OpenRaiser/Intern-Atlas huggingface dataset:
Design and Optimizing of On-Chip Kinesin Substrates for Molecular Communication
Venue: arXiv cs.IT 2015
Year: 2015

Lab-on-chip devices and point-of-care diagnostic chip devices are composed of many different components such as nanosensors that must be able to communicate with other components within the device. Molecular communication is a promising solution for on-chip communication. In particular, kinesin driven microtubule (MT) motility is an effective means of transferring information particles from one component to another. However, finding an optimal shape for these channels can be challenging. In this paper we derive a mathematical optimization model that can be used to find the optimal channel shape and dimensions for any transmission period. We derive three specific models for the rectangular channels, regular polygonal channels, and regular polygonal ring channels. We show that the optimal channel shapes are the square-shaped channel for the rectangular channel, and circular-shaped channel for the other classes of shapes. Finally, we show that among all 2 dimensional shapes the optimal design choice that maximizes information rate is the circular-shaped channel.
TPAD: Hardware Trojan Prevention and Detection for Trusted Integrated Circuits
Venue: arXiv cs.AR 2015
Year: 2015

There are increasing concerns about possible malicious modifications of integrated circuits (ICs) used in critical applications. Such attacks are often referred to as hardware Trojans. While many techniques focus on hardware Trojan detection during IC testing, it is still possible for attacks to go undetected. Using a combination of new design techniques and new memory technologies, we present a new approach that detects a wide variety of hardware Trojans during IC testing and also during system operation in the field. Our approach can also prevent a wide variety of attacks during synthesis, place-and-route, and fabrication of ICs. It can be applied to any digital system, and can be tuned for both traditional and split-manufacturing methods. We demonstrate its applicability for both ASICs and FPGAs. Using fabricated test chips with Trojan emulation capabilities and also using simulations, we demonstrate: 1. The area and power costs of our approach can range between 7.4-165% and 0.07-60%, respectively, depending on the design and the attacks targeted; 2. The speed impact can be minimal (close to 0%); 3. Our approach can detect 99.998% of Trojans (emulated using test chips) that do not require detailed knowledge of the design being attacked; 4. Our approach can prevent 99.98% of specific attacks (simulated) that utilize detailed knowledge of the design being attacked (e.g., through reverse-engineering). 5. Our approach never produces any false positives, i.e., it does not report attacks when the IC operates correctly.
Observability of Lattice Graphs
Venue: arXiv cs.DM 2015
Year: 2015

We consider a graph observability problem: how many edge colors are needed for an unlabeled graph so that an agent, walking from node to node, can uniquely determine its location from just the observed color sequence of the walk? Specifically, let G(n,d) be an edge-colored subgraph of d-dimensional (directed or undirected) lattice of size n^d = n * n * ... * n. We say that G(n,d) is t-observable if an agent can uniquely determine its current position in the graph from the color sequence of any t-dimensional walk, where the dimension is the number of different directions spanned by the edges of the walk. A walk in an undirected lattice G(n,d) has dimension between 1 and d, but a directed walk can have dimension between 1 and 2d because of two different orientations for each axis. We derive bounds on the number of colors needed for t-observability. Our main result is that Theta(n^(d/t)) colors are both necessary and sufficient for t-observability of G(n,d), where d is considered a constant. This shows an interesting dependence of graph observability on the ratio between the dimension of the lattice and that of the walk. In particular, the number of colors for full-dimensional walks is Theta(n^(1/2)) in the directed case, and Theta(n) in the undirected case, independent of the lattice dimension. All of our results extend easily to non-square lattices: given a lattice graph of size N = n_1 * n_2 * ... * n_d, the number of colors for t-observability is Theta (N^(1/t)).
Subset Feature Learning for Fine-Grained Category Classification
Venue: arXiv cs.CV 2015
Year: 2015

Fine-grained categorisation has been a challenging problem due to small inter-class variation, large intra-class variation and low number of training images. We propose a learning system which first clusters visually similar classes and then learns deep convolutional neural network features specific to each subset. Experiments on the popular fine-grained Caltech-UCSD bird dataset show that the proposed method outperforms recent fine-grained categorisation methods under the most difficult setting: no bounding boxes are presented at test time. It achieves a mean accuracy of 77.5%, compared to the previous best performance of 73.2%. We also show that progressive transfer learning allows us to first learn domain-generic features (for bird classification) which can then be adapted to specific set of bird classes, yielding improvements in accuracy.
Should we really use post-hoc tests based on mean-ranks?
Venue: arXiv cs.LG 2015
Year: 2015

The statistical comparison of multiple algorithms over multiple data sets is fundamental in machine learning. This is typically carried out by the Friedman test. When the Friedman test rejects the null hypothesis, multiple comparisons are carried out to establish which are the significant differences among algorithms. The multiple comparisons are usually performed using the mean-ranks test. The aim of this technical note is to discuss the inconsistencies of the mean-ranks post-hoc test with the goal of discouraging its use in machine learning as well as in medicine, psychology, etc.. We show that the outcome of the mean-ranks test depends on the pool of algorithms originally included in the experiment. In other words, the outcome of the comparison between algorithms A and B depends also on the performance of the other algorithms included in the original experiment. This can lead to paradoxical situations. For instance the difference between A and B could be declared significant if the pool comprises algorithms C, D, E and not significant if the pool comprises algorithms F, G, H. To overcome these issues, we suggest instead to perform the multiple comparison using a test whose outcome only depends on the two algorithms being compared, such as the sign-test or the Wilcoxon signed-rank test.
Parameters for minimal unsatisfiability: Smarandache primitive numbers and full clauses
Venue: arXiv cs.DM 2015
Year: 2015

We establish a new bridge between propositional logic and elementary number theory. The main objects are "minimally unsatisfiable clause-sets", short "MUs", unsatisfiable conjunctive normal forms rendered satisfiable by elimination of any clause. In other words, irredundant coverings of the boolean hypercube by subcubes. The main parameter for MUs is the "deficiency" k, the difference between the number of clauses and the number of variables (the difference between the number of elements in the covering and the dimension of the hypercube), and the fundamental fact is that k >= 1 holds. A "full clause" in an MU contains all variables (corresponding to a singleton in the covering). We show the lower bound S_2(k) <= FCM(k), where FCM(k) is the maximal number of full clauses in MUs of deficiency k, while S_2(k) is the smallest n such that 2^k divides n!. The proof rests on two methods: On the logic-combinatorial side, applying subsumption resolution and its inverse, a fundamental method since Boole in 1854 introduced the "expansion method". On the arithmetical side, analysing certain recursions, combining an application-specific recursion with a recursion from the field of meta-Fibonacci sequences (indeed S_2 equals twice the Conolly sequence). A further tool is the consideration of unsatisfiable "hitting clause-sets" (UHITs), special cases of MUs, which correspond to the partitions of the boolean hypercube by subcubes; they are also known as orthogonal or disjoint DNF tautologies. We actually show the sharper lower bound S_2(k) <= FCH(k), where FCH(k) is the maximal number of full clauses in UHITs of deficiency k. We conjecture that for all k holds S_2(k) = FCH(k), which would establish a surprising connection between the extremal combinatorics of (un)satisfiability and elementary number theory. We apply the lower bound to analyse the structure of MUs and UHITs.
Simultaneous Clustering and Model Selection for Multinomial Distribution: A Comparative Study
Venue: arXiv cs.LG 2015
Year: 2015

In this paper, we study different discrete data clustering methods, which use the Model-Based Clustering (MBC) framework with the Multinomial distribution. Our study comprises several relevant issues, such as initialization, model estimation and model selection. Additionally, we propose a novel MBC method by efficiently combining the partitional and hierarchical clustering techniques. We conduct experiments on both synthetic and real data and evaluate the methods using accuracy, stability and computation time. Our study identifies appropriate strategies to be used for discrete data analysis with the MBC methods. Moreover, our proposed method is very competitive w.r.t. clustering accuracy and better w.r.t. stability and computation time.
Active Search with a Cost for Switching Actions
Venue: arXiv cs.IT 2015
Year: 2015

Active Sequential Hypothesis Testing (ASHT) is an extension of the classical sequential hypothesis testing problem with controls. Chernoff (Ann. Math. Statist., 1959) proposed a policy called Procedure A and showed its asymptotic optimality as the cost of sampling was driven to zero. In this paper we study a further extension where we introduce costs for switching of actions. We show that a modification of Chernoff's Procedure A, one that we call Sluggish Procedure A, is asymptotically optimal even with switching costs. The growth rate of the total cost, as the probability of false detection is driven to zero, and as a switching parameter of the Sluggish Procedure A is driven down to zero, is the same as that without switching costs.
Network Filtering for Big Data: Triangulated Maximally Filtered Graph
Venue: arXiv cs.DS 2015
Year: 2015

We propose a network-filtering method, the Triangulated Maximally Filtered Graph (TMFG), that provides an approximate solution to the Weighted Maximal Planar Graph problem. The underlying idea of TMFG consists in building a triangulation that maximizes a score function associated with the amount of information retained by the network. TMFG uses as weights any arbitrary similarity measure to arrange data into a meaningful network structure that can be used for clustering, community detection and modeling. The method is fast, adaptable and scalable to very large datasets, it allows online updating and learning as new data can be inserted and deleted with combinations of local and non-local moves. TMFG permits readjustments of the network in consequence of changes in the strength of the similarity measure. The method is based on local topological moves and can therefore take advantage of parallel and GPUs computing. We discuss how this network-filtering method can be used intuitively and efficiently for big data studies and its significance from an information-theoretic perspective.
An alternative proof for the constructive Asymmetric Lovász Local Lemma
Venue: arXiv cs.DM 2015
Year: 2015

We provide an alternative constructive proof of the Asymmetric Lovász Local Lemma. Our proof uses the classic algorithmic framework of Moser and the analysis introduced by Giotis, Kirousis, Psaromiligkos, and Thilikos in "On the algorithmic Lovász Local Lemma and acyclic edge coloring", combined with the work of Bender and Richmond on the multivariable Lagrange Inversion formula.
Probabilistic existence results for separable codes
Venue: arXiv cs.IT 2015
Year: 2015

Separable codes were defined by Cheng and Miao in 2011, motivated by applications to the identification of pirates in a multimedia setting. Combinatorially, $\overline{t}$-separable codes lie somewhere between $t$-frameproof and $(t-1)$-frameproof codes: all $t$-frameproof codes are $\overline{t}$-separable, and all $\overline{t}$-separable codes are $(t-1)$-frameproof. Results for frameproof codes show that (when $q$ is large) there are $q$-ary $\overline{t}$-separable codes of length $n$ with approximately $q^{\lceil n/t\rceil}$ codewords, and that no $q$-ary $\overline{t}$-separable codes of length $n$ can have more than approximately $q^{\lceil n/(t-1)\rceil}$ codewords. The paper provides improved probabilistic existence results for $\overline{t}$-separable codes when $t\geq 3$. More precisely, for all $t\geq 3$ and all $n\geq 3$, there exists a constant $κ$ (depending only on $t$ and $n$) such that there exists a $q$-ary $\overline{t}$-separable code of length $n$ with at least $κq^{n/(t-1)}$ codewords for all sufficiently large integers $q$. This shows, in particular, that the upper bound (derived from the bound on $(t-1)$-frameproof codes) on the number of codewords in a $\overline{t}$-separable code is realistic. The results above are more surprising after examining the situation when $t=2$. Results due to Gao and Ge show that a $q$-ary $\overline{2}$-separable code of length $n$ can contain at most $\frac{3}{2}q^{2\lceil n/3\rceil}-\frac{1}{2}q^{\lceil n/3\rceil}$ codewords, and that codes with at least $κq^{2n/3}$ codewords exist. So optimal $\overline{2}$-separable codes behave neither like $2$-frameproof nor $1$-frameproof codes. Also, the Gao--Ge bound is strengthened to show that a $q$-ary $\overline{2}$-separable code of length $n$ can have at most \[ q^{\lceil 2n/3\rceil}+\tfrac{1}{2}q^{\lfloor n/3\rfloor}(q^{\lfloor n/3\rfloor}-1) \] codewords.
Features of transformation of marketing in e-commerce
Venue: arXiv cs.CY 2015
Year: 2015

Article about influence of e-commerce on transformation of the theory and practice of marketing. The author considers Internet-marketing as the independent form of marketing formed under the general laws in new institutional conditions.
On the Role of Transmit Correlation Diversity in Multiuser MIMO Systems
Venue: arXiv cs.IT 2015
Year: 2015

Correlation across transmit antennas, in multiple antenna systems (MIMO), has been studied in various scenarios and has been shown to be detrimental or provide benefits depending on the particular system and underlying assumptions. In this paper, we investigate the effect of transmit correlation on the capacity of the Gaussian MIMO broadcast channel (BC), with a particular interest in the large-scale array (or massive MIMO) regime. To this end, we introduce a new type of diversity, referred to as transmit correlation diversity, which captures the fact that the channel vectors of different users may have different, and often nearly mutually orthogonal, large-scale channel eigen-directions. In particular, when taking the cost of downlink training properly into account, transmit correlation diversity can yield significant capacity gains in all regimes of interest. Our analysis shows that the system multiplexing gain can be increased by a factor up to $\lfloor{M}/{r}\rfloor$, where $M$ is the number of antennas and $r\le M$ is the common rank of the users transmit correlation matrices, with respect to standard schemes that are agnostic of the transmit correlation and treat the channels as if they were isotropically distributed. Thus, this new form of diversity reveals itself as a valuable "new resource" in multiuser communications.
Automatic Script Identification in the Wild
Venue: arXiv cs.CV 2015
Year: 2015

With the rapid increase of transnational communication and cooperation, people frequently encounter multilingual scenarios in various situations. In this paper, we are concerned with a relatively new problem: script identification at word or line levels in natural scenes. A large-scale dataset with a great quantity of natural images and 10 types of widely used languages is constructed and released. In allusion to the challenges in script identification in real-world scenarios, a deep learning based algorithm is proposed. The experiments on the proposed dataset demonstrate that our algorithm achieves superior performance, compared with conventional image classification methods, such as the original CNN architecture and LLC.
Power, Energy and Speed of Embedded and Server Multi-Cores applied to Distributed Simulation of Spiking Neural Networks: ARM in NVIDIA Tegra vs Intel Xeon quad-cores
Venue: arXiv cs.DC 2015
Year: 2015

This short note regards a comparison of instantaneous power, total energy consumption, execution time and energetic cost per synaptic event of a spiking neural network simulator (DPSNN-STDP) distributed on MPI processes when executed either on an embedded platform (based on a dual socket quad-core ARM platform) or a server platform (INTEL-based quad-core dual socket platform). We also compare the measure with those reported by leading custom and semi-custom designs: TrueNorth and SpiNNaker. In summary, we observed that: 1- we spent 2.2 micro-Joule per simulated event on the "embedded platform", approx. 4.4 times lower than what was spent by the "server platform"; 2- the instantaneous power consumption of the "embedded platform" was 14.4 times better than the "server" one; 3- the server platform is a factor 3.3 faster. The "embedded platform" is made of NVIDIA Jetson TK1 boards, interconnected by Ethernet, each mounting a Tegra K1 chip including a quad-core ARM Cortex-A15 at 2.3GHz. The "server platform" is based on dual-socket quad-core Intel Xeon CPUs (E5620 at 2.4GHz). The measures were obtained with the DPSNN-STDP simulator (Distributed Simulator of Polychronous Spiking Neural Network with synaptic Spike Timing Dependent Plasticity) developed by INFN, that already proved its efficient scalability and execution speed-up on hundreds of similar "server" cores and MPI processes, applied to neural nets composed of several billions of synapses.
Knowledge workers collaborative learning behavior modeling in an organizational social network
Venue: arXiv cs.CY 2015
Year: 2015

Computations related to learning processes within an organizational social network area require some network model preparation and specific algorithms in order to implement human behaviors in simulated environments. The proposals in this research model of collaborative learning in an organizational social network are based on knowledge resource distribution through the establishment of a knowledge flow. The nodes, which represent knowledge workers, contain information about workers social and cognitive abilities. Moreover, the workers are described by their set of competences, their skill level, and the collaborative learning behavior that can be detected through knowledge flow analysis. The proposed approach assumes that an increase in workers competence is a result of collaborative learning. In other words, collaborative learning can be analyzed as a process of knowledge flow that is being broadcast in a network. In order to create a more effective organizational social network for co-learning, the authors found the best strategies for knowledge facilitator, knowledge collector, and expert roles allocation. Special attention is paid to the process of knowledge flow in the community of practice. Acceleration within the community of practice happens when knowledge flows more effectively between community members. The presented procedure makes it possible to add new ties to the community of practice in order to influence community members competences. Both the proposed allocation and acceleration approaches were confirmed through simulations.
Hybrid data clustering approach using K-Means and Flower Pollination Algorithm
Venue: arXiv cs.LG 2015
Year: 2015

Data clustering is a technique for clustering set of objects into known number of groups. Several approaches are widely applied to data clustering so that objects within the clusters are similar and objects in different clusters are far away from each other. K-Means, is one of the familiar center based clustering algorithms since implementation is very easy and fast convergence. However, K-Means algorithm suffers from initialization, hence trapped in local optima. Flower Pollination Algorithm (FPA) is the global optimization technique, which avoids trapping in local optimum solution. In this paper, a novel hybrid data clustering approach using Flower Pollination Algorithm and K-Means (FPAKM) is proposed. The proposed algorithm results are compared with K-Means and FPA on eight datasets. From the experimental results, FPAKM is better than FPA and K-Means.
Feature selection using Fisher's ratio technique for automatic speech recognition
Venue: arXiv cs.CL 2015
Year: 2015

Automatic Speech Recognition involves mainly two steps; feature extraction and classification . Mel Frequency Cepstral Coefficient is used as one of the prominent feature extraction techniques in ASR. Usually, the set of all 12 MFCC coefficients is used as the feature vector in the classification step. But the question is whether the same or improved classification accuracy can be achieved by using a subset of 12 MFCC as feature vector. In this paper, Fisher's ratio technique is used for selecting a subset of 12 MFCC coefficients that contribute more in discriminating a pattern. The selected coefficients are used in classification with Hidden Markov Model algorithm. The classification accuracies that we get by using 12 coefficients and by using the selected coefficients are compared.
A Comparative Study of Homomorphic and Searchable Encryption Schemes for Cloud Computing
Venue: arXiv cs.CR 2015
Year: 2015

Cloud computing is a popular distributed network and utility model based technology. Since in cloud the data is outsourced to third parties, the protection of confidentiality and privacy of user data becomes important. Different methods for securing the data in cloud have been proposed by researchers including but not limited to Oblivious RAM, Searchable Encryption, Functional Encryption, Homomorphic Encryption etc. This paper focuses on Searchable and Homomorphic Encryption methods. Finally, a comparative study of these two efficient cloud cryptographic methods has been carried out and given here.
Innovative forms of sales in the e-commerce
Venue: arXiv cs.CY 2015
Year: 2015

Article about transformation of methods of remote sales in the conditions of e-commerce. The author classifies and analyzes features of new methods of electronic sales in the virtual environment.