OpenRaiser/Intern-Atlas huggingface dataset:
A Practical Guide to CNNs and Fisher Vectors for Image Instance Retrieval
Venue: arXiv cs.CV 2015
Year: 2015

With deep learning becoming the dominant approach in computer vision, the use of representations extracted from Convolutional Neural Nets (CNNs) is quickly gaining ground on Fisher Vectors (FVs) as favoured state-of-the-art global image descriptors for image instance retrieval. While the good performance of CNNs for image classification are unambiguously recognised, which of the two has the upper hand in the image retrieval context is not entirely clear yet. In this work, we propose a comprehensive study that systematically evaluates FVs and CNNs for image retrieval. The first part compares the performances of FVs and CNNs on multiple publicly available data sets. We investigate a number of details specific to each method. For FVs, we compare sparse descriptors based on interest point detectors with dense single-scale and multi-scale variants. For CNNs, we focus on understanding the impact of depth, architecture and training data on retrieval results. Our study shows that no descriptor is systematically better than the other and that performance gains can usually be obtained by using both types together. The second part of the study focuses on the impact of geometrical transformations such as rotations and scale changes. FVs based on interest point detectors are intrinsically resilient to such transformations while CNNs do not have a built-in mechanism to ensure such invariance. We show that performance of CNNs can quickly degrade in presence of rotations while they are far less affected by changes in scale. We then propose a number of ways to incorporate the required invariances in the CNN pipeline. Overall, our work is intended as a reference guide offering practically useful and simply implementable guidelines to anyone looking for state-of-the-art global descriptors best suited to their specific image instance retrieval problem.
Assessment of LTE Wireless Access for Monitoring of Energy Distribution in the Smart Grid
Venue: arXiv cs.IT 2015
Year: 2015

While LTE is becoming widely rolled out for human-type services, it is also a promising solution for cost-efficient connectivity of the smart grid monitoring equipment. This is a type of machine-to-machine (M2M) traffic that consists mainly of sporadic uplink transmissions. In such a setting, the amount of traffic that can be served in a cell is not constrained by the data capacity, but rather by the signaling constraints in the random access channel and control channel. In this paper we explore these limitations using a detailed simulation of the LTE access reservation protocol (ARP). We find that 1) assigning more random access opportunities may actually worsen performance; and 2) the additional signaling that follows the ARP has very large impact on the capacity in terms of the number of supported devices; we observed a reduction in the capacity by almost a factor of 3. This suggests that a lightweight access method, with a reduced number of signaling messages, needs to be considered in standardization for M2M applications. Additionally we propose a tractable analytical model to calculate the outage that can be rapidly implemented and evaluated. The model accounts for the features of the random access, control channel and uplink and downlink data channels, as well as retransmissions.
Can JSP Code be Generated Using XML Tags?
Venue: arXiv cs.OH 2015
Year: 2015

Over the years, a variety of web services have started using server-side scripting to deliver results back to a client as a paid or free service; one such server-side scripting language is Java Server Pages (JSP). Also Extensible markup language (XML), is being adopted by most web developers as a tool to describe data.Therefore, we present a conversion method which uses predefined XML tags as input and generates the corresponding JSP code. However, the end users are required to have a basic experience with web pages. This conversion method aims to reduce the time and effort spent by the user (web developer) to get acquainted with JSP. The conversion process abstracts the user from the intricacies of JSP and enables him to focus on the business logic.
Augmenting Agent Platforms to Facilitate Conversation Reasoning
Venue: arXiv cs.MA 2015
Year: 2015

Within Multi Agent Systems, communication by means of Agent Communication Languages (ACLs) has a key role to play in the co-operation, co-ordination and knowledge-sharing between agents. Despite this, complex reasoning about agent messaging, and specifically about conversations between agents, tends not to have widespread support amongst general-purpose agent programming languages. ACRE (Agent Communication Reasoning Engine) aims to complement the existing logical reasoning capabilities of agent programming languages with the capability of reasoning about complex interaction protocols in order to facilitate conversations between agents. This paper outlines the aims of the ACRE project and gives details of the functioning of a prototype implementation within the Agent Factory multi agent framework.
Symbolic construction of GR(1) contracts for synchronous systems with full information
Venue: arXiv cs.LO 2015
Year: 2015

This work proposes a symbolic algorithm for the construction of assume-guarantee specifications that allow multiple agents to cooperate. Each agent is assigned goals expressed in a fragment of linear temporal logic known as generalized reactivity of rank 1 (GR(1)). These goals may be unrealizable, unless additional assumptions are made by each agent about the behavior of the other agents. The proposed algorithm constructs weakly fair assumptions for each agent, to ensure that they can cooperate successfully. A necessary requirement is that the given goals be cooperatively satisfiable. We prove that there exist games for which the GR(1) fragment with liveness properties over states is not sufficient to ensure realizability from any state in the cooperatively winning set. The obstruction is due to circular dependencies of liveness goals. To prevent circularity, we introduce nested games as a formalism to express specifications with conditional assumptions. The algorithm is symbolic, with fixpoint structure similar to the GR(1) synthesis algorithm, implying time complexity polynomial in the number of states, and linear in the number of recurrence goals.
A Game of Attribute Decomposition for Software Architecture Design
Venue: arXiv cs.GT 2015
Year: 2015

Attribute-driven software architecture design aims to provide decision support by taking into account the quality attributes of softwares. A central question in this process is: What architecture design best fulfills the desirable software requirements? To answer this question, a system designer needs to make tradeoffs among several potentially conflicting quality attributes. Such decisions are normally ad-hoc and rely heavily on experiences. We propose a mathematical approach to tackle this problem. Game theory naturally provides the basic language: Players represent requirements, and strategies involve setting up coalitions among the players. In this way we propose a novel model, called decomposition game, for attribute-driven design. We present its solution concept based on the notion of cohesion and expansion-freedom and prove that a solution always exists. We then investigate the computational complexity of obtaining a solution. The game model and the algorithms may serve as a general framework for providing useful guidance for software architecture design. We present our results through running examples and a case study on a real-life software project.
Cellular-Automata and Innovation within Indonesian Traditional Weaving Crafts: A Discourse of Human-Computer Interaction
Venue: arXiv cs.CY 2015
Year: 2015

The paper reports the possibility of Indonesian traditional artisans of weaving designs and crafts to explore the cellular automata, a dynamical model in computation that may yield similar patterns. The reviews of the cellular automata due to the perspective of weaving process reveals that the latter would focus on macro-properties, i.e.: the strength of structural construction beside the aesthetic patterns and designs. The meeting of traditional weaving practice and the computational model is delivered and open the door for interesting discourse of computer-aided designs for the traditional artists and designers to come.
Deep Neural Network Based Malware Detection Using Two Dimensional Binary Program Features
Venue: arXiv cs.CR 2015
Year: 2015

Malware remains a serious problem for corporations, government agencies, and individuals, as attackers continue to use it as a tool to effect frequent and costly network intrusions. Machine learning holds the promise of automating the work required to detect newly discovered malware families, and could potentially learn generalizations about malware and benign software that support the detection of entirely new, unknown malware families. Unfortunately, few proposed machine learning based malware detection methods have achieved the low false positive rates required to deliver deployable detectors. In this paper we a deep neural network malware classifier that achieves a usable detection rate at an extremely low false positive rate and scales to real world training example volumes on commodity hardware. Specifically, we show that our system achieves a 95% detection rate at 0.1% false positive rate (FPR), based on more than 400,000 software binaries sourced directly from our customers and internal malware databases. We achieve these results by directly learning on all binaries, without any filtering, unpacking, or manually separating binary files into categories. Further, we confirm our false positive rates directly on a live stream of files coming in from Invincea's deployed endpoint solution, provide an estimate of how many new binary files we expected to see a day on an enterprise network, and describe how that relates to the false positive rate and translates into an intuitive threat score. Our results demonstrate that it is now feasible to quickly train and deploy a low resource, highly accurate machine learning classification model, with false positive rates that approach traditional labor intensive signature based methods, while also detecting previously unseen malware.
Probabilistic Dependency Networks for Prediction and Diagnostics
Venue: arXiv cs.LG 2015
Year: 2015

Research in transportation frequently involve modelling and predicting attributes of events that occur at regular intervals. The event could be arrival of a bus at a bus stop, the volume of a traffic at a particular point, the demand at a particular bus stop etc. In this work, we propose a specific implementation of probabilistic graphical models to learn the probabilistic dependency between the events that occur in a network. A dependency graph is built from the past observed instances of the event and we use the graph to understand the causal effects of some events on others in the system. The dependency graph is also used to predict the attributes of future events and is shown to have a good prediction accuracy compared to the state of the art.
Logical N-AND Gate on a Molecular Turing Machine
Venue: arXiv cs.ET 2015
Year: 2015

In Boolean algebra, it is known that the logical function that corresponds to the negation of the conjunction --NAND-- is universal in the sense that any other logical function can be built based on it. This property makes it essential to modern digital electronics and computer processor design. Here, we design a molecular Turing machine that computes the NAND function over binary strings of arbitrary length. For this purpose, we will perform a mathematical abstraction of the kind of operations that can be done over a double-stranded DNA molecule, as well as presenting a molecular encoding of the input symbols for such a machine.
On the Design of a User-in-the-Loop Channel. With Application to Emergency Egress
Venue: arXiv cs.CY 2015
Year: 2015

The herein approach addresses the case when the user is part of the communication channel. A purpose of the abstraction is to provide a framework for the field of communications, with the user included in the system, reckoning the current 7 Layer model allows safeguards for data only. Solid grounds for application were identified as contribution to ensuring the need for safety which becomes tight during emergency events where timely evacuation is critical. One of the components of a communication system [1] as described in information theory, is the communication channel. It allows the transmitter signal representing the message, to reach the receiver. A hardware setup with two different communication systems in a user-in-the-loop (UIL) [2] configuration is described and assessed pertinent to the specific application.
Space-Frequency Block Code for MIMO-OFDM Communication Systems with Reconfigurable Antennas
Venue: arXiv cs.IT 2015
Year: 2015

We propose a space-frequency (SF) block coding scheme for a multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system using antennas with reconfigurable radiation patterns. In this system, each element of the antenna array at the transmitter side is assumed to be reconfigurable so that it can independently change the physical characteristics of its radiation pattern. The proposed block code is full rate and benefits from spatial, frequency, and reconfigurable radiation pattern state diversity over frequency-selective fading channels. We provide simulation results to demonstrate the performance of the proposed block coding technique and make comparisons with that of the previous SF coding schemes in MIMO-OFDM systems. The results indicate that the proposed code achieves higher diversity and coding gain compared to other available SF codes.
An Integrated Mobile Application for Enhancing Management of Nutrition Information in Arusha Tanzania
Venue: arXiv cs.CY 2015
Year: 2015

Based on the fact that management of nutrition information is still a problem in many developing countries including Tanzania and nutrition information is only verbally provided without emphasis, this study proposes mobile application for enhancing management of nutrition information. The paper discusses the implementation of an integrated mobile application for enhancing management of nutrition information based on literature review and interviews, which were conducted in Arusha region for the collection of key information and details required for designing the mobile application. In this application, PHP technique has been used to build the application logic and MySQL technology for developing the back-end database. Using XML and Java, we have built an application interface that provides easy interactive view.
A Potential Reduction Algorithm for Two-person Zero-sum Mean Payoff Stochastic Games
Venue: arXiv cs.GT 2015
Year: 2015

We suggest a new algorithm for two-person zero-sum undiscounted stochastic games focusing on stationary strategies. Given a positive real $ε$, let us call a stochastic game $ε$-ergodic, if its values from any two initial positions differ by at most $ε$. The proposed new algorithm outputs for every $ε>0$ in finite time either a pair of stationary strategies for the two players guaranteeing that the values from any initial positions are within an $ε$-range, or identifies two initial positions $u$ and $v$ and corresponding stationary strategies for the players proving that the game values starting from $u$ and $v$ are at least $ε/24$ apart. In particular, the above result shows that if a stochastic game is $ε$-ergodic, then there are stationary strategies for the players proving $24ε$-ergodicity. This result strengthens and provides a constructive version of an existential result by Vrieze (1980) claiming that if a stochastic game is $0$-ergodic, then there are $ε$-optimal stationary strategies for every $ε> 0$. The suggested algorithm is based on a potential transformation technique that changes the range of local values at all positions without changing the normal form of the game.
A Lower Bound on the Diameter of the Flip Graph
Venue: arXiv cs.CG 2015
Year: 2015

The flip graph is the graph whose nodes correspond to non-isomorphic combinatorial triangulations and whose edges connect pairs of triangulations that can be obtained one from the other by flipping a single edge. In this note we show that the diameter of the flip graph is at least $\frac{7n}{3} + Θ(1)$, improving upon the previous $2n + Θ(1)$ lower bound.
Bounded Determinization of Timed Automata with Silent Transitions
Venue: arXiv cs.FL 2015
Year: 2015

Deterministic timed automata are strictly less expressive than their non-deterministic counterparts, which are again less expressive than those with silent transitions. As a consequence, timed automata are in general non-determinizable. This is unfortunate since deterministic automata play a major role in model-based testing, observability and implementability. However, by bounding the length of the traces in the automaton, effective determinization becomes possible. We propose a novel procedure for bounded determinization of timed automata. The procedure unfolds the automata to bounded trees, removes all silent transitions and determinizes via disjunction of guards. The proposed algorithms are optimized to the bounded setting and thus are more efficient and can handle a larger class of timed automata than the general algorithms. The approach is implemented in a prototype tool and evaluated on several examples. To our best knowledge, this is the first implementation of this type of procedure for timed automata.
Smoothed Analysis of Dynamic Networks
Venue: arXiv cs.DC 2015
Year: 2015

We generalize the technique of smoothed analysis to distributed algorithms in dynamic network models. Whereas standard smoothed analysis studies the impact of small random perturbations of input values on algorithm performance metrics, dynamic graph smoothed analysis studies the impact of random perturbations of the underlying changing network graph topologies. Similar to the original application of smoothed analysis, our goal is to study whether known strong lower bounds in dynamic network models are robust or fragile: do they withstand small (random) perturbations, or do such deviations push the graphs far enough from a precise pathological instance to enable much better performance? Fragile lower bounds are likely not relevant for real-world deployment, while robust lower bounds represent a true difficulty caused by dynamic behavior. We apply this technique to three standard dynamic network problems with known strong worst-case lower bounds: random walks, flooding, and aggregation. We prove that these bounds provide a spectrum of robustness when subjected to smoothing---some are extremely fragile (random walks), some are moderately fragile / robust (flooding), and some are extremely robust (aggregation).
Light-field Microscopy with a Consumer Light-field Camera
Venue: arXiv cs.GR 2015
Year: 2015

We explore the use of inexpensive consumer light- field camera technology for the purpose of light-field mi- croscopy. Our experiments are based on the Lytro (first gen- eration) camera. Unfortunately, the optical systems of the Lytro and those of microscopes are not compatible, lead- ing to a loss of light-field information due to angular and spatial vignetting when directly recording microscopic pic- tures. We therefore consider an adaptation of the Lytro op- tical system. We demonstrate that using the Lytro directly as an oc- ular replacement, leads to unacceptable spatial vignetting. However, we also found a setting that allows the use of the Lytro camera in a virtual imaging mode which prevents the information loss to a large extent. We analyze the new vir- tual imaging mode and use it in two different setups for im- plementing light-field microscopy using a Lytro camera. As a practical result, we show that the camera can be used for low magnification work, as e.g. common in quality control, surface characterization, etc. We achieve a maximum spa- tial resolution of about 6.25μm, albeit at a limited SNR for the side views.
Online Assignment of Heterogeneous Tasks in Crowdsourcing Markets
Venue: arXiv cs.DS 2015
Year: 2015

We investigate the problem of heterogeneous task assignment in crowdsourcing markets from the point of view of the requester, who has a collection of tasks. Workers arrive online one by one, and each declare a set of feasible tasks they can solve, and desired payment for each feasible task. The requester must decide on the fly which task (if any) to assign to the worker, while assigning workers only to feasible tasks. The goal is to maximize the number of assigned tasks with a fixed overall budget. We provide an online algorithm for this problem and prove an upper bound on the competitive ratio of this algorithm against an arbitrary (possibly worst-case) sequence of workers who want small payments relative to the requester's total budget. We further show an almost matching lower bound on the competitive ratio of any algorithm in this setting. Finally, we propose a different algorithm that achieves an improved competitive ratio in the random permutation model, where the order of arrival of the workers is chosen uniformly at random. Apart from these strong theoretical guarantees, we carry out experiments on simulated data which demonstrates the practical applicability of our algorithms.
Is Stack Overflow Overflowing With Questions and Tags
Venue: arXiv cs.SI 2015
Year: 2015

Programming question and answer (Q & A) websites, such as Quora, Stack Overflow, and Yahoo! Answer etc. helps us to understand the programming concepts easily and quickly in a way that has been tested and applied by many software developers. Stack Overflow is one of the most frequently used programming Q\&A website where the questions and answers posted are presently analyzed manually, which requires a huge amount of time and resource. To save the effort, we present a topic modeling based technique to analyze the words of the original texts to discover the themes that run through them. We also propose a method to automate the process of reviewing the quality of questions on Stack Overflow dataset in order to avoid ballooning the stack overflow with insignificant questions. The proposed method also recommends the appropriate tags for the new post, which averts the creation of unnecessary tags on Stack Overflow.
Is That Twitter Hashtag Worth Reading
Venue: arXiv cs.SI 2015
Year: 2015

Online social media such as Twitter, Facebook, Wikis and Linkedin have made a great impact on the way we consume information in our day to day life. Now it has become increasingly important that we come across appropriate content from the social media to avoid information explosion. In case of Twitter, popular information can be tracked using hashtags. Studying the characteristics of tweets containing hashtags becomes important for a number of tasks, such as breaking news detection, personalized message recommendation, friends recommendation, and sentiment analysis among others. In this paper, we have analyzed Twitter data based on trending hashtags, which is widely used nowadays. We have used event based hashtags to know users' thoughts on those events and to decide whether the rest of the users might find it interesting or not. We have used topic modeling, which reveals the hidden thematic structure of the documents (tweets in this case) in addition to sentiment analysis in exploring and summarizing the content of the documents. A technique to find the interestingness of event based twitter hashtag and the associated sentiment has been proposed. The proposed technique helps twitter follower to read, relevant and interesting hashtag.
Undecidability of a Very Simple Modal Logic with Binding
Venue: arXiv cs.LO 2015
Year: 2015

We show undecidability of the satisfiability problem of what is arguably the simplest non-sub-Boolean modal logic with an implicit notion of binding. This work enriches the series of existing results of undecidability of modal logics with binders, which started with Hybrid Logics and continued with Memory Logics.