Miracle-dz/UniFAR-FTUs huggingface dataset:
Through Biometric Card in Romania : Person Identification by Face , Fingerprint and Voice Recognition

verification and identification, i.e. by means of fingerprints, face and voice recognition, are studied. Face recognition uses parts-based representation methods and a manifold learning approach. The assessment criterion is recognition accuracy. The techniques under investigation are: a) Local Non-negative Matrix Factorization (LNMF); b) Independent Components Analysis (ICA); c) NMF with sparse constraints (NMFsc); d) Locality Preserving Projections (Laplacianfaces). Fingerprint detection was approached by classical minutiae (small graphical patterns) matching through image segmentation by using a structural approach and a neural network as decision block. As to voice / speaker recognition, melodic cepstral and delta delta mel cepstral analysis were used as main methods, in order to construct a supervised speaker-dependent voice recognition system. The final decision (e.g. " accept-reject " for a verification task) is taken by using a majority voting technique applied to the three biometrics. The preliminary results, obtained for medium databases of fingerprints, faces and voice recordings, indicate the feasibility of our study and an overall recognition precision (about 92%) permitting the utilization of our system for a future complex biometric card.
Is There Really a Green Paradox?

The Green Paradox states that, in the absence of a tax on CO2 emissions, subsidizing a renewable backstop such as solar or wind energy brings forward the date at which fossil fuels become exhausted and consequently global warming is aggravated. We shed light on this issue by solving a model of depletion of non-renewable fossil fuels followed by a switch to a renewable backstop, paying attention to timing of the switch and the amount of fossil fuels remaining unexploited. We show that the Green Paradox occurs for relatively expensive but clean backstops (such as solar or wind), but does not occur if the backstop is sufficiently cheap relative to marginal global warming damages (e.g., nuclear energy) as then it is attractive to leave fossil fuels unexploited and thus limit CO2 emissions. We show that, without a CO2 tax, subsidizing the backstop might enhance welfare. If the backstop is relatively dirty and cheap (e.g., coal), there might be a period with simultaneous use of the non-renewable and renewable fuels. If the backstop is very dirty compared to oil or gas (e.g., tar sands), there is no simultaneous use. The optimum policy requires an initially rising CO2 tax followed by a gradually declining CO2 tax once the dirty backstop has been introduced. We also discuss the potential for limit pricing when the non-renewable resource is owned by a monopolist.
Smart Cameras

We review camera architecture in the age of artificial intelligence. Modern cameras use physical components and software to capture, compress and display image data. Over the past 5 years, deep learning solutions have become superior to traditional algorithms for each of these functions. Deep learning enables 10-100x reduction in electrical sensor power per pixel, 10x improvement in depth of field and dynamic range and 10-100x improvement in image pixel count. Deep learning enables multiframe and multiaperture solutions that fundamentally shift the goals of physical camera design. Here we review the state of the art of deep learning in camera operations and consider the impact of AI on the physical design of cameras.
The Journal of Logic and Algebraic Programming

We present an algebraic approach to separation logic. In particular, we give an algebraic characterisation for assertions of separation logic, discuss different classes of assertions and prove abstract laws fully algebraically. After that, we use our algebraic framework to give a relational semantics of the commands of a simple programming language associated with separation logic. On this basis we prove the frame rule in an abstract and concise way, parametric in the operator of separating conjunction, of which two particular variants are discussed. In this we also show how to algebraically formulate the requirement that a commandpreservescertainvariables.Thealgebraicviewdoesnotonlyyieldnewinsightson separation logic but also shortens proofs due to a point free representation. It is largely ﬁrst-order and hence enables the use of off-the-shelf automated theorem provers for verifying properties at an abstract level.
ScholarWorks@UMass Amherst ScholarWorks@UMass Amherst

This paper describes a method for determining the dynamical interaction between extended halo and spheroid components and an environmental disturbance. One ﬁnds that resonant interaction between a galaxy and passing interlopers or satellite companions can carry the disturbance inward, deep inside the halo, where it can perturb the disk. Applied to the Milky Way for example, the LMC and SMC appear to be suﬃcient to cause the observed Galactic warp and possibly seed other asymmetries. This is a multi-scale interaction in which the halo wake has a feature at roughly half the satellite orbital radius due to a 2:1 orbital resonance. The rotating disturbance then excites an m = 1 vertical disk mode which has the classic integral-sign morphology. A polar satellite orbit produces the largest warp and therefore the inferred LMC orbit is nearly optimal for maximum warp production. Both the magnitude and morphology of the response depend on the details of the disk and halo models. Most critically, a change in the halo proﬁle will shift the resonant frequencies and response location and consequently alter the coupling to the bending disk. Increasing the halo support relative to the disk, a sub-maximal disk model, decreases the warp amplitude. Finally, the results and prognosis for N-body simulations are discussed. Discrete-ness noise in the halo, similar to that due to a population of 10 6 M ⊙ black holes, can produce observable warping. Details are discussed in an associated paper.
Markov Chains : A Random Walk Through Particles , Cryptography , Websites , and Card Shuffling

In this paper, I will discuss the origins of Markov chains, the theory behind them, and their convergent quality seen in the Ergodic theorem. From there, I will outline the MetropolisHastings algorithm, one of the most important applications of Markov chains, and give examples of its effectiveness and applicability in various areas. ”Life calls the tune, we dance. ” John Galsworthy Notation • N is the set of nonnegative integers.
Non-commercial Research and Educational Use including without Limitation Use in Instruction at Your Institution, Sending It to Specific Colleagues That You Know, and Providing a Copy to Your Institution's Administrator. All Other Uses, Reproduction and Distribution, including without Limitation Comm

Safe development of glacierized regions requires a systematic and objective method for assessing the hazard posed by moraine-dammed lakes. Empirical relations exist for estimating outburst flood magnitude, but, until now, no standardized procedures have been developed for estimating outburst flood probability. To make quick and inexpensive preliminary assessments that are reproducible, we propose using a statistical, remote sensing-based approach to estimate the probability of catastrophic drainage of moraine-dammed lakes. We completed a comprehensive inventory of 175 moraine-dammed lakes in the southern Coast Mountains of British Columbia, Canada. By applying logistic regression analysis to the data set, we identified and weighted the following four independent predictor variables that best discriminate drained lakes from undrained lakes: moraine height-to-width ratio, presence/ absence of an ice-core in the moraine, lake area, and main rock type forming the moraine. With an appropriate classification cutoff value, the predictive model correctly classifies 70% of drained lakes and 90% of undrained lakes, for an overall accuracy of 88%. Our model provides engineers and geoscientists with a tool for making first-order estimates of the probability of catastrophic drainage from moraine-dammed lakes in southwestern British Columbia.
A fast binocular vision stereo matching algorithm

To resolve the problem of large computational cost and complexity of current binocular vision stereo matching algorithm, a fast Indoor stereo matching algorithm based on line moments and the angle vector is presented. Firstly, the method detects image edge using Canny operator, and finds the target objects according line moments, then feature points of the objects' contours are extracted. Finally, matching the pixel in stereo image pair according the angle vector. The algorithm effectively reduces the computational complexity, computational cost is decreased greatly. The experimental results show that The algorithm is possible and valid.
LDBAS: Location-aware Data Block Allocation Strategy for HDFS-based Applications in the Cloud

Big data processing applications have been migrated into cloud gradually, due to the advantages of cloud computing. Hadoop Distributed File System (HDFS) is one of the fundamental support systems for big data processing on MapReduce-like frameworks, such as Hadoop and Spark. Since HDFS is not aware of the co-location of virtual machines in the cloud, the default scheme of block allocation in HDFS does not fit well in the cloud environments behaving in two aspects: data reliability loss and performance degradation. In this paper, we present a novel location-aware data block allocation strategy (LDBAS). LDBAS jointly optimizes data reliability and performance for upper-layer applications by allocating data blocks according to the locations and different processing capacities of virtual nodes in the cloud. We apply LDBAS to two stages of data allocation of HDFS in the cloud (the initial data allocation and data recovery), and design the corresponding algorithms. Finally, we implement LDBAS into an actual Hadoop cluster and evaluate the performance with the benchmark suite BigDataBench. The experimental results show that LDBAS can guarantee the designed data reliability while reducing the job execution time of the I/O-intensive applications in Hadoop by 8.9% on average and up to 11.2% compared with the original Hadoop in the cloud.
Hannu Salonen ― Hannu Vartiainen Valuating Payoff Streams under Unequal Discount Factors

We study repeated prize allocation problem when the discount factors f the agents are not equal. It is shown that the feasible set of payoffs is not well behaved. In particular, it is not convex as it contains holes and caves. The Pareto frontier is everywhere discontinuous and there is an open subset of discount factors such that the feasible set is totally disconnected. JEL Classification: C60, C70
Localization Techniques in WSN : A Review

Wireless Sensor Network (WSN) is a kind of wireless network, which is composed of groups of very small devices known as „Sensor Nodes‟. It is one of the fastest evolving fields. Applications of WSN comprise of search, disaster relief, remote environmental monitoring, target tracking etc. In all such applications, data gathered by the network is not useful, without location information. As nodes location is required to report the origin of event, about which the data is gathered. Node localization is highly important, for large sensor networks where users desire, to know about the exact location of the nodes to know the event location. This paper reviews different localization techniques, used for nodes location discovery in WSN and presents their parametric comparison in tabular form. This comparison is useful for better understanding of existing techniques and for the development of other novel technique.
Perceptual Learning and the Emergence of Performer-Instrument Interactions with Digital Systems

The relationship between human and computers within the area of HCI has shifted from being represented by cognitive, information-processing approaches to more recent situated and embodied perspectives. This matter has analogously developed within interactive digital musical system research. However, the nature of this interaction, while commonly drawing upon J.J. Gibson’s theory of affordances for analysis, often fails to characterize the emergent relationship between performer and musical system. This has led to regard affordances as mere design features, as well as taking for granted the skillful contributions of the performer. Interactions in this manner are represented as static. In this paper, I present the findings of a long-term phenomenological research study describing the evolving nature of performer-instrument interactions. I resort to E.J. Gibson’s perceptual learning approach to frame the experiences of performers, both individually and socially, as they learned to play a new digital musical instrument, the Pulley Synth. I argue that the nature of such interactions is grounded on learning and that the changing perception of the system contributes to the process of enskilment. In this view, more than being an acquisition of conceptual knowledge of the instrument’s operation, learning suggests a holistic behavioral change towards the system in which musical and sonic possibilities of the entire performer-instrument-environment ecology are explored and enacted. I conclude that perceptual learning is significant within the context of HCI and musical technology, given that current design and performance practices with interactive digital music systems remain influenced by established musical practices (for example, Classical music). If one of the aims of this domain is the development of new musical interactions and practices, the ability to overcome the influence of musical traditions and to perceive new sonic possibilities must be considered in both the design and instrumental learning processes.
IMPROVING SERVICE CREDIBILITY IN PASSWORD AUTHENTICATED PEER SERVICES

Two server secret word-based authentication protocols(Two-Server PAKE), where two servers co- operate to authenticate a client on the basis of secret word only and if one server is compromised due to denial of service attack (DDOS), the attacker still cannot make believe to be the client with information from the compromised server. New research advances in secret word based authentication a n d follow two models. The initial model, called Public key infrastructure suggests, that the client having the server's public key in additional to share a secret word to the server. In this setup, the client has to send the secret word only to the server by public key encryption (PKE). The next model is called secret word- only model which follows encrypted key exchange (EKE) protocols, where the password is used as a secret key to encrypt random numbers for key exchange purpose. A secret word-only authentication protocol which is both convenient and provably secure identify with cryptographic assumption. Our protocol is symmetric and, can run in similar to establish secret session keys between the client and peer servers, respectively. In case any one of the two peer servers shuts down due to the Distributed Denial-of service attack (DDOS), other server can proceed to provide ceremony to valid clients. In case of similar computation and reliable service, a symmetrical protocol is superior to an asymmetrical protocol.
A pr 2 01 9 Reduction of a family of metric gravities With highlights on conservation laws in metric formulations , consistency before dynamics , and a fresh view on the unity of Newtonian and Einsteinian gravity

A recent proposal by Shuler regarding a postulate-based derivation of a family of metrics describing the gravitational field outside a static spherically symmetric mass distribution is reviewed. All of Shuler’s gravities agree with the Schwarzschild solution in the weak-field limit, but they differ in the strong-field domain, i.e., close enough to a sufficiently compact source of the field. It is found that the evoked postulates of i) momentum conservation and ii) consistency of field strength measurement are satisfied in all metric theories of gravity compatible with the Einstein equivalence principle, no matter what the form of the metric. Therefore, they cannot be used, within any correct deduction, to derive a particular metric. Shuler’s derivations are based on an inconsistent set of correspondences between local and distant quantities. Furthermore, it is shown here that out of the family of possible metrics given by Shuler only one member, the Schwarzschild metric, satisfies a standard relativistic generalization of Newton’s law of gravitation, suggesting the others to be unphysical.
Out of the blue: the evolution of horizontally polarized signals in Haptosquilla (Crustacea, Stomatopoda, Protosquillidae)

The polarization of light provides information that is used by many animals for a number of different visually guided behaviours. Several marine species, such as stomatopod crustaceans and cephalopod molluscs, communicate using visual signals that contain polarized information, content that is often part of a more complex multi-dimensional visual signal. In this work, we investigate the evolution of polarized signals in species of Haptosquilla, a widespread genus of stomatopod, as well as related protosquillids. We present evidence for a pre-existing bias towards horizontally polarized signal content and demonstrate that the properties of the polarization vision system in these animals increase the signal-to-noise ratio of the signal. Combining these results with the increase in efficacy that polarization provides over intensity and hue in a shallow marine environment, we propose a joint framework for the evolution of the polarized form of these complex signals based on both efficacy-driven (proximate) and content-driven (ultimate) selection pressures.
AIS Electronic Library (AISeL)

In the much-observed field of weblogs, corporate blogs are of particular relevance and interest. This study 1 empirically examines the corporate blog phenomenon by reviewing the blog status of 250 companies from the consumer goods industry. Their blogs – if any – were tested with the help of different variables, such as the location of the company, the blog’s updating frequency or its interactivity. This allowed for testing certain hypotheses, in particular concerning the existence of corporate blogs in certain companies, industries and regions, or whether a blog’s traffic rank depends upon these variables. This survey suggests that a blog's traffic rank is significantly influenced by the frequency of blog postings and its interactivity features. These factors seem to greatly depend upon the sales volume of a company. However, the data sample at hand suggests that there is not yet a widespread usage of corporate weblogs.
An Operational Semantics of Java 2 Access Control

Java 2 Security enhanced with the Java Authentication and Authorization Service (JAAS) provide sophisticated access control features via a user-configurable authorization policy. Fine-grained access control, code-based as well as user-based authorization, and implicit access rights allow the implementation of real-world policies, but of the cost of increased complexity. In this paper we provide a formal specification of the Java 2 and JAAS access control model that helps remove ambiguities of the informal definitions. It defines Java 2 access control in terms of an abstract machine, whose behavior is determined by a small set of transition rules. We illustrate the power of Java 2 access control by showing how commonly encountered authorization requirements can be implemented in Java 2.
EasyChair Preprint No 287 An Improved Recommender for Travel Itineraries

Given the vast amount of information, including the numerous points-of-interest (POIs) and the various hotels, available on travel websites such as tripadvisor or booking, a recommender system would help users, who are planning their next trip, filter out unnecessary information based on their requirements. We improved our previous work on a recommendation system that was intended to facilitate the generation of daily travel itineraries. We used the X-Means clustering algorithm to divide all attraction sites and hotels into groups according to geographical location. Meanwhile, a Word2Vec model was trained using the Wikipedia text corpus to obtain similar tags of specific ones. A tag-based mapping algorithm was applied to create a list of candidate attractions that best match with the user’s favorite spots. Finally, by taking into account the weather information, our recommender can further refine the list of candidate attractions and work out a daily itinerary that involves desirable hotels and attractions. The shortest itinerary (SI) and the itinerary with the highest performance/price ratio (MEI) will then be produced for user selection. The results of a series of experiments demonstrated that, compared to others, our personalized recommender for travel planning can provide a more appealing and detailed travel plan containing daily itineraries for users.
Improving the Sustainability of Open Government Data

In the context of big data, opening government data to society for development and utilization would improve the transparency of government work and promote harmonious social development. Improving the sustainability of open government data (OGD) is an important and challenging issue, and has received the attention of multiple governments. The goals of this study are to construct a new evaluation model for the sustainability of OGD that explores the main influential factors and amends the priorities. We used a combination of the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method and the Analytical Network Process (ANP) method known as DANP to construct an influential network relationship map (INRM) of the evaluation system and calculate the criterion weights. The INRM and weights can help decision makers understand the complex assessment system and set priorities for improving OGD. The results demonstrate that the improvement priorities of dimensions have the following order: impact (D4), use (D3), data (D2), and environment (D1). Economic, social, and political values are the three critical factors for improvement of the sustainability of OGD. Some implications for management are also provided.
The Effect of Internet Security Breach Announcements on Market Value of Breached Firms and Internet Security Developers

Assessing the value of information technology (IT) security investments by firms is a challenging task because of difficulties in the measurement of tangible and intangible benefits. Event study methodology that uses market valuations is a widely used in these cases. We employ the event study methodology to assess the impact of Internet security breaches on the market value of the breached firms. We also study the information transfer effect of security breaches, namely the effect of security breaches of other firms on market values of firms that develop security technology. The results of our study show that the announcement of Internet security breach is negatively associated with the market value of the announcing firm. Compromised firms, on average, lose approximately 2.1% of their market values within two days surrounding the events. This translates into $ 1.65 billion average loss in market capitalization per incident. We find that firm type, firm size, and time are important factors that explain the crosssectional variations in abnormal returns. Our results also show that the effects of security breaches are not restricted to breached firms. The market values of security developers are positively associated with the disclosure of security breaches by other firms. Each security developer, on average, gains 1.36 % more than normal gain expected by market model. This translates into, on average, a total gain of $ 1.06 billion per security firm over a two-day period.