Miracle-dz/UniFAR-FTUs huggingface dataset:
Comments On: Constant Time Modular Inversion

Modular inversion is a challenge for cryptographic implementations as it is one of the most time consuming field operations in the ECC calculations. Basically it is performed by using of the Fermats little theorem, Extended Euclidean algorithm or any of its binary variants based on the Montgomery modular inverse algorithm [1]. A typical implementation of an Extended Euclidean algorithm for modular inversion can be the source of information leakage. It happens due to the fact that these algorithms have an input-centric sequence of conditional branches and therefore the time for calculating the result depends on the inputs. In [2] a constant time modification of the Montgomery modular inverse algorithm was proposed that can prevent Simple Power Analysis attacks. The main idea in [2] is to calculate an inverse by performing always the same number of constant time iterations. This algorithm for inverse calculculation is also very fast. It requires for example only 4(224 1) iterations, i.e. 892 clock cycles, for calculation of an inverse elment of GF(p) for the NIST EC P-224. Due to this fact we implemented this modular inverse algorithm in VHDL according to the Algorithm 2 as it is given in [2]. We tested the functionality of our design using Cadence SimVision and we simulated its power traces for different inputs using Synopsys PrimeTime for the IHP 250nm technology. Despite the fact that author of [2] claims a constant calculation time for any inversion, it can be easily seen that after several numbers of iterations dependent on the processed input the values of intermediate variables are not changing anymore and the power consumption of the design is reduced significantly. Thus, the execution time of each inverse calculation can be easy estimated analysing the measured power trace, i.e. the algorithm proposed in [2] cannot prevent time and power analysis attacks.
Proposal for Integrating Existing Measures Measuring the ‘ Bridging ’ versus ‘ Bonding ’ Nature of Social Networks : A

Recent research illustrates that two distinct interpretations and operationalizations of ‘bridging’ and ‘bonding’ social networks co-exist in the literature (based on links between diverse networks or between socio-economic groups within a given network, respectively), and that these do not coincide in empirical applications. The present contribution first confirms this conclusion using data from the United Kingdom. Then, we suggest a simple way to integrate both existing approaches into a more general measure of bridging and bonding. Applying this more general index to UK and Flemish data, a) provides stronger empirical support for the idea that memberships in bridging groups are more strongly linked to positive civic values than those in bonding ones, and b) shows that the extended index behaves more consistently across institutional settings (i.e. Flanders and the UK) than both underlying measures independently.
COMPARISON OF SEOI-NAGE TECHNIQUE FOR JUDO ATHLETES OF DIFFERENT SKILL LEVELS

The purpose of the present study was to compare the biomechanics parameters of seoinage in judo between highly skilled judo athletes and skilled ones. The motion data of the seoi-nage were collected on three male elite judo athletes and sixteen male student judo athletes using a three-dimensional motion analysis technique. This study found that the anterior-posterior component of the ankle and hip peak velocity of the tori in turning phase were significantly larger in the highly skilled group than the skilled group. In addition, the peak velocities of the ankle and hip were significantly correlated to the peak angular momentum of the tori. The results suggested that it would be useful for judo coaches to pay a greater attention to linear velocity of the lower extremities to evaluate the seoi-nage skill than the knee extension.
Wireless Sensor Networks and Their Applications : Where Do We Stand ? And Where Do We Go ?

Research on wireless sensor networks has been ongoing for more than 15 years. As a result, an enormous number of novel ideas have been proposed in academic and industrial research since then. These comprise the design of new hardware components, novel communication and processing regimes, and the realization of systems that would have been unimaginable before wireless sensor networks came into existence. The resulting application areas are broad, ranging from deployments of a few low-cost sensor nodes to the installation of large numbers of highly specialized sensing systems. In this paper, we summarize wireless sensor network application trends and point out future directions and emerging novel application domains that bear high research potential.
Conditional Computation in Deep and Recurrent Neural Networks

Recently, deep learning models such as convolutional and recurrent neural networks have displaced state-of-the-art techniques in a variety of application domains. While the computationally heavy process of training is usually conducted on powerful graphics processing units (GPUs) distributed in large computing clusters, the resulting models can still be somewhat heavy, making deployment in resourceconstrained environments potentially problematic. This work is concerned with the idea of conditional computation, where the model is given the capability to learn how to avoid computing parts of the graph. This allows for models where the number of parameters (and in a sense, the model’s capacity to learn) can grow at a faster rate than the computation that is required to propagate information through the graph. Two cases of conditional computation are explored – in the feed forward case, a technique is developed that trades off accuracy for potential computational benefits, and in the recurrent case, techniques that yield practical speed benefits on a language modeling task are demonstrated. Given the rapidly expanding domain of problems where deep learning proves useful, the work presented here can help enable the future scalability requirements of deploying trained models.
Appendix to Vision-based Navigation with Language-based Assistance via Imitation Learning with Indirect Intervention 1

We would like thank to Microsoft Research Redmond interns Xin Wang, Ziyu Yao, Shrimai Prabhumoye, Shi Feng, Amr Sharaf, Chen Zhao, and Evan Pu for useful discussions. We are grateful also to Michel Galley and Hal Daumé III for their advice and support. Special thanks goes to Vighnesh Shiv for his meticulous review of the paper. We also greatly appreciate the CVPR reviewers for their thorough and insightful comments.
DupNet: Towards Very Tiny Quantized CNN With Improved Accuracy for Face Detection

Deploying deep learning based face detectors on edge devices is a challenging task due to the limited computation resources. Even though binarizing the weights of a very tiny network gives impressive compactness on model size (e.g. 240.9 KB for IFQ-Tinier-YOLO), it is not tiny enough to fit in the embedded devices with strict memory constraints. In this paper, we propose DupNet which consists of two parts. Firstly, we employ weights with duplicated channels for the weight-intensive layers to reduce the model size. Secondly, for the quantization-sensitive layers whose quantization causes notable accuracy drop, we duplicate its input feature maps. It allows us to use more weights channels for convolving more representative outputs. Based on that, we propose a very tiny face detector, DupNet-Tinier-YOLO, which is 6.5x times smaller on model size and 42.0% less complex on computation and meanwhile 2.4% higher detection than IFQ-Tinier-YOLO. Comparing with the full precision Tiny-YOLO, our DupNet-Tinier-YOLO gives 1,694.2x and 389.9x times savings on model size and computation complexity respectively with only 4.0% drop on detection rate (0.880 vs. 0.920). Moreover, our DupNet-Tinier-YOLO is only 36.9 KB, which is the tiniest deep face detector to our best knowledge.
Dichromatic Model Based Temporal Color Constancy for AC Light Sources

Existing dichromatic color constancy approach commonly requires a number of spatial pixels which have high specularity. In this paper, we propose a novel approach to estimate the illuminant chromaticity of AC light source using high-speed camera. We found that the temporal observations of an image pixel at a fixed location distribute on an identical dichromatic plane. Instead of spatial pixels with high specularity, multiple temporal samples of a pixel are exploited to determine AC pixels for dichromatic plane estimation, whose pixel intensity is sinusoidally varying well. A dichromatic plane is calculated per each AC pixel, and illuminant chromaticity is determined by the intersection of dichromatic planes. From multiple dichromatic planes, an optimal illuminant is estimated with a novel MAP framework. It is shown that the proposed method outperforms both existing dichromatic based methods and temporal color constancy methods, irrespective of the amount of specularity.
Approximate Leading One Detector Design for a Hardware-Efficient Mitchell Multiplier

We propose two approximate leading one detector (LOD) designs and an approximate adder (for summing two logarithms) that can be used to improve the hardware efficiency of the Mitchell logarithmic multiplier. The first LOD design uses a single fixed value to approximate the ‘d’ least significant bits (LSBs). For d=16 this design reduces the hardware cost by 19.91% compared to the conventional 32-bit Mitchell multiplier and by 15.19% when compared to a recent design in the literature. Our design is smaller by 32.33% and more energy-efficient by 56.77% with respect to a conventional Mitchell design. The second design partitions the ‘d’ bits into smaller fields and increases the accuracy by using a multiplexing scheme that selects a closer approximation to the actual input value. This design reduces the hardware cost by 17.98% compared to the original Mitchell multiplier and by 13.15% when compared to the other recent design. Our design is smaller by 29.17% and more energy-efficient by 56.18% with respect to the conventional Mitchell design. In the approximate adder, the ‘m’ least significant bits are set to a fixed bias of alternating ones and zeros. The optimal values of ‘d’ and ‘m’ are chosen to preserve the full accuracy of the conventional Mitchell multiplier while reducing the hardware cost. The new designs produce increased signed errors for inputs less than or equal to 216 but for larger numbers the accuracy is equal to that of the conventional Mitchell multiplier. The approximation affects only the $2^{16} -1$ smallest input values out of $2^{32} -1$. The new approximate multipliers are suitable for applications where approximation errors affecting the least significant digits can be tolerated.
Integrating Voice Commands for Software Modelling using UML on a Smart Board

Software modelling on a Smart board is a fairly new approach and using the same interaction modalities as on a computer might not be the most efficient way. The software modelling process could potentially be improved by integrating voice recognition for some of its functions. We implemented voice commands to a software modelling tool and let 14 variously experienced students test it and reflect on the possibilities of using this tool in the future. Our results will show that the Smart board presents a good environment for collaborative work and that the voice commands can eliminate the need for using a keyboard and thus making the process more efficient and interactive. Keywords—Software Engineering, Smart Board, Voice Recognition, UML-Modeling
Recommendations as Imperative Propositions in the Operation of Abductive Reasoning: Peirce and Beyond

: Peirce’s explicit directive that abductions must “recommend a course of action” (1909: MS 637: 12) is in line with his increasing pragmatic emphasis. This recommendation is not generated consequent to extensive deliberation; rather it arises spontaneously (CP 5.181). This spontaneous reasoning emerges in a “flash” to preclude any contrivance from infecting the recommendation. The present account proposes that it is recommendations for courses of action as imperatives which drive abductive reasoning: finding/recommending best practices, rather than engaging in interrogative strategies alone. It highlights how children’s event judgments acquire an action-based, social force, recommending a course of action for another. Diverse participation in social role-taking provides the instinct to correctly guess the conduct and thoughts of the participant-holders. Abductive endeavors require proposing retroductions of participant’s past habits (preferences/conduct). The insight to propose a recommendation for a viable course of action ultimately derives from self-participation as well as anticipation of others’ epistemic complexions toward expected event involvement.
RECIPIENT ' S CATALOG NUMBER Coordination of Freeway Ramp Meters and Arterial Traffic Signals Phase IIA – Site Selection and Simulation Development

The independent operation of freeway ramp meters and the adjacent arterial traffic signals often causes queue spillback on the freeway on-ramps and the surface street network that result in activation of queue override, which negates the benefits of ramp metering. The objectives of this study are to develop and implement a control algorithm for coordinated operation of metered freeway on-ramps and adjacent signalized intersections. The report describes the research performed in phase IIA of the project: development of a control algorithm, test site selection, and evaluation of a proposed algorithm on the test site through simulation. The field implementation and testing of the proposed algorithm at the selected test site will take place in the upcoming phase IIB of the project. A control algorithm was developed and evaluated at a real-world test site. The algorithm considers the available on-ramp storage and dynamically reduces the cycle length in order to avoid on-ramp queue spillback and mitigate unnecessary delay in the conflicting directions. The simulation results show the proposed coordination strategy eliminated the queue spillback on the metered on-ramps that activate the queue override. This resulted in 17.9% reduction on freeway delay. The analysis of field data on bottleneck discharge flows indicate that the proposed strategy may improve the freeway capacity by 5 to 10 percent. The delay on the parallel arterial was increased on the approaches feeding the on-ramps but decreased on the rest of the signal controlled approaches. The system-wide delay was reduced by 7 percent.
Attention Distribution and Trust in Higher Levels of Automation within Air Traffic Control

Air traffic control (ATC) is constantly changing and developing to handle more traffic and increase fuel efficiency among aircrafts, but still maintain a highly safe environment. The levels of automation are increasing to respond to the new demands and challenges, but this comes with an uncertainty for the automation behavior. Situation awareness and attention distribution for the operators are important factors to maintaining control and trust within automation. This paper presents findings from one case study including distributed attention and trust in automation within ATC. An approach on how to investigate trust in higher levels of automation is then proposed. Further, this paper will also present an approach on how to proceed with future research in this area, and the importance of investigating trust in automation and levels of automation in all domains of air traffic control. Keywords-component; air traffic control, levels of automation, attention distribution, trust in automation
Super-resolution Reconstruction Method Based on Wavelet Domain and Compressive Sensing

In order to improve the effect of image super-resolution reconstruction,a super-resolution reconstruction method based on wavelet domain and compressive sensing is proposed in this paper.Firstly,wavelet transform is used to decompose the low resolution images and get the low frequency and high frequency sub bands,and then the low resolution frequency sub bands and the high frequency sub bands of image are reconstructed respectively by compressed sensing and get the final image reconstructed by the wavelet inverse transform.Finally,the simulation experiments are carried out to test performance on the platform of MATLAB2012.The results show that,compared with other image reconstruction methods,the proposed method not only can obtain better reconstruction image visual effect,enhance the low resolution image reconstruction quality,but also improve the efficiency of image reconstruction,can meet the real-time,online requirement of image processing.
Foreword: Drought complexity and assessment under climate change conditions

Drought is one of the most complex climate hazards, affecting several natural systems and socioeconomic sectors (Wilhite, 2000). This makes that although several studies have focused on droughts conceptual issues (Wilhite and Glantz, 1985), it is really impractical to establish an unique definition of this phenomenon (Lloyd-Hughes, 2014). Drought is usually detected when an impact is recorded. It may refer to damages in agriculture (crop yield reductions), ecological impacts (tree decay and/or mortality), but it may also be related to a hydrological dimension, associated to reductions in streamflow, reservoir storages or groundwater decreases (Van Loon, 2015). Drought conditions in different systems may coincide or not in space and time, which makes even more complex the drought characterization and analysis.
bserving system simulations for small satellite formations stimating bidirectional reflectance

The bidirectional reflectance distribution function (BRDF) gives the reflectance of a target as a function of illumination geometry and viewing geometry, hence carries information about the anisotropy of the surface. BRDF is needed in remote sensing for the correction of view and illumination angle effects (for example in image standardization and mosaicing), for deriving albedo, for land cover classification, for cloud detection, for atmospheric correction, and other applications. However, current spaceborne instruments provide sparse angular sampling of BRDF and airborne instruments are limited in the spatial and temporal coverage. To fill the gaps in angular coverage within spatial, spectral and temporal requirements, we propose a new measurement technique: Use of small satellites in formation flight, each satellite with a VNIR (visible and near infrared) imaging spectrometer, to make multi-spectral, near-simultaneous measurements of every ground spot in the swath at multiple angles. This paper describes an observing system simulation experiment (OSSE) to evaluate the proposed concept and select the optimal formation architecture that minimizes BRDF uncertainties. The variables of the OSSE are identified; number of satellites, measurement spread in the view zenith and relative azimuth with respect to solar plane, solar zenith angle, BRDF models and wavelength of reflection. Analyzing the sensitivity of BRDF estimation errors to the variables allow simplification of the OSSE, to enable its use to rapidly evaluate formation architectures. A 6-satellite formation is shown to produce lower BRDF estimation errors, purely in terms of angular sampling as evaluated by the OSSE, than a single spacecraft with 9 forward-aft sensors. We demonstrate the ability to use OSSEs to design small satellite formations as complements to flagship mission data. The formations can fill angular sampling gaps and enable better BRDF products than currently
The Cleansing Effect of Banking Crises

We assess the cleansing effects of the recent banking crisis. In U.S. regions with higher levels of supervisory forbearance on distressed banks during the crisis, there is less restructuring in the real sector and the banking sector remains less healthy for several years after the crisis. Regions with less supervisory forbearance experience higher productivity growth after the crisis with more firm entries, job creation, and employment, wages, patents, and output growth. Supervisory forbearance is greater for state-chartered banks and in regions with weaker banking competition and more independent banks, while recapitalisation of distressed banks through TARP does not facilitate cleansing.
Information Systems for Sustainable Business Development

IT is likely to be as important to the way companies will organize in the future as electricity was to the industrial revolution. IT will revolutionize entire industries and markets. IT will create new types of organizations that will surpass and outsmart traditional organizations. This has been predicted for more than a decade. But now it is happening especially in the music, newspaper and publishing industries, and shall see it even more pronounced in these sectors in the future. But it will not be limited to these industries; it will influence all types of industry and government organizations. Already today, we see many examples of innovative organizational designs, enhancing organizational effectiveness and competitiveness. The paper will briefly discuss the potential of future IT developments, and will proceed to give a short theoretical background for why we see a growth in IT-facilitated new organizational forms. A couple of interesting organizational design will be mentioned, before we proceed to making the argument that any business process in principle may be reengineered, centralized or outsourced in one way or other. Interesting examples will be presented. We suggest that future IT will have such a profound impact on organizational structure going far beyond the traditional „virtual organization‟ that it calls for a new organizational concept, which we have chosen to label the “Ambient Organization‟.
Multi-Levels Image Encryption Technique based on Multiple Chaotic Maps and Dynamic Matrix

The rapid development in internet technologies and applications have led to great increase in the amount of information sent and received electronically. Transmitting information on networks have become insecure because of new threats continue to evolve. This research aims to provide an efficient technique with highly protection degree of secret images being transmitted “in a meaningless form” over a communication channel through the use of chaotic maps by taking its advantages over other methods of encryption. Chaotic based encryption algorithm is employed at the present time because of its best security and good performance according to the random sequences that are generated from nonlinear system in a high speed calculations. The obtained results from the experimental tests proved that the proposed encryption algorithm is a powerful and efficient technique according to the higher (Entropy ≤ 8) and (Correlation ≤ 1) with perfect reconstruction of the decryption image.
THE EFFECT OF STUTTERING AND FLUENCY- ENHANCING CONDITIONS ON A MANUAL MOVEMENT TASK

I am submitting herewith a thesis written by Mary Rhodes Robbins entitled “The Effect of Stuttering and Fluency-enhancing Conditions on a Manual Movement Task. ” I have examined the final electronic copy of this thesis for form and content and recommend that it be accepted in partial fulfillment of the requirements for the degree of Master of Arts with a major in Speech Pathology. Tim Saltuklaroglu Major Professor We have read this thesis and recommend its acceptance: