Miracle-dz/UniFAR-FTUs huggingface dataset:
Waveform Design and Signal Processing Aspects for Fusion of Wireless Communications and Radar Sensing

Since traditional radar signals are “unintelligent,” regarding the amount of information they convey on the bandwidth they occupy, a joint radar and wireless communication system would constitute a unique platform for future intelligent transportation networks effecting the essential tasks of environmental sensing and the allocation of ad-hoc communication links, in terms of both spectrum efficiency and cost-effectiveness. In this paper, approaches to the design of intelligent waveforms, that are suitable for simultaneously performing both data transmission and radar sensing, are proposed. The approach is based on classical phase-coded waveforms utilized in wireless communications. In particular, requirements that allow for employing such signals for radar measurements with high dynamic range are investigated. Also, a variety of possible radar processing algorithms are discussed. Moreover, the applicability of multiple antenna techniques for direction-of-arrival estimation is considered. In addition to theoretical considerations, the paper presents system simulations and measurement results of complete “RadCom” systems, demonstrating the practical feasibility of integrated communications and radar applications.
A Microcoded Elliptic Curve Processor for GF(2m) Using FPGA Technology

The implementation of a microcoded elliptic curve processor for GF(2m) using FPGA technology is described. It is a scalable architecture in terms of area and speed that exploits the abilities of reconfigurable hardware to deliver optimized circuitry for different elliptic curves and finite fields. And it simply consists of only one arithmetic unit and one control unit, which is microcoded, facilitating rapid development and functional extension: for example, new applications could be supported simply by inserting more microcodes. The design was successfully tested on a Xilinx Virtex2 XC2V1000-256 device and could perform elliptic curve scalar multiplications with arbitrary points in 0.167 msec in the field GF(2193).
MemoLine: evaluating long-term UX with children

Recently, there has been an increased interest in long-term user experience. This paper reports an explorative study concerning the MemoLine instrument, a child-friendly adaptation of the UX Curve method to study long-term user experience concerning games in a retrospective way. The results suggest that children aged 9-11 years were able to use this instrument for recalling and relocating memories on a timeline in a dedicated and consistent way. Furthermore the results also indicate that the children heavily relied upon the visual recognition points, which were added to support recalling and relocating experiences in time.
The effect of selective, chronic stimulation on motor unit size in developing rat muscle

One of the two peripheral nerves which innervate rat lumbrical muscle was stimulated chronically in vivo during the postnatal period of synapse elimination to determine whether the differential stimulation would affect the outcome of the elimination process. Rats were anesthetized for about 4 hr a day for 5 to 6 consecutive days, during which time the sural nerve (or, in other animals, the lateral plantar nerve) was electrically stimulated. Each animal received about 10(6) stimuli. After the last stimulation period, the sizes of motor units in both nerves were estimated from motor unit tension recorded in vitro. We found that, on average, sural motor units were larger than others in animals which had received sural nerve stimulation and smaller than others in animals which had received lateral planter nerve stimulation. These results are consistent with the hypothesis that more active nerve terminals possess a relative advantage in competing for occupancy of the endplate.
Downlink Interference Alignment

We develop an interference alignment (IA) technique for a downlink cellular system. In the uplink, IA schemes need channel-state-information exchange across base-stations of different cells, but our downlink IA technique requires feedback only within a cell. As a result, the proposed scheme can be implemented with minimal changes to an existing cellular system where the feedback mechanism (within a cell) is already being considered for supporting multi-user MIMO. Not only is our proposed scheme implementable with little effort, it can in fact provide substantial gain especially when interference from a dominant interferer is significantly stronger than the remaining interference: it is shown that in the two-isolated cell layout, our scheme provides four-fold gain in throughput performance over a standard multi-user MIMO technique. We show through simulations that our technique provides respectable gain under a more realistic scenario: it gives approximately 20% gain for a 19 hexagonal wrap-around-cell layout.
Speaker adaptation using an eigenphone basis

We describe a new method of estimating speaker-dependent hidden Markov models for speakers in a closed population. Our method differs from previous approaches in that it is based on an explicit model of the correlations between all of the speakers in the population, the idea being that if there is not enough data to estimate a Gaussian mean vector for a given speaker then data from other speakers can be used provided that we know how the speakers are correlated with each other. We explain how to estimate inter-speaker correlations using a Kullback-Leibler divergence minimization technique which can be applied to the problem of estimating the parameters of all of the hyperdistributions that are currently used in Bayesian speaker adaptation.
Women Empowerment, Household Condition and Personal Characteristics: Their Interdependencies in Developing Countries.

Women’s rights and issues have become a subject of serious concern of both academicians and policy makers and have received tremendous attention in the planning, discussions and forums at national and global platforms in both developed and developing countries. The women in developing countries usually take part in the production processes in agricultural and informal sectors. However, study shows that in the South Asian countries the educational and occupational patterns have changed and widened with women entering the domains during past decade (Pandey, 2005). There has been increasing employment of women in the formal sectors as well. However, the grass root situation has not been changed to a great extent might be because of the existing lacuna in the formulation and execution of the policies. The social position of women, especially in the developing world, still needs much attention. On the other hand, women in the developed countries enjoy much of the desired freedom and rights. Therefore, the core issue, which still remains unanswered, is that of women’s right and empowerment. The question may arise 'what, then, is women's empowerment? '
Polarization Transfer from Ligands Hyperpolarized by Dissolution Dynamic Nuclear Polarization for Screening in Drug Discovery

Nuclear magnetic resonance (NMR) spectroscopy is a valuable technique for ligand screening, because it exhibits high specificity toward chemical structure and interactions. Dissolution dynamic nuclear polarization (DNP) is a recent advance in NMR methodology that enables the creation of non‐equilibrium spin states, which can dramatically increase NMR sensitivity. Here, the transfer of such spin polarization from hyperpolarized ligand to protein is observed. Mixing hyperpolarized benzamidine with the serine protease trypsin, a “fingerprint” of enhanced protein signals is observed, which shows a different intensity profile than the equilibrium NMR spectrum of the protein, but coincides closely to the frequency profile of a saturation transfer difference (STD) NMR experiment. The DNP experiment benefits from hyperpolarization and enables observation of all frequencies in a single, rapid experiment. Based on these merits, it is an interesting alternative to the widely used STD experiment for identification of protein–ligand interactions.
Amplitude Reduction and Phase Shifts of Melatonin, Cortisol and Other Circadian Rhythms after a Gradual Advance of Sleep and Light Exposure in Humans

Background The phase and amplitude of rhythms in physiology and behavior are generated by circadian oscillators and entrained to the 24-h day by exposure to the light-dark cycle and feedback from the sleep-wake cycle. The extent to which the phase and amplitude of multiple rhythms are similarly affected during altered timing of light exposure and the sleep-wake cycle has not been fully characterized. Methodology/Principal Findings We assessed the phase and amplitude of the rhythms of melatonin, core body temperature, cortisol, alertness, performance and sleep after a perturbation of entrainment by a gradual advance of the sleep-wake schedule (10 h in 5 days) and associated light-dark cycle in 14 healthy men. The light-dark cycle consisted either of moderate intensity ‘room’ light (∼90–150 lux) or moderate light supplemented with bright light (∼10,000 lux) for 5 to 8 hours following sleep. After the advance of the sleep-wake schedule in moderate light, no significant advance of the melatonin rhythm was observed whereas, after bright light supplementation the phase advance was 8.1 h (SEM 0.7 h). Individual differences in phase shifts correlated across variables. The amplitude of the melatonin rhythm assessed under constant conditions was reduced after moderate light by 54% (17–94%) and after bright light by 52% (range 12–84%), as compared to the amplitude at baseline in the presence of a sleep-wake cycle. Individual differences in amplitude reduction of the melatonin rhythm correlated with the amplitude of body temperature, cortisol and alertness. Conclusions/Significance Alterations in the timing of the sleep-wake cycle and associated bright or moderate light exposure can lead to changes in phase and reduction of circadian amplitude which are consistent across multiple variables but differ between individuals. These data have implications for our understanding of circadian organization and the negative health outcomes associated with shift-work, jet-lag and exposure to artificial light.
Requirements analysis from multiple perspectives: experiences with conceptual modeling technology

The paper discusses experiences in several commercial requirements engineering (RE) projects in augmenting an informal, teamwork oriented method with formally based computer support for the analysis and interrelation of heterogeneous perspectives. For several years, the German consulting firm USU had been working with a methodology called PFR (Presence and Future Requirements analysis). PFR is targeted towards the rapid and focused requirements capture in a setting that alternates between team workshops and distributed interviews, in order to avoid the well known problem that requirements change while they are being analyzed. PFR creates a lot of visual, partially overlapping and conflicting requirements perspectives in a very short time. The successful evolution of an RE project depends on the rapid and accurate cross analysis of these viewpoints for possible incompleteness, inconsistency, and conflicts of perception or opinion. In the past few years, meta modeling has been promoted as a step towards solving such problems. To become robust against variations of notations used in different organizations or situations, you can further abstract the different modeling languages to an axiomatic meta meta model which defines the principle concepts of "what information systems are". The meta data management system ConceptBase jointly manages multiple levels of abstraction and handles queries and updates across these levels.
Experimentally verified Iterative Learning Control based on repetitive process stability theory

This paper gives new results on the design and experimental evaluation of an Iterative Learning Control (ILC) law in a repetitive process setting. The experimental results given are from a gantry robot facility that has been extensively used in the benchmarking of linear model based ILC designs. An example is also given to demonstrate that this new design offers much superior performance in comparison to some previous designs based on the Roesser model for 2D linear systems.
The partitioned scheduling of sporadic tasks according to static-priorities

A polynomial-time algorithm is presented for partitioning a collection of sporadic tasks among the processors of an identical multiprocessor platform with static-priority scheduling on each individual processor. Since the partitioning problem is easily seen to be NP-hard in the strong sense, this algorithm is not optimal. A quantitative characterization of its worst-case performance is provided in terms of sufficient conditions and resource augmentation approximation bounds. The partitioning algorithm is also evaluated over randomly generated task systems
Geostatistical Characterization of the Transmissivity: An Example of Kuwait Aquifers

: Management of groundwater resources is critical to arid countries like Kuwait. One crucial information that is often not available to groundwater modelers is transmissivity of aquifers. Kriging is used to characterize the transmissivity of the two most commonly used aquifers in Kuwait (the Dammam and Kuwait Group aquifers). The transmissivity of the two aquifers is represented as a random spatial function where heterogeneity is described by the probability distribution and variogram of sample values. A structural analysis was performed which consisted of the construction and interpretation of sample variograms and the selection of model variograms to best ﬁt the structure of the log-transformed transmissivity. The analysis indicated that the transmissivity of the Dammam aquifer is highly anisotropic and has a longer range of inﬂuence and larger variance (39 km; 333,487) than those for the Kuwait Group aquifer (10 km; 44,613). The model variograms were used in the kriging analysis to estimate the spatial average value of the transmissivity of the two aquifers in Kuwait. The estimated transmissivity of the Kuwait Group aquifer ranges from <50 to about 800 m 2 day − 1 , and is controlled principally by the thickness of the saturated zone in the aquifer. The estimated transmissivity in Dammam aquifer ranges from ~100 to 2200 m 2 day − 1 , with high transmissivity ﬁelds coinciding with both the areas of major anticline and fault structures and the areas of aquifer recharge by fresh water, indicating the enhancement of the transmissivity on these structures by dissolution. Low transmissivity ﬁelds are located in the areas where the aquifer waters are stagnant. The performed analysis can be used to aid in the development of numerical models for sustainable management of the aquifer system in Kuwait, deﬁning artiﬁcial recharge sites, and in optimizing the locations of future development wellﬁelds. on broader spatial the effectiveness of kriging in the large-scale extrapolation of transmissivities. This case study highlights, as an example, the two principal aquifers in Kuwait, i.e., Kuwait Group aquifer and Dammam aquifer. Mapping T will aid in the optimum development of groundwater and wellfield management; i.e., understanding the flow system and flow patterns, optimizing placement of development wells, selecting areas for artificial recharge, and conducting numerical modeling studies.
Mining Your Ps and Qs: Detection of Widespread Weak Keys in Network Devices

RSA and DSA can fail catastrophically when used with malfunctioning random number generators, but the extent to which these problems arise in practice has never been comprehensively studied at Internet scale. We perform the largest ever network survey of TLS and SSH servers and present evidence that vulnerable keys are surprisingly widespread. We find that 0.75% of TLS certificates share keys due to insufficient entropy during key generation, and we suspect that another 1.70% come from the same faulty implementations and may be susceptible to compromise. Even more alarmingly, we are able to obtain RSA private keys for 0.50% of TLS hosts and 0.03% of SSH hosts, because their public keys shared nontrivial common factors due to entropy problems, and DSA private keys for 1.03% of SSH hosts, because of insufficient signature randomness. We cluster and investigate the vulnerable hosts, finding that the vast majority appear to be headless or embedded devices. In experiments with three software components commonly used by these devices, we are able to reproduce the vulnerabilities and identify specific software behaviors that induce them, including a boot-time entropy hole in the Linux random number generator. Finally, we suggest defenses and draw lessons for developers, users, and the security community.
“Ask Not What Textual Entailment Can Do for You...”

We challenge the NLP community to participate in a large-scale, distributed effort to design and build resources for developing and evaluating solutions to new and existing NLP tasks in the context of Recognizing Textual Entailment. We argue that the single global label with which RTE examples are annotated is insufficient to effectively evaluate RTE system performance; to promote research on smaller, related NLP tasks, we believe more detailed annotation and evaluation are needed, and that this effort will benefit not just RTE researchers, but the NLP community as a whole. We use insights from successful RTE systems to propose a model for identifying and annotating textual inference phenomena in textual entailment examples, and we present the results of a pilot annotation study that show this model is feasible and the results immediately useful.
Building User-defined Runtime Adaptation Routines for Stream Processing Applications

Stream processing applications are deployed as continuous queries that run from the time of their submission until their cancellation. This deployment mode limits developers who need their applications to perform runtime adaptation, such as algorithmic adjustments, incremental job deployment, and application-specific failure recovery. Currently, developers do runtime adaptation by using external scripts and/or by inserting operators into the stream processing graph that are unrelated to the data processing logic. In this paper, we describe a component called orchestrator that allows users to write routines for automatically adapting the application to runtime conditions. Developers build an orchestrator by registering and handling events as well as specifying actuations. Events can be generated due to changes in the system state (e.g., application component failures), built-in system metrics (e.g., throughput of a connection), or custom application metrics (e.g., quality score). Once the orchestrator receives an event, users can take adaptation actions by using the orchestrator actuation APIs. We demonstrate the use of the orchestrator in IBM's System S in the context of three different applications, illustrating application adaptation to changes on the incoming data distribution, to application failures, and on-demand dynamic composition.
Talking Heads: Detecting Humans and Recognizing Their Interactions

The objective of this work is to accurately and efficiently detect configurations of one or more people in edited TV material. Such configurations often appear in standard arrangements due to cinematic style, and we take advantage of this to provide scene context. We make the following contributions: first, we introduce a new learnable context aware configuration model for detecting sets of people in TV material that predicts the scale and location of each upper body in the configuration, second, we show that inference of the model can be solved globally and efficiently using dynamic programming, and implement a maximum margin learning framework, and third, we show that the configuration model substantially outperforms a Deformable Part Model (DPM) for predicting upper body locations in video frames, even when the DPM is equipped with the context of other upper bodies. Experiments are performed over two datasets: the TV Human Interaction dataset, and 150 episodes from four different TV shows. We also demonstrate the benefits of the model in recognizing interactions in TV shows.
Automated design of security protocols

Security protocols play an important role in modern communications. However, security protocol development is a delicate task, and experience shows that computer security protocols are notoriously difficult to get right. Recently, Clark and Jacob (2001) provided a framework for automatic protocol generation based on combinatorial optimization techniques and the symmetric key part of BAN logic. This paper shows how such an approach can be further developed to encompass the full BAN logic without loss of efficiency and thereby synthesize public key protocols and hybrid protocols.
COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution

Information diffusion in online social networks is affected by the underlying network topology, but it also has the power to change it. Online users are constantly creating new links when they are exposed to new information sources, and in turn these links are alternating the way information spreads. However, these two highly intertwined stochastic processes---information diffusion and network evolution---have been typically studied separately, ignoring their co-evolutionary dynamics. In this work, we propose a temporal point process model, COEVOLVE, for such joint dynamics, allowing the intensity of one process to be modulated by that of the other. The model allows us to efficiently simulate interleaved diffusion and network events, and generate traces obeying common diffusion and network patterns observed in real-world networks. Moreover, we develop a convex optimization framework to learn the parameters of the model from historical diffusion and network evolution traces. Experiments in both synthetic data and real data gathered from Twitter show that our model provides a good fit to the data as well as more accurate predictions than alternatives.
The Open University ’ s repository of research publications and other research outputs Hierarchical classification for multiple , distributed web databases

The proliferation of online information resources increases the importance of effective and efficient distributed searching. Our research aims to provide an alternative hierarchical categorization and search capability based on a Bayesian network learning algorithm. Our proposed approach, which is grounded on automatic textual analysis of subject content of online web databases, attempts to address the database selection problem by first classifying web databases into a hierarchy of topic categories. The experimental results reported demonstrate that such a classification approach not only effectively reduces the class search space, but also helps to significantly improve the accuracy of classification performance.