OpenRaiser/Intern-Atlas huggingface dataset:
NPGLM: A Non-Parametric Method for Temporal Link Prediction
Venue: arXiv cs.LG 2017
Year: 2017

In this paper, we try to solve the problem of temporal link prediction in information networks. This implies predicting the time it takes for a link to appear in the future, given its features that have been extracted at the current network snapshot. To this end, we introduce a probabilistic non-parametric approach, called "Non-Parametric Generalized Linear Model" (NP-GLM), which infers the hidden underlying probability distribution of the link advent time given its features. We then present a learning algorithm for NP-GLM and an inference method to answer time-related queries. Extensive experiments conducted on both synthetic data and real-world Sina Weibo social network demonstrate the effectiveness of NP-GLM in solving temporal link prediction problem vis-a-vis competitive baselines.
Security Incident Recognition and Reporting (SIRR): An Industrial Perspective
Venue: arXiv cs.CR 2017
Year: 2017

Reports and press releases highlight that security incidents continue to plague organizations. While researchers and practitioners' alike endeavor to identify and implement realistic security solutions to prevent incidents from occurring, the ability to initially identify a security incident is paramount when researching a security incident lifecycle. Hence, this research investigates the ability of employees in a Global Fortune 500 financial organization, through internal electronic surveys, to recognize and report security incidents to pursue a more holistic security posture. The research contribution is an initial insight into security incident perceptions by employees in the financial sector as well as serving as an initial guide for future security incident recognition and reporting initiatives.
Expert and Non-Expert Opinion about Technological Unemployment
Venue: arXiv cs.AI 2017
Year: 2017

There is significant concern that technological advances, especially in Robotics and Artificial Intelligence (AI), could lead to high levels of unemployment in the coming decades. Studies have estimated that around half of all current jobs are at risk of automation. To look into this issue in more depth, we surveyed experts in Robotics and AI about the risk, and compared their views with those of non-experts. Whilst the experts predicted a significant number of occupations were at risk of automation in the next two decades, they were more cautious than people outside the field in predicting occupations at risk. Their predictions were consistent with their estimates for when computers might be expected to reach human level performance across a wide range of skills. These estimates were typically decades later than those of the non-experts. Technological barriers may therefore provide society with more time to prepare for an automated future than the public fear. In addition, public expectations may need to be dampened about the speed of progress to be expected in Robotics and AI.
Topology Control Schema for Better QoS in Hybrid RF/FSO Mesh Networks
Venue: arXiv cs.NI 2017
Year: 2017

The practical limitations and challenges of radio frequency (RF) based communication networks have become increasingly apparent over the past decade, leading researchers to seek new hybrid communication approaches. One promising strategy that has been the subject of considerable interest is the augmentation of RF technology by Free Space Optics (FSO), using the strength of each communication technology to overcome the limitations of the other. In this article, we introduce a new scheme for controlling the topology in hybrid Radio-Frequency/Free Space Optics (RF/FSO) wireless mesh networks. Our scheme is based on adaptive adjustments to both transmission power (of RF and FSO transmitters) and the optical beam-width (of FSO transmitters) at individual nodes, with the objective of meeting specified Quality of Service (QoS) requirements, specifically end-to-end delay and throughput. We show how one can effectively encode the instantaneous objectives and constraints of the system as an instance of Integer Linear Programming (ILP). We demonstrate that the technique of Lagrangian Relaxation (LR), augmented with iterative repair heuristics, can be used to determine good (albeit sub-optimal) solutions for the ILP problem, making the approach feasible for mid-sized networks. We make the proposed scheme viable for large-scale networks in terms of number of nodes, number of transceivers, and number of source-destination pairs by solving the ILP problem using a Particle Swarm Optimization (PSO) implementation.
Online Submodular Maximization Problem with Vector Packing Constraint
Venue: arXiv cs.DM 2017
Year: 2017

We consider the online vector packing problem in which we have a $d$ dimensional knapsack and items $u$ with weight vectors $\mathbf{w}_u \in \mathbb{R}_+^d$ arrive online in an arbitrary order. Upon the arrival of an item, the algorithm must decide immediately whether to discard or accept the item into the knapsack. When item $u$ is accepted, $\mathbf{w}_u(i)$ units of capacity on dimension $i$ will be taken up, for each $i\in[d]$. To satisfy the knapsack constraint, an accepted item can be later disposed of with no cost, but discarded or disposed of items cannot be recovered. The objective is to maximize the utility of the accepted items $S$ at the end of the algorithm, which is given by $f(S)$ for some non-negative monotone submodular function $f$. For any small constant $ε> 0$, we consider the special case that the weight of an item on every dimension is at most a $(1-ε)$ fraction of the total capacity, and give a polynomial-time deterministic $O(\frac{k}{ε^2})$-competitive algorithm for the problem, where $k$ is the (column) sparsity of the weight vectors. We also show several (almost) tight hardness results even when the algorithm is computationally unbounded. We show that under the $ε$-slack assumption, no deterministic algorithm can obtain any $o(k)$ competitive ratio, and no randomized algorithm can obtain any $o(\frac{k}{\log k})$ competitive ratio. For the general case (when $ε= 0$), no randomized algorithm can obtain any $o(k)$ competitive ratio. In contrast to the $(1+δ)$ competitive ratio achieved in Kesselheim et al. (STOC 2014) for the problem with random arrival order of items and under large capacity assumption, we show that in the arbitrary arrival order case, even when $\| \mathbf{w}_u \|_\infty$ is arbitrarily small for all items $u$, it is impossible to achieve any $o(\frac{\log k}{\log\log k})$ competitive ratio.
Static Dalvik VM bytecode instrumentation
Venue: arXiv cs.CR 2017
Year: 2017

This work proposes a novel approach to restricting the access for blacklisted Android system API calls. Main feature of the suggested method introduced in this paper is that it requires only rootless or (user-mode) access to the system unlike previous works. For that reason this method is valuable for end-users due to the possibility of project distribution via Play Market and it does not require any phone system modifications and/or updates. This paper explains the required background of Android OS necessary for understanding and describes the method for modification Android application. In this paper the proof-of-concept implementation. That is able to block the application's IMEI requests is introduced. Also this paper lists unsuccessful methods that tried to provide the user security. Obviously with those restrictions application may lack some of features that can only be granted in unsecured environment.
Faster Monte-Carlo Algorithms for Fixation Probability of the Moran Process on Undirected Graphs
Venue: arXiv cs.NE 2017
Year: 2017

Evolutionary graph theory studies the evolutionary dynamics in a population structure given as a connected graph. Each node of the graph represents an individual of the population, and edges determine how offspring are placed. We consider the classical birth-death Moran process where there are two types of individuals, namely, the residents with fitness 1 and mutants with fitness r. The fitness indicates the reproductive strength. The evolutionary dynamics happens as follows: in the initial step, in a population of all resident individuals a mutant is introduced, and then at each step, an individual is chosen proportional to the fitness of its type to reproduce, and the offspring replaces a neighbor uniformly at random. The process stops when all individuals are either residents or mutants. The probability that all individuals in the end are mutants is called the fixation probability. We present faster polynomial-time Monte-Carlo algorithms for finidng the fixation probability on undirected graphs. Our algorithms are always at least a factor O(n^2/log n) faster as compared to the previous algorithms, where n is the number of nodes, and is polynomial even if r is given in binary. We also present lower bounds showing that the upper bound on the expected number of effective steps we present is asymptotically tight for undirected graphs.
Lumping of Degree-Based Mean Field and Pair Approximation Equations for Multi-State Contact Processes
Venue: arXiv cs.SI 2017
Year: 2017

Contact processes form a large and highly interesting class of dynamic processes on networks, including epidemic and information spreading. While devising stochastic models of such processes is relatively easy, analyzing them is very challenging from a computational point of view, particularly for large networks appearing in real applications. One strategy to reduce the complexity of their analysis is to rely on approximations, often in terms of a set of differential equations capturing the evolution of a random node, distinguishing nodes with different topological contexts (i.e., different degrees of different neighborhoods), like degree-based mean field (DBMF), approximate master equation (AME), or pair approximation (PA). The number of differential equations so obtained is typically proportional to the maximum degree kmax of the network, which is much smaller than the size of the master equation of the underlying stochastic model, yet numerically solving these equations can still be problematic for large kmax. In this paper, we extend AME and PA, which has been proposed only for the binary state case, to a multi-state setting and provide an aggregation procedure that clusters together nodes having similar degrees, treating those in the same cluster as indistinguishable, thus reducing the number of equations while preserving an accurate description of global observables of interest. We also provide an automatic way to build such equations and to identify a small number of degree clusters that give accurate results. The method is tested on several case studies, where it shows a high level of compression and a reduction of computational time of several orders of magnitude for large networks, with minimal loss in accuracy.
A Generative Model of Group Conversation
Venue: arXiv cs.CL 2017
Year: 2017

Conversations with non-player characters (NPCs) in games are typically confined to dialogue between a human player and a virtual agent, where the conversation is initiated and controlled by the player. To create richer, more believable environments for players, we need conversational behavior to reflect initiative on the part of the NPCs, including conversations that include multiple NPCs who interact with one another as well as the player. We describe a generative computational model of group conversation between agents, an abstract simulation of discussion in a small group setting. We define conversational interactions in terms of rules for turn taking and interruption, as well as belief change, sentiment change, and emotional response, all of which are dependent on agent personality, context, and relationships. We evaluate our model using a parameterized expressive range analysis, observing correlations between simulation parameters and features of the resulting conversations. This analysis confirms, for example, that character personalities will predict how often they speak, and that heterogeneous groups of characters will generate more belief change.
A Novel VHR Image Change Detection Algorithm Based on Image Fusion and Fuzzy C-Means Clustering
Venue: arXiv cs.CV 2017
Year: 2017

This thesis describes a study to perform change detection on Very High Resolution satellite images using image fusion based on 2D Discrete Wavelet Transform and Fuzzy C-Means clustering algorithm. Multiple other methods are also quantitatively and qualitatively compared in this study.
RelNet: End-to-End Modeling of Entities & Relations
Venue: arXiv cs.CL 2017
Year: 2017

We introduce RelNet: a new model for relational reasoning. RelNet is a memory augmented neural network which models entities as abstract memory slots and is equipped with an additional relational memory which models relations between all memory pairs. The model thus builds an abstract knowledge graph on the entities and relations present in a document which can then be used to answer questions about the document. It is trained end-to-end: only supervision to the model is in the form of correct answers to the questions. We test the model on the 20 bAbI question-answering tasks with 10k examples per task and find that it solves all the tasks with a mean error of 0.3%, achieving 0% error on 11 of the 20 tasks.
GraphHP: A Hybrid Platform for Iterative Graph Processing
Venue: arXiv cs.DC 2017
Year: 2017

The Bulk Synchronous Parallel(BSP) computational model has emerged as the dominant distributed framework to build large-scale iterative graph processing systems. While its implementations(e.g., Pregel, Giraph, and Hama) achieve high scalability, frequent synchronization and communication among the workers can cause substantial parallel inefficiency. To help address this critical concern, this paper introduces the GraphHP(Graph Hybrid Processing) platform which inherits the friendly vertex-centric BSP programming interface and optimizes its synchronization and communication overhead. To achieve the goal, we first propose a hybrid execution model which differentiates between the computations within a graph partition and across the partitions, and decouples the computations within a partition from distributed synchronization and communication. By implementing the computations within a partition by pseudo-superstep iteration in memory, the hybrid execution model can effectively reduce synchronization and communication overhead while not requiring heavy scheduling overhead or graph-centric sequential algorithms. We then demonstrate how the hybrid execution model can be easily implemented within the BSP abstraction to preserve its simple programming interface. Finally, we evaluate our implementation of the GraphHP platform on classical BSP applications and show that it performs significantly better than the state-of-the-art BSP implementations. Our GraphHP implementation is based on Hama, but can easily generalize to other BSP platforms.
A universal negative group delay filter for the prediction of band-limited signals
Venue: arXiv cs.SD 2017
Year: 2017

A filter for universal real-time prediction of band-limited signals is presented. The filter consists of multiple time-delayed feedback terms in order to accomplish anticipatory coupling, which again leads to a negative group delay for frequencies in the baseband. The universality of the filter arises from its property that it does not rely on a specific model of the signal. Specifically, as long as the signal to be predicted is band-limited with a known cutoff frequency, the filter order, the only parameter of the filter, follows and the filter predicts the signal in real time up to a prediction horizon that depends on the cutoff frequency, too. It is worked out in detail how signal prediction arises from the negative group delay of the filter. Its properties, including stability, are investigated theoretically, by numerical simulations, and by application to a physiological signal. Possible control and signal processing applications of this filter are discussed.
Human decisions in moral dilemmas are largely described by Utilitarianism: virtual car driving study provides guidelines for ADVs
Venue: arXiv cs.CY 2017
Year: 2017

Ethical thought experiments such as the trolley dilemma have been investigated extensively in the past, showing that humans act in a utilitarian way, trying to cause as little overall damage as possible. These trolley dilemmas have gained renewed attention over the past years; especially due to the necessity of implementing moral decisions in autonomous driving vehicles. We conducted a set of experiments in which participants experienced modified trolley dilemmas as the driver in a virtual reality environment. Participants had to make decisionsbetween two discrete options: driving on one of two lanes where different obstacles came into view. Obstacles included a variety of human-like avatars of different ages and group sizes. Furthermore, we tested the influence of a sidewalk as a potential safe harbor and a condition implicating a self-sacrifice. Results showed that subjects, in general, decided in a utilitarian manner, sparing the highest number of avatars possible with a limited influence of the other variables. Our findings support that human behavior is in line with the utilitarian approach to moral decision making. This may serve as a guideline for the implementation of moral decisions in ADVs.
Efficient Convex Optimization with Membership Oracles
Venue: arXiv cs.DS 2017
Year: 2017

We consider the problem of minimizing a convex function over a convex set given access only to an evaluation oracle for the function and a membership oracle for the set. We give a simple algorithm which solves this problem with $\tilde{O}(n^2)$ oracle calls and $\tilde{O}(n^3)$ additional arithmetic operations. Using this result, we obtain more efficient reductions among the five basic oracles for convex sets and functions defined by Grötschel, Lovasz and Schrijver.
Smart Wireless Communication is the Cornerstone of Smart Infrastructures
Venue: arXiv cs.CY 2017
Year: 2017

Emerging smart infrastructures, such as Smart City, Smart Grid, Smart Health, and Smart Transportation, need smart wireless connectivity. However, the requirements of these smart infrastructures cannot be met with today's wireless networks. A new wireless infrastructure is needed to meet unprecedented needs in terms of agility, reliability, security, scalability, and partnerships. We are at the beginning of a revolution in how we live with technology, resulting from a convergence of machine learning (ML), the Internet-of-Things (IoT), and robotics. A smart infrastructure monitors and processes a vast amount of data, collected from a dense and wide distribution of heterogeneous sensors (e.g., the IoT), as well as from web applications like social media. In real time, using machine learning, patterns and relationships in the data over space, time, and application can be detected and predictions can be made; on the basis of these, resources can be managed, decisions can be made, and devices can be actuated to optimize metrics, such as cost, health, safety, and convenience.
Parameterized Approximation Algorithms for some Location Problems in Graphs
Venue: arXiv cs.DS 2017
Year: 2017

We develop efficient parameterized, with additive error, approximation algorithms for the (Connected) $r$-Domination problem and the (Connected) $p$-Center problem for unweighted and undirected graphs. Given a graph $G$, we show how to construct a (connected) $\big(r + \mathcal{O}(μ) \big)$-dominating set $D$ with $|D| \leq |D^*|$ efficiently. Here, $D^*$ is a minimum (connected) $r$-dominating set of $G$ and $μ$ is our graph parameter, which is the tree-breadth or the cluster diameter in a layering partition of $G$. Additionally, we show that a $+ \mathcal{O}(μ)$-approximation for the (Connected) $p$-Center problem on $G$ can be computed in polynomial time. Our interest in these parameters stems from the fact that in many real-world networks, including Internet application networks, web networks, collaboration networks, social networks, biological networks, and others, and in many structured classes of graphs these parameters are small constants.
IoT-enabled Distributed Cyber-attacks on Transmission and Distribution Grids
Venue: arXiv cs.SY 2017
Year: 2017

The Internet of things (IoT) will make it possible to interconnect and simultaneously control distributed electrical loads. Various technical and regulatory concerns have been raised that IoT-operated loads are being deployed without appropriately considering and systematically addressing potential cyber-security challenges. Hence, one can envision a hypothetical scenario when an ensemble of IoT-controlled loads can be hacked with malicious intentions of compromising operations of the electrical grid. Under this scenario, the attacker would use geographically distributed IoT-controlled loads to alternate their net power injections into the electrical grid in such a way that may disrupt normal grid operations. This paper presents a modeling framework to analyze grid impacts of distributed cyber-attacks on IoT-controlled loads. This framework is used to demonstrate how a hypothetical distributed cyber-attack propagates from the distribution electrical grid, where IoT-controlled loads are expected to be installed, to the transmission electrical grid. The techno-economic interactions between the distribution and transmission electrical grids are accounted for by means of bilevel optimization. The case study is carried out on the modified versions of the 3-area IEEE Reliability Test System (RTS) and the IEEE 13-bus distribution feeder. Our numerical results demonstrate that the severity of such attacks depends on the penetration level of IoT-controlled loads and the strategy of the attacker.
Simultaneous Transmit and Receive Operation in Next Generation IEEE 802.11 WLANs: A MAC Protocol Design Approach
Venue: arXiv cs.NI 2017
Year: 2017

Full-duplex (FD) technology is likely to be adopted in various legacy communications standards. The IEEE 802.11ax working group has been considering a simultaneous transmit and receive (STR) mode for the next generation wireless local area networks (WLANs). Enabling STR mode (FD communication mode) in 802.11 networks creates bi-directional FD (BFD) and uni-directional FD (UFD) links. The key challenge is to integrate STR mode with minimal protocol modifications, while considering the co-existence of FD and legacy half-duplex (HD) stations (STAs) and backwards compatibility. This paper proposes a simple and practical approach to enable STR mode in 802.11 networks with co-existing FD and HD STAs. The protocol explicitly accounts for the peculiarities of FD environments and backwards compatibility. Key aspects of the proposed solution include FD capability discovery, handshake mechanism for channel access, node selection for UFD transmission, adaptive acknowledgement (ACK) timeout for STAs engaged in BFD or UFD transmission, and mitigation of contention unfairness. Performance evaluation demonstrates the effectiveness of the proposed solution in realizing the gains of FD technology for next generation WLANs.