Query: 2011 Senior Thesis Project Reports Place Recognition for Indoor Blind Navigation Contents

Relevant passages:
A Passive RFID Information Grid for Location and Proximity Sensing for the Blind User <=SEP=> We describe a navigation and location determination system for the blind using an RFID tag grid. Each RFID tag is programmed upon installation with spatial coordinates and information describing the surroundings. This allows for a self-describing, localized information system with no dependency on a centralized database or wireless infrastructure for communications. The system could be integrated into building code requirements as part of ADA (Americans with Disabilities Act) at a cost of less than $1 per square foot. With an established RFID grid infrastructure blind children and adults will gain the independence and freedom to explore and participate in activities without external assistance. An established RFID grid infrastructure will also enable advances in robotics which will benefit from knowing precise location. In this paper, we present an RFID based information grid system with a reader integrated into the user’s shoe, which is connected to the user PDA or cell phone via a Bluetooth. An emphasis is placed on the architecture and design to allow for a truly integrated pervasive environment.

FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance <=SEP=> This paper describes a probabilistic approach to the problem of recognizing places based on their appearance. The system we present is not limited to localization, but can determine that a new observation comes from a previously unseen place, and so augment its map. Effectively this is a SLAM system in the space of appearance. Our probabilistic approach allows us to explicitly account for perceptual aliasing in the environment—identical but indistinctive observations receive a low probability of having come from the same place. We achieve this by learning a generative model of place appearance. By partitioning the learning problem into two parts, new place models can be learned online from only a single observation of a place. The algorithm complexity is linear in the number of places in the map, and is particularly suitable for online loop closure detection in mo-

Multi-modal Semantic Place Classification <=SEP=> The ability to represent knowledge about space and its position therein is crucial for a mobile robot. To this end, topological and semantic descriptions are gaining popularity for augmenting purely metric space representations. In this paper we present a multi-modal place classification system that allows a mobile robot to identify places and recognize semantic categories in an indoor environment. The system effectively utilizes information from different robotic sensors by fusing multiple visual cues and laser range data. This is achieved using a high-level cue integration scheme based on a Support Vector Machine (SVM) that learns how to optimally combine and weight each cue. Our multi-modal place classification approach can be used to obtain a real-time semantic space labeling system which integrates information over time and space. We perform an extensive experimental evaluation of the method for two different platforms and environments, on a realistic off-line database and in a live experiment on an autonomous robot. The results clearly demonstrate the effecThe International Journal of Robotics Research Vol. 00, No. 00, Xxxxxxxx 2009, pp. 000–000 DOI: 10.1177/0278364909356483 c The Author(s), 2009. Reprints and permissions: http://www.sagepub.co.uk/journalsPermissions.nav Figures 1–15, 17, 18 appear in color online: http://ijr.sagepub.com tiveness of our cue integration scheme and its value for robust place classification under varying conditions. KEY WORDS—recognition, sensor fusion, localization, multi-modal place classification, sensor and cue integration, semantic annotation of space

Object Recognition from Local Scale-Invariant Features <=SEP=> Proc. of the International Conference on Computer Vision, Corfu (Sept. 1999) An object recognition system has been developed that uses a new class of local image features. The features are invariant to image scaling, translation, and rotation, and partially invariant to illumination changes and affine or 3D projection. These features share similar properties with neurons in inferior temporal cortex that are used for object recognition in primate vision. Features are efficiently detected through a staged filtering approach that identifies stable points in scale space. Image keys are created that allow for local geometric deformations by representing blurred image gradients in multiple orientation planes and at multiple scales. The keys are used as input to a nearest-neighbor indexing method that identifies candidate object matches. Final verification of each match is achieved by finding a low-residual least-squares solution for the unknown model parameters. Experimental results show that robust object recognition can be achieved in cluttered partially-occluded images with a computation time of under 2 seconds.

RADAR: An In-Building RF-Based User Location and Tracking System <=SEP=> The proliferation of mobile computing devices and local-area wireless networks has fostered a growing interest in location-aware systems and services. In this paper we present RADAR, a radio-frequency (RF) based system for locating and tracking users inside buildings. RADAR operates by recording and processing signal strength information at multiple base stations positioned to provide overlapping coverage in the area of interest. It combines empirical measurements with signal propagation modeling to determine user location and thereby enable locationaware services and applications. We present experimental results that demonstrate the ability of RADAR to estimate user location with a high degree of accuracy.

Indian Sign Language gesture classification as single or double handed gestures <=SEP=> The development of a sign language recognition system can have a great impact on the daily lives of humans with hearing disabilities. Recognizing gestures from the Indian Sign Language (ISL) with a camera can be difficult due to complexity of various gestures. The motivation behind the paper is to develop an approach to successfully classify gestures in the ISL under ambiguous conditions from static images. A novel approach involving the decomposition of gestures into single handed or double handed gesture has been presented in this paper. Classifying gesture into these subcategories simplifies the process of gesture recognition in the ISL due to presence of lesser number of gestures in each subcategory. Various approaches making use of Histogram of Gradients (HOG) features and geometric descriptors using KNN and SVM classifiers were tried on a dataset consisting of images of all 26 English alphabets present in the ISL under variable background. HOG features when classified with Support Vector Machine were found to be the most efficient approach resulting in an accuracy of 94.23%.

A Survey on Automatically Mining Facets for Web Queries <=SEP=> Received Jan 4, 2017 Revised Jun 2, 2017 Accepted Jun 26, 2017 In this paper, a detailed survey on different facet mining techniques, their advantages and disadvantages is carried out. Facets are any word or phrase which summarize an important aspect about the web query. Researchers proposed different efficient techniques which improves the user’s web query search experiences magnificently. Users are happy when they find the relevant information to their query in the top results. The objectives of their research are: (1) To present automated solution to derive the query facets by analyzing the text query; (2) To create taxonomy of query refinement strategies for efficient results; and (3) To personalize search according to user interest. Keyword:

Visualizing Topic Models <=SEP=> Managing large collections of documents is an important problem for many areas of science, industry, and culture. Probabilistic topic modeling offers a promising solution. Topic modeling is an unsupervised machine learning method that learns the underlying themes in a large collection of otherwise unorganized documents. This discovered structure summarizes and organizes the documents. However, topic models are high-level statistical tools—a user must scrutinize numerical distributions to understand and explore their results. In this paper, we present a method for visualizing topic models. Our method creates a navigator of the documents, allowing users to explore the hidden structure that a topic model discovers. These browsing interfaces reveal meaningful patterns in a collection, helping end-users explore and understand its contents in new ways. We provide open source software of our method. Understanding and navigating large collections of documents has become an important activity in many spheres. However, many document collections are not coherently organized and organizing them by hand is impractical. We need automated ways to discover and visualize the structure of a collection in order to more easily explore its contents. Probabilistic topic modeling is a set of machine learning tools that may provide a solution (Blei and Lafferty 2009). Topic modeling algorithms discover a hidden thematic structure in a collection of documents; they find salient themes and represent each document as a combination of themes. However, topic models are high-level statistical tools. A user must scrutinize numerical distributions to understand and explore their results; the raw output of the model is not enough to create an easily explored corpus. We propose a method for using a fitted topic model to organize, summarize, visualize, and interact with a corpus. With our method, users can explore the corpus, moving between high level discovered summaries (the “topics”) and the documents themselves, as Figure 1 illustrates. Our design is centered around the idea that the model both summarizes and organizes the collection. Our method translates these representations into a visual system for exploring a collection, but visualizing this structure is not enough. The discovered structure induces relationships—between topics and articles, and between articles and articles—which lead to interactions in the visualization. Copyright c © 2012, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. Thus, we have three main goals in designing the visualization: summarize the corpus for the user; reveal the relationships between the content and summaries; and, reveal the relationships across content. We aim to present these in a ways that are accessible and useful to a spectrum of users, not just machine learning experts.

Qualitative Research & Evaluation Methods: Integrating Theory and Practice <=SEP=> In what case do you like reading so much? What about the type of the qualitative research evaluation methods integrating theory and practice book? The needs to read? Well, everybody has their own reason why should read some books. Mostly, it will relate to their necessity to get knowledge from the book and want to read just to get entertainment. Novels, story book, and other entertaining books become so popular this day. Besides, the scientific books will also be the best reason to choose, especially for the students, teachers, doctors, businessman, and other professions who are fond of reading.

Capturing the Temporal Domain in Echonest Features for Improved Classification Effectiveness <=SEP=> This paper proposes Temporal Echonest Features to harness the information available from the beat-aligned vector sequences of the features provided by The Echo Nest. Rather than aggregating them via simple averaging approaches, the statistics of temporal variations are analyzed and used to represent the audio content. We evaluate the performance on four traditional music genre classification test collections and compare them to state of the art audio descriptors. Experiments reveal, that the exploitation of temporal variability from beat-aligned vector sequences and combinations of different descriptors leads to an improvement of classification accuracy. Comparing the results of Temporal Echonest Features to those of approved conventional audio descriptors used as benchmarks, these approaches perform well, often significantly outperforming their predecessors, and can be effectively used for large scale music genre classification.

Learning Algorithms from Data <=SEP=> Statistical machine learning is concerned with learning models that describe observations. We train our models from data on tasks like machine translation or object recognition because we cannot explicitly write down programs to solve such problems. A statistical model is only useful when it generalizes to unseen data. Solomonoff114 has proved that one should choose the model that agrees with the observed data, while preferring the model that can be compressed the most, because such a choice guarantees the best possible generalization. The size of the best possible compression of the model is called the Kolmogorov complexity of the model. We define an algorithm as a function with small Kolmogorov complexity. This Ph.D. thesis outlines the problem of learning algorithms from data and shows several partial solutions to it. Our data model is mainly neural networks as they have proven to be successful in various domains like object recognition67,109,122, language modelling90, speech recognition48,39 and others. First, we examine empirical trainability limits for classical neural networks. Then, we extend them by providing interfaces, which provide a way to read memory, access the input, and postpone predictions. The model learns how to use them with reinforcement learning techniques like REINFORCE and Q-learning. Next, we ex-

Generative Topic Embedding: a Continuous Representation of Documents <=SEP=> Word embedding maps words into a lowdimensional continuous embedding space by exploiting the local word collocation patterns in a small context window. On the other hand, topic modeling maps documents onto a low-dimensional topic space, by utilizing the global word collocation patterns in the same document. These two types of patterns are complementary. In this paper, we propose a generative topic embedding model to combine the two types of patterns. In our model, topics are represented by embedding vectors, and are shared across documents. The probability of each word is influenced by both its local context and its topic. A variational inference method yields the topic embeddings as well as the topic mixing proportions for each document. Jointly they represent the document in a low-dimensional continuous space. In two document classification tasks, our method performs better than eight existing methods, with fewer features. In addition, we illustrate with an example that our method can generate coherent topics even based on only one document.

A study of array antenna with phase compensated technique for 60 GHz communication <=SEP=> This paper presents phase compensated techniques for 60 GHz communication. A phase compensation method for antenna embedded in a mobile device and a planar lens for base station antenna are introduced. For the Line-of Sight (LoS) scenario, end-fire antenna arrays are adapted for mobile device. 8×1 end-fire patch antenna arrays are designed in Low temperature co-fired ceramic (LTCC) substrate. Simulated max gain of the antenna arrays is 13.03 dBi. When the antenna module is mounted, scattering problem is occurred and its max gain is severely degraded to 6.4 dBi. By using phase compensated technique, max gain of the antenna arrays are enhanced to 12.5 dBi. The beam steered gain of the arrays is also simulated and good coverage can be achieved. A planar lens antenna is also studied for high gain of the base station antenna.

Comparison and Analysis of Single-Phase Transformerless Grid-Connected PV Inverters <=SEP=> Leakage current minimization is one of the most important considerations in transformerless photovoltaic (PV) inverters. In the past, various transformerless PV inverter topologies have been introduced, with leakage current minimized by the means of galvanic isolation and common-mode voltage (CMV) clamping. The galvanic isolation can be achieved via dc-decoupling or ac-decoupling, for isolation on the dc- or ac-side of the inverter, respectively. It has been shown that the latter provides lower losses due to the reduced switch count in conduction path. Nevertheless, leakage current cannot be simply eliminated by galvanic isolation and modulation techniques, due to the presence of switches' junction capacitances and resonant circuit effects. Hence, CMV clamping is used in some topologies to completely eliminate the leakage current. In this paper, several recently proposed transformerless PV inverters with different galvanic isolation methods and CMV clamping technique are analyzed and compared. A simple modified H-bridge zero-voltage state rectifier is also proposed, to combine the benefits of the low-loss ac-decoupling method and the complete leakage current elimination of the CMV clamping method. The performances of different topologies, in terms of CMV, leakage current, total harmonic distortion, losses and efficiencies are compared. The analyses are done theoretically and via simulation studies, and further validated with experimental results. This paper is helpful for the researchers to choose the appropriate topology for transformerless PV applications and to provide the design principles in terms of common-mode behavior and efficiency.

A Comparative Look into Public IXP Datasets <=SEP=> Internet eXchange Points (IXPs) are core components of the Internet infrastructure where Internet Service Providers (ISPs) meet and exchange traffic. During the last few years, the number and size of IXPs have increased rapidly, driving the flattening and shortening of Internet paths. However, understanding the present status of the IXP ecosystem and its potential role in shaping the future Internet requires rigorous data about IXPs, their presence, status, participants, etc. In this work, we do the first cross-comparison of three well-known publicly available IXP databases, namely of PeeringDB, Euro-IX, and PCH. A key challenge we address is linking IXP identifiers across databases maintained by different organizations. We find different AS-centric versus IXP-centric views provided by the databases as a result of their data collection approaches. In addition, we highlight differences and similarities w.r.t. IXP participants, geographical coverage, and co-location facilities. As a side-product of our linkage heuristics, we make publicly available the union of the three databases, which includes 40.2% more IXPs and 66.3% more IXP participants than the commonly-used PeeringDB. We also publish our analysis code to foster reproducibility of our experiments and shed preliminary insights into the accuracy of the union dataset.

OWLIM: A family of scalable semantic repositories <=SEP=> An explosion in the use of RDF for representing information about resources has driven the requirements for Webscale server systems that can store and process huge quantities of data, and furthermore provide powerful data access and mining functionalities. This paper describes OWLIM, a family of semantic repositories that provide storage, inference and novel data-access features delivered in a scalable, resilient, industrial-strength platform. Ontotext AD, 135 Tsarigradsko Chaussee, Sofia 1784, Bulgaria

Has the athlete trained enough to return to play safely? The acute:chronic workload ratio permits clinicians to quantify a player's risk of subsequent injury. <=SEP=> The return to sport from injury is a difficult multifactorial decision, and risk of reinjury is an important component. Most protocols for ascertaining the return to play status involve assessment of the healing status of the original injury and functional tests which have little proven predictive ability. Little attention has been paid to ascertaining whether an athlete has completed sufficient training to be prepared for competition. Recently, we have completed a series of studies in cricket, rugby league and Australian rules football that have shown that when an athlete's training and playing load for a given week (acute load) spikes above what they have been doing on average over the past 4 weeks (chronic load), they are more likely to be injured. This spike in the acute:chronic workload ratio may be from an unusual week or an ebbing of the athlete's training load over a period of time as in recuperation from injury. Our findings demonstrate a strong predictive (R(2)=0.53) polynomial relationship between acute:chronic workload ratio and injury likelihood. In the elite team setting, it is possible to quantify the loads we are expecting athletes to endure when returning to sport, so assessment of the acute:chronic workload ratio should be included in the return to play decision-making process.

Automatic Evaluation of Text Coherence: Models and Representations <=SEP=> This paper investigates the automatic evaluation of text coherence for machine-generated texts. We introduce a fully-automatic, linguistically rich model of local coherence that correlates with human judgments. Our modeling approach relies on shallow text properties and is relatively inexpensive. We present experimental results that assess the predictive power of various discourse representations proposed in the linguistic literature. Our results demonstrate that certain models capture complementary aspects of coherence and thus can be combined to improve performance.

Support vector machine approach for protein subcellular localization prediction <=SEP=> MOTIVATION
Subcellular localization is a key functional characteristic of proteins. A fully automatic and reliable prediction system for protein subcellular localization is needed, especially for the analysis of large-scale genome sequences.


RESULTS
In this paper, Support Vector Machine has been introduced to predict the subcellular localization of proteins from their amino acid compositions. The total prediction accuracies reach 91.4% for three subcellular locations in prokaryotic organisms and 79.4% for four locations in eukaryotic organisms. Predictions by our approach are robust to errors in the protein N-terminal sequences. This new approach provides superior prediction performance compared with existing algorithms based on amino acid composition and can be a complementary method to other existing methods based on sorting signals.


AVAILABILITY
A web server implementing the prediction method is available at http://www.bioinfo.tsinghua.edu.cn/SubLoc/.


SUPPLEMENTARY INFORMATION
Supplementary material is available at http://www.bioinfo.tsinghua.edu.cn/SubLoc/.

Enabling network programmability in LTE/EPC architecture using OpenFlow <=SEP=> Nowadays, mobile operators face the challenge to sustain the future data tsunami. In fact, today's increasing data and control traffic generated by new kinds of network usage puts strain on mobile operators', without creating any corresponding equivalent revenue. In our previous work, we analyzed the 3GPP LTE/EPC architecture and showed that a redesign of this architecture is needed to suit future network usages and to provide new revenue generating services. Moreover, we proposed a new control plane based on the OpenFlow (OF) protocol for the LTE/EPC architecture that enables flexibility and programmability aspects. In this paper, we are interested in the programmability aspect. We show how the data plane can be easily configured thanks to OF. In addition, we evaluate the signaling load of our proposed architecture and compare it to that of 3GPP LTE/EPC architecture. The preliminary findings suggest that managing the data plane with OF has little impact on the signaling load while the network programmability is improved.

Toward open manufacturing: A cross-enterprises knowledge and services exchange framework based on blockchain and edge computing <=SEP=> 

Android malware detection method based on naive Bayes and permission correlation algorithm <=SEP=> In order to detect Android malware more effectively, an Android malware detection model was proposed based on improved naive Bayes classification. Firstly, considering the unknown permission that may be malicious in detection samples, and in order to improve the Android detection rate, the algorithm of malware detection is proposed based on improved naive Bayes. Considering the limited training samples, limited permissions, and the new malicious permissions in the test samples, we used the impact of the new malware permissions and training permissions as the weight. The weighted naive Bayesian algorithm improves the Android malware detection efficiency. Secondly, taking into account the detection model, we proposed a detection model of permissions and information theory based on the improved naive Bayes algorithm. We analyzed the correlation of the permission. By calculating the Pearson correlation coefficient, we determined the value of Pearson correlation coefficient r, and delete the permissions whose value r is less than the threshold $$\rho $$ ρ and get the new permission set. So, we got the improved detection model by clustering based on information theory. Finally, we detected the 1725 Android malware and 945 non malicious application of multiple data sets in the same simulation environment. The detection rate of the improved the naive Bayes algorithm is 86.54%, and the detection rate of the non-malicious application is increased to 97.59%. Based on the improved naive Bayes algorithm, the false detection rate of the improved detection model is reduced by 8.25%.

Heroin epidemics, treatment and ODE modelling. <=SEP=> The UN [United Nations Office on Drugs and Crime (UNODC): World Drug Report, 2005, vol. 1: Analysis. UNODC, 2005.], EU [European Monitoring Centre for Drugs and Drug Addiction (EMCDDA): Annual Report, 2005.http://annualreport.emcdda.eu.int/en/home-en.html.] and WHO [World Health Organisation (WHO): Biregional Strategy for Harm Reduction, 2005-2009. HIV and Injecting Drug Use. WHO, 2005.] have consistently highlighted in recent years the ongoing and persistent nature of opiate and particularly heroin use on a global scale. While this is a global phenomenon, authors have emphasised the significant impact such an epidemic has on individual lives and on society. National prevalence studies have indicated the scale of the problem, but the drug-using career, typically consisting of initiation, habitual use, a treatment-relapse cycle and eventual recovery, is not well understood. This paper presents one of the first ODE models of opiate addiction, based on the principles of mathematical epidemiology. The aim of this model is to identify parameters of interest for further study, with a view to informing and assisting policy-makers in targeting prevention and treatment resources for maximum effectiveness. An epidemic threshold value, R(0), is proposed for the drug-using career. Sensitivity analysis is performed on R(0) and it is then used to examine the stability of the system. A condition under which a backward bifurcation may exist is found, as are conditions that permit the existence of one or more endemic equilibria. A key result arising from this model is that prevention is indeed better than cure.

Multivalued logics: a uniform approach to reasoning in artificial intelligence <=SEP=> This paper describes a uniform formalization of much of the current work in artificial intelligence on inference systems. We show that many of these systems, including first-order theorem provers, assumption-based truth maintenance systems (ATMSS), and unimplemented formal systems such as default logic or circumscription, can be subsumed under a single general framework. We begin by defining this framework, which is based on a mathematical structure known as a bilattice. We present a formal definition of inference using this structure and show that this definition generalizes work involving ATMSS and some simple nonmonotonic logics. Following the theoretical description, we describe a constructive approach to inference in this setting; the resulting generalization of both conventional inference and ATMSS is achieved without incurring any substantial computational overhead. We show that our approach can also be used to implement a default reasoner, and discuss a combination of default and ATMS methods that enables us to formally describe an “incremental” default reasoning system. This incremental system does not need to perform consistency checks before drawing tentative conclusions, but can instead adjust its beliefs when a default premise or conclusion is overturned in the face of convincing contradictory evidence. The system is therefore much more computationally viable than earlier approaches. Finally, we discuss the implementation of our ideas. We begin by considering general issues that need to be addressed when implementing a multivalued approach such as that we are proposing, and then turn to specific examples showing the results of an existing implementation. This single implementation is used to solve a digital simulation task using first-order logic, a diagnostic task using ATMSS as suggested by de Kleer and Williams, a problem in default reasoning as in Reiter’s default logic or McCarthy’s circumscription, and to solve the same problem more efficiently by combining default methods with justification information. All of these applications use the same general-purpose bilattice theorem prover and differ only in the choice of bilattice being considered.

Data resource profile: the World Health Organization Study on global AGEing and adult health (SAGE). <=SEP=> Population ageing is rapidly becoming a global issue and will have a major impact on health policies and programmes. The World Health Organization's Study on global AGEing and adult health (SAGE) aims to address the gap in reliable data and scientific knowledge on ageing and health in low- and middle-income countries. SAGE is a longitudinal study with nationally representative samples of persons aged 50+ years in China, Ghana, India, Mexico, Russia and South Africa, with a smaller sample of adults aged 18-49 years in each country for comparisons. Instruments are compatible with other large high-income country longitudinal ageing studies. Wave 1 was conducted during 2007-2010 and included a total of 34 124 respondents aged 50+ and 8340 aged 18-49. In four countries, a subsample consisting of 8160 respondents participated in Wave 1 and the 2002/04 World Health Survey (referred to as SAGE Wave 0). Wave 2 data collection will start in 2012/13, following up all Wave 1 respondents. Wave 3 is planned for 2014/15. SAGE is committed to the public release of study instruments, protocols and meta- and micro-data: access is provided upon completion of a Users Agreement available through WHO's SAGE website (www.who.int/healthinfo/systems/sage) and WHO's archive using the National Data Archive application (http://apps.who.int/healthinfo/systems/surveydata).

Gain Improvement of Rectangular Dielectric Resonator Antenna by Engraving Grooves on Its Side Walls <=SEP=> A new technique for increasing the boresight gain of a rectangular dielectric resonator antenna (DRA) operating at its fundamental radiating <inline-formula><tex-math notation="LaTeX">$TE_{111}^y$</tex-math></inline-formula> mode is introduced. The idea is to increase the radiations from the side walls of the DRA compared to that of its top wall by engraving grooves on the side walls. A model based on the array theory is developed to explain the high-gain nature of the antenna. The measured results demonstrate that the proposed antenna achieves an impedance bandwidth of 21% over a band of 3.24–4 GHz, with a maximum gain of 9.6 dB. This is significantly higher with respect to available data in the literature.

Comparative Analysis of 6 Bit Thermometer-to-Binary Decoders for Flash Analog-to-Digital Converter <=SEP=> In the design of high speed Flash ADC selection of Thermometer to Binary decoder plays an important role. This paper describes different decoder topologies suitable for Flash ADCs. Comparative analysis between them is presented in terms of hardware required, propagation delay & power consumption. Result shows that fat tree & Mux based topologies are suitable for high speed conversions, but Mux based topology is effective in terms of power consumption. Presence of bubble error reduces output correction capability. In this paper advance scheme is proposed for correction of bubble error in Mux based decoder.

E-Readers and Visual Fatigue <=SEP=> The mass digitization of books is changing the way information is created, disseminated and displayed. Electronic book readers (e-readers) generally refer to two main display technologies: the electronic ink (E-ink) and the liquid crystal display (LCD). Both technologies have advantages and disadvantages, but the question whether one or the other triggers less visual fatigue is still open. The aim of the present research was to study the effects of the display technology on visual fatigue. To this end, participants performed a longitudinal study in which two last generation e-readers (LCD, E-ink) and paper book were tested in three different prolonged reading sessions separated by--on average--ten days. Results from both objective (Blinks per second) and subjective (Visual Fatigue Scale) measures suggested that reading on the LCD (Kindle Fire HD) triggers higher visual fatigue with respect to both the E-ink (Kindle Paperwhite) and the paper book. The absence of differences between E-ink and paper suggests that, concerning visual fatigue, the E-ink is indeed very similar to the paper.

Three-Dimensional Skin Deformation as Force Substitution: Wearable Device Design and Performance During Haptic Exploration of Virtual Environments <=SEP=> Virtual reality systems would benefit from a compelling force sensory substitute when workspace or stability limitations prevent the use of kinesthetic force feedback systems. We present a wearable fingertip haptic device with the ability to make and break contact in addition to rendering both shear and normal skin deformation to the fingerpad. A delta mechanism with novel bias spring and tether actuator relocation method enables the use of high-end motors and encoders, allowing precise device control: 10 Hz bandwidth and 0.255 mm RMS tracking error were achieved during testing. In the first of two experiments, participants determined the orientation of a stiff region in a surrounding compliant virtual surface with an average angular error of 7.6 degree, similar to that found in previous studies using traditional force feedback. In the second experiment, we evaluated participants’ ability to interpret differences in friction. The Just Noticeable Difference (JND) of surface friction coefficient discrimination using our skin deformation device was 0.20, corresponding with a reference friction coefficient of 0.5. While higher than that found using kinesthetic feedback, this demonstrates that users can perceive differences in surface friction without world-grounded kinesthetic forces. These experiments show that three DoF skin deformation enables both stiffness and friction discrimination capability in the absence of kinesthetic force feedback.

The possession game? A comparative analysis of ball retention and team success in European and international football, 2007-2010. <=SEP=> Possession is thought of as central to success in modern football, but questions remain about its impact on positive team outcomes (Bate, 1988; Hughes & Franks, 2005; Pollard & Reep, 1997; Stanhope, 2001). Recent studies (e.g. Bloomfield, Polman, & O'Donoghue, 2005; Carling, Williams, & Reilly, 2005; James, Mellallieu, & Holley, 2002; Jones, James, & Mellalieu, 2004; Lago, 2009; Lago & Martin, 2007; Lago-Peñas & Dellal, 2010; Lago-Peñas, Lago-Ballesteros, Dellal, & Gómez, 2010; Taylor, Mellalieu, & James, 2005; Tucker, Mellalieu, James, & Taylor, 2005) that have examined these questions have often been constrained by an exclusive focus on English or Spanish domestic play. Using data from five European leagues, UEFA and FIFA tournaments, the study found that while possession time and passing predicted aggregated team success in domestic league play, both variables were poor predictors at the individual match level once team quality and home advantage were accounted for. In league play, the effect of greater possession was consistently negative; in the Champions League, it had virtually no impact. In national team tournaments, possession failed to reach significance when offensive factors were accounted for. Much of the success behind the 'possession game' was thus a function of elite teams confined in geographic and competitive space. That ball hegemony was not consistently tied to success suggests that a nuanced approach to possession is needed to account for variant strategic environments (e.g. James et al., 2002) and compels match analysts to re-examine the metric's overall value.