Miracle-dz/UniFAR-FTUs huggingface dataset:
Short term face recognition for Automatic Teller Machine (ATM) users

Automatic Teller Machines (ATMs) are widely used in our daily lives due to their convenience, wide-spread availability and time-independent operation. Automatic retraction of forgotten card or cash by ATMs is a problem with serious consequences (lost time and money), typically caused by user inattention/negligence. In this work, we propose a scheme in which the retraction rate of an ATM is decreased using face detection and recognition methods via ATM's built-in camera. The short time frame of ATM usage and severe motion artifacts make this problem very different from an ordinary face authentication or face recognition problem. We evaluate the proposed system under challenging conditions of real ATM usage. The experimental results on multiple databases reveal that our proposed system is promising for mitigating card/cash forgetting issue and improving ATM user experience.
Growing Hierarchical Trees for Data Stream clustering and visualization

Data stream clustering aims at studying large volumes of data that arrive continuously and the objective is to build a good clustering of the stream, using a small amount of memory and time. Visualization is still a big challenge for large data streams. In this paper we present a new approach using a hierarchical and topological structure (or network) for both clustering and visualization. The topological network is represented by a graph in which each neuron represents a set of similar data points and neighbor neurons are connected by edges. The hierarchical component consists of multiple tree-like hierarchic of clusters which allow to describe the evolution of data stream, and then analyze explicitly their similarity. This adaptive structure can be exploited by descending top-down from the topological level to any hierarchical level. The performance of the proposed algorithm is evaluated on both synthetic and real-world datasets.
STUDIES ON THE ANTIOXIDANT ACTIVITY OF ACTINORHYTIS CALAPPARIA

In the present study, preliminary phytochemical screening and in-vitro antioxidant activity of aqueous and methanolic fruit extracts of Actinorhytis calapparia H.Wendl. & Drude was investigated. The antioxidant activity was studied by using in vitro antioxidant models viz., DPPH radical scavenging activity and reducing power assay. Both the extracts showed antioxidant activity by inhibiting DPPH free radicals and also showed reducing power ability in ferric reducing model which was a dose dependent. The IC 50 value was found to be 15 and 26 µg/ml for methanolic and aqueous extract respectively. Phytochemical screening of the extract revealed the presence of tannins, steroids, carbohydrates and amino acids. The total phenolic content of the extract was determined using the Folin-Ciocalteu method. The total phenolic content observed for aqueous and methanolic extracts were 56 and 64.3 mg/g equivalent of gallic acid respectively.
Nasal detection module for a knowledge-based speech recognition system

The Lexical Access From Features (LAFF) project tries to model the representation and perception of speech by human listeners. The derivation of such a representation involves first finding certain acoustic landmarks. Based on the landmarks and the acoustic cues surrounding the landmarks, distinctive features of the speech segments may be deciphered. The present study concentrates on the nasality module that attempts to detect the presence of an underlying nasal consonant, which is almost always adjacent to a vowel. For an underlying nasal in English, the features [+voiced, +sonorant, +consonant, +nasal, -continuant] are specified. The features are then mapped into measurable acoustic properties. Normally, cues from three regions in the sound indicate the presence of a nasal consonant: (1) abrupt spectral change from the vowel to the nasal murmur, (2) vowel nasalization, and (3) nasal murmur. These cues are quantified by acoustic parameters whose values are combined to indicate the presence of a nasal. The nasality module that has been developed is a sonorant landmark detector that greatly reduces false landmark detection and distinguishes nasals from laterals by incorporating additional nasal manner cues. The module also addresses cases where one or more of the three nasal cues is absent.
Low Complexity Iterative Algorithms for Power Estimation in Ultra-Dense Load Coupled Networks

This study investigates the interplay between load and power in load coupled interference networks. In more detail, the first objective of this study is to derive a positive concave mapping having as its fixed point the power allocation inducing a desired network load. Knowledge of this mapping is important for many theoretical and practical reasons. First, it opens up the possibility of applying many existing algorithms to compute the power inducing a desired load, which is an estimation problem typically used to obtain energy efficient network configurations. With the results in this study, systems designers can now select an algorithm based on practical considerations such as the computational complexity, memory requirements, and convergence speed. In particular, we show that algorithms based on simple fixed point iterations already have many advantages over the previously only known method for the power estimation problem. Second, knowledge of specific properties of the mapping, such as concavity, enables us to use standard tools in convex analysis to analyze the network, and it may also give rise to novel optimization tools for self-organizing networks. The second main objective of this study is the development of a truly distributed algorithm for power estimation in real networks. This algorithm uses only information that is readily available at base stations, and it does not require any additional signaling overhead. These two characteristics make the proposed algorithm especially useful in ultra-dense wireless networks, one of the main visions for 5G networks.
Life-Cycle Models, Economic Puzzles and Temptation Preferences

This paper focuses on the difficulty of standard life-cycle models to predict the behavior observed in the reality, most noticeably the excess sensitivity of consumption to income, the under-provision for old-age consumption, the limited participation in the financial market, and the lack of asset decumulation after retirement. It shows that allowing for preference reversals, as it is the case in the “quasi-hyperbolic discounting” and “temptation” models, may contribute to explain jointly these economic puzzles. A life-cycle model based on temptation preferences, in particular, is attractive as it preserves time consistency and can be solved with standard dynamic programming techniques.
Scheme of User Privacy Protection Applied to Online Marketing

Research has shown the incredible evolution of mobile marketing and, on the other hand, has also revealed that email marketing is still widely used. Online marketing has evolved considerably in recent times and is becoming a key for companies wishing to ensure their survival in the online market. Online behavioral advertising (OBA) is a tool that has leveraged the evolution of digital marketing, but it is causing a big debate on the Internet. Many say that when OBA is implemented, user privacy is seriously compromised, since the tracking of user information, without their consent, is key to the OBA implementation. Based on past and current needs of new marketing trends and trying to balance the dilemma of privacy versus OBA, a scheme was developed to safeguard user privacy, as well as allow for the continued evolution of the OBA.
Video streaming over software defined networks with server load balancing

Software Defined Networking is a promising Internet architecture to deliver multimedia with end-to-end quality of service (QoS) since it enables optimal dynamic management of network resources and on-demand QoS provisioning by a network operator. We propose a framework for server load-balancing over a single-operator OpenFlow network to improve the quality of service levels of video streaming services. We design a new OpenFlow controller application for dynamic server load balancing by continuous monitoring of load of each video server and dynamic rerouting of clients to alternate servers with lower loads when an overload condition is detected. The proposed controller application is implemented on top of an open source OpenDaylight controller. Our results show that the proposed load-balancer improves the quality of streaming video experienced by end-users, and OpenFlow provides a powerful framework to provide video services with end-to-end quality of service over the future Internet.
SMALL-x PHYSICS: From HERA to LHC and Beyond

▪ Abstract We summarize the lessons learned from studies of hard scattering processes in high-energy electron-proton collisions at HERA and antiproton-proton collisions at the Tevatron, with the aim of predicting new strong interaction phenomena observable in next-generation experiments at the Large Hadron Collider (LHC). Processes reviewed include inclusive deep-inelastic scattering (DIS) at small x, exclusive and diffractive processes in DIS and hadron-hadron scattering, as well as color transparency and nuclear shadowing effects. A unified treatment of these processes is outlined on the basis of factorization theorems of quantum chromodynamics, and using the correspondence between the “parton” picture in the infinite-momentum frame and the “dipole” picture of high-energy processes in the target rest frame. The crucial role of the three dimensional quark and gluon structure of the nucleon is emphasized. A new dynamical effect predicted at high energies is the unitarity, or black disk, limit (BDL) in the.
Disentangling the role of heat sources on microhabitat selection of two Neotropical lizard species

Abstract Our aim was to disentangle the effects of different heat sources and the non-thermal properties of the substrate in the microhabitat choices of two lizard species living in savanna habitats of central-western Brazil: the teiid Ameivula aff. ocellifera (N = 43) and the tropidurid Tropidurus oreadicus (N = 23). To this end, a mixed structural resource selection function (mixed-SRSF) approach was used, modelling the probability of finding a lizard on a certain microhabitat based on environmental variables of used and simultaneously available places. First, we controlled for the effects of solar radiation, convection and the physical thermal properties of the substrate on substrate temperature. Then we assessed the effects of solar radiation, convection, conduction and the non-thermal properties of the substrate in the probability of use of a certain microhabitat. Results confirmed that substrate temperature was mediated by: air convection > solar radiation > physical thermal properties of the substrates. Moreover, the mixed-SRSF revealed that direct solar radiation and the non-thermal properties of the substrates were the only drivers of microhabitat selection for both species, with approximately the same strength. Our novel approach allowed splitting of the effect of different mechanisms in the microhabitat selection of lizards, which makes it a powerful tool for assessing the conformation of the interactions between different environmental variables mediating animal behaviour.
Can Sophie's Choice Be Adequately Captured by Cold Computation of Minimizing Losses? An fMRI Study of Vital Loss Decisions

The vast majority of decision-making research is performed under the assumption of the value maximizing principle. This principle implies that when making decisions, individuals try to optimize outcomes on the basis of cold mathematical equations. However, decisions are emotion-laden rather than cool and analytic when they tap into life-threatening considerations. Using functional magnetic resonance imaging (fMRI), this study investigated the neural mechanisms underlying vital loss decisions. Participants were asked to make a forced choice between two losses across three conditions: both losses are trivial (trivial-trivial), both losses are vital (vital-vital), or one loss is trivial and the other is vital (vital-trivial). Our results revealed that the amygdala was more active and correlated positively with self-reported negative emotion associated with choice during vital-vital loss decisions, when compared to trivial-trivial loss decisions. The rostral anterior cingulate cortex was also more active and correlated positively with self-reported difficulty of choice during vital-vital loss decisions. Compared to the activity observed during trivial-trivial loss decisions, the orbitofrontal cortex and ventral striatum were more active and correlated positively with self-reported positive emotion of choice during vital-trivial loss decisions. Our findings suggest that vital loss decisions involve emotions and cannot be adequately captured by cold computation of minimizing losses. This research will shed light on how people make vital loss decisions.
Improving pesticide spray application in vineyards by automated analysis of the foliage distribution pattern in the leaf wall

A novel color-based recording and evaluation technique is presented which allows to determine the spatial distribution of foliage along approximately planar vine rows with high accuracy. The approach uses optical flow tracking to construct a composite from an image sequence and user-trainable bayesian color classification to segment foilage from a distinctively colored canvas carried along behind the row under evaluation. The gained information furthers insight into the seasonal growth patterns of commercial plantations and also allows to validate the performance of new-generation, selective spraying pesticide sprayers.
VPA-Based Aspects: Better Support for AOP over Protocols

Aspect-oriented programming is a promising approach to the construction of large-scale software systems. The declarativeness of aspect definitions and support for verification of AO programs crucially depends on the expressiveness of the aspect languages used. Currently, a large spectrum of pointcut languages, i.e., the languages that define where aspects may apply modifications to an application, have been proposed. Their expressiveness ranges from regular expression languages, which, e.g., provide support for static interaction analysis, to context-free or turing complete languages, the latter almost without any support for analysis or verification. In this paper we investigate the use of visibly pushdown automata (VPA) [4] as a basis for an aspect language in order to enable more declarative aspect definitions (compared to regular approaches) for protocol like relationships and static verification of properties, in particular analysis of interactions among aspects. Concretely, we present four contributions: (i) we provide a set of examples motivating the use of VPA-based aspect definitions in the context of P2P systems, (ii) formally define a core aspect language for protocols with a VPA-based pointcut language, (iii) show that this language supports the analysis of interaction properties among aspects, and (iv) briefly present a freely available library implementing basic VPA operations, which we have used to analyze some interaction examples
Leveraging Altruism in Cooperative Services

When there is no central administrator to control the actions of nodes in a distributed system, the users may deviate for personal gain. The BAR model describes the three types of nodes in these environments: Byzantine nodes deviate arbitrarily, Altruistic nodes follow the protocol, and Rational nodes deviate for gain. Previous attempts at writing BAR-Tolerant protocols have relied on a form of policing that makes sure that all non-Byzantine nodes follow the same protocol. This method makes it impossible to take advantage of the Altruistic nodes. In this paper we introduce a new equilibrium concept that does not rely on such strong policing. As a result, we can leverage Altruistic nodes when they are present. We give a condition that is sufficient to ensure that protocol guarantees hold despite Rational and Byzantine nodes, and we show how to use the new equilibrium concept and condition to build a BAR-Tolerant Terminating Reliable Broadcast protocol. Our protocol leverages Altruistic nodes to reduce the amount of extra work that Byzantine nodes can inflict on the system.
Information Services for Mathematics in the Internet (Math-Net)

The present paper gives a brief description of the Math-Net project which is carried out by nine mathematical institutions in Germany, supported by Deutsches Forschungsnetz (DFN) and Deutsche Telekom. The project aims at setting up the technical and organizational infrastructure for efficient, inexpensive and user-driven information services for mathematics. With the aid of active (structured retrieval mechanisms) and passive (profile services) components, electronic mathematical information in Germany will be made available to the scientist at his workplace. The emphasis is put on information about publications, software and data collections, teaching and research activities, but also on organizational and bibliographical information. Decentral organization structures, distributed search systems as well as the use of meta-information (metadata) in accordance with the Dublin Core (hopefully) guarantee a longterm, high-quality repository of data. The well-known mathematical software and data collection netlib\/ will be used as an example to illustrate how such a collection can be adapted to Math-Net. An integration of netlib into HyperWave offers additional perspectives and functionalities.
Pattern Class Degeneracy in an Unrestricted Storage Density Memory

The study of distributed memory systems has produced a number of models which work well in limited domains. However, until recently, the application of such systems to real­ world problems has been difficult because of storage limitations, and their inherent architectural (and for serial simulation, computational) complexity. Recent development of memories with unrestricted storage capacity and economical feedforward architectures has opened the way to the application of such systems to complex pattern recognition problems. However, such problems are sometimes underspecified by the features which describe the environment, and thus a significant portion of the pattern environment is often non-separable. We will review current work on high density memory systems and their network implementations. We will discuss a general learning algorithm for such high density memories and review its application to separable point sets. Finally, we will introduce an extension of this method for learning the probability distributions of non-separable point sets.
Implementation of Hardwired Distributive Tactile Sensing for Innovative Flexible Digit

This paper focuses on the design of an efficient automated data interpretation system that is able to output its interpretation directly to describe the nature of contact with the tactile surface. The work integrates distributive tactile sensing technology, artificial neural networks (ANNs), and advanced FPGA-based application-specific real-time digital signal processing, to produce working systems for use in a steerable endoscope that retrieves shape and 'touch' information. Different configurations of the signal interpretation such as single and cascade neural networks were assessed. It was shown that the cascaded ANN architecture could achieve an overall accuracy of better than 94% when measuring clinically significant contact information. This technology has the potential to discriminate contact and palpation in minimal invasive surgery (MIS) tools.
Fault Tolerance Against Design Faults

This chapter surveys techniques for tolerating the effects of design defects in computer systems, paying special attention to software. Design faults are a major cause of failure in modern computer systems, and their relative importance is growing as techniques for tolerating physical faults gain wider acceptance. Although design faults could in principle be eliminated, in practice they are inevitable in many categories of systems, and designers need to apply fault tolerance for mitigating their effects. Limited degrees of fault tolerance in software – “defensive programming” – are common, but systematic application of fault tolerance for design faults is still rare and mostly limited to highly critical systems. However, the increasing dependence of system designers on off-the-shelf components often makes fault tolerance a necessary, feasible and probably cost-effective solution for achieving modest dependability improvements at affordable cost. This chapter introduces techniques and principles, outlines similarities and differences with fault tolerance against physical faults, provides a structured description of the space of design solutions, and discusses some design issues and trade-offs.
Massive MIMO and small cells: Improving energy efficiency by optimal soft-cell coordination

To improve the cellular energy efficiency, without sacrificing quality-of-service (QoS) at the users, the network topology must be densified to enable higher spatial reuse. We analyze a combination of two densification approaches, namely “massive” multiple-input multiple-output (MIMO) base stations and small-cell access points. If the latter are operator-deployed, a spatial soft-cell approach can be taken where the multiple transmitters serve the users by joint non-coherent multiflow beamforming. We minimize the total power consumption (both dynamic emitted power and static hardware power) while satisfying QoS constraints. This problem is proved to have a hidden convexity that enables efficient solution algorithms. Interestingly, the optimal solution promotes exclusive assignment of users to transmitters. Furthermore, we provide promising simulation results showing how the total power consumption can be greatly improved by combining massive MIMO and small cells; this is possible with both optimal and low-complexity beamforming.
Search strategies for developing characterizations of graphs without small wheel subdivisions

Practical algorithms for solving the Subgraph Homeomorphism Problem are known for only a few small pattern graphs: among these are the wheel graphs with four, five, six, and seven spokes. The length and difficulty of the proofs leading to these algorithms increase greatly as the size of the pattern graph increases. Proving a result for the wheel with six spokes requires extensive case analysis on many small graphs, and even more such analysis is needed for the wheel with seven spokes. This paper describes algorithms and programs used to automate the generation and testing of the graphs that arise as cases in these proofs. The main algorithm given may be useful in a more general context, for developing other characterizations of SHP-related properties.