OpenRaiser/Intern-Atlas huggingface dataset:
Product Evaluation In Elliptical Helical Pipe Bending
Venue: arXiv cs.CE 2014
Year: 2014

This research proposes a computation approach to address the evaluation of end product machining accuracy in elliptical surfaced helical pipe bending using 6dof parallel manipulator as a pipe bender. The target end product is wearable metal muscle supporters used in build-to-order welfare product manufacturing. This paper proposes a product testing model that mainly corrects the surface direction estimation errors of existing least squares ellipse fittings, followed by arc length and central angle evaluations. This post-machining modelling requires combination of reverse rotations and translations to a specific location before accuracy evaluation takes place, i.e. the reverse comparing to pre-machining product modelling. This specific location not only allows us to compute surface direction but also the amount of excessive surface twisting as a rotation angle about a specified axis, i.e. quantification of surface torsion. At first we experimented three ellipse fitting methods such as, two least-squares fitting methods with Bookstein constraint and Trace constraint, and one non- linear least squares method using Gauss-Newton algorithm. From fitting results, we found that using Trace constraint is more reliable and designed a correction filter for surface torsion observation. Finally we apply 2D total least squares line fitting method with a rectification filter for surface direction detection.
Network Sampling Based on NN Representatives
Venue: arXiv cs.SI 2014
Year: 2014

The amount of large-scale real data around us increase in size very quickly and so does the necessity to reduce its size by obtaining a representative sample. Such sample allows us to use a great variety of analytical methods, whose direct application on original data would be infeasible. There are many methods used for different purposes and with different results. In this paper we outline a simple and straightforward approach based on analyzing the nearest neighbors (NN) that is generally applicable. This feature is illustrated on experiments with weighted networks and vector data. The properties of the representative sample show that the presented approach maintains very well internal data structures (e.g. clusters and density). Key technical parameters of the approach is low complexity and high scalability. This allows the application of this approach to the area of big data.
Hierarchical organization versus self-organization
Venue: arXiv cs.MA 2014
Year: 2014

In this paper we try to define the difference between hierarchical organization and self-organization. Organization is defined as a structure with a function. So we can define the difference between hierarchical organization and self-organization both on the structure as on the function. In the next two chapters these two definitions are given. For the structure we will use some existing definitions in graph theory, for the function we will use existing theory on (self-)organization. In the third chapter we will look how these two definitions agree. Finally we give a conclusion.
A Hybrid Pricing Framework for TV White Space Database
Venue: arXiv cs.NI 2014
Year: 2014

According to the recent rulings of the Federal Communications Commission (FCC), TV white spaces (TVWS) can now be accessed by secondary users (SUs) after a list of vacant TV channels is obtained via a geo-location database. Proper business models are therefore essential for database operators to manage geo-location databases. Database access can be simultaneously priced under two different schemes: the registration scheme and the service plan scheme. In the registration scheme, the database reserves part of the TV bandwidth for registered White Space Devices (WSDs). In the service plan scheme, the WSDs are charged according to their queries. In this paper, we investigate the business model for the TVWS database under a hybrid pricing scheme. We consider the scenario where a database operator employs both the registration scheme and the service plan scheme to serve the SUs. The SUs' choices of different pricing schemes are modeled as a non-cooperative game and we derive distributed algorithms to achieve Nash Equilibrium (NE). Considering the NE of the SUs, the database operator optimally determines pricing parameters for both pricing schemes in terms of bandwidth reservation, registration fee and query plans.
On Subversive Miner Strategies and Block Withholding Attack in Bitcoin Digital Currency
Venue: arXiv cs.CR 2014
Year: 2014

Bitcoin is a "crypto currency", a decentralized electronic payment scheme based on cryptography. Bitcoin economy grows at an incredibly fast rate and is now worth some 10 billions of dollars. Bitcoin mining is an activity which consists of creating (minting) the new coins which are later put into circulation. Miners spend electricity on solving cryptographic puzzles and they are also gatekeepers which validate bitcoin transactions of other people. Miners are expected to be honest and have some incentives to behave well. However. In this paper we look at the miner strategies with particular attention paid to subversive and dishonest strategies or those which could put bitcoin and its reputation in danger. We study in details several recent attacks in which dishonest miners obtain a higher reward than their relative contribution to the network. In particular we revisit the concept of block withholding attacks and propose a new concrete and practical block withholding attack which we show to maximize the advantage gained by rogue miners. RECENT EVENTS: it seems that the attack was recently executed, see Section XI-A.
From the Information Bottleneck to the Privacy Funnel
Venue: arXiv cs.IT 2014
Year: 2014

We focus on the privacy-utility trade-off encountered by users who wish to disclose some information to an analyst, that is correlated with their private data, in the hope of receiving some utility. We rely on a general privacy statistical inference framework, under which data is transformed before it is disclosed, according to a probabilistic privacy mapping. We show that when the log-loss is introduced in this framework in both the privacy metric and the distortion metric, the privacy leakage and the utility constraint can be reduced to the mutual information between private data and disclosed data, and between non-private data and disclosed data respectively. We justify the relevance and generality of the privacy metric under the log-loss by proving that the inference threat under any bounded cost function can be upper-bounded by an explicit function of the mutual information between private data and disclosed data. We then show that the privacy-utility tradeoff under the log-loss can be cast as the non-convex Privacy Funnel optimization, and we leverage its connection to the Information Bottleneck, to provide a greedy algorithm that is locally optimal. We evaluate its performance on the US census dataset.
Reliable Link-Based Routing Protocol for Highly Dynamic Mobile Adhoc Networks
Venue: arXiv cs.NI 2014
Year: 2014

Traditional topology-based MANET routing protocols use stateful routing which increases the processing,communication and memory overheads. The high mobility of nodes in MANETs makes it difficult to maintain a deterministic route. To overcome this, stateless geographic routing protocols which ensure reliable data delivery have been proposed. It is found that link instability can be a major factor for unreliable data delivery. Driven by this issue, Link and Position based Opportunistic Routing (L-POR) protocol which chooses a forwarder based on the reception power of a node has been proposed. A back-up scheme is also proposed to handle communication holes. Simulation results show that the proposed protocol achieves excellent performance even under high node mobility.
Study of Cloud Computing in HealthCare Industry
Venue: arXiv cs.CY 2014
Year: 2014

In Todays real world technology has become a domiant crucial component in every industry including healthcare industry. The benefits of storing electronically the records of patients have increased the productivity of patient care and easy accessibility and usage. The recent technological innovations in the health care is the invention of cloud based Technology. But many fears and security measures regarding patient records storing remotely is a concern for many in health care industry. One needs to understand the benefits and fears of implementation of cloud computing its advantages and disadvantages of this new technology.
A Hybrid Loss for Multiclass and Structured Prediction
Venue: arXiv cs.LG 2014
Year: 2014

We propose a novel hybrid loss for multiclass and structured prediction problems that is a convex combination of a log loss for Conditional Random Fields (CRFs) and a multiclass hinge loss for Support Vector Machines (SVMs). We provide a sufficient condition for when the hybrid loss is Fisher consistent for classification. This condition depends on a measure of dominance between labels--specifically, the gap between the probabilities of the best label and the second best label. We also prove Fisher consistency is necessary for parametric consistency when learning models such as CRFs. We demonstrate empirically that the hybrid loss typically performs least as well as--and often better than--both of its constituent losses on a variety of tasks, such as human action recognition. In doing so we also provide an empirical comparison of the efficacy of probabilistic and margin based approaches to multiclass and structured prediction.
Integer Set Compression and Statistical Modeling
Venue: arXiv cs.IT 2014
Year: 2014

Compression of integer sets and sequences has been extensively studied for settings where elements follow a uniform probability distribution. In addition, methods exist that exploit clustering of elements in order to achieve higher compression performance. In this work, we address the case where enumeration of elements may be arbitrary or random, but where statistics is kept in order to estimate probabilities of elements. We present a recursive subset-size encoding method that is able to benefit from statistics, explore the effects of permuting the enumeration order based on element probabilities, and discuss general properties and possibilities for this class of compression problem.
No NAT'd User left Behind: Fingerprinting Users behind NAT from NetFlow Records alone
Venue: arXiv cs.CR 2014
Year: 2014

It is generally recognized that the traffic generated by an individual connected to a network acts as his biometric signature. Several tools exploit this fact to fingerprint and monitor users. Often, though, these tools assume to access the entire traffic, including IP addresses and payloads. This is not feasible on the grounds that both performance and privacy would be negatively affected. In reality, most ISPs convert user traffic into NetFlow records for a concise representation that does not include, for instance, any payloads. More importantly, large and distributed networks are usually NAT'd, thus a few IP addresses may be associated to thousands of users. We devised a new fingerprinting framework that overcomes these hurdles. Our system is able to analyze a huge amount of network traffic represented as NetFlows, with the intent to track people. It does so by accurately inferring when users are connected to the network and which IP addresses they are using, even though thousands of users are hidden behind NAT. Our prototype implementation was deployed and tested within an existing large metropolitan WiFi network serving about 200,000 users, with an average load of more than 1,000 users simultaneously connected behind 2 NAT'd IP addresses only. Our solution turned out to be very effective, with an accuracy greater than 90%. We also devised new tools and refined existing ones that may be applied to other contexts related to NetFlow analysis.
Classification Tree Diagrams in Health Informatics Applications
Venue: arXiv cs.IR 2014
Year: 2014

Health informatics deal with the methods used to optimize the acquisition, storage and retrieval of medical data, and classify information in healthcare applications. Healthcare analysts are particularly interested in various computer informatics areas such as; knowledge representation from data, anomaly detection, outbreak detection methods and syndromic surveillance applications. Although various parametric and non-parametric approaches are being proposed to classify information from data, classification tree diagrams provide an interactive visualization to analysts as compared to other methods. In this work we discuss application of classification tree diagrams to classify information from medical data in healthcare applications.
A Novel Approach to Detect Spam Worms Propagation with Monitoring the Footprinting
Venue: arXiv cs.NI 2014
Year: 2014

One of the key security threats on the Internet are the compromised machines that can be used to launch various security attacks such as spamming and spreading malware, accessing useful information and DDoS. Attackers for spamming activity are volunteer by large number of compromised machines. Our main focus is on detection of the compromised machines in a network that may be or are involved in the spamming activities; these machines are commonly known as spam zombies. Activities such as port scan, DB scan and so on are treated as malicious activity within the network. So to overcome that we develop one of the most effective spam zombie detection system within the network based on the behavior of other systems as if performing the above activities are treated as zombies machines. If any system within the network try's to gather some information about any other system then this is treated as a malicious activity and should be not allowed to do so. SYN packets are used in order to initiate communication within the network so as to establish connection. If any system try's to flood the network with these packets we can make an assumption that the system is trying to gather the information about other system. This is what called footprinting. So we will try to detect any system involved in footprinting and report to the administrator.
A System for Deduction-based Formal Verification of Workflow-oriented Software Models
Venue: arXiv cs.SE 2014
Year: 2014

The work concerns formal verification of workflow-oriented software models using deductive approach. The formal correctness of a model's behaviour is considered. Manually building logical specifications, which are considered as a set of temporal logic formulas, seems to be the significant obstacle for an inexperienced user when applying the deductive approach. A system, and its architecture, for the deduction-based verification of workflow-oriented models is proposed. The process of inference is based on the semantic tableaux method which has some advantages when compared to traditional deduction strategies. The algorithm for an automatic generation of logical specifications is proposed. The generation procedure is based on the predefined workflow patterns for BPMN, which is a standard and dominant notation for the modeling of business processes. The main idea for the approach is to consider patterns, defined in terms of temporal logic,as a kind of (logical) primitives which enable the transformation of models to temporal logic formulas constituting a logical specification. Automation of the generation process is crucial for bridging the gap between intuitiveness of the deductive reasoning and the difficulty of its practical application in the case when logical specifications are built manually. This approach has gone some way towards supporting, hopefully enhancing our understanding of, the deduction-based formal verification of workflow-oriented models.
Locality and Availability in Distributed Storage
Venue: arXiv cs.IT 2014
Year: 2014

This paper studies the problem of code symbol availability: a code symbol is said to have $(r, t)$-availability if it can be reconstructed from $t$ disjoint groups of other symbols, each of size at most $r$. For example, $3$-replication supports $(1, 2)$-availability as each symbol can be read from its $t= 2$ other (disjoint) replicas, i.e., $r=1$. However, the rate of replication must vanish like $\frac{1}{t+1}$ as the availability increases. This paper shows that it is possible to construct codes that can support a scaling number of parallel reads while keeping the rate to be an arbitrarily high constant. It further shows that this is possible with the minimum distance arbitrarily close to the Singleton bound. This paper also presents a bound demonstrating a trade-off between minimum distance, availability and locality. Our codes match the aforementioned bound and their construction relies on combinatorial objects called resolvable designs. From a practical standpoint, our codes seem useful for distributed storage applications involving hot data, i.e., the information which is frequently accessed by multiple processes in parallel.
Foreground segmentation based on multi-resolution and matting
Venue: arXiv cs.CV 2014
Year: 2014

We propose a foreground segmentation algorithm that does foreground extraction under different scales and refines the result by matting. First, the input image is filtered and resampled to 5 different resolutions. Then each of them is segmented by adaptive figure-ground classification and the best segmentation is automatically selected by an evaluation score that maximizes the difference between foreground and background. This segmentation is upsampled to the original size, and a corresponding trimap is built. Closed-form matting is employed to label the boundary region, and the result is refined by a final figure-ground classification. Experiments show the success of our method in treating challenging images with cluttered background and adapting to loose initial bounding-box.
Reduction of Maximum Flow Network Interdiction Problem from The Clique Problem
Venue: arXiv cs.DS 2014
Year: 2014

Maximum Flow Network Interdiction Problem (MFNIP) is known to be strongly NP-hard problem. We solve a simple form of MFNIP in polynomial time. We review the reduction of MFNIP from the clique problem. We propose a polynomial time solution to the Clique Problem.
Longest Common Subsequence in k-length substrings
Venue: arXiv cs.DS 2014
Year: 2014

In this paper we define a new problem, motivated by computational biology, $LCSk$ aiming at finding the maximal number of $k$ length $substrings$, matching in both input strings while preserving their order of appearance. The traditional LCS definition is a special case of our problem, where $k = 1$. We provide an algorithm, solving the general case in $O(n^2)$ time, where $n$ is the length of the input strings, equaling the time required for the special case of $k=1$. The space requirement of the algorithm is $O(kn)$. %, however, in order to enable %backtracking of the solution, $O(n^2)$ space is needed. We also define a complementary $EDk$ distance measure and show that $EDk(A,B)$ can be computed in $O(nm)$ time and $O(km)$ space, where $m$, $n$ are the lengths of the input sequences $A$ and $B$ respectively.
In-network Aggregation using Efficient Routing Techniques for Event Driven Sensor Network
Venue: arXiv cs.NI 2014
Year: 2014

Sensors used in applications such as agriculture, weather, etc., monitoring physical parameters like soil moisture, temperature, humidity, will have to sustain their battery power for long intervals of time. In order to accomplish this, parameter which assists in reducing the consumption of power from battery need to be attended to. One of the factors affecting the consumption of energy is transmit and receive power. This energy consumption can be reduced by avoiding unnecessary transmission and reception. Efficient routing techniques and incorporating aggregation whenever possible can save considerable amount of energy. Aggregation reduces repeated transmission of relative values and also reduces lot of computation at the base station. In this paper, the benefits of aggregation over direct transmission in saving the amount of energy consumed is discussed. Routing techniques which assist aggregation are incorporated. Aspects like transmission of average value of sensed data around an area of the network, minimum value in the whole of the network, triggering of event when there is low battery are assimilated.
Structural Refinement for the Modal nu-Calculus
Venue: arXiv cs.LO 2014
Year: 2014

We introduce a new notion of structural refinement, a sound abstraction of logical implication, for the modal nu-calculus. Using new translations between the modal nu-calculus and disjunctive modal transition systems, we show that these two specification formalisms are structurally equivalent. Using our translations, we also transfer the structural operations of composition and quotient from disjunctive modal transition systems to the modal nu-calculus. This shows that the modal nu-calculus supports composition and decomposition of specifications.
Using content features to enhance performance of user-based collaborative filtering performance of user-based collaborative filtering
Venue: arXiv cs.IR 2014
Year: 2014

Content-based and collaborative filtering methods are the most successful solutions in recommender systems. Content based method is based on items attributes. This method checks the features of users favourite items and then proposes the items which have the most similar characteristics with those items. Collaborative filtering method is based on the determination of similar items or similar users, which are called item-based and user-based collaborative filtering, respectively.In this paper we propose a hybrid method that integrates collaborative filtering and content-based methods. The proposed method can be viewed as user-based Collaborative filtering technique. However to find users with similar taste with active user, we used content features of the item under investigation to put more emphasis on users rating for similar items. In other words two users are similar if their ratings are similar on items that have similar context. This is achieved by assigning a weight to each rating when calculating the similarity of two users.We used movielens data set to access the performance of the proposed method in comparison with basic user-based collaborative filtering and other popular methods.
A Characterization of Locally Testable Affine-Invariant Properties via Decomposition Theorems
Venue: arXiv cs.CC 2014
Year: 2014

Let $\mathcal{P}$ be a property of function $\mathbb{F}_p^n \to \{0,1\}$ for a fixed prime $p$. An algorithm is called a tester for $\mathcal{P}$ if, given a query access to the input function $f$, with high probability, it accepts when $f$ satisfies $\mathcal{P}$ and rejects when $f$ is "far" from satisfying $\mathcal{P}$. In this paper, we give a characterization of affine-invariant properties that are (two-sided error) testable with a constant number of queries. The characterization is stated in terms of decomposition theorems, which roughly claim that any function can be decomposed into a structured part that is a function of a constant number of polynomials, and a pseudo-random part whose Gowers norm is small. We first give an algorithm that tests whether the structured part of the input function has a specific form. Then we show that an affine-invariant property is testable with a constant number of queries if and only if it can be reduced to the problem of testing whether the structured part of the input function is close to one of a constant number of candidates.