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This paper is focused on comparing corpus-based methods for estimating word sentiment. Evaluated algorithms represent varying degrees of supervision and range from regression alike approaches to more heavily supervised classifications. The main idea is to explore the opportunities arising from mining medium sized, balanced corpora -- as opposed to web as a corpus paradigm. The comparisons have been...
OCCAMS is a new algorithm for the Multi-Document Summarization (MDS) problem. We use Latent Semantic Analysis (LSA) to produce term weights which identify the main theme(s) of a set of documents. These are used by our heuristic for extractive sentence selection which borrows techniques from combinatorial optimization to select a set of sentences such that the combined weight of the terms covered is...
Whenever a research scholar starts working on some innovative ideas he/she searches for the domain specific technical research articles published as research papers in most of the international journals, conferences or workshops. The problems associated with these papers are similarity in contents and repeated relevant information. Reading these all relatedpapers completely one by one to get the latest...
When human exercises multi-degrees of freedom (DOF) motion, they just pay attention to only part of the body motion and can control the whole body motion. By consciously adjusting low-DOF movements, it is possible to induce multi-DOF motion, which is referred as a “knack” in the sport. Acquiring knacks can drastically improve multi-DOF motor skills by low-DOF information presentation, and it is also...
Motivated by models of human decision making, we consider a heuristic solution for explore-exploit problems. In a numerical example we show that, with appropriate parameter values, the algorithm performs well. However, the parameters of the algorithm trade off exploration against exploitation in a complicated way so that finding the optimal parameter values is not obvious. We show that the optimal...
This paper proposes the analysis of two strategies for motion imitation of articulated systems with balance constraint. The two systems have different dynamic characteristics and their respective motions are restricted to the sagittal plane. The first strategy is based on nonlinear time scaling of joint trajectories ensuring that the balance of the imitating system is maintained through the motion...
This paper describes the optimization of a planar wearable active orthosis for hip and knee assistance during overground walking. A non-anthropomorphic design is pursued in order to improve ergonomics and to reduce torque requirements. Based on a previously-developed systematic search algorithm of the admissible generalized solutions for the selected problem, a solution is selected and optimized by...
Despite evidence that human wayfinders consider directions involving landmarks or topological descriptions easier to follow, the majority of commerical direction-planning services and GPS navigation units plan routes based on metrically or temporally shortest paths, ignoring this potentially valuable information. We propose a method for generating directions that maximizes the probability of a human...
Throwing is a complex and highly dynamic task. Humans usually exploit passive dynamics of their limbs to optimize their movement and muscle activation. In order to approach human throwing, we developed a double pendulum robotic platform. To introduce passivity into the actuated joints, clutches were included in the drive train. In this paper, we demonstrate the advantage of exploiting passive dynamics...
Flexible needle with bevel tip offers greater mobility for puncture surgery. This would expand the scope of the puncture surgery. However, motion planning for flexible needle is still a challenge due to its non-holonomic property and the complicated interactions with soft tissues. In this paper, a multilayer tissue model is constructed to simulate human tissue, and a dynamic programming is employed...
This paper proposes a method for optimizing a control system that includes a human in the loop. The method uses human-operator testing to measure the system's performance for a given value of a control parameter. Root-mean-squared (RMS) tracking error is used to quantify performance. The optimum control parameter value is found using a one-dimensional search algorithm. As an example application, the...
This paper presents a method for achieving stable “human-like” running in simulation by using human-inspired control. Data from human running experiments are processed, analyzed and split into the two domains: stance phase and flight phase. By examining this data, we present a set of outputs, i.e., functions of the kinematics, which appear to represent human running; moreover, we show that this output...
Collective problem solving can lead to the development of new methods and algorithms that can potentially contribute to novel Artificial Intelligence applications and tools. Socially-inspired optimization algorithms are a class of algorithms that aim at conducting a search over a large solution space using mechanisms similar to how humans solve problems in a social context. Several such algorithms...
Recently, attributes have been introduced to help object classification. Multi-task learning is an effective methodology to achieve this goal, which shares low-level features between attribute and object classifiers. Yet such a method neglects the constraints that attributes impose on classes which may fail to constrain the semantic relationship between the attribute and object classifiers. In this...
The difference between interactive evolution-ary computation (IEC) and traditional evolutionary computation (TEC) is that in IEC individuals' fitness is subjectively assigned by the user, while in TEC the fitness is objectively given by function or others. The user in IEC assigns fitness according to his/her preference. Therefore, if his/her preference drifts, the implicit fitness function for preference...
This paper is concerned with parameter identification for the double Debye model of the Terahertz wave's propagation and reflection in human skin. The existing methods could provide estimators, which are accurate at the frequencies higher than one THz but rather row at the lower frequencies, where the majority of contrast for differentiating the changes of skin content is present. We propose another...
In this paper, we present a novel generative method for human motion tracking. The principle contribution is the development of clonal selection algorithm for pose analysis in latent space of human motion. Firstly, we use ISOMAP to learn the low-dimensional latent space of pose state and a manifold reconstruction method is proposed to establish the smooth mappings between the latent and original space...
Fast alignment of small sequences to a very large sequence has recently been under attention of many researchers, due to the applications in processing the biological sequences and specially mapping the short reads of Next Generation Sequencing to an already assembled reference genome. The MEMOCODE 2012 contest was aimed to design a very efficient exact DNA sequence matching method to map a huge number...
The algorithmic generation of detailed manufacturing plans close to an optimal solution is computationally unfeasible due to the enormous size of the space of potential solutions which makes searching a process of exponential time complexity. Human-computer interaction may lead to practical solutions. Conventional approaches rely on appealing visualizations. Modern media technologies allow for directly...
Control of finite-valued networks, including Boolean networks, is currently a hot topic. In this paper the optimization control of the networks with present value performance criterion is discussed. The problem is formulated as a finite strategy game between human and machine. It is firstly proved that the optimal strategy can be found in the set of periodic strategies, which makes the problem finitely...
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