justin

Today I read a paper titled “Living City, a Collaborative Browser-based Massively Multiplayer Online Game”

The abstract is:
This work presents the design and implementation of our Browser-based Massively Multiplayer Online Game, Living City, a simulation game fully developed at the University of Messina

Living City is a persistent and real-time digital world, running in the Web browser environment and accessible from users without any client-side installation

Today Massively Multiplayer Online Games attract the attention of Computer Scientists both for their architectural peculiarity and the close interconnection with the social network phenomenon

We will cover these two aspects paying particular attention to some aspects of the project: game balancing (e.g

algorithms behind time and money balancing); business logic (e.g., handling concurrency, cheating avoidance and availability) and, finally, social and psychological aspects involved in the collaboration of players, analyzing their activities and interconnections

Today I read a paper titled “Color scales that are effective in both color and grayscale”

The abstract is:
We consider the problem of finding a color scale which performs well when converted to a grayscale

We assume that each color is converted to a shade of gray with the same intensity as the color

We also assume that the color scales have a linear variation of intensity and hue, and find scales which maximize the average chroma (or “colorfulness”) of the colors

We find two classes of solutions, which traverse the color wheel in opposite directions

The two classes of scales start with hues near cyan and red

The average chroma of the scales are 65-77% those of the pure colors

Today I read a paper titled “Collaborating Robotics Using Nature-Inspired Meta-Heuristics”

The abstract is:
This paper introduces collaborating robots which provide the possibility of enhanced task performance, high reliability and decreased

Collaborating-bots are a collection of mobile robots able to self-assemble and to self-organize in order to solve problems that cannot be solved by a single robot

These robots combine the power of swarm intelligence with the flexibility of self-reconfiguration as aggregate Collaborating-bots can dynamically change their structure to match environmental variations

Collaborating robots are more than just networks of independent agents, they are potentially reconfigurable networks of communicating agents capable of coordinated sensing and interaction with the environment

Robots are going to be an important part of the future

Collaborating robots are limited in individual capability, but robots deployed in large numbers can represent a strong force similar to a colony of ants or swarm of bees

We present a mechanism for collaborating robots based on swarm intelligence such as Ant colony optimization and Particle swarm Optimization

Today I read a paper titled “Memristors can implement fuzzy logic”

The abstract is:
In our work we propose implementing fuzzy logic using memristors

Min and max operations are done by antipodally configured memristor circuits that may be assembled into computational circuits

We discuss computational power of such circuits with respect to m-efficiency and experimentally observed behavior of memristive devices

Circuits implemented with real devices are likely to manifest learning behavior

The circuits presented in the work may be applicable for instance in fuzzy classifiers

Today I read a paper titled “An Intelligent Fire Alert System using Wireless Mobile Communication”

The abstract is:
The system has come to light through the way of inspiration to develop a compact system, based on the fundamental ideas of safety, security and control

Once this system is installed to operation specifying temperature and smoke threshold, in case of any emergency situation due to increasing temperature and/or smoke at place surpassing the threshold, the system immediately sends automatic alert-notifications to the users, concerned with the situations

The user gets total control over the system through mobile SMS, even from the distant location, that to change the threshold, turn on/off the feature of sending ‘alert notification’ and also to reset the system after the emergency situation is overcome

Before executing any command (through SMS) from the user, the system asks for the preset password to verify an authorized user

The security issues have been considered with utter attention in this system to ensure its applicability in industries and business organizations, where security is an important concern

Hence, the fundamental ideas of safety, security and control have been entirely ensured through the system, which have definitely worked as the gear moving factor to look for a new dimension of an ‘Intelligent Fire Alert System’

Today I read a paper titled “Climbing depth-bounded adjacent discrepancy search for solving hybrid flow shop scheduling problems with multiprocessor tasks”

The abstract is:
This paper considers multiprocessor task scheduling in a multistage hybrid flow-shop environment

The problem even in its simplest form is NP-hard in the strong sense

The great deal of interest for this problem, besides its theoretical complexity, is animated by needs of various manufacturing and computing systems

We propose a new approach based on limited discrepancy search to solve the problem

Our method is tested with reference to a proposed lower bound as well as the best-known solutions in literature

Computational results show that the developed approach is efficient in particular for large-size problems

Today I read a paper titled “A Domain-Independent Algorithm for Plan Adaptation”

The abstract is:
The paradigms of transformational planning, case-based planning, and plan debugging all involve a process known as plan adaptation – modifying or repairing an old plan so it solves a new problem

In this paper we provide a domain-independent algorithm for plan adaptation, demonstrate that it is sound, complete, and systematic, and compare it to other adaptation algorithms in the literature

Our approach is based on a view of planning as searching a graph of partial plans

Generative planning starts at the graph’s root and moves from node to node using plan-refinement operators

In planning by adaptation, a library plan – an arbitrary node in the plan graph – is the starting point for the search, and the plan-adaptation algorithm can apply both the same refinement operators available to a generative planner and can also retract constraints and steps from the plan

Our algorithm’s completeness ensures that the adaptation algorithm will eventually search the entire graph and its systematicity ensures that it will do so without redundantly searching any parts of the graph.

Today I read a paper titled “Emotional State Categorization from Speech: Machine vs. Human”

The abstract is:
This paper presents our investigations on emotional state categorization from speech signals with a psychologically inspired computational model against human performance under the same experimental setup

Based on psychological studies, we propose a multistage categorization strategy which allows establishing an automatic categorization model flexibly for a given emotional speech categorization task

We apply the strategy to the Serbian Emotional Speech Corpus (GEES) and the Danish Emotional Speech Corpus (DES), where human performance was reported in previous psychological studies

Our work is the first attempt to apply machine learning to the GEES corpus where the human recognition rates were only available prior to our study

Unlike the previous work on the DES corpus, our work focuses on a comparison to human performance under the same experimental settings

Our studies suggest that psychology-inspired systems yield behaviours that, to a great extent, resemble what humans perceived and their performance is close to that of humans under the same experimental setup

Furthermore, our work also uncovers some differences between machine and humans in terms of emotional state recognition from speech

Today I read a paper titled “Are Happy Developers more Productive? The Correlation of Affective States of Software Developers and their self-assessed Productivity”

The abstract is:
For decades now, it has been claimed that a way to improve software developers’ productivity is to focus on people

Indeed, while human factors have been recognized in Software Engineering research, few empirical investigations have attempted to verify the claim

Development tasks are undertaken through cognitive processing abilities

Affective states – emotions, moods, and feelings – have an impact on work-related behaviors, cognitive processing activities, and the productivity of individuals

In this paper, we report an empirical study on the impact of affective states on software developers’ performance while programming

Two affective states dimensions are positively correlated with self-assessed productivity

We demonstrate the value of applying psychometrics in Software Engineering studies and echo a call to valorize the human, individualized aspects of software developers

We introduce and validate a measurement instrument and a linear mixed-effects model to study the correlation of affective states and the productivity of software developers

Today I read a paper titled “An Educative Brain-Computer Interface”

The abstract is:
In this paper we will describe all necessary parts of Brain-Computer Interface (BCI), such as source of signals, hardware, software, analysis, architectures of complete system

We also will go along various applications of BCI, view some subject fields and their specifics

After preface we will consider the main point of this work-concepts of using BCI in education

Represented direction of BCI development has not been reported prior

In this work a computer system, currently being elaborated in author’s laboratory, will be specified

A purpose of it is to determine a degree of clearness of studied information for certain user according to their indications of brain electrical signals

On the basis of this information the system is able to find an optimal approach to interact with each single user

Feedback individualization leads to learning effectiveness increasing

Stated investigations will be supplemented by author’s analytical reasoning on the nature of thinking process

Today I read a paper titled “Self-paced brain-computer interface control of ambulation in a virtual reality environment”

The abstract is:
Objective: Spinal cord injury (SCI) often leaves affected individuals unable to ambulate

Electroencephalogramme (EEG) based brain-computer interface (BCI) controlled lower extremity prostheses may restore intuitive and able-body-like ambulation after SCI

To test its feasibility, the authors developed and tested a novel EEG-based, data-driven BCI system for intuitive and self-paced control of the ambulation of an avatar within a virtual reality environment (VRE)

Approach: Eight able-bodied subjects and one with SCI underwent the following 10-min training session: subjects alternated between idling and walking kinaesthetic motor imageries (KMI) while their EEG were recorded and analysed to generate subject-specific decoding models

Subjects then performed a goal-oriented online task, repeated over 5 sessions, in which they utilised the KMI to control the linear ambulation of an avatar and make 10 sequential stops at designated points within the VRE

Main results: The average offline training performance across subjects was 77.2 +/- 9.5%, ranging from 64.3% (p = 0.00176) to 94.5% (p = 6.26*10^-23), with chance performance being 50%

The average online performance was 8.4 +/- 1.0 (out of 10) successful stops and 303 +/- 53 sec completion time (perfect = 211 sec)

All subjects achieved performances significantly different than those of random walk (p < 0.05) in 44 of the 45 online sessions

Significance: By using a data-driven machine learning approach to decode users’ KMI, this BCIVRE system enabled intuitive and purposeful self-paced control of ambulation after only a 10-minute training

The ability to achieve such BCI control with minimal training indicates that the implementation of future BCI-lower extremity prosthesis systems may be feasible

Today I read a paper titled “The Smartphone Brain Scanner: A Mobile Real-time Neuroimaging System”

The abstract is:
Combining low cost wireless EEG sensors with smartphones offers novel opportunities for mobile brain imaging in an everyday context

We present a framework for building multi-platform, portable EEG applications with real-time 3D source reconstruction

The system – Smartphone Brain Scanner – combines an off-the-shelf neuroheadset or EEG cap with a smartphone or tablet, and as such represents the first fully mobile system for real-time 3D EEG imaging

We discuss the benefits and challenges of a fully portable system, including technical limitations as well as real-time reconstruction of 3D images of brain activity

We present examples of the brain activity captured in a simple experiment involving imagined finger tapping, showing that the acquired signal in a relevant brain region is similar to that obtained with standard EEG lab equipment

Although the quality of the signal in a mobile solution using a off-the-shelf consumer neuroheadset is lower compared to that obtained using high density standard EEG equipment, we propose that mobile application development may offset the disadvantages and provide completely new opportunities for neuroimaging in natural settings

Today I read a paper titled “Robust Multi biometric Recognition Using Face and Ear Images”

The abstract is:
This study investigates the use of ear as a biometric for authentication and shows experimental results obtained on a newly created dataset of 420 images

Images are passed to a quality module in order to reduce False Rejection Rate

The Principal Component Analysis (eigen ear) approach was used, obtaining 90.7 percent recognition rate

Improvement in recognition results is obtained when ear biometric is fused with face biometric

The fusion is done at decision level, achieving a recognition rate of 96 percent

Today I read a paper titled “Reconstructing Experiences through Sketching”

The abstract is:
We present iScale, a survey tool for the retrospective elicitation of longitudinal user experience data

iScale employs sketching in imposing a process in the reconstruction of one’s experiences with the aim to minimize retrospection bias

Two versions, the Constructive and the Value-Account iScale, were motivated by two distinct theories on how people reconstruct emotional experiences from memory

These two versions were tested in two separate studies

Study 1 aimed at providing qualitative insight into the use of iScale and compared its performance to that of free-hand sketching

Study 2 compared the two versions of iScale to free recall, a control condition that does not influence the reconstruction process

Significant differences between iScale and free recall were found

Overall, iScale resulted in an increase in the amount, the richness, and the test-retest reliability of recalled information

These results provide support for the viability of retrospective techniques as a cost-effective alternative to longitudinal studies

Today I read a paper titled “Creating Usable Pin Array Tactons for Non-Visual Information”

The abstract is:
Spatial information can be difficult to present to a visually impaired computer user

In this paper we examine a new kind of tactile cueing for non-visual interaction as a potential solution, building on earlier work on vibrotactile Tactons

However, unlike vibrotactile Tactons, we use a pin array to stimulate the finger tip

Here, we describe how to design static and dynamic Tactons by defining their basic components

We then present user tests examining how easy it is to distinguish between different forms of pin array Tactons demonstrating accurate Tacton sets to represent directions

These experiments demonstrate usable patterns for static, wave and blinking pin array Tacton sets for guiding a user in one of eight directions

A study is then described that shows the benefits of structuring Tactons to convey information through multiple parameters of the signal

By using multiple independent parameters for a Tacton, this study demonstrates participants perceive more information through a single Tacton

Two applications using these Tactons are then presented: a maze exploration application and an electric circuit exploration application designed for use by and tested with visually impaired users

Today I read a paper titled “Multigraph Sampling of Online Social Networks”

The abstract is:
State-of-the-art techniques for probability sampling of users of online social networks (OSNs) are based on random walks on a single social relation (typically friendship)

While powerful, these methods rely on the social graph being fully connected

Furthermore, the mixing time of the sampling process strongly depends on the characteristics of this graph

In this paper, we observe that there often exist other relations between OSN users, such as membership in the same group or participation in the same event

We propose to exploit the graphs these relations induce, by performing a random walk on their union multigraph

We design a computationally efficient way to perform multigraph sampling by randomly selecting the graph on which to walk at each iteration

We demonstrate the benefits of our approach through (i) simulation in synthetic graphs, and (ii) measurements of Last.fm – an Internet website for music with social networking features

More specifically, we show that multigraph sampling can obtain a representative sample and faster convergence, even when the individual graphs fail, i.e., are disconnected or highly clustered

Today I read a paper titled “Glyph Sorting: Interactive Visualization for Multi-dimensional Data”

The abstract is:
Glyph-based visualization is an effective tool for depicting multivariate information

Since sorting is one of the most common analytical tasks performed on individual attributes of a multi-dimensional data set, this motivates the hypothesis that introducing glyph sorting would significantly enhance the usability of glyph-based visualization

In this paper, we present a glyph-based conceptual framework as part of a visualization process for interactive sorting of multivariate data

We examine several technical aspects of glyph sorting and provide design principles for developing effective, visually sortable glyphs

Glyphs that are visually sortable provide two key benefits: 1) performing comparative analysis of multiple attributes between glyphs and 2) to support multi-dimensional visual search

We describe a system that incorporates focus and context glyphs to control sorting in a visually intuitive manner and for viewing sorted results in an Interactive, Multi-dimensional Glyph (IMG) plot that enables users to perform high-dimensional sorting, analyse and examine data trends in detail

To demonstrate the usability of glyph sorting, we present a case study in rugby event analysis for comparing and analysing trends within matches

This work is undertaken in conjunction with a national rugby team

From using glyph sorting, analysts have reported the discovery of new insight beyond traditional match analysis

Today I read a paper titled “HoloHands: Kinect Control of Optical Tweezers”

The abstract is:
The increasing number of applications for holographic manipulation techniques has sparked the development of more accessible control interfaces

Here, we describe a holographic optical tweezers experiment that is controlled by gestures which are detected by a Microsoft Kinect

We demonstrate that this technique can be used to calibrate the tweezers using the Stokes Drag method and compare this to automated calibrations

We also show that multiple particle manipulation can be handled

This is a promising new line of research for gesture-based control that could find applications in a wide variety of experimental situations

Today I read a paper titled “Engaging Stakeholders through Twitter: How Nonprofit Organizations are Getting More Out of 140 Characters or Less”

The abstract is:
140 characters seems like too small a space for any meaningful information to be exchanged, but Twitter users have found creative ways to get the most out of each Tweet by using different communication tools

This paper looks into how 73 nonprofit organizations use Twitter to engage stakeholders not only through their tweets, but also through other various communication methods

Specifically, it looks into the organizations’ utilization of tweet frequency, following behavior, hyperlinks, hashtags, public messages, retweets, and multimedia files

After analyzing 4,655 tweets, the study found that the nation’s largest nonprofits are not using Twitter to maximize stakeholder involvement

Instead, they continue to use social media as a one-way communication channel, as less than 20% of their total tweets demonstrate conversations and roughly 16% demonstrate indirect connections to specific users

Today I read a paper titled “Efficient Bayesian Social Learning on Trees”

The abstract is:
We consider a set of agents who are attempting to iteratively learn the ‘state of the world’ from their neighbors in a social network

Each agent initially receives a noisy observation of the true state of the world

The agents then repeatedly ‘vote’ and observe the votes of some of their peers, from which they gain more information

The agents’ calculations are Bayesian and aim to myopically maximize the expected utility at each iteration

This model, introduced by Gale and Kariv (2003), is a natural approach to learning on networks

However, it has been criticized, chiefly because the agents’ decision rule appears to become computationally intractable as the number of iterations advances

For instance, a dynamic programming approach (part of this work) has running time that is exponentially large in \min(n, (d-1)^t), where n is the number of agents

We provide a new algorithm to perform the agents’ computations on locally tree-like graphs

Our algorithm uses the dynamic cavity method to drastically reduce computational effort

Let d be the maximum degree and t be the iteration number

The computational effort needed per agent is exponential only in O(td) (note that the number of possible information sets of a neighbor at time t is itself exponential in td)

Under appropriate assumptions on the rate of convergence, we deduce that each agent is only required to spend polylogarithmic (in 1/\eps) computational effort to approximately learn the true state of the world with error probability \eps, on regular trees of degree at least five

We provide numerical and other evidence to justify our assumption on convergence rate

We extend our results in various directions, including loopy graphs

Our results indicate efficiency of iterative Bayesian social learning in a wide range of situations, contrary to widely held beliefs

Today I read a paper titled “SilentSense: Silent User Identification via Dynamics of Touch and Movement Behavioral Biometrics”

The abstract is:
With the increased popularity of smartphones, various security threats and privacy leakages targeting them are discovered and investigated

In this work, we present \ourprotocoltight, a framework to authenticate users silently and transparently by exploiting dynamics mined from the user touch behavior biometrics and the micro-movement of the device caused by user’s screen-touch actions

We build a “touch-based biometrics” model of the owner by extracting some principle features, and then verify whether the current user is the owner or guest/attacker

When using the smartphone, the unique operating dynamics of the user is detected and learnt by collecting the sensor data and touch events silently

When users are mobile, the micro-movement of mobile devices caused by touch is suppressed by that due to the large scale user-movement which will render the touch-based biometrics ineffective

To address this, we integrate a movement-based biometrics for each user with previous touch-based biometrics

We conduct extensive evaluations of our approaches on the Android smartphone, we show that the user identification accuracy is over 99%

Today I read a paper titled “Breathfinding: A Wireless Network that Monitors and Locates Breathing in a Home”

The abstract is:
This paper explores using RSS measurements on many links in a wireless network to estimate the breathing rate of a person, and the location where the breathing is occurring, in a home, while the person is sitting, laying down, standing, or sleeping

The main challenge in breathing rate estimation is that “motion interference”, i.e., movements other than a person’s breathing, generally cause larger changes in RSS than inhalation and exhalation

We develop a method to estimate breathing rate despite motion interference, and demonstrate its performance during multiple short (3-7 minute) tests and during a longer 66 minute test

Further, for the same experiments, we show the location of the breathing person can be estimated, to within about 2 m average error in a 56 square meter apartment

Being able to locate a breathing person who is not otherwise moving, without calibration, is important for applications in search and rescue, health care, and security

Today I read a paper titled “Twitter mood predicts the stock market”

The abstract is:
Behavioral economics tells us that emotions can profoundly affect individual behavior and decision-making

Does this also apply to societies at large, i.e., can societies experience mood states that affect their collective decision making? By extension is the public mood correlated or even predictive of economic indicators? Here we investigate whether measurements of collective mood states derived from large-scale Twitter feeds are correlated to the value of the Dow Jones Industrial Average (DJIA) over time

We analyze the text content of daily Twitter feeds by two mood tracking tools, namely OpinionFinder that measures positive vs

negative mood and Google-Profile of Mood States (GPOMS) that measures mood in terms of 6 dimensions (Calm, Alert, Sure, Vital, Kind, and Happy)

We cross-validate the resulting mood time series by comparing their ability to detect the public’s response to the presidential election and Thanksgiving day in 2008

A Granger causality analysis and a Self-Organizing Fuzzy Neural Network are then used to investigate the hypothesis that public mood states, as measured by the OpinionFinder and GPOMS mood time series, are predictive of changes in DJIA closing values

Our results indicate that the accuracy of DJIA predictions can be significantly improved by the inclusion of specific public mood dimensions but not others

We find an accuracy of 87.6% in predicting the daily up and down changes in the closing values of the DJIA and a reduction of the Mean Average Percentage Error by more than 6%