A novel human-machine interface using subdermal magnetic implants

This paper explores a novel tactile human-machine interface based on the controlled stimulation of mechanoreceptors by a subdermal magnetic implant manipulated through an external electromagnet. The selection of a suitable implant magnet and implant site is discussed and an external interface for manipulating the implant is described. The paper also reports on the basic properties of such an interface, including magnetic field strength sensitivity and frequency sensitivity obtained through experimentation on two participants. Finally, the paper presents two practical application scenarios for the interface.

Good machine performance in Turing’s imitation game

In this paper we consider transcripts which originated from a practical series of Turing’s Imitation Game which was held on 23rd June 2012 at Bletchley Park, England. In some cases the tests involved a 3-participant simultaneous comparison of two hidden entities whereas others were the result of a direct 2-participant interaction. Each of the transcripts considered here resulted in a human interrogator being fooled, by a machine, into concluding that they had been conversing with a human. Particular features of the conversation are highlighted, successful ploys on the part of each machine discussed and likely reasons for the interrogator being fooled are considered. Subsequent feedback from the interrogators involved is also included

The development of a data-driven application benchmarking approach to performance modelling

Performance modelling is a useful tool in the lifeycle of high performance scientific software, such as weather and climate models, especially as a means of ensuring efficient use of available computing resources. In particular, sufficiently accurate performance prediction could reduce the effort and experimental computer time required when porting and optimising a climate model to a new machine. In this paper, traditional techniques are used to predict the computation time of a simple shallow water model which is illustrative of the computation (and communication) involved in climate models. These models are compared with real execution data gathered on AMD Opteron-based systems, including several phases of the U.K. academic community HPC resource, HECToR. Some success is had in relating source code to achieved performance for the K10 series of Opterons, but the method is found to be inadequate for the next-generation Interlagos processor. The experience leads to the investigation of a data-driven application benchmarking approach to performance modelling. Results for an early version of the approach are presented using the shallow model as an example.

Extraction of unexpected rules from Twitter hashtags and its application to sport events

Twitter has become a dependable microblogging tool for real time information dissemination and newsworthy events broadcast. Its users sometimes break news on the network faster than traditional newsagents due to their presence at ongoing real life events at most times. Different topic detection methods are currently used to match Twitter posts to real life news of mainstream media. In this paper, we analyse tweets relating to the English FA Cup finals 2012 by applying our novel method named TRCM to extract association rules present in hash tag keywords of tweets in different time-slots. Our system identify evolving hash tag keywords with strong association rules in each time-slot. We then map the identified hash tag keywords to event highlights of the game as reported in the ground truth of the main stream media. The performance effectiveness measure of our experiments show that our method perform well as a Topic Detection and Tracking approach.

Shear strength of the bond to primary dentin: influence of Er:YAG laser irradiation distance

The aim of this study was to assess in vitro the influence of Er:YAG laser irradiation distance on the shear strength of the bond between an adhesive restorative system and primary dentin. A total of 60 crowns of primary molars were embedded in acrylic resin and mechanically ground to expose a flat dentin surface and were randomly assigned to six groups (n = 10). The control group was etched with 37% phosphoric acid. The remaining five groups were irradiated (80 mJ, 2 Hz) at different irradiation distances (11, 12, 16, 17 and 20 mm), followed by acid etching. An adhesive agent (Single Bond) was applied to the bonding sites, and resin cylinders (Filtek Z250) were prepared. The shear bond strength tests were performed in a universal testing machine (0.5 mm/min). Data were submitted to statistical analysis using one-way ANOVA and the Kruskal-Wallis test (p < 0.05). The mean shear bond strengths were: 7.32 +/- 3.83, 5.07 +/- 2.62, 6.49 +/- 1.64, 7.71 +/- 0.66, 7.33 +/- 0.02, and 9.65 +/- 2.41 MPa in the control group and the groups irradiated at 11, 12, 16, 17, and 20 mm, respectively. The differences between the bond strengths in groups II and IV and between the bond strengths in groups II and VI were statistically significant (p < 0.05). Increasing the laser irradiation distance resulted in increasing shear strength of the bond to primary dentin.

Adhesion to Er : YAG laser-prepared dentin after long-term water storage and thermocycling

This in vitro study evaluated the microtensile bond strength of a resin composite to Er:YAG-prepared dentin after long-term storage and thermocycling. Eighty bovine incisors were selected and their roots removed. The crowns were ground to expose superficial dentin. The samples were randomly divided according to cavity preparation method (I-Er:YAG laser and II-carbide bur). Subsequently, an etch & rinse adhesive system was applied and the samples were restored with a resin composite. The samples were subdivided according to time of water storage (WS)/number of thermocycles (TC) performed: A) 24 hours WS/no TC; B) 7 days WS/500 TC; C) 1 month WS/2,000 TC; D) 6 months WS/12,000 TC. The teeth were sectioned in sticks with a cross-sectional area of 1.0-mm(2), which were loaded in tension in a universal testing machine. The data were subjected to two-way ANOVA, Scheffe and Fisher`s tests at a 5% level. In general, the bur-prepared group displayed higher microtensile bond strength values than the laser-treated group. Based on one-month water storage and 2,000 thermocycles, the performance of the tested adhesive system to Er:YAG-laser irradiated dentin was negatively affected (Group IC), while adhesion of the bur-prepared group decreased only within six months of water storage combined with 12,000 thermocycles (Group IID). It may be concluded that adhesion to the Er:YAG laser cavity preparation was more affected by the methods used for simulating degradation of the adhesive interface.

An investigation into feature construction to assist word sense disambiguation

Identifying the correct sense of a word in context is crucial for many tasks in natural language processing (machine translation is an example). State-of-the art methods for Word Sense Disambiguation (WSD) build models using hand-crafted features that usually capturing shallow linguistic information. Complex background knowledge, such as semantic relationships, are typically either not used, or used in specialised manner, due to the limitations of the feature-based modelling techniques used. On the other hand, empirical results from the use of Inductive Logic Programming (ILP) systems have repeatedly shown that they can use diverse sources of background knowledge when constructing models. In this paper, we investigate whether this ability of ILP systems could be used to improve the predictive accuracy of models for WSD. Specifically, we examine the use of a general-purpose ILP system as a method to construct a set of features using semantic, syntactic and lexical information. This feature-set is then used by a common modelling technique in the field (a support vector machine) to construct a classifier for predicting the sense of a word. In our investigation we examine one-shot and incremental approaches to feature-set construction applied to monolingual and bilingual WSD tasks. The monolingual tasks use 32 verbs and 85 verbs and nouns (in English) from the SENSEVAL-3 and SemEval-2007 benchmarks; while the bilingual WSD task consists of 7 highly ambiguous verbs in translating from English to Portuguese. The results are encouraging: the ILP-assisted models show substantial improvements over those that simply use shallow features. In addition, incremental feature-set construction appears to identify smaller and better sets of features. Taken together, the results suggest that the use of ILP with diverse sources of background knowledge provide a way for making substantial progress in the field of WSD.

A hybrid approach to learn with imbalanced classes using evolutionary algorithms

There is an increasing interest in the application of Evolutionary Algorithms (EAs) to induce classification rules. This hybrid approach can benefit areas where classical methods for rule induction have not been very successful. One example is the induction of classification rules in imbalanced domains. Imbalanced data occur when one or more classes heavily outnumber other classes. Frequently, classical machine learning (ML) classifiers are not able to learn in the presence of imbalanced data sets, inducing classification models that always predict the most numerous classes. In this work, we propose a novel hybrid approach to deal with this problem. We create several balanced data sets with all minority class cases and a random sample of majority class cases. These balanced data sets are fed to classical ML systems that produce rule sets. The rule sets are combined creating a pool of rules and an EA is used to build a classifier from this pool of rules. This hybrid approach has some advantages over undersampling, since it reduces the amount of discarded information, and some advantages over oversampling, since it avoids overfitting. The proposed approach was experimentally analysed and the experimental results show an improvement in the classification performance measured as the area under the receiver operating characteristics (ROC) curve.

Entropy-Based Approach to Analyze and Classify Mineral Aggregates

This paper presents an automatic method to detect and classify weathered aggregates by assessing changes of colors and textures. The method allows the extraction of aggregate features from images and the automatic classification of them based on surface characteristics. The concept of entropy is used to extract features from digital images. An analysis of the use of this concept is presented and two classification approaches, based on neural networks architectures, are proposed. The classification performance of the proposed approaches is compared to the results obtained by other algorithms (commonly considered for classification purposes). The obtained results confirm that the presented method strongly supports the detection of weathered aggregates.

Influence of Er:YAG laser on surface treatment of aged composite resin to repair restoration

The purpose of this study was to investigate the effect of Er:YAG laser on surface treatment to the bond strength of repaired composite resin after aged. Sixty specimens (n = 10) were made with composite resin (Z250, 3M) and thermocycled with 500 cycles, oscillating between 5 to 55A degrees C. The specimens were randomly separated in six groups which suffered the following superficial treatments: no treatment (GI, control), wearing with diamond bur (GII), sandblasted with aluminum oxide with 27.5 A mu m particles (GIII) for 10 s, 200 mJ Er:YAG laser (GIV), 300 mJ Er:YAG laser (GV), and 400 mJ Er:YAG laser (GVI), with the last 3 groups under a 10 Hz frequency for 10 s. Restoration repair was done using the same composite. The shear test was done into the Universal testing machine MTS-810. Analyzing the results through ANOVA and Tukey test, no significant differences were found (p-value is 0.5120). Average values analysis showed that superficial treatment with aluminum oxide presented the highest resistance to shear repair interface (8.91MPa) while 400 mJ Er:YAG laser presented the lowest (6.76 MPa). Fracture types analysis revealed that 90% suffered cohesive fractures to GIII. The Er:YAG laser used as superficial treatment of the aged composite resin before the repair showed similar results when used diamond bur and sandblasting with aluminum oxide particles.