper, we analyze the relationship between perceived emotional intelligence, measured by the Trait Meta-Mood Scale (TMMS-24 questionnaire, general intelligence assessed by the Cattell factor "g" test, scale 3, and extrinsic indicators of career success, in a sample of 130 graduates at the beginning of their careers. Results from hierarchical regression analysis indicate that emotional intelligence makes a specific contribution to the prediction of salary, after controlling the general intelligence effect. The perceived emotional intelligence dimensions of TMMS repair, TMMS attention and sex show a higher correlation and make a greater contribution to professional success than general intelligence. The implications of these results for the development of socio-emotional skills among University graduates are discussed.

Generative Adversarial Networks-Based Semi-Supervised Learning for Hyperspectral Image Classification

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Zhi He

2017-10-01

Full Text Available Classification of hyperspectral image (HSI is an important research topic in the remote sensing community. Significant efforts (e.g., deep learning have been concentrated on this task. However, it is still an open issue to classify the high-dimensional HSI with a limited number of training samples. In this paper, we propose a semi-supervised HSI classification method inspired by the generative adversarial networks (GANs. Unlike the supervised methods, the proposed HSI classification method is semi-supervised, which can make full use of the limited labeled samples as well as the sufficient unlabeled samples. Core ideas of the proposed method are twofold. First, the three-dimensional bilateral filter (3DBF is adopted to extract the spectral-spatial features by naturally treating the HSI as a volumetric dataset. The spatial information is integrated into the extracted features by 3DBF, which is propitious to the subsequent classification step. Second, GANs are trained on the spectral-spatial features for semi-supervised learning. A GAN contains two neural networks (i.e., generator and discriminator trained in opposition to one another. The semi-supervised learning is achieved by adding samples from the generator to the features and increasing the dimension of the classifier output. Experimental results obtained on three benchmark HSI datasets have confirmed the effectiveness of the proposed method , especially with a limited number of labeled samples.

Proactive malware detection

Science.gov (United States)

Gloster, Jonathan; Diep, Michael; Dredden, David; Mix, Matthew; Olsen, Mark; Price, Brian; Steil, Betty

2014-06-01

Small-to-medium sized businesses lack resources to deploy and manage high-end advanced solutions to deter sophisticated threats from well-funded adversaries, but evidence shows that these types of businesses are becoming key targets. As malicious code and network attacks become more sophisticated, classic signature-based virus and malware detection methods are less effective. To augment the current malware methods of detection, we developed a proactive approach to detect emerging malware threats using open source tools and intelligence to discover patterns and behaviors of malicious attacks and adversaries. Technical and analytical skills are combined to track adversarial behavior, methods and techniques. We established a controlled (separated domain) network to identify, monitor, and track malware behavior to increase understanding of the methods and techniques used by cyber adversaries. We created a suite of tools that observe the network and system performance looking for anomalies that may be caused by malware. The toolset collects information from open-source tools and provides meaningful indicators that the system was under or has been attacked. When malware is discovered, we analyzed and reverse engineered it to determine how it could be detected and prevented. Results have shown that with minimum resources, cost effective capabilities can be developed to detect abnormal behavior that may indicate malicious software.

Complementary Machine Intelligence and Human Intelligence in Virtual Teaching Assistant for Tutoring Program Tracing

Science.gov (United States)

Chou, Chih-Yueh; Huang, Bau-Hung; Lin, Chi-Jen

2011-01-01

This study proposes a virtual teaching assistant (VTA) to share teacher tutoring tasks in helping students practice program tracing and proposes two mechanisms of complementing machine intelligence and human intelligence to develop the VTA. The first mechanism applies machine intelligence to extend human intelligence (teacher answers) to evaluate…

A Belief-Space Approach to Integrated Intelligence - Research Area 10.3: Intelligent Networks

Science.gov (United States)

2017-12-05

A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks The views, opinions and/or findings contained in this...Technology (MIT) Title: A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks Report Term: 0-Other Email: tlp...students presented progress and received feedback from the research group . o wrote papers on their research and submitted them to leading conferences

Artificial Intelligence

CERN Document Server

Warwick, Kevin

2011-01-01

if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory

Intelligence of programs

Energy Technology Data Exchange (ETDEWEB)

Novak, D

1982-01-01

A general discussion about the level of artificial intelligence in computer programs is presented. The suitability of various languages for the development of complex, intelligent programs is discussed, considering fourth-generation language as well as the well established structured COBOL language. It is concluded that the success of automation in many administrative fields depends to a large extent on the development of intelligent programs.

The Breakthrough Listen Search for Intelligent Life: Radio Frequency Interference in the Green Bank Telescope

Science.gov (United States)

Dana, Ryan

2018-01-01

In the search for extra terrestrial intelligence, the vast majority of our “signals of interest,” are simply satellite radio frequency interference. The goal to my research, therefore, was to accurately predict the exact locations of satellites in our sky to analyze specific satellites causing the interference as well as potentially predict when satellites will cross in the way of our beams so that we can further optimize our scripts and get more usable data.I have built an algorithm that plots the exact location in altitude and azimuth of any grouping of satellites that you want in the sky from any position on earth in latitude, longitude, and elevation. From there, you can input a specific right ascension and declination of the location you are trying to track in the sky with a telescope. Using these inputs, we can calculate the angular and positional distance of certain satellites to our beam to further analyze satellite radio frequency interference.The process begins by importing a list of Two Line Element information that the algorithm reads in. Two Line Elements are how Satellites are organized and are updated frequently. They give a variety of information ranging from the Satellite ID to its Mean Motion or anomaly. From there, the code breaks up the information given by these elements to predict their location. The algorithm can also plot in 3D coordinates around an earthlike sphere to conceptualize the route that each Satellite has taken.The code has been used in a variety of ways but most notably to identify satellites interfering with the beam for Arecibo’s Ross 128 Candidate signal. From here, the code will be the backbone to calculating drift rates, Doppler shifts and intensity of certain satellites and why our team consistently receives estranged satellite signals of interest. Furthermore, in the case of a serious candidate signal in the near future, it will be important to analyze satellites interfering in the beam.

Relationships between the Kaufman Brief Intelligence Test and the Wechsler Adult Intelligence Scale-Third Edition.

Science.gov (United States)

Walters, Steven O; Weaver, Kenneth A

2003-06-01

The Kaufman Brief Intelligence Test detects learning problems of young students and is a screen for whether a more comprehensive test of intelligence is needed. A study to assess whether this test was valid as an adult intelligence test was conducted with 20 undergraduate psychology majors. The correlations between the Kaufman Brief Intelligence Test's Composite, Vocabulary, and Matrices test scores and their corresponding Wechsler Adult Intelligence Scale-Third Edition test scores, the Full Scale (r=.88), Verbal (r=.77), and Performance scores (r=.87), indicated very strong relationships. In addition, no significant differences were obtained between the Composite, Vocabulary, and Matrices means of the Kaufman Brief Intelligence Test and the Full Scale, Verbal, and Performance means of the WAIS-III. The Kaufman Brief Intelligence Test appears to be a valid test of intelligence for adults.

Artificial intelligence based models for stream-flow forecasting: 2000-2015

Science.gov (United States)

Yaseen, Zaher Mundher; El-shafie, Ahmed; Jaafar, Othman; Afan, Haitham Abdulmohsin; Sayl, Khamis Naba

2015-11-01

The use of Artificial Intelligence (AI) has increased since the middle of the 20th century as seen in its application in a wide range of engineering and science problems. The last two decades, for example, has seen a dramatic increase in the development and application of various types of AI approaches for stream-flow forecasting. Generally speaking, AI has exhibited significant progress in forecasting and modeling non-linear hydrological applications and in capturing the noise complexity in the dataset. This paper explores the state-of-the-art application of AI in stream-flow forecasting, focusing on defining the data-driven of AI, the advantages of complementary models, as well as the literature and their possible future application in modeling and forecasting stream-flow. The review also identifies the major challenges and opportunities for prospective research, including, a new scheme for modeling the inflow, a novel method for preprocessing time series frequency based on Fast Orthogonal Search (FOS) techniques, and Swarm Intelligence (SI) as an optimization approach.

Fluid intelligence: A brief history.

Science.gov (United States)

Kent, Phillip

2017-01-01

The concept of fluid and crystallized intelligence was introduced to the psychological community approximately 75 years ago by Raymond B. Cattell, and it continues to be an area of active research and controversy. The purpose of this paper is to provide a brief overview of the origin of the concept, early efforts to define intelligence and uses of intelligence tests to address pressing social issues, and the ongoing controversies associated with fluid intelligence and the structure of intelligence. The putative neuropsychological underpinnings and neurological substrates of fluid intelligence are discussed.

Educational Programs for Intelligence Professionals.

Science.gov (United States)

Miller, Jerry P.

1994-01-01

Discusses the need for education programs for competitive intelligence professionals. Highlights include definitions of intelligence functions, focusing on business intelligence; information utilization by decision makers; information sources; competencies for intelligence professionals; and the development of formal education programs. (38…

A literature search tool for intelligent extraction of disease-associated genes.

Science.gov (United States)

Jung, Jae-Yoon; DeLuca, Todd F; Nelson, Tristan H; Wall, Dennis P

2014-01-01

To extract disorder-associated genes from the scientific literature in PubMed with greater sensitivity for literature-based support than existing methods. We developed a PubMed query to retrieve disorder-related, original research articles. Then we applied a rule-based text-mining algorithm with keyword matching to extract target disorders, genes with significant results, and the type of study described by the article. We compared our resulting candidate disorder genes and supporting references with existing databases. We demonstrated that our candidate gene set covers nearly all genes in manually curated databases, and that the references supporting the disorder-gene link are more extensive and accurate than other general purpose gene-to-disorder association databases. We implemented a novel publication search tool to find target articles, specifically focused on links between disorders and genotypes. Through comparison against gold-standard manually updated gene-disorder databases and comparison with automated databases of similar functionality we show that our tool can search through the entirety of PubMed to extract the main gene findings for human diseases rapidly and accurately.

The Importance of Trust in the Adoption and Use of Intelligent Assistive Technology by Older Adults to Support Aging in Place: Scoping Review Protocol.

Science.gov (United States)

McMurray, Josephine; Strudwick, Gillian; Forchuk, Cheryl; Morse, Adam; Lachance, Jessica; Baskaran, Arani; Allison, Lauren; Booth, Richard

2017-11-02

Intelligent assistive technologies that complement and extend human abilities have proliferated in recent years. Service robots, home automation equipment, and other digital assistant devices possessing artificial intelligence are forms of assistive technologies that have become popular in society. Older adults (>55 years of age) have been identified by industry, government, and researchers as a demographic who can benefit significantly from the use of intelligent assistive technology to support various activities of daily living. The purpose of this scoping review is to summarize the literature on the importance of the concept of "trust" in the adoption of intelligent assistive technologies to assist aging in place by older adults. Using a scoping review methodology, our search strategy will examine the following databases: ACM Digital Library, Allied and Complementary Medicine Database (AMED), Cumulative Index to Nursing and Allied Health Literature (CINAHL), Medline, PsycINFO, Scopus, and Web of Science. Two reviewers will independently screen the initial titles obtained from the search, and these results will be further inspected by other members of the research team for inclusion in the review. This review will provide insights into how the concept of trust is actualized in the adoption of intelligent assistive technology by older adults. Preliminary sensitization to the literature suggests that the concept of trust is fluid, unstable, and intimately tied to the type of intelligent assistive technology being examined. Furthermore, a wide range of theoretical lenses that include elements of trust have been used to examine this concept. This review will describe the concept of trust in the adoption of intelligent assistive technology by older adults, and will provide insights for practitioners, policy makers, and technology vendors for future practice. ©Josephine McMurray, Gillian Strudwick, Cheryl Forchuk, Adam Morse, Jessica Lachance, Arani Baskaran, Lauren

Harmonizing intelligence terminologies in business: Literature review

Directory of Open Access Journals (Sweden)

Sivave Mashingaidze

2014-11-01

Full Text Available The principal objective of this article is to do a literature review of different intelligence terminology with the aim of establishing the common attributes and differences, and to propose a universal and comprehensive definition of intelligence for common understanding amongst users. The findings showed that Competitive Intelligence has the broadest scope of intelligence activities covering the whole external operating environment of the company and targeting all levels of decision-making for instance; strategic intelligence, tactical intelligence and operative intelligence. Another terminology was found called Cyber IntelligenceTM which encompasses competitor intelligence, strategic intelligence, market intelligence and counterintelligence. In conclusion although CI has the broadest scope of intelligence and umbrella to many intelligence concepts, still Business Intelligence, and Corporate Intelligence are often used interchangeably as CI

Business Intelligence using Software Agents

OpenAIRE

Ana-Ramona BOLOGA; Razvan BOLOGA

2011-01-01

This paper presents some ideas about business intelligence today and the importance of developing real time business solutions. The authors make an exploration of links between business intelligence and artificial intelligence and focuses specifically on the implementation of software agents-based systems in business intelligence. There are briefly presented some of the few solutions proposed so far that use software agents properties for the benefit of business intelligence. The authors then...

Advances in intelligent analysis of medical data and decision support systems

CERN Document Server

Iantovics, Barna

2013-01-01

This volume is a result of the fruitful and vivid discussions during the MedDecSup'2012 International Workshop bringing together a relevant body of knowledge, and new developments in the increasingly important field of medical informatics. This carefully edited book presents new ideas aimed at the development of intelligent processing of various kinds of medical information and the perfection of the contemporary computer systems for medical decision support. The book presents advances of the medical information systems for intelligent archiving, processing, analysis and search-by-content which will improve the quality of the medical services for every patient and of the global healthcare system. The book combines in a synergistic way theoretical developments with the practicability of the approaches developed and presents the last developments and achievements in  medical informatics to a broad range of readers: engineers, mathematicians, physicians, and PhD students.

Intelligent Data Storage and Retrieval for Design Optimisation – an Overview

Directory of Open Access Journals (Sweden)

C. Peebles

2005-01-01

Full Text Available This paper documents the findings of a literature review conducted by the Sir Lawrence Wackett Centre for Aerospace Design Technology at RMIT University. The review investigates aspects of a proposed system for intelligent design optimisation. Such a system would be capable of efficiently storing (and compressing if required a range of types of design data into an intelligent database. This database would be accessed by the system during subsequent design processes, allowing for search of relevant design data for re-use in later designs, allowing it to become very efficient in reducing the time for later designs as the database grows in size. Extensive research has been performed, in both theoretical aspects of the project, and practical examples of current similar systems. This research covers the areas of database systems, database queries, representation and compression of design data, geometric representation and heuristic methods for design applications. 

78 FR 32241 - Defense Intelligence Agency National Intelligence University Board of Visitors; Notice of Closed...

Science.gov (United States)

2013-05-29

... DEPARTMENT OF DEFENSE Office of the Secretary Defense Intelligence Agency National Intelligence University Board of Visitors; Notice of Closed Meeting AGENCY: National Intelligence University, Defense Intelligence Agency, Department of Defense. ACTION: Notice of closed meeting. SUMMARY: Pursuant to the...

75 FR 76423 - Defense Intelligence Agency National Defense Intelligence College Board of Visitors Closed Meeting

Science.gov (United States)

2010-12-08

... DEPARTMENT OF DEFENSE Office of the Secretary Defense Intelligence Agency National Defense Intelligence College Board of Visitors Closed Meeting AGENCY: National Defense Intelligence College, Defense Intelligence Agency, Department of Defense. ACTION: Notice of Closed Meeting. SUMMARY: Pursuant to the...

76 FR 28960 - Defense Intelligence Agency National Defense Intelligence College Board of Visitors Closed Meeting

Science.gov (United States)

2011-05-19

... DEPARTMENT OF DEFENSE Office of the Secretary Defense Intelligence Agency National Defense Intelligence College Board of Visitors Closed Meeting AGENCY: National Defense Intelligence College, Defense Intelligence Agency, Department of Defense. ACTION: Notice of Closed Meeting. SUMMARY: Pursuant to the...

Open source intelligence, open social intelligence and privacy by design

OpenAIRE

Casanovas, Pompeu; Royal Melbourne Institute of Technology (Austràlia). Centre for Applied Social Research

2014-01-01

Ponència presentada a European Conference on Social Intelligence (ECSI-2014) OSINT stands for Open Source Intelligence, (O)SI for (Open) Social Intelligence, PbD for Privacy by Design. The CAPER project has built an OSINT solution oriented to the prevention of organized crime. How to balance freedom and security? This position paper describes a way to embed the legal and ethical issues raised by the General Data Reform Package (GDRP) in Europe into this kind of surveillance platforms. It f...

Beyond AI: Multi-Intelligence (MI) Combining Natural and Artificial Intelligences in Hybrid Beings and Systems

OpenAIRE

Stephen Fox

2017-01-01

Framing strongly influences actions among technology proponents and end-users. Underlying much debate about artificial intelligence (AI) are several fundamental shortcomings in its framing. First, discussion of AI is atheoretical, and therefore has limited potential for addressing the complexity of causation. Second, intelligence is considered from an anthropocentric perspective that sees human intelligence, and intelligence developed by humans, as superior to all other intelligences. Thus, t...

Artificial Intelligence.

Science.gov (United States)

Wash, Darrel Patrick

1989-01-01

Making a machine seem intelligent is not easy. As a consequence, demand has been rising for computer professionals skilled in artificial intelligence and is likely to continue to go up. These workers develop expert systems and solve the mysteries of machine vision, natural language processing, and neural networks. (Editor)

Estimation of the Intelligence Quotient Using Wechsler Intelligence Scales in Children and Adolescents with Asperger Syndrome

Science.gov (United States)

Merchan-Naranjo, Jessica; Mayoral, Maria; Rapado-Castro, Marta; Llorente, Cloe; Boada, Leticia; Arango, Celso; Parellada, Mara

2012-01-01

Asperger syndrome (AS) patients show heterogeneous intelligence profiles and the validity of short forms for estimating intelligence has rarely been studied in this population. We analyzed the validity of Wechsler Intelligence Scale (WIS) short forms for estimating full-scale intelligence quotient (FSIQ) and assessing intelligence profiles in 29…

Business Intelligence using Software Agents

Directory of Open Access Journals (Sweden)

Ana-Ramona BOLOGA

2011-12-01

Full Text Available This paper presents some ideas about business intelligence today and the importance of developing real time business solutions. The authors make an exploration of links between business intelligence and artificial intelligence and focuses specifically on the implementation of software agents-based systems in business intelligence. There are briefly presented some of the few solutions proposed so far that use software agents properties for the benefit of business intelligence. The authors then propose some basic ideas for developing real-time agent-based software system for business intelligence in supply chain management, using Case Base Reasoning Agents.

Towards new success factors in technology intelligence evidence from a european benchmarking study

OpenAIRE

Schuh, Günther; Lau, Felix; Kabasci, Patrick; Bachmann, Heidi

2017-01-01

As a reaction to the fast changing, complex business environments of today, many technology-driven firms rely on technology intelligence - an integrated process of searching, assessing and disseminating relevant information and insights to decision makers within an organization. Despite this, many firms fail at assessing the relevant trends of their business appropriately. This paper addresses the underlying problem and examines antecedents of successful technology forecasting. Using the cons...

Intelligently interactive combat simulation

Science.gov (United States)

Fogel, Lawrence J.; Porto, Vincent W.; Alexander, Steven M.

2001-09-01

To be fully effective, combat simulation must include an intelligently interactive enemy... one that can be calibrated. But human operated combat simulations are uncalibratable, for we learn during the engagement, there's no average enemy, and we cannot replicate their culture/personality. Rule-based combat simulations (expert systems) are not interactive. They do not take advantage of unexpected mistakes, learn, innovate, and reflect the changing mission/situation. And it is presumed that the enemy does not have a copy of the rules, that the available experts are good enough, that they know why they did what they did, that their combat experience provides a sufficient sample and that we know how to combine the rules offered by differing experts. Indeed, expert systems become increasingly complex, costly to develop, and brittle. They have face validity but may be misleading. In contrast, intelligently interactive combat simulation is purpose- driven. Each player is given a well-defined mission, reference to the available weapons/platforms, their dynamics, and the sensed environment. Optimal tactics are discovered online and in real-time by simulating phenotypic evolution in fast time. The initial behaviors are generated randomly or include hints. The process then learns without instruction. The Valuated State Space Approach provides a convenient way to represent any purpose/mission. Evolutionary programming searches the domain of possible tactics in a highly efficient manner. Coupled together, these provide a basis for cruise missile mission planning, and for driving tank warfare simulation. This approach is now being explored to benefit Air Force simulations by a shell that can enhance the original simulation.

Generative Artificial Intelligence : Philosophy and Theory of Artificial Intelligence

NARCIS (Netherlands)

van der Zant, Tijn; Kouw, Matthijs; Schomaker, Lambertus; Mueller, Vincent C.

2013-01-01

The closed systems of contemporary Artificial Intelligence do not seem to lead to intelligent machines in the near future. What is needed are open-ended systems with non-linear properties in order to create interesting properties for the scaffolding of an artificial mind. Using post-structuralistic

A heuristic approach for the evaluation of Physical Protection System effectiveness

International Nuclear Information System (INIS)

Zou, Bowen; Yang, Ming; Guo, Jia; Benjamin, Emi-Reybold; Wu, Wenfei

2017-01-01

Highlights: • A heuristic approach is applied for the evaluation of PPS effectiveness (HAPPS). • Import 2-D engineering drawings into the analysis application, identify the information contained in the model. Use the HAPPS method as search algorithm to seek the vulnerable adversary intrusion and escape path under certain conditions. • Redesign the PPS by the evaluation results. - Abstract: Physical Protection System (PPS) is essential for each nuclear power plant to safeguard its nuclear materials and nuclear facilities from theft, robbery, illegal transport and sabotage. This paper presents a novel method (HAPPS) combined with Estimate of Adversary Sequence Interruption (EASI) method and heuristic approach (Ant Colony Optimization, ACO) for analyzing and evaluating the PPS effectiveness of NPPs. Import 2-D engineering drawings into the analysis application, identify the information contained in the model, and use the HAPPS method as search algorithm to seek the vulnerable adversary intrusion and escape path under certain conditions. The results of PPS effectiveness analysis will provide a detailed technical feedback for redesigning PPS.

Progress and Challenge of Artificial Intelligence

Institute of Scientific and Technical Information of China (English)

Zhong-Zhi Shi; Nan-Ning Zheng

2006-01-01

Artificial Intelligence (AI) is generally considered to be a subfield of computer science, that is concerned to attempt simulation, extension and expansion of human intelligence. Artificial intelligence has enjoyed tremendous success over the last fifty years. In this paper we only focus on visual perception, granular computing, agent computing, semantic grid. Human-level intelligence is the long-term goal of artificial intelligence. We should do joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. A new cross discipline intelligence science is undergoing a rapid development. Future challenges are given in final section.

Ichthyoplankton Classification Tool using Generative Adversarial Networks and Transfer Learning

KAUST Repository

Aljaafari, Nura

2018-04-15

The study and the analysis of marine ecosystems is a significant part of the marine science research. These systems are valuable resources for fisheries, improving water quality and can even be used in drugs production. The investigation of ichthyoplankton inhabiting these ecosystems is also an important research field. Ichthyoplankton are fish in their early stages of life. In this stage, the fish have relatively similar shape and are small in size. The currently used way of identifying them is not optimal. Marine scientists typically study such organisms by sending a team that collects samples from the sea which is then taken to the lab for further investigation. These samples need to be studied by an expert and usually end needing a DNA sequencing. This method is time-consuming and requires a high level of experience. The recent advances in AI have helped to solve and automate several difficult tasks which motivated us to develop a classification tool for ichthyoplankton. We show that using machine learning techniques, such as generative adversarial networks combined with transfer learning solves such a problem with high accuracy. We show that using traditional machine learning algorithms fails to solve it. We also give a general framework for creating a classification tool when the dataset used for training is a limited dataset. We aim to build a user-friendly tool that can be used by any user for the classification task and we aim to give a guide to the researchers so that they can follow in creating a classification tool.

Intelligence and treaty ratification

International Nuclear Information System (INIS)

Sojka, G.L.

1990-01-01

What did the intelligence community and the Intelligence Committee di poorly in regard to the treaty ratification process for arms control? We failed to solve the compartmentalization problem/ This is a second-order problem, and, in general, analysts try to be very open; but there are problems nevertheless. There are very few, if any, people within the intelligence community who are cleared for everything relevant to our monitoring capability emdash short of probably the Director of Central Intelligence and the president emdash and this is a major problem. The formal monitoring estimates are drawn up by individuals who do not have access to all the information to make the monitoring judgements. This paper reports that the intelligence community did not present a formal document on either Soviet incentives of disincentives to cheat or on the possibility of cheating scenarios, and that was a mistake. However, the intelligence community was very responsive in producing those types of estimates, and, ultimately, the evidence behind them in response to questions. Nevertheless, the author thinks the intelligence community would do well to address this issue up front before a treaty is submitted to the Senate for advice and consent

Rural architecture between artificial intelligence and natural intelligence

Energy Technology Data Exchange (ETDEWEB)

Cennamo, M.; Palma, P. di; Ricciardelli, A. [University of Naples Frederico II (Italy). Dept. of Configurazione e Attuazione dell Architettra

2000-02-01

Following the field of research carried out and reported in the Second International Conference for Teachers of Architecture held in Florence on October 16, 17 and 18, 1997, which stated the central position of Architectural project in relation to Human Intelligence, Natural Intelligence and Artificial Intelligence, the present paper suggests a phase of application of the theoretical assumptions to spacial models paradigmatic of the complexity of projects and building technique, as well as of the relationship between man-made environment and natural one. Among the different typologies in architecture, this research focuses on the rural buildings in Campania, mainly on the ones in the Vesuvius area, as those are the most suitable to be studied and salvaged with the help of biology, mathematics and high engineering. (author)

An Intelligent Agent-Controlled and Robot-Based Disassembly Assistant

Science.gov (United States)

Jungbluth, Jan; Gerke, Wolfgang; Plapper, Peter

2017-09-01

One key for successful and fluent human-robot-collaboration in disassembly processes is equipping the robot system with higher autonomy and intelligence. In this paper, we present an informed software agent that controls the robot behavior to form an intelligent robot assistant for disassembly purposes. While the disassembly process first depends on the product structure, we inform the agent using a generic approach through product models. The product model is then transformed to a directed graph and used to build, share and define a coarse disassembly plan. To refine the workflow, we formulate “the problem of loosening a connection and the distribution of the work” as a search problem. The created detailed plan consists of a sequence of actions that are used to call, parametrize and execute robot programs for the fulfillment of the assistance. The aim of this research is to equip robot systems with knowledge and skills to allow them to be autonomous in the performance of their assistance to finally improve the ergonomics of disassembly workstations.

Algorithms in ambient intelligence

NARCIS (Netherlands)

Aarts, E.H.L.; Korst, J.H.M.; Verhaegh, W.F.J.; Weber, W.; Rabaey, J.M.; Aarts, E.

2005-01-01

We briefly review the concept of ambient intelligence and discuss its relation with the domain of intelligent algorithms. By means of four examples of ambient intelligent systems, we argue that new computing methods and quantification measures are needed to bridge the gap between the class of

Artificial Intelligence Research at the Artificial Intelligence Laboratory, Massachusetts Institute of Technology

OpenAIRE

Winston, Patrick H.

1983-01-01

The primary goal of the Artificial Intelligence Laboratory is to understand how computers can be made to exhibit intelligence. Two corollary goals are to make computers more useful and to understand certain aspects of human intelligence. Current research includes work on computer robotics and vision, expert systems, learning and commonsense reasoning, natural language understanding, and computer architecture.

Development of a utility system for charged particle nuclear reaction data by using intelligentPad

International Nuclear Information System (INIS)

Aoyama, Shigeyoshi; Ohbayashi, Yoshihide; Masui, Hiroshi; Kato, Kiyoshi; Chiba, Masaki

2000-01-01

We have developed a utility system, WinNRDF2, for a nuclear charged particle reaction data of NRDF (Nuclear Reaction Data File) on the IntelligentPad architecture. By using the system, we can search the experimental data of a charged particle reaction of NRDF. Furthermore, we also see the experimental data by using graphic pads which was made through the CONTIP project. (author)

Moral Intelligence in the Schools

Science.gov (United States)

Clarken, Rodney H.

2009-01-01

Moral intelligence is newer and less studied than the more established cognitive, emotional and social intelligences, but has great potential to improve our understanding of learning and behavior. Moral intelligence refers to the ability to apply ethical principles to personal goals, values and actions. The construct of moral intelligence consists…

Modelling intelligent behavior

Science.gov (United States)

Green, H. S.; Triffet, T.

1993-01-01

An introductory discussion of the related concepts of intelligence and consciousness suggests criteria to be met in the modeling of intelligence and the development of intelligent materials. Methods for the modeling of actual structure and activity of the animal cortex have been found, based on present knowledge of the ionic and cellular constitution of the nervous system. These have led to the development of a realistic neural network model, which has been used to study the formation of memory and the process of learning. An account is given of experiments with simple materials which exhibit almost all properties of biological synapses and suggest the possibility of a new type of computer architecture to implement an advanced type of artificial intelligence.

Multiple intelligences: Can they be measured?

OpenAIRE

Kirsi Tirri; Petri Nokelainen; Erkki Komulainen

2013-01-01

This paper is about issues relating to the assessment of multiple intelligences. The first section introduces the authors’ work on building measures of multiple intelligences and moral sensitivities. It also provides a conceptual definition of multiple intelligences based on Multiple Intelligences theory by Howard Gardner (1983). The second section discusses the context specificity of intelligences and alternative approaches to measuring multiple intelligences. The third section analyses the ...

Reflection on robotic intelligence

NARCIS (Netherlands)

Bartneck, C.

2006-01-01

This paper reflects on the development or robots, both their physical shape as well as their intelligence. The later strongly depends on the progress made in the artificial intelligence (AI) community which does not yet provide the models and tools necessary to create intelligent robots. It is time

Intelligent manipulation technique for multi-branch robotic systems

Science.gov (United States)

Chen, Alexander Y. K.; Chen, Eugene Y. S.

1990-01-01

New analytical development in kinematics planning is reported. The INtelligent KInematics Planner (INKIP) consists of the kinematics spline theory and the adaptive logic annealing process. Also, a novel framework of robot learning mechanism is introduced. The FUzzy LOgic Self Organized Neural Networks (FULOSONN) integrates fuzzy logic in commands, control, searching, and reasoning, the embedded expert system for nominal robotics knowledge implementation, and the self organized neural networks for the dynamic knowledge evolutionary process. Progress on the mechanical construction of SRA Advanced Robotic System (SRAARS) and the real time robot vision system is also reported. A decision was made to incorporate the Local Area Network (LAN) technology in the overall communication system.

Multiple Intelligences and quotient spaces

OpenAIRE

Malatesta, Mike; Quintana, Yamilet

2006-01-01

The Multiple Intelligence Theory (MI) is one of the models that study and describe the cognitive abilities of an individual. In [7] is presented a referential system which allows to identify the Multiple Intelligences of the students of a course and to classify the level of development of such Intelligences. Following this tendency, the purpose of this paper is to describe the model of Multiple Intelligences as a quotient space, and also to study the Multiple Intelligences of an individual in...

Deploying swarm intelligence in medical imaging identifying metastasis, micro-calcifications and brain image segmentation.

Science.gov (United States)

al-Rifaie, Mohammad Majid; Aber, Ahmed; Hemanth, Duraiswamy Jude