OpenRaiser/Intern-Atlas huggingface dataset:
VLSI Extreme Learning Machine: A Design Space Exploration
Venue: arXiv cs.LG 2016
Year: 2016

In this paper, we describe a compact low-power, high performance hardware implementation of the extreme learning machine (ELM) for machine learning applications. Mismatch in current mirrors are used to perform the vector-matrix multiplication that forms the first stage of this classifier and is the most computationally intensive. Both regression and classification (on UCI data sets) are demonstrated and a design space trade-off between speed, power and accuracy is explored. Our results indicate that for a wide set of problems, $σV_T$ in the range of $15-25$mV gives optimal results. An input weight matrix rotation method to extend the input dimension and hidden layer size beyond the physical limits imposed by the chip is also described. This allows us to overcome a major limit imposed on most hardware machine learners. The chip is implemented in a $0.35 μ$m CMOS process and occupies a die area of around 5 mm $\times$ 5 mm. Operating from a $1$ V power supply, it achieves an energy efficiency of $0.47$ pJ/MAC at a classification rate of $31.6$ kHz.
Fast Detection of Orthogonal Space-Time Block Codes with Unknown Channel
Venue: arXiv cs.IT 2016
Year: 2016

This letter investigates the problem of blind detection of orthogonal space-time block codes (OSTBC) over a quasi-static flat multiple-input multiple-output (MIMO) Rayleigh fading channel. We first introduce a core iterative least-squares (ILS) algorithm to blindly detect OSTBC signals without the knowledge of channel state information (SCI) at the receiver. This ILS algorithm has low computational complexity but may converge to local optimum which offers unreliable detection result. Then, in order to improve the detection performance, we propose an enhanced ILS (E-ILS) approach which is based on statistical analysis of repeated independent ILS procedures on received data. Extensive simulation studies prove the efficiency of the proposed E-ILS algorithm with blind detection performance approaching the optimal maximum-likelihood detector with known CSI.
Enhancement in the effectiveness of requirement change management model for global software development
Venue: arXiv cs.SE 2016
Year: 2016

The need for change in project requirements is necessary for every organization due to change in technology,change in government policy,and change of customer or stakeholders requirements.Requirement Change Management RCM is not an easy task,especially in Global Software Development GSD where team members are globally distributed in different geographical location and a cultural difference is present between team members. So it becomes more difficult to manage these changes. There are a number of risks that are faced during requirement change management in global software development process. The aim of this research is to discuss these issues,tools and techniques that are being used to reduce the effectiveness of these issues in requirement change management. On the basis of these methods,propose a new model that will enhance the effectiveness of requirement change management process.
Diagonal Unloading Beamforming for Source Localization
Venue: arXiv cs.SD 2016
Year: 2016

In sensor array beamforming methods, a class of algorithms commonly used to estimate the position of a radiating source, the diagonal loading of the beamformer covariance matrix is generally used to improve computational accuracy and localization robustness. This paper proposes a diagonal unloading (DU) method which extends the conventional response power beamforming method by imposing an additional constraint to the covariance matrix of the array output vector. The regularization is obtained by subtracting a given amount of white noise from the main diagonal of the covariance matrix. Specifically, the DU beamformer aims at subtracting the signal subspace from the noisy signal space and it is computed by constraining the regularized covariance matrix to be negative definite. It is hence a data-dependent covariance matrix conditioning method. We show how to calculate precisely the unloading parameter, and we present an eigenvalue analysis for comparing the proposed DU beamforming, the minimum variance distortionless response (MVDR) filter and the multiple signal classification (MUSIC) method. Theoretical analysis and experiments with acoustic sources demonstrate that the DU beamformer localization performance is comparable to that of MVDR and MUSIC. Since the DU beamformer computational cost is comparable to that of a conventional beamformer, the proposed method can be attractive in array processing due to its simplicity, effectiveness and computational efficiency.
Improving Image Captioning by Concept-based Sentence Reranking
Venue: arXiv cs.CV 2016
Year: 2016

This paper describes our winning entry in the ImageCLEF 2015 image sentence generation task. We improve Google's CNN-LSTM model by introducing concept-based sentence reranking, a data-driven approach which exploits the large amounts of concept-level annotations on Flickr. Different from previous usage of concept detection that is tailored to specific image captioning models, the propose approach reranks predicted sentences in terms of their matches with detected concepts, essentially treating the underlying model as a black box. This property makes the approach applicable to a number of existing solutions. We also experiment with fine tuning on the deep language model, which improves the performance further. Scoring METEOR of 0.1875 on the ImageCLEF 2015 test set, our system outperforms the runner-up (METEOR of 0.1687) with a clear margin.
QoS Web Service Security Dynamic Intruder Detection System for HTTP SSL services
Venue: arXiv cs.CR 2016
Year: 2016

Web services are expected to play significant role for message communications over internet applications. Most of the future work is web security. Online shopping and web services are increasing at rapid rate. In this paper we presented the fundamental concepts related to Network security, web security threats. QoS web service security intrusion detection is important concern in network communications and firewalls security; we discussed various issues and challenges related to web security. The fundamental concepts network security XML firewall, XML networks. We proposed a novel Dynamic Intruder Detection System (DIDA) is safe guard against SSL secured transactions over message communications in intermediate routers that enable services to sender and receiver use Secured Session Layer protocol messages. This can be into three stages 1. Sensor 2. Analyzer and 3.User Interface.
Bloom Filters and Compact Hash Codes for Efficient and Distributed Image Retrieval
Venue: arXiv cs.MM 2016
Year: 2016

This paper presents a novel method for efficient image retrieval, based on a simple and effective hashing of CNN features and the use of an indexing structure based on Bloom filters. These filters are used as gatekeepers for the database of image features, allowing to avoid to perform a query if the query features are not stored in the database and speeding up the query process, without affecting retrieval performance. Thanks to the limited memory requirements the system is suitable for mobile applications and distributed databases, associating each filter to a distributed portion of the database. Experimental validation has been performed on three standard image retrieval datasets, outperforming state-of-the-art hashing methods in terms of precision, while the proposed indexing method obtains a $2\times$ speedup.
Does disaggregated electricity feedback reduce domestic electricity consumption? A systematic review of the literature
Venue: arXiv cs.CY 2016
Year: 2016

We examine 12 studies on the efficacy of disaggregated energy feedback. The average electricity reduction across these studies is 4.5%. However, 4.5% may be a positively-biased estimate of the savings achievable across the entire population because all 12 studies are likely to be prone to opt-in bias hence none test the effect of disaggregated feedback on the general population. Disaggregation may not be required to achieve these savings: Aggregate feedback alone drives 3% reductions; and the 4 studies which directly compared aggregate feedback against disaggregated feedback found that aggregate feedback is at least as effective as disaggregated feedback, possibly because web apps are viewed less often than in-home-displays (in the short-term, at least) and because some users do not trust fine-grained disaggregation (although this may be an issue with the specific user interface studied). Disaggregated electricity feedback may help a motivated sub-group of the population to save more energy but fine-grained disaggregation may not be necessary to achieve these energy savings. Disaggregation has many uses beyond those discussed in this paper but, on the specific question of promoting energy reduction in the general population, there is no robust evidence that current forms of disaggregated energy feedback are more effective than aggregate energy feedback. The effectiveness of disaggregated feedback may increase if the general population become more energy-conscious (e.g. if energy prices rise or concern about climate change deepens); or if users' trust in fine-grained disaggregation improves; or if innovative new approaches or alternative disaggregation strategies (e.g. disaggregating by behaviour rather than by appliance) out-perform existing feedback. We also discuss opportunities for new research into the effectiveness of disaggregated feedback.
Phase 2: DCL System Using Deep Learning Approaches for Land-based or Ship-based Real-Time Recognition and Localization of Marine Mammals - Machine Learning Detection Algorithms
Venue: arXiv cs.CV 2016
Year: 2016

Overarching goals for this work aim to advance the state of the art for detection, classification and localization (DCL) in the field of bioacoustics. This goal is primarily achieved by building a generic framework for detection-classification (DC) using a fast, efficient and scalable architecture, demonstrating the capabilities of this system using on a variety of low-frequency mid-frequency cetacean sounds. Two primary goals are to develop transferable technologies for detection and classification in, one: the area of advanced algorithms, such as deep learning and other methods; and two: advanced systems, capable of real-time and archival processing. For each key area, we will focus on producing publications from this work and providing tools and software to the community where/when possible. Currently massive amounts of acoustic data are being collected by various institutions, corporations and national defense agencies. The long-term goal is to provide technical capability to analyze the data using automatic algorithms for (DC) based on machine intelligence. The goal of the automation is to provide effective and efficient mechanisms by which to process large acoustic datasets for understanding the bioacoustic behaviors of marine mammals. This capability will provide insights into the potential ecological impacts and influences of anthropogenic ocean sounds. This work focuses on building technologies using a maturity model based on DARPA 6.1 and 6.2 processes, for basic and applied research, respectively.
On the Delay of Geographical Caching Methods in Two-Tiered Heterogeneous Networks
Venue: arXiv cs.IT 2016
Year: 2016

We consider a hierarchical network that consists of mobile users, a two-tiered cellular network (namely small cells and macro cells) and central routers, each of which follows a Poisson point process (PPP). In this scenario, small cells with limited-capacity backhaul are able to cache content under a given set of randomized caching policies and storage constraints. Moreover, we consider three different content popularity models, namely fixed content popularity, distance-dependent and load-dependent, in order to model the spatio-temporal behavior of users' content request patterns. We derive expressions for the average delay of users assuming perfect knowledge of content popularity distributions and randomized caching policies. Although the trend of the average delay for all three content popularity models is essentially identical, our results show that the overall performance of cached-enabled heterogeneous networks can be substantially improved, especially under the load-dependent content popularity model.
ICT and Health System Performance in Africa: A Multi-Method Approach
Venue: arXiv cs.CY 2016
Year: 2016

For the past two decades, the discussion regarding the effect of ICT on health systems is becoming apparent. However, past studies have mainly focused on ICT impact on specific social-economic phenomena. Little empirical research on ICT and health systems exists. Many African countries have invested in ICT and there is a need to examine if such investments have impacted on health system of these countries. Using a multi-method approach, data for 27 African countries were analysed. We employed Data Envelopment Analysis, Cluster Analysis and Partial Least Squares to examine the impact. The findings indicate that the 27 countries can be grouped into three clusters based on their relative efficiency scores of ICT and health systems. More compelling, the findings indicate that countries that performed efficiently in ICT inputs also do so in their health systems. Further, findings indicate that ICT significantly improves life expectancy at birth and reduces infant mortality rate. African countries must significantly invest in ICT to improve their health systems so as to achieve socio-economic development. The current study has theoretical, methodological and policy implications.
Successive Interference Cancellation in Bipolar Ad Hoc Networks with SWIPT
Venue: arXiv cs.IT 2016
Year: 2016

Successive interference cancellation (SIC) is based on the idea that some interfering signals may be strong enough to decode in order to be removed from the aggregate received signal and thus boost performance. In this letter, we study the SIC technique from a simultaneous wireless information and power transfer (SWIPT) standpoint. We consider a bipolar ad hoc network and evaluate the impact of SIC on the SWIPT performance for the power splitting technique. Theoretical and numerical results show that our proposed approach can achieve significant energy gains and under certain scenarios the average harvested energy converges to its upper bound.
A Qualitative Comparison of MPSoC Mobile and Embedded Virtualization Techniques
Venue: arXiv cs.OS 2016
Year: 2016

Virtualization is generally adopted in server and desktop environments to provide for fault tolerance, resource management, and energy efficiency. Virtualization enables parallel execution of multiple operating systems (OSs) while sharing the hardware resources. Virtualization was previously not deemed as feasible technology for mobile and embedded devices due to their limited processing and memory resource. However, the enterprises are advocating Bring Your Own Device (BYOD) applications that enable co-existence of heterogeneous OSs on a single mobile device. Moreover, embedded device require virtualization for logical isolation of secure and general purpose OSs on a single device. In this paper, we investigate the processor architectures in the mobile and embedded space while examining their formal visualizability. We also compare the virtualization solutions enabling coexistence of multiple OSs in Multicore Processor System-on-Chip (MPSoC) mobile and embedded systems. We advocate that virtualization is necessary to manage resource in MPSoC designs and to enable BYOD, security, and logical isolation use cases.
Optimal Degrees of Freedom Region for the Asymmetric MIMO Y Channel
Venue: arXiv cs.IT 2016
Year: 2016

This letter studies the optimal degrees of freedom (DoF) region for the asymmetric three-user MIMO Y channel with antenna configuration $(M_1,M_2,M_3,N)$, where $M_i$ is the number of antennas at user $i$ and $N$ is the number of antennas at the relay node. The converse is proved by using the cut-set theorem and the genie-message approach. To prove the achievability, we divide the DoF tuples in the outer bound into two cases. For each case, we show that the DoF tuples are achievable by collectively utilizing antenna deactivation, pairwise signal alignment and cyclic signal alignment techniques. This work not only offers a complete characterization of DoF region for the considered channel model, but also provides a new and elegant achievability proof.
A Step from Probabilistic Programming to Cognitive Architectures
Venue: arXiv cs.AI 2016
Year: 2016

Probabilistic programming is considered as a framework, in which basic components of cognitive architectures can be represented in unified and elegant fashion. At the same time, necessity of adopting some component of cognitive architectures for extending capabilities of probabilistic programming languages is pointed out. In particular, implicit specification of generative models via declaration of concepts and links between them is proposed, and usefulness of declarative knowledge for achieving efficient inference is briefly discussed.
On empirical cumulant generating functions of code lengths for individual sequences
Venue: arXiv cs.IT 2016
Year: 2016

We consider the problem of lossless compression of individual sequences using finite-state (FS) machines, from the perspective of the best achievable empirical cumulant generating function (CGF) of the code length, i.e., the normalized logarithm of the empirical average of the exponentiated code length. Since the probabilistic CGF is minimized in terms of the Rényi entropy of the source, one of the motivations of this study is to derive an individual-sequence analogue of the Rényi entropy, in the same way that the FS compressibility is the individual-sequence counterpart of the Shannon entropy. We consider the CGF of the code-length both from the perspective of fixed-to-variable (F-V) length coding and the perspective of variable-to-variable (V-V) length coding, where the latter turns out to yield a better result, that coincides with the FS compressibility. We also extend our results to compression with side information, available at both the encoder and decoder. In this case, the V-V version no longer coincides with the FS compressibility, but results in a different complexity measure.
Fast rates with high probability in exp-concave statistical learning
Venue: arXiv cs.LG 2016
Year: 2016

We present an algorithm for the statistical learning setting with a bounded exp-concave loss in $d$ dimensions that obtains excess risk $O(d \log(1/δ)/n)$ with probability at least $1 - δ$. The core technique is to boost the confidence of recent in-expectation $O(d/n)$ excess risk bounds for empirical risk minimization (ERM), without sacrificing the rate, by leveraging a Bernstein condition which holds due to exp-concavity. We also show that with probability $1 - δ$ the standard ERM method obtains excess risk $O(d (\log(n) + \log(1/δ))/n)$. We further show that a regret bound for any online learner in this setting translates to a high probability excess risk bound for the corresponding online-to-batch conversion of the online learner. Lastly, we present two high probability bounds for the exp-concave model selection aggregation problem that are quantile-adaptive in a certain sense. The first bound is a purely exponential weights type algorithm, obtains a nearly optimal rate, and has no explicit dependence on the Lipschitz continuity of the loss. The second bound requires Lipschitz continuity but obtains the optimal rate.
EDF-VD Scheduling of Mixed-Criticality Systems with Degraded Quality Guarantees
Venue: arXiv cs.OH 2016
Year: 2016

This paper studies real-time scheduling of mixed-criticality systems where low-criticality tasks are still guaranteed some service in the high-criticality mode, with reduced execution budgets. First, we present a utilization-based schedulability test for such systems under EDF-VD scheduling. Second, we quantify the suboptimality of EDF-VD (with our test condition) in terms of speedup factors. In general, the speedup factor is a function with respect to the ratio between the amount of resource required by different types of tasks in different criticality modes, and reaches 4/3 in the worst case. Furthermore, we show that the proposed utilization-based schedulability test and speedup factor results apply to the elastic mixed-criticality model as well. Experiments show effectiveness of our proposed method and confirm the theoretical suboptimality results.
On the capacity of the binary adversarial wiretap channel
Venue: arXiv cs.IT 2016
Year: 2016

New bounds on the semantic secrecy capacity of the binary adversarial wiretap channel are established . Against an adversary which reads a $ρ_r$ fraction of the transmitted codeword and modifies a $ρ_w$ fraction of the codeword, we show an achievable rate of $1-h(ρ_w)-ρ_r$, where $h(\cdot)$ is the binary entropy function. We also give an upper bound which is nearly matching when $ρ_r$ is small.
Default Rules for Curry
Venue: arXiv cs.PL 2016
Year: 2016

In functional logic programs, rules are applicable independently of textual order, i.e., any rule can potentially be used to evaluate an expression. This is similar to logic languages and contrary to functional languages, e.g., Haskell enforces a strict sequential interpretation of rules. However, in some situations it is convenient to express alternatives by means of compact default rules. Although default rules are often used in functional programs, the non-deterministic nature of functional logic programs does not allow to directly transfer this concept from functional to functional logic languages in a meaningful way. In this paper we propose a new concept of default rules for Curry that supports a programming style similar to functional programming while preserving the core properties of functional logic programming, i.e., completeness, non-determinism, and logic-oriented use of functions. We discuss the basic concept and propose an implementation which exploits advanced features of functional logic languages.
Fully dynamic data structure for LCE queries in compressed space
Venue: arXiv cs.DS 2016
Year: 2016

A Longest Common Extension (LCE) query on a text $T$ of length $N$ asks for the length of the longest common prefix of suffixes starting at given two positions. We show that the signature encoding $\mathcal{G}$ of size $w = O(\min(z \log N \log^* M, N))$ [Mehlhorn et al., Algorithmica 17(2):183-198, 1997] of $T$, which can be seen as a compressed representation of $T$, has a capability to support LCE queries in $O(\log N + \log \ell \log^* M)$ time, where $\ell$ is the answer to the query, $z$ is the size of the Lempel-Ziv77 (LZ77) factorization of $T$, and $M \geq 4N$ is an integer that can be handled in constant time under word RAM model. In compressed space, this is the fastest deterministic LCE data structure in many cases. Moreover, $\mathcal{G}$ can be enhanced to support efficient update operations: After processing $\mathcal{G}$ in $O(w f_{\mathcal{A}})$ time, we can insert/delete any (sub)string of length $y$ into/from an arbitrary position of $T$ in $O((y+ \log N\log^* M) f_{\mathcal{A}})$ time, where $f_{\mathcal{A}} = O(\min \{ \frac{\log\log M \log\log w}{\log\log\log M}, \sqrt{\frac{\log w}{\log\log w}} \})$. This yields the first fully dynamic LCE data structure. We also present efficient construction algorithms from various types of inputs: We can construct $\mathcal{G}$ in $O(N f_{\mathcal{A}})$ time from uncompressed string $T$; in $O(n \log\log n \log N \log^* M)$ time from grammar-compressed string $T$ represented by a straight-line program of size $n$; and in $O(z f_{\mathcal{A}} \log N \log^* M)$ time from LZ77-compressed string $T$ with $z$ factors. On top of the above contributions, we show several applications of our data structures which improve previous best known results on grammar-compressed string processing.