OpenRaiser/Intern-Atlas huggingface dataset:
New Method for Localization and Human Being Detection using UWB Technology: Helpful Solution for Rescue Robots
Venue: arXiv cs.RO 2013
Year: 2013

Two challenges for rescue robots are to detect human beings and to have an accurate positioning system. In indoor positioning, GPS receivers cannot be used due to the reflections or attenuation caused by obstacles. To detect human beings, sensors such as thermal camera, ultrasonic and microphone can be embedded on the rescue robot. The drawback of these sensors is the detection range. These sensors have to be in close proximity to the victim in order to detect it. UWB technology is then very helpful to ensure precise localization of the rescue robot inside the disaster site and detect human beings. We propose a new method to both detect human beings and locate the rescue robot at the same time. To achieve these goals we optimize the design of UWB pulses based on B-splines. The spectral effectiveness is optimized so the symbols are easier to detect and the mitigation with noise is reduced. Our positioning system performs to locate the rescue robot with an accuracy about 2 centimeters. During some tests we discover that UWB signal characteristics abruptly change after passing through a human body. Our system uses this particular signature to detect human body.
Selecting source image sensor nodes based on 2-hop information to improve image transmissions to mobile robot sinks in search \& rescue operations
Venue: arXiv cs.NI 2013
Year: 2013

We consider Robot-assisted Search $\&$ Rescue operations enhanced with some fixed image sensor nodes capable of capturing and sending visual information to a robot sink. In order to increase the performance of image transfer from image sensor nodes to the robot sinks we propose a 2-hop neighborhood information-based cover set selection to determine the most relevant image sensor nodes to activate. Then, in order to be consistent with our proposed approach, a multi-path extension of Greedy Perimeter Stateless Routing (called T-GPSR) wherein routing decisions are also based on 2-hop neighborhood information is proposed. Simulation results show that our proposal reduces packet losses, enabling fast packet delivery and higher visual quality of received images at the robot sink.
Computing Scalable Multivariate Glocal Invariants of Large (Brain-) Graphs
Venue: arXiv cs.SY 2013
Year: 2013

Graphs are quickly emerging as a leading abstraction for the representation of data. One important application domain originates from an emerging discipline called "connectomics". Connectomics studies the brain as a graph; vertices correspond to neurons (or collections thereof) and edges correspond to structural or functional connections between them. To explore the variability of connectomes---to address both basic science questions regarding the structure of the brain, and medical health questions about psychiatry and neurology---one can study the topological properties of these brain-graphs. We define multivariate glocal graph invariants: these are features of the graph that capture various local and global topological properties of the graphs. We show that the collection of features can collectively be computed via a combination of daisy-chaining, sparse matrix representation and computations, and efficient approximations. Our custom open-source Python package serves as a back-end to a Web-service that we have created to enable researchers to upload graphs, and download the corresponding invariants in a number of different formats. Moreover, we built this package to support distributed processing on multicore machines. This is therefore an enabling technology for network science, lowering the barrier of entry by providing tools to biologists and analysts who otherwise lack these capabilities. As a demonstration, we run our code on 120 brain-graphs, each with approximately 16M vertices and up to 90M edges.
Learning Deep Representations By Distributed Random Samplings
Venue: arXiv cs.LG 2013
Year: 2013

In this paper, we propose an extremely simple deep model for the unsupervised nonlinear dimensionality reduction -- deep distributed random samplings, which performs like a stack of unsupervised bootstrap aggregating. First, its network structure is novel: each layer of the network is a group of mutually independent $k$-centers clusterings. Second, its learning method is extremely simple: the $k$ centers of each clustering are only $k$ randomly selected examples from the training data; for small-scale data sets, the $k$ centers are further randomly reconstructed by a simple cyclic-shift operation. Experimental results on nonlinear dimensionality reduction show that the proposed method can learn abstract representations on both large-scale and small-scale problems, and meanwhile is much faster than deep neural networks on large-scale problems.
Achievable Diversity-Rate Tradeoff of MIMO AF Relaying Systems with MMSE Transceivers
Venue: arXiv cs.IT 2013
Year: 2013

This paper investigates the diversity order of the minimum mean squared error (MMSE) based optimal transceivers in multiple-input multiple-output (MIMO) amplify-and-forward (AF) relaying systems. While the diversity-multiplexing tradeoff (DMT) analysis accurately predicts the behavior of the MMSE receiver for the positive multiplexing gain, it turned out that the performance is very unpredictable via DMT for the case of fixed rates, because MMSE strategies exhibit a complicated rate dependent behavior. In this paper, we establish the diversity-rate tradeoff performance of MIMO AF relaying systems with the MMSE transceivers as a closed-form for all fixed rates, thereby providing a complete characterization of the diversity order together with the earlier work on DMT.
Call-by-value non-determinism in a linear logic type discipline
Venue: arXiv cs.LO 2013
Year: 2013

We consider the call-by-value lambda-calculus extended with a may-convergent non-deterministic choice and a must-convergent parallel composition. Inspired by recent works on the relational semantics of linear logic and non-idempotent intersection types, we endow this calculus with a type system based on the so-called Girard's second translation of intuitionistic logic into linear logic. We prove that a term is typable if and only if it is converging, and that its typing tree carries enough information to give a bound on the length of its lazy call-by-value reduction. Moreover, when the typing tree is minimal, such a bound becomes the exact length of the reduction.
Counting Triangulations and other Crossing-free Structures via Onion Layers
Venue: arXiv cs.CG 2013
Year: 2013

Let $P$ be a set of $n$ points in the plane. A crossing-free structure on $P$ is a plane graph with vertex set $P$. Examples of crossing-free structures include triangulations of $P$, spanning cycles of $P$, also known as polygonalizations of $P$, among others. In this paper we develop a general technique for computing the number of crossing-free structures of an input set $P$. We apply the technique to obtain algorithms for computing the number of triangulations, matchings, and spanning cycles of $P$. The running time of our algorithms is upper bounded by $n^{O(k)}$, where $k$ is the number of onion layers of $P$. In particular, for $k = O(1)$ our algorithms run in polynomial time. In addition, we show that our algorithm for counting triangulations is never slower than $O^{*}(3.1414^{n})$, even when $k = Θ(n)$. Given that there are several well-studied configurations of points with at least $Ω(3.464^{n})$ triangulations, and some even with $Ω(8^{n})$ triangulations, our algorithm asymptotically outperforms any enumeration algorithm for such instances. In fact, it is widely believed that any set of $n$ points must have at least $Ω(3.464^{n})$ triangulations. If this is true, then our algorithm is strictly sub-linear in the number of triangulations counted. We also show that our techniques are general enough to solve the "Restricted-Triangulation-Counting-Problem", which we prove to be $W[2]$-hard in the parameter $k$. This implies a "no free lunch" result: In order to be fixed-parameter tractable, our general algorithm must rely on additional properties that are specific to the considered class of structures.
Designing Spontaneous Speech Search Interface for Historical Archives
Venue: arXiv cs.HC 2013
Year: 2013

Spontaneous speech in the form of conversations, meetings, voice-mail, interviews, oral history, etc. is one of the most ubiquitous forms of human communication. Search engines providing access to such speech collections have the potential to better inform intelligence and make relevant data over vast audio/video archives available to users. This project presents a search user interface design supporting search tasks over a speech collection consisting of an historical archive with nearly 52,000 audiovisual testimonies of survivors and witnesses of the Holocaust and other genocides. The design incorporates faceted search, along with other UI elements like highlighted search items, tags, snippets, etc., to promote discovery and exploratory search. Two different designs have been created to support both manual and automated transcripts. Evaluation was performed using human subjects to measure accuracy in retrieving results, understanding user-perspective on the design elements, and ease of parsing information.
Subjective Logic Operators in Trust Assessment: an Empirical Study
Venue: arXiv cs.CR 2013
Year: 2013

Computational trust mechanisms aim to produce trust ratings from both direct and indirect information about agents' behaviour. Subjective Logic (SL) has been widely adopted as the core of such systems via its fusion and discount operators. In recent research we revisited the semantics of these operators to explore an alternative, geometric interpretation. In this paper we present a principled desiderata for discounting and fusion operators in SL. Building upon this we present operators that satisfy these desirable properties, including a family of discount operators. We then show, through a rigorous empirical study, that specific, geometrically interpreted operators significantly outperform standard SL operators in estimating ground truth. These novel operators offer real advantages for computational models of trust and reputation, in which they may be employed without modifying other aspects of an existing system.
Toward Security Verification against Inference Attacks on Data Trees
Venue: arXiv cs.CR 2013
Year: 2013

This paper describes our ongoing work on security verification against inference attacks on data trees. We focus on infinite secrecy against inference attacks, which means that attackers cannot narrow down the candidates for the value of the sensitive information to finite by available information to the attackers. Our purpose is to propose a model under which infinite secrecy is decidable. To be specific, we first propose tree transducers which are expressive enough to represent practical queries. Then, in order to represent attackers' knowledge, we propose data tree types such that type inference and inverse type inference on those tree transducers are possible with respect to data tree types, and infiniteness of data tree types is decidable.
Bid-Centric Cloud Service Provisioning
Venue: arXiv cs.DC 2013
Year: 2013

Bid-centric service descriptions have the potential to offer a new cloud service provisioning model that promotes portability, diversity of choice and differentiation between providers. A bid matching model based on requirements and capabilities is presented that provides the basis for such an approach. In order to facilitate the bidding process, tenders should be specified as abstractly as possible so that the solution space is not needlessly restricted. To this end, we describe how partial TOSCA service descriptions allow for a range of diverse solutions to be proposed by multiple providers in response to tenders. Rather than adopting a lowest common denominator approach, true portability should allow for the relative strengths and differentiating features of cloud service providers to be applied to bids. With this in mind, we describe how TOSCA service descriptions could be augmented with additional information in order to facilitate heterogeneity in proposed solutions, such as the use of coprocessors and provider-specific services.
A Comparative Evaluation of Curriculum Learning with Filtering and Boosting
Venue: arXiv cs.LG 2013
Year: 2013

Not all instances in a data set are equally beneficial for inferring a model of the data. Some instances (such as outliers) are detrimental to inferring a model of the data. Several machine learning techniques treat instances in a data set differently during training such as curriculum learning, filtering, and boosting. However, an automated method for determining how beneficial an instance is for inferring a model of the data does not exist. In this paper, we present an automated method that orders the instances in a data set by complexity based on the their likelihood of being misclassified (instance hardness). The underlying assumption of this method is that instances with a high likelihood of being misclassified represent more complex concepts in a data set. Ordering the instances in a data set allows a learning algorithm to focus on the most beneficial instances and ignore the detrimental ones. We compare ordering the instances in a data set in curriculum learning, filtering and boosting. We find that ordering the instances significantly increases classification accuracy and that filtering has the largest impact on classification accuracy. On a set of 52 data sets, ordering the instances increases the average accuracy from 81% to 84%.
Comparative analysis of evolutionary algorithms for image enhancement
Venue: arXiv cs.CV 2013
Year: 2013

Evolutionary algorithms are metaheuristic techniques that derive inspiration from the natural process of evolution. They can efficiently solve (generate acceptable quality of solution in reasonable time) complex optimization (NP-Hard) problems. In this paper, automatic image enhancement is considered as an optimization problem and three evolutionary algorithms (Genetic Algorithm, Differential Evolution and Self Organizing Migration Algorithm) are employed to search for an optimum solution. They are used to find an optimum parameter set for an image enhancement transfer function. The aim is to maximize a fitness criterion which is a measure of image contrast and the visibility of details in the enhanced image. The enhancement results obtained using all three evolutionary algorithms are compared amongst themselves and also with the output of histogram equalization method.
Fake View Analytics in Online Video Services
Venue: arXiv cs.MM 2013
Year: 2013

Online video-on-demand(VoD) services invariably maintain a view count for each video they serve, and it has become an important currency for various stakeholders, from viewers, to content owners, advertizers, and the online service providers themselves. There is often significant financial incentive to use a robot (or a botnet) to artificially create fake views. How can we detect the fake views? Can we detect them (and stop them) using online algorithms as they occur? What is the extent of fake views with current VoD service providers? These are the questions we study in the paper. We develop some algorithms and show that they are quite effective for this problem.
A Platform for Teaching Applied Distributed Software Development: The Ongoing Journey of the Helsinki Software Factory
Venue: arXiv cs.SE 2013
Year: 2013

Teaching distributed software development (DSD) in project courses where student teams are geographically distributed promises several benefits. One main benefit is that in contrast to traditional classroom courses, students can experience the effects of distribution and the mechanisms for coping with distribution by themselves, therefore understanding their relevance for software development. They can thus learn to take more care of distribution challenges and risks when starting to develop software in industry. However, providing a sustainable environment for such project courses is difficult. A development environment is needed that can connect to different distributed teams and an ongoing routine to conduct such courses needs to be established. This article sketches a picture of the Software Factory, a platform that supports teaching distributed student projects and that has now been operational for more than three years. We describe the basic steps of conducting Software Factory projects, and portray experiences from past factory projects. In addition, we provide a short overview of related approaches and future activities.
A Cellular Automaton Based Controller for a Ms. Pac-Man Agent
Venue: arXiv cs.AI 2013
Year: 2013

Video games can be used as an excellent test bed for Artificial Intelligence (AI) techniques. They are challenging and non-deterministic, this makes it very difficult to write strong AI players. An example of such a video game is Ms. Pac-Man. In this paper we will outline some of the previous techniques used to build AI controllers for Ms. Pac-Man as well as presenting a new and novel solution. My technique utilises a Cellular Automaton (CA) to build a representation of the environment at each time step of the game. The basis of the representation is a 2-D grid of cells. Each cell has a state and a set of rules which determine whether or not that cell will dominate (i.e. pass its state value onto) adjacent cells at each update. Once a certain number of update iterations have been completed, the CA represents the state of the environment in the game, the goals and the dangers. At this point, Ms. Pac-Man will decide her next move based only on her adjacent cells, that is to say, she has no knowledge of the state of the environment as a whole, she will simply follow the strongest path. This technique shows promise and allows the controller to achieve high scores in a live game, the behaviour it exhibits is interesting and complex. Moreover, this behaviour is produced by using very simple rules which are applied many times to each cell in the grid. Simple local interactions with complex global results are truly achieved.
Codes between MBR and MSR Points with Exact Repair Property
Venue: arXiv cs.IT 2013
Year: 2013

In this paper distributed storage systems with exact repair are studied. A construction for regenerating codes between the minimum storage regenerating (MSR) and the minimum bandwidth regenerating (MBR) points is given. To the best of author's knowledge, no previous construction of exact-regenerating codes between MBR and MSR points is done except in the work by Tian et al. On contrast to their work, the methods used here are elementary. In this paper it is shown that in the case that the parameters $n$, $k$, and $d$ are close to each other, the given construction is close to optimal when comparing to the known functional repair capacity. This is done by showing that when the distances of the parameters $n$, $k$, and $d$ are fixed but the actual values approach to infinity, the fraction of the performance of constructed codes with exact repair and the known capacity of codes with functional repair, approaches to one. Also a simple variation of the constructed codes with almost the same performance is given.
Sistem pendukung keputusan kelayakan TKI ke luar negeri menggunakan FMADM
Venue: arXiv cs.AI 2013
Year: 2013

BP3TKI Palembang is the government agencies that coordinate, execute and selection of prospective migrants registration and placement. To simplify the existing procedures and improve decision-making is necessary to build a decision support system (DSS) to determine eligibility for employment abroad by applying Fuzzy Multiple Attribute Decision Making (FMADM), using the linear sequential systems development methods. The system is built using Microsoft Visual Basic. Net 2010 and SQL Server 2008 database. The design of the system using use case diagrams and class diagrams to identify the needs of users and systems as well as systems implementation guidelines. This Decision Support System able to rank and produce the prospective migrants, making it easier for parties to take decision BP3TKI the workers who will be working out of the country.
Min Flow Rate Maximization for Software Defined Radio Access Networks
Venue: arXiv cs.IT 2013
Year: 2013

We consider a heterogeneous network (HetNet) of base stations (BSs) connected via a backhaul network of routers and wired/wireless links with limited capacity. The optimal provision of such networks requires proper resource allocation across the radio access links in conjunction with appropriate traffic engineering within the backhaul network. In this paper we propose an efficient algorithm for joint resource allocation across the wireless links and the flow control within the backhaul network. The proposed algorithm, which maximizes the minimum rate among all the users and/or flows, is based on a decomposition approach that leverages both the Alternating Direction Method of Multipliers (ADMM) and the weighted-MMSE (WMMSE) algorithm. We show that this algorithm is easily parallelizable and converges globally to a stationary solution of the joint optimization problem. The proposed algorithm can also be extended to deal with per-flow quality of service constraint, or to networks with multi-antenna nodes.
Network Traffic Analysis:Hadoop Pig vs Typical MapReduce
Venue: arXiv cs.DC 2013
Year: 2013

Big data analysis has become much popular in the present day scenario and the manipulation of big data has gained the keen attention of researchers in the field of data analytics. Analysis of big data is currently considered as an integral part of many computational and statistical departments. As a result, novel approaches in data analysis are evolving on a daily basis. Thousands of transaction requests are handled and processed everyday by different websites associated with e-commerce, e-banking, e-shopping carts etc. The network traffic and weblog analysis comes to play a crucial role in such situations where Hadoop can be suggested as an efficient solution for processing the Netflow data collected from switches as well as website access-logs during fixed intervals.
Design of Field Programmable Gate Array (FPGA) Based Emulators for Motor Control Applications
Venue: arXiv cs.SY 2013
Year: 2013

Problem Statement: Field Programmable Gate Array (FPGA) circuits play a significant role in major recent embedded process control designs. However, exploiting these platforms requires deep hardware conception skills and remains an important time consuming stage in a design flow. High Level Synthesis technique avoids this bottleneck and increases design productivity as witnessed by industry specialists. Approach: This study proposes to apply this technique for the conception and implementation of a Real Time Direct Current Machine (RTDCM) emulator for an embedded control application. Results: Several FPGA-based configuration scenarios are studied. A series of tests including design and timing-precision analysis were conducted to discuss and validate the obtained hardware architectures. Conclusion/Recommendations: The proposed methodology has accelerated the design time besides it has provided an extra time to refine the hardware core of the DCM emulator. The high level synthesis technique can be applied to the control field especially to test with low cost and short delays newest algorithms and motor models.