OpenRaiser/Intern-Atlas huggingface dataset:
A Flow Level Perspective on Base Station Power Allocation in Green Networks
Venue: arXiv cs.NI 2012
Year: 2012

In this work, we propose a novel power allocation mechanism which allows one to optimize the energy-efficiency of base stations operating in the downlink. The energy-efficiency refers to the amount of bits that can be transmitted by the base station per unit of energy consumed. This work studies the impact of flow-level dynamics on the energy efficiency of base stations, by considering user arrivals and departures. Our proposed power allocation scheme optimizes the energyefficiency, accounting for the dynamic nature of users (referred to as the global energy-efficiency). We emphasize our numerical results that study the influence of the radio conditions, transmit power and the user traffic on the energy-efficiency in an LTE compliant framework. Finally, we show that the power allocation scheme that considers traffic dynamics, is significantly different from the power allocation scheme when the number of users is considered as constant, and that it has a better performance.
Satisfaction, Restriction and Amalgamation of Constraints in the Framework of M-Adhesive Categories
Venue: arXiv cs.LO 2012
Year: 2012

Application conditions for rules and constraints for graphs are well-known in the theory of graph transformation and have been extended already to M-adhesive transformation systems. According to the literature we distinguish between two kinds of satisfaction for constraints, called general and initial satisfaction of constraints, where initial satisfaction is defined for constraints over an initial object of the base category. Unfortunately, the standard definition of general satisfaction is not compatible with negation in contrast to initial satisfaction. Based on the well-known restriction of objects along type morphisms, we study in this paper restriction and amalgamation of application conditions and constraints together with their solutions. In our main result, we show compatibility of initial satisfaction for positive constraints with restriction and amalgamation, while general satisfaction fails in general. Our main result is based on the compatibility of composition via pushouts with restriction, which is ensured by the horizontal van Kampen property in addition to the vertical one that is generally satisfied in M-adhesive categories.
Underspecified Scientific Claims in Nanopublications
Venue: arXiv cs.DL 2012
Year: 2012

The application range of nanopublications --- small entities of scientific results in RDF representation --- could be greatly extended if complete formal representations are not mandatory. To that aim, we present an approach to represent and interlink scientific claims in an underspecified way, based on independent English sentences.
Sequential Auctions of Identical Items with Budget-Constrained Bidders
Venue: arXiv cs.GT 2012
Year: 2012

In this paper, we study sequential auctions with two budget constrained bidders and any number of identical items. All prior results on such auctions consider only two items. We construct a canonical outcome of the auction that is the only natural equilibrium and is unique under a refinement of subgame perfect equilibria. We show certain interesting properties of this equilibrium; for instance, we show that the prices decrease as the auction progresses. This phenomenon has been observed in many experiments and previous theoretic work attributed it to features such as uncertainty in the supply or risk averse bidders. We show that such features are not needed for this phenomenon and that it arises purely from the most essential features: budget constraints and the sequential nature of the auction. A little surprisingly we also show that in this equilibrium one agent wins all his items in the beginning and then the other agent wins the rest. The major difficulty in analyzing such sequential auctions has been in understanding how the selling prices of the first few rounds affect the utilities of the agents in the later rounds. We tackle this difficulty by identifying certain key properties of the auction and the proof is via a joint induction on all of them.
Performance Evaluation of on demand and Table driven Protocol for Wireless Ad hoc Network
Venue: arXiv cs.NI 2012
Year: 2012

Mobile Adhoc Network is a wireless network without infrastructure.It is a kind of wireless adhoc network,and is a self configuring network of mobile routers connected by wireless links.The routers are free to move randomly and organize themselves arbitrarily,thus the network's wireless topology may change rapidly and unpredictably. Such a network may operate in a standalone fashion,or may be connected to the larger Internet.There are various routing protocols available for MANET.The most popular ones are DSR,AODV and DSDV.This paper examines two routing protocols for mobile ad hoc networks :the Destination Sequenced Distance Vector,the table driven protocol and the Ad hoc On Demand Distance Vector routing,an On Demand protocol and evaluates both protocols based on packet delivery fraction, average end to end delay,throughput and routing overhead while varying pause time.The performance evaluation has been done by using simulation tool NS2 which is the main simulator, NAM(Network Animator)and excel graph which is used for preparing the graphs from the trace files.Simulation revealed that although DSDV perfectly scales to small networks with low node speeds,AODV is preferred due to its more efficient use of bandwidth.
A New Similairty Measure For Spatial Personalization
Venue: arXiv cs.DB 2012
Year: 2012

Extracting the relevant information by exploiting the spatial data warehouse becomes increasingly hard. In fact, because of the enormous amount of data stored in the spatial data warehouse, the user, usually, don't know what part of the cube contain the relevant information and what the forthcoming query should be. As a solution, we propose to study the similarity between the behaviors of the users, in term of the spatial MDX queries launched on the system, as a basis to recommend the next relevant MDX query to the current user. This paper introduces a new similarity measure for comparing spatial MDX queries. The proposed similarity measure could directly support the development of spatial personalization approaches. The proposed similarity measure takes into account the basic components of the similarity assessment models: the topology, the direction and the distance.
An Empirical Study of MAUC in Multi-class Problems with Uncertain Cost Matrices
Venue: arXiv cs.LG 2012
Year: 2012

Cost-sensitive learning relies on the availability of a known and fixed cost matrix. However, in some scenarios, the cost matrix is uncertain during training, and re-train a classifier after the cost matrix is specified would not be an option. For binary classification, this issue can be successfully addressed by methods maximizing the Area Under the ROC Curve (AUC) metric. Since the AUC can measure performance of base classifiers independent of cost during training, and a larger AUC is more likely to lead to a smaller total cost in testing using the threshold moving method. As an extension of AUC to multi-class problems, MAUC has attracted lots of attentions and been widely used. Although MAUC also measures performance of base classifiers independent of cost, it is unclear whether a larger MAUC of classifiers is more likely to lead to a smaller total cost. In fact, it is also unclear what kinds of post-processing methods should be used in multi-class problems to convert base classifiers into discrete classifiers such that the total cost is as small as possible. In the paper, we empirically explore the relationship between MAUC and the total cost of classifiers by applying two categories of post-processing methods. Our results suggest that a larger MAUC is also beneficial. Interestingly, simple calibration methods that convert the output matrix into posterior probabilities perform better than existing sophisticated post re-optimization methods.
Bulk content delivery using co-operating end-nodes with upload/download limits
Venue: arXiv cs.NI 2012
Year: 2012

We study the problem of optimizing the cost of content delivery in a cooperative network of caches at end-nodes. The caches could be, for example, within the computers of users downloading videos from websites (such as Netflix, Blockbuster etc.), DVRs (such as TiVo, or cable boxes) used as part of video on demand services or public hot-spots (e.g. Wi-Fi access points with a cache) deployed over a city to serve content to mobile users. Each cache serves user requests locally over a medium that incurs no additional costs (i.e. WiFi, home LAN); if a request is not cached, it must be fetched from another cache or a central server. In our model, each cache has a tiered back-haul internet connection, with a usage cap (and fixed per-byte costs thereafter). Redirecting requests intended for the central server to other caches with unused back-haul capacity can bring down the network costs. Our goal is to develop a mechanism to optimally 1) place data into the caches and 2) route requests to caches to reduce the overall cost of content delivery. We develop a multi-criteria approximation based on a LP rounding procedure that with a small (constant factor) blow-up in storage and upload limits of each cache, gives a data placement that is within constant factor of the optimum. Further, to speed up the solution, we propose a technique to cluster caches into groups, solve the data placement problem within a group, and combine the results in the rounding phase to get the global solution.Based on extensive simulations, we show that our schemes perform very well in practice, giving costs within $5--15$% to the optimal, and reducing the network load at a central server by as much as 55% with only a marginal blow up in the limits. Also we demonstrate that our approach out-performs a non-cooperative caching mechanism by about 20%.
A matrix approach for computing extensions of argumentation frameworks
Venue: arXiv cs.AI 2012
Year: 2012

The matrices and their sub-blocks are introduced into the study of determining various extensions in the sense of Dung's theory of argumentation frameworks. It is showed that each argumentation framework has its matrix representations, and the core semantics defined by Dung can be characterized by specific sub-blocks of the matrix. Furthermore, the elementary permutations of a matrix are employed by which an efficient matrix approach for finding out all extensions under a given semantics is obtained. Different from several established approaches, such as the graph labelling algorithm, Constraint Satisfaction Problem algorithm, the matrix approach not only put the mathematic idea into the investigation for finding out various extensions, but also completely achieve the goal to compute all the extensions needed.
Model-Checking of Ordered Multi-Pushdown Automata
Venue: arXiv cs.LO 2012
Year: 2012

We address the verification problem of ordered multi-pushdown automata: A multi-stack extension of pushdown automata that comes with a constraint on stack transitions such that a pop can only be performed on the first non-empty stack. First, we show that the emptiness problem for ordered multi-pushdown automata is in 2ETIME. Then, we prove that, for an ordered multi-pushdown automata, the set of all predecessors of a regular set of configurations is an effectively constructible regular set. We exploit this result to solve the global model-checking which consists in computing the set of all configurations of an ordered multi-pushdown automaton that satisfy a given w-regular property (expressible in linear-time temporal logics or the linear-time μ-calculus). As an immediate consequence, we obtain an 2ETIME upper bound for the model-checking problem of w-regular properties for ordered multi-pushdown automata (matching its lower-bound).
Sorting distinct integer keys using in-place associative sort
Venue: arXiv cs.DS 2012
Year: 2012

In-place associative integer sorting technique was proposed for integer lists which requires only constant amount of additional memory replacing bucket sort, distribution counting sort and address calculation sort family of algorithms. The technique was explained by the analogy with the three main stages in the formation and retrieval of memory in cognitive neuroscience which are (i) practicing, (ii) storing and (iii) retrieval. In this study, the technique is specialized with two variants one for read-only integer keys and the other for modifiable integers. Hence, a novel algorithm is obtained that does not require additional memory other than a constant amount and sorts faster than all no matter how large is the list provided that m = O (n logn) where m is the range and n is the number of keys (or integers).
Semantic web applications with regard to math and environment
Venue: arXiv cs.DL 2012
Year: 2012

The following is an outline of possible strategies in using semantic web techniques and math with regard to environmental issues. The article uses concrete examples and applications and provides partially a rather basic treatment of semantic web techniques and math in order to adress a broader audience.
Optimality Properties, Distributed Strategies, and Measurement-Based Evaluation of Coordinated Multicell OFDMA Transmission
Venue: arXiv cs.IT 2012
Year: 2012

The throughput of multicell systems is inherently limited by interference and the available communication resources. Coordinated resource allocation is the key to efficient performance, but the demand on backhaul signaling and computational resources grows rapidly with number of cells, terminals, and subcarriers. To handle this, we propose a novel multicell framework with dynamic cooperation clusters where each terminal is jointly served by a small set of base stations. Each base station coordinates interference to neighboring terminals only, thus limiting backhaul signalling and making the framework scalable. This framework can describe anything from interference channels to ideal joint multicell transmission. The resource allocation (i.e., precoding and scheduling) is formulated as an optimization problem (P1) with performance described by arbitrary monotonic functions of the signal-to-interference-and-noise ratios (SINRs) and arbitrary linear power constraints. Although (P1) is non-convex and difficult to solve optimally, we are able to prove: 1) Optimality of single-stream beamforming; 2) Conditions for full power usage; and 3) A precoding parametrization based on a few parameters between zero and one. These optimality properties are used to propose low-complexity strategies: both a centralized scheme and a distributed version that only requires local channel knowledge and processing. We evaluate the performance on measured multicell channels and observe that the proposed strategies achieve close-to-optimal performance among centralized and distributed solutions, respectively. In addition, we show that multicell interference coordination can give substantial improvements in sum performance, but that joint transmission is very sensitive to synchronization errors and that some terminals can experience performance degradations.
Power Allocation for Conventional and Buffer-Aided Link Adaptive Relaying Systems with Energy Harvesting Nodes
Venue: arXiv cs.IT 2012
Year: 2012

Energy harvesting (EH) nodes can play an important role in cooperative communication systems which do not have a continuous power supply. In this paper, we consider the optimization of conventional and buffer-aided link adaptive EH relaying systems, where an EH source communicates with the destination via an EH decode-and-forward relay. In conventional relaying, source and relay transmit signals in consecutive time slots whereas in buffer-aided link adaptive relaying, the state of the source-relay and relay-destination channels determines whether the source or the relay is selected for transmission. Our objective is to maximize the system throughput over a finite number of transmission time slots for both relaying protocols. In case of conventional relaying, we propose an offline and several online joint source and relay transmit power allocation schemes. For offline power allocation, we formulate an optimization problem which can be solved optimally. For the online case, we propose a dynamic programming (DP) approach to compute the optimal online transmit power. To alleviate the complexity inherent to DP, we also propose several suboptimal online power allocation schemes. For buffer-aided link adaptive relaying, we show that the joint offline optimization of the source and relay transmit powers along with the link selection results in a mixed integer non-linear program which we solve optimally using the spatial branch-and-bound method. We also propose an efficient online power allocation scheme and a naive online power allocation scheme for buffer-aided link adaptive relaying. Our results show that link adaptive relaying provides performance improvement over conventional relaying at the expense of a higher computational complexity.
Multimodal diffusion geometry by joint diagonalization of Laplacians
Venue: arXiv cs.CV 2012
Year: 2012

We construct an extension of diffusion geometry to multiple modalities through joint approximate diagonalization of Laplacian matrices. This naturally extends classical data analysis tools based on spectral geometry, such as diffusion maps and spectral clustering. We provide several synthetic and real examples of manifold learning, retrieval, and clustering demonstrating that the joint diffusion geometry frequently better captures the inherent structure of multi-modal data. We also show that many previous attempts to construct multimodal spectral clustering can be seen as particular cases of joint approximate diagonalization of the Laplacians.
Optimization of fuzzy analogy in software cost estimation using linguistic variables
Venue: arXiv cs.SE 2012
Year: 2012

One of the most important objectives of software engineering community has been the increase of useful models that beneficially explain the development of life cycle and precisely calculate the effort of software cost estimation. In analogy concept, there is deficiency in handling the datasets containing categorical variables though there are innumerable methods to estimate the cost. Due to the nature of software engineering domain, generally project attributes are often measured in terms of linguistic values such as very low, low, high and very high. The imprecise nature of such value represents the uncertainty and vagueness in their elucidation. However, there is no efficient method that can directly deal with the categorical variables and tolerate such imprecision and uncertainty without taking the classical intervals and numeric value approaches. In this paper, a new approach for optimization based on fuzzy logic, linguistic quantifiers and analogy based reasoning is proposed to improve the performance of the effort in software project when they are described in either numerical or categorical data. The performance of this proposed method exemplifies a pragmatic validation based on the historical NASA dataset. The results were analyzed using the prediction criterion and indicates that the proposed method can produce more explainable results than other machine learning methods.
Internal joint forces in dynamics of a 3-PRP planar parallel robot
Venue: arXiv cs.RO 2012
Year: 2012

Recursive matrix relations for the complete dynamics of a 3-PRP planar parallel robot are established in this paper. Three identical planar legs connecting to the moving platform are located in the same vertical plane. Knowing the motion of the platform, we develop first the inverse kinematical problem and determine the positions, velocities and accelerations of the robot. Further, the inverse dynamic problem is solved using an approach based on the principle of virtual work. Finally, some graphs of simulation for the input powers of three actuators and the internal joint forces are obtained.
TCP/IP communication between two USRP-E110
Venue: arXiv cs.NI 2012
Year: 2012

This short report intends to provide an overview of the procedure and statistics of establishing a TCP/IP link between two USRP-E110. The testings are performed using an example GNURadio code and the networking protocol stack provided by the Linux operating system embedded in the USRP-E110.
Regret Bounds for Restless Markov Bandits
Venue: arXiv cs.LG 2012
Year: 2012

We consider the restless Markov bandit problem, in which the state of each arm evolves according to a Markov process independently of the learner's actions. We suggest an algorithm that after $T$ steps achieves $\tilde{O}(\sqrt{T})$ regret with respect to the best policy that knows the distributions of all arms. No assumptions on the Markov chains are made except that they are irreducible. In addition, we show that index-based policies are necessarily suboptimal for the considered problem.
Protecting oracle pl/sql source code from a dba user
Venue: arXiv cs.DB 2012
Year: 2012

In this paper we are presenting a new way to disable DDL statements on some specific PL/SQL procedures to a dba user in the Oracle database. Nowadays dba users have access to a lot of data and source code even if they do not have legal permissions to see or modify them. With this method we can disable the ability to execute DDL and DML statements on some specific pl/sql procedures from every Oracle database user even if it has a dba role. Oracle gives to developer the possibility to wrap the pl/sql procedures, functions and packages but those wrapped scripts can be unwrapped by using third party tools. The scripts that we have developed analyzes all database sessions, and if they detect a DML or a DDL statement from an unauthorized user to procedure, function or package which should be protected then the execution of the statement is denied. Furthermore, these scripts do not allow a dba user to drop or disable the scripts themselves. In other words by managing sessions prior to the execution of an eventual statement from a dba user, we can prevent the execution of eventual statements which target our scripts.
Cultural Algorithm Toolkit for Multi-objective Rule Mining
Venue: arXiv cs.NE 2012
Year: 2012

Cultural algorithm is a kind of evolutionary algorithm inspired from societal evolution and is composed of a belief space, a population space and a protocol that enables exchange of knowledge between these sources. Knowledge created in the population space is accepted into the belief space while this collective knowledge from these sources is combined to influence the decisions of the individual agents in solving problems. Classification rules comes under descriptive knowledge discovery in data mining and are the most sought out by users since they represent highly comprehensible form of knowledge. The rules have certain properties which make them useful forms of actionable knowledge to users. The rules are evaluated using these properties namely the rule metrics. In the current study a Cultural Algorithm Toolkit for Classification Rule Mining (CAT-CRM) is proposed which allows the user to control three different set of parameters namely the evolutionary parameters, the rule parameters as well as agent parameters and hence can be used for experimenting with an evolutionary system, a rule mining system or an agent based social system. Results of experiments conducted to observe the effect of different number and type of metrics on the performance of the algorithm on bench mark data sets is reported.