OpenRaiser/Intern-Atlas huggingface dataset:
Seven Key Drivers to Online Retailing Growth in KSA
Venue: arXiv cs.CY 2012
Year: 2012

Retailers in Saudi Arabia have been reserved in their adoption of electronically delivered aspects of their business. This paper reports research that identifies and explores key issues to enhance the diffusion of online retailing in Saudi Arabia. Despite the fact that Saudi Arabia has the largest and fastest growth of ICT marketplaces in the Arab region, e-commerce activities are not progressing at the same speed. Only very few Saudi companies, mostly medium and large companies from the manufacturing sector, are involved in e-commerce implementation. Based on qualitative data collected by conducting interviews with 16 retailers and 16 potential customers in Saudi Arabia, 7 key drivers to online retailing diffusion in Saudi Arabia are identified. These key drivers are government support, providing trustworthy and secure online payments options, provision of individual house mailboxes, providing high speed Internet connection at low cost, providing educational programs, the success of bricks-and-clicks model, and competitive prices.
On the Delay Advantage of Coding in Packet Erasure Networks
Venue: arXiv cs.IT 2012
Year: 2012

We consider the delay of network coding compared to routing with retransmissions in packet erasure networks with probabilistic erasures. We investigate the sub-linear term in the block delay required for unicasting $n$ packets and show that there is an unbounded gap between network coding and routing. In particular, we show that delay benefit of network coding scales at least as $\sqrt{n}$. Our analysis of the delay function for the routing strategy involves a major technical challenge of computing the expectation of the maximum of two negative binomial random variables. This problem has been studied previously and we derive the first exact characterization which may be of independent interest. We also use a martingale bounded differences argument to show that the actual coding delay is tightly concentrated around its expectation.
SWEET: Serving the Web by Exploiting Email Tunnels
Venue: arXiv cs.CR 2012
Year: 2012

Open communication over the Internet poses a serious threat to countries with repressive regimes, leading them to develop and deploy censorship mechanisms within their networks. Unfortunately, existing censorship circumvention systems do not provide high availability guarantees to their users, as censors can identify, hence disrupt, the traffic belonging to these systems using today's advanced censorship technologies. In this paper we propose SWEET, a highly available censorship-resistant infrastructure. SWEET works by encapsulating a censored user's traffic to a proxy server inside email messages that are carried over by public email service providers, like Gmail and Yahoo Mail. As the operation of SWEET is not bound to specific email providers we argue that a censor will need to block all email communications in order to disrupt SWEET, which is infeasible as email constitutes an important part of today's Internet. Through experiments with a prototype of our system we find that SWEET's performance is sufficient for web traffic. In particular, regular websites are downloaded within couple of seconds.
Dynamic Optimization of Generalized Least Squares Handover Algorithms
Venue: arXiv cs.NI 2012
Year: 2012

Efficient handover algorithms are essential for highly performing mobile wireless communications. These algorithms depend on numerous parameters, whose settings must be appropriately optimized to offer a seamless connectivity. Nevertheless, such an optimization is difficult in a time varying context, unless adaptive strategies are used. In this paper, a new approach for the handover optimization is proposed. First, a new modeling of the handover process by a hybrid system that takes as input the handover parameters is established. Then, this hybrid system is used to pose some dynamical optimization approaches where the probability of outage and the probability of handover are considered. Since it is shown that these probabilities are difficult to compute, simple approximations of adequate accuracy are developed. Based on these approximations, a new approach to the solution of the handover optimizations is proposed by the use of a trellis diagram. A distributed optimization algorithm is then developed to maximize handover performance. From an extensive set of results obtained by numerical computations and simulations, it is shown that the proposed algorithm allows to improve performance of the handover considerably when compared to more traditional approaches.
The Benefits of Model-Driven Development in Institutional Repositories - Los Beneficios del Desarrollo Dirigido por Modelos en los Repositorios Institucionales
Venue: arXiv cs.DL 2012
Year: 2012

The Institutional Repositories (IR) have been consolidated into the institutions in scientific and academic areas, as shown by the directories existing open access repositories and the deposits daily of articles made by different ways, such as by self-archiving of registered users and the cataloging by librarians. IR systems are based on various conceptual models, so in this paper a bibliographic survey Model-Driven Development (MDD) in systems and applications for RI in order to expose the benefits of applying MDD in IR. The MDD is a paradigm for building software that assigns a central role models and active under which derive models ranging from the most abstract to the concrete, this is done through successive transformations. This paradigm provides a framework that allows interested parties to share their views and directly manipulate representations of the entities of this domain. Therefore, the benefits are grouped by actors that are present, namely, developers, business owners and domain experts. In conclusion, these benefits help make more formal software implementations, resulting in a consolidation of such systems, where the main beneficiaries are the end users through the services are offered
A Comparison of Meta-heuristic Search for Interactive Software Design
Venue: arXiv cs.AI 2012
Year: 2012

Advances in processing capacity, coupled with the desire to tackle problems where a human subjective judgment plays an important role in determining the value of a proposed solution, has led to a dramatic rise in the number of applications of Interactive Artificial Intelligence. Of particular note is the coupling of meta-heuristic search engines with user-provided evaluation and rating of solutions, usually in the form of Interactive Evolutionary Algorithms (IEAs). These have a well-documented history of successes, but arguably the preponderance of IEAs stems from this history, rather than as a conscious design choice of meta-heuristic based on the characteristics of the problem at hand. This paper sets out to examine the basis for that assumption, taking as a case study the domain of interactive software design. We consider a range of factors that should affect the design choice including ease of use, scalability, and of course, performance, i.e. that ability to generate good solutions within the limited number of evaluations available in interactive work before humans lose focus. We then evaluate three methods, namely greedy local search, an evolutionary algorithm and ant colony optimization, with a variety of representations for candidate solutions. Results show that after suitable parameter tuning, ant colony optimization is highly effective within interactive search and out-performs evolutionary algorithms with respect to increasing numbers of attributes and methods in the software design problem. However, when larger numbers of classes are present in the software design, an evolutionary algorithm using a naive grouping integer-based representation appears more scalable.
The Feasibility Conditions for Interference Alignment in MIMO Networks
Venue: arXiv cs.IT 2012
Year: 2012

Interference alignment (IA) has attracted great attention in the last few years for its breakthrough performance in interference networks. However, despite the numerous works dedicated to IA, the feasibility conditions of IA remains unclear for most network topologies. The IA feasibility analysis is challenging as the IA constraints are sets of high-degree polynomials, for which no systematic tool to analyze the solvability conditions exists. In this work, by developing a new mathematical framework that maps the solvability of sets of polynomial equations to the linear independence of their first-order terms, we propose a sufficient condition that applies to MIMO interference networks with general configurations. We have further proved that this sufficient condition matches with the necessary conditions under a wide range of configurations. These results further consolidate the theoretical basis of IA.
Nexus Authorization Logic (NAL): Logical Results
Venue: arXiv cs.CR 2012
Year: 2012

Nexus Authorization Logic (NAL) [Schneider et al. 2011] is a logic for reasoning about authorization in distributed systems. A revised version of NAL is given here, including revised syntax, a revised proof theory using localized hypotheses, and a new Kripke semantics. The proof theory is proved sound with respect to the semantics, and that proof is formalized in Coq.
Sequence Transduction with Recurrent Neural Networks
Venue: arXiv cs.NE 2012
Year: 2012

Many machine learning tasks can be expressed as the transformation---or \emph{transduction}---of input sequences into output sequences: speech recognition, machine translation, protein secondary structure prediction and text-to-speech to name but a few. One of the key challenges in sequence transduction is learning to represent both the input and output sequences in a way that is invariant to sequential distortions such as shrinking, stretching and translating. Recurrent neural networks (RNNs) are a powerful sequence learning architecture that has proven capable of learning such representations. However RNNs traditionally require a pre-defined alignment between the input and output sequences to perform transduction. This is a severe limitation since \emph{finding} the alignment is the most difficult aspect of many sequence transduction problems. Indeed, even determining the length of the output sequence is often challenging. This paper introduces an end-to-end, probabilistic sequence transduction system, based entirely on RNNs, that is in principle able to transform any input sequence into any finite, discrete output sequence. Experimental results for phoneme recognition are provided on the TIMIT speech corpus.
Maximum Eigenmode Relaying with statistical Channel State Information at the Relay
Venue: arXiv cs.IT 2012
Year: 2012

Optimal precoding in the relay is investigated to maximize ergodic capacity of a multiple antenna relay channel. The source and the relay nodes are equipped with multiple antennas and the destination with a single antenna. It is assumed that the channel covariance matrices of the relay's receive and transmit channels are available to the relay, and optimal precoding at the relay is investigated. It is shown that the optimal transmission from the relay should be conducted in the direction of the eigenvectors of the transmit-channel covariance matrix. Then, we derive the necessary and sufficient conditions under which the relay transmission only from the strongest eigenvector achieves capacity; this method is called Maximum Eigenmode Relaying (MER).
The Performance of Betting Lines for Predicting the Outcome of NFL Games
Venue: arXiv cs.SI 2012
Year: 2012

We investigated the performance of the collective intelligence of NFL fans predicting the outcome of games as realized through the Vegas betting lines. Using data from 2560 games (all post-expansion, regular- and post-season games from 2002-2011), we investigated the opening and closing lines, and the margin of victory. We found that the line difference (the difference between the opening and closing line) could be used to retroactively predict divisional winners with no less accuracy than 75% accuracy (i.e., "straight up" predictions). We also found that although home teams only beat the spread 47% of the time, a strategy of betting the home team underdogs (from 2002-2011) would have produced a cumulative winning strategy of 53.5%, above the threshold of 52.38% needed to break even.
Implementing the Stochastics Brane Calculus in a Generic Stochastic Abstract Machine
Venue: arXiv cs.CE 2012
Year: 2012

In this paper, we deal with the problem of implementing an abstract machine for a stochastic version of the Brane Calculus. Instead of defining an ad hoc abstract machine, we consider the generic stochastic abstract machine introduced by Lakin, Paulevé and Phillips. The nested structure of membranes is flattened into a set of species where the hierarchical structure is represented by means of names. In order to reduce the overhead introduced by this encoding, we modify the machine by adding a copy-on-write optimization strategy. We prove that this implementation is adequate with respect to the stochastic structural operational semantics recently given for the Brane Calculus. These techniques can be ported also to other stochastic calculi dealing with nested structures.
RNA interference and Register Machines (extended abstract)
Venue: arXiv cs.LO 2012
Year: 2012

RNA interference (RNAi) is a mechanism whereby small RNAs (siRNAs) directly control gene expression without assistance from proteins. This mechanism consists of interactions between RNAs and small RNAs both of which may be single or double stranded. The target of the mechanism is mRNA to be degraded or aberrated, while the initiator is double stranded RNA (dsRNA) to be cleaved into siRNAs. Observing the digital nature of RNAi, we represent RNAi as a Minsky register machine such that (i) The two registers hold single and double stranded RNAs respectively, and (ii) Machine's instructions are interpreted by interactions of enzyme (Dicer), siRNA (with RISC com- plex) and polymerization (RdRp) to the appropriate registers. Interpreting RNAi as a computational structure, we can investigate the computational meaning of RNAi, especially its complexity. Initially, the machine is configured as a Chemical Ground Form (CGF), which generates incorrect jumps. To remedy this problem, the system is remodeled as recursive RNAi, in which siRNA targets not only mRNA but also the machine instructional analogues of Dicer and RISC. Finally, probabilistic termination is investigated in the recursive RNAi system.
Linearly Refined Session Types
Venue: arXiv cs.LO 2012
Year: 2012

Session types capture precise protocol structure in concurrent programming, but do not specify properties of the exchanged values beyond their basic type. Refinement types are a form of dependent types that can address this limitation, combining types with logical formulae that may refer to program values and can constrain types using arbitrary predicates. We present a pi calculus with assume and assert operations, typed using a session discipline that incorporates refinement formulae written in a fragment of Multiplicative Linear Logic. Our original combination of session and refinement types, together with the well established benefits of linearity, allows very fine-grained specifications of communication protocols in which refinement formulae are treated as logical resources rather than persistent truths.
Relating Reasoning Methodologies in Linear Logic and Process Algebra
Venue: arXiv cs.LO 2012
Year: 2012

We show that the proof-theoretic notion of logical preorder coincides with the process-theoretic notion of contextual preorder for a CCS-like calculus obtained from the formula-as-process interpretation of a fragment of linear logic. The argument makes use of other standard notions in process algebra, namely a labeled transition system and a coinductively defined simulation relation. This result establishes a connection between an approach to reason about process specifications and a method to reason about logic specifications.
Some new similarity measures for hesitant fuzzy sets and their applications in multiple attribute decision making
Venue: arXiv cs.IT 2012
Year: 2012

Similarity measure is a very important topic in fuzzy set theory. Torra (2010) proposed the notion of hesitant fuzzy set(HFS), which is a generalization of the notion of Zadeh' fuzzy set. In this paper, some new similarity measures for HFSs are developed. Based on the proposed similarity measures, a method of multiple attribute decision making under hesitant fuzzy environment is also introduced. Additionally, a numerical example is given to illustrate the application of the proposed similarity measures of HFSs to decision-making.
Efficiently Learning from Revealed Preference
Venue: arXiv cs.GT 2012
Year: 2012

In this paper, we consider the revealed preferences problem from a learning perspective. Every day, a price vector and a budget is drawn from an unknown distribution, and a rational agent buys his most preferred bundle according to some unknown utility function, subject to the given prices and budget constraint. We wish not only to find a utility function which rationalizes a finite set of observations, but to produce a hypothesis valuation function which accurately predicts the behavior of the agent in the future. We give efficient algorithms with polynomial sample-complexity for agents with linear valuation functions, as well as for agents with linearly separable, concave valuation functions with bounded second derivative.
Semantic Polarity of Adjectival Predicates in Online Reviews
Venue: arXiv cs.CL 2012
Year: 2012

Web users produce more and more documents expressing opinions. Because these have become important resources for customers and manufacturers, many have focused on them. Opinions are often expressed through adjectives with positive or negative semantic values. In extracting information from users' opinion in online reviews, exact recognition of the semantic polarity of adjectives is one of the most important requirements. Since adjectives have different semantic orientations according to contexts, it is not satisfying to extract opinion information without considering the semantic and lexical relations between the adjectives and the feature nouns appropriate to a given domain. In this paper, we present a classification of adjectives by polarity, and we analyze adjectives that are undetermined in the absence of contexts. Our research should be useful for accurately predicting semantic orientations of opinion sentences, and should be taken into account before relying on an automatic methods.
Minimum CSIT to achieve Maximum Degrees of Freedom for the MISO BC
Venue: arXiv cs.IT 2012
Year: 2012

Channel state information at the transmitter (CSIT) is a key ingredient in realizing the multiplexing gain provided by distributed MIMO systems. For a downlink multiple-input single output (MISO) broadcast channel, with M antennas at the transmitters and K single antenna receivers, the maximum multiplexing gain or the maximum degrees of freedom (DoF) is min(M,K). The optimal DoF of min(M,K) is achievable if the transmitter has access to perfect, instantaneous CSIT from all receivers. In this paper, we pose the question that what is minimum amount of CSIT required per user in order to achieve the maximum DoF of min(M,K). By minimum amount of CSIT per user, we refer to the minimum fraction of time that the transmitter has access to perfect and instantaneous CSIT from a user. Through a novel converse proof and an achievable scheme, it is shown that the minimum fraction of time, perfect CSIT is required per user in order to achieve the DoF of min(M,K) is given by min(M,K)/K.
Cost Efficient High Capacity Indoor Wireless Access: Denser Wi-Fi or Coordinated Pico-cellular?
Venue: arXiv cs.IT 2012
Year: 2012

Rapidly increasing traffic demand has forced indoor operators to deploy more and more Wi-Fi access points (APs). As AP density increases, inter-AP interference rises and may limit the capacity. Alternatively, cellular technologies using centralized interference coordination can provide the same capacity with the fewer number of APs at the price of more expensive equipment and installation cost. It is still not obvious at what demand level more sophisticated coordination pays off in terms of total system cost. To make this comparison, we assess the required AP density of three candidate systems for a given average demand: a Wi-Fi network, a conventional pico-cellular network with frequency planning, and an advanced system employing multi-cell joint processing. Numerical results show that dense Wi-Fi is the cheapest solution at a relatively low demand level. However, the AP density grows quickly at a critical demand level regardless of propagation conditions. Beyond this Wi-Fi network limit, the conventional pico-cellular network works and is cheaper than the joint processing in obstructed environments, e.g., furnished offices with walls. In line of sight condition such as stadiums, the joint processing becomes the most viable solution. The drawback is that extremely accurate channel state information at transmitters is needed.
The crossing number of the generalized Petersen graph P(10, 3) is six
Venue: arXiv cs.DM 2012
Year: 2012

The crossing number of a graph is the least number of crossings of edges among all drawings of the graph in the plane. In this article, we prove that the crossing number of the generalized Petersen graph P(10, 3) is equal to 6.
Algebraic Model Counting
Venue: arXiv cs.LO 2012
Year: 2012

Weighted model counting (WMC) is a well-known inference task on knowledge bases, used for probabilistic inference in graphical models. We introduce algebraic model counting (AMC), a generalization of WMC to a semiring structure. We show that AMC generalizes many well-known tasks in a variety of domains such as probabilistic inference, soft constraints and network and database analysis. Furthermore, we investigate AMC from a knowledge compilation perspective and show that all AMC tasks can be evaluated using sd-DNNF circuits. We identify further characteristics of AMC instances that allow for the use of even more succinct circuits.
Distributed Control of Generation in a Transmission Grid with a High Penetration of Renewables
Venue: arXiv cs.SY 2012
Year: 2012

Deviations of grid frequency from the nominal frequency are an indicator of the global imbalance between genera- tion and load. Two types of control, a distributed propor- tional control and a centralized integral control, are cur- rently used to keep frequency deviations small. Although generation-load imbalance can be very localized, both controls primarily rely on frequency deviation as their in- put. The time scales of control require the outputs of the centralized integral control to be communicated to distant generators every few seconds. We reconsider this con- trol/communication architecture and suggest a hybrid ap- proach that utilizes parameterized feedback policies that can be implemented in a fully distributed manner because the inputs to these policies are local observables at each generator. Using an ensemble of forecasts of load and time-intermittent generation representative of possible fu- ture scenarios, we perform a centralized off-line stochas- tic optimization to select the generator-specific feedback parameters. These parameters need only be communi- cated to generators once per control period (60 minutes in our simulations). We show that inclusion of local power flows as feedback inputs is crucial and reduces frequency deviations by a factor of ten. We demonstrate our con- trol on a detailed transmission model of the Bonneville Power Administration (BPA). Our findings suggest that a smart automatic and distributed control, relying on ad- vanced off-line and system-wide computations commu- nicated to controlled generators infrequently, may be a viable control and communication architecture solution. This architecture is suitable for a future situation when generation-load imbalances are expected to grow because of increased penetration of time-intermittent generation.