nils-herrmann/clean_scirepeval huggingface dataset:
Orientation Modulation for Data Hiding in Clustered-Dot Halftone Prints

We present a new framework for data hiding in images printed with clustered dot halftones. Our application scenario, like other hardcopy embedding methods, encounters fundamental challenges due to extreme bilevel quantization inherent in halftoning, the stringent requirements of image fidelity, and other unavoidable printing and scanning distortions. To overcome these challenges, while still allowing for automated extraction of the embedded data and a high embedding capacity, we propose a number of innovations. First, we perform the embedding jointly with the halftoning by employing an analytical halftone threshold function that allows steering of the halftone spot orientation within each halftone cell based upon embedded data. In this process, image fidelity is emphasized and, if necessary, the capability to recover individual data values is sacrificed resulting in unavoidable erasures and errors. To overcome these and other sources of errors, we propose a suitable data detection and error control methodology based upon a statistical representation for the print-scan channel that effectively models the channel dependence upon the cover image gray-level. To combat the geometric distortion inherent in the print-scan process, we exploit the periodic halftone structure to recover from global scaling and rotation and propose a novel decision directed synchronization technique that counters locally varying printing distortion. Experimental results demonstrate the power of the proposed framework: we achieve high operational rates while preserving halftone image quality.
Scalable Nonlinear Embeddings for Semantic Category-Based Image Retrieval

We propose a novel algorithm for the task of supervised discriminative distance learning by nonlinearly embedding vectors into a low dimensional Euclidean space. We work in the challenging setting where supervision is with constraints on similar and dissimilar pairs while training. The proposed method is derived by an approximate kernelization of a linear Mahalanobis-like distance metric learning algorithm and can also be seen as a kernel neural network. The number of model parameters and test time evaluation complexity of the proposed method are O(dD) where D is the dimensionality of the input features and d is the dimension of the projection space -- this is in contrast to the usual kernelization methods as, unlike them, the complexity does not scale linearly with the number of training examples. We propose a stochastic gradient based learning algorithm which makes the method scalable (w.r.t. the number of training examples), while being nonlinear. We train the method with up to half a million training pairs of 4096 dimensional CNN features. We give empirical comparisons with relevant baselines on seven challenging datasets for the task of low dimensional semantic category based image retrieval.
Design and modeling of a protein based nanoGripper

The design hypothesis, architectures, and computational modeling of a novel peptide based nanoGripper are presented in this paper. We engineered the alpha-helical coiled coil portion of the yeast transcriptional activator peptide called GCN4 to obtain an environmentally-responsive nanoGripper. The dimeric coiled-coil peptide consists of two identical ~4.5nm long and ~3nm wide polypeptide chains. The actuation mechanism depends on the modification of electrostatic charges along the peptide by varying the pH of the solution resulting in the reversible movement of helices and therefore, creating the motion of a gripper. Using molecular dynamics simulations we showed that pH changes led to a reversible opening of up-to 1.5 nm which is approximately 150 % of the initial separation of the nanoGripper. We also investigated the forces generated by the nanoGripper upon pH actuation. Using a new method based on a modified steered molecular dynamics technique we were able to show that the force output of the nanoGripper is comparable to that generated by ATP-based molecular motors such as myosin and kinesin even though our molecular tweezer is smaller in size to these molecular motors.
Thermal modeling and characterization of the embedded micro wafer level package (EMWLP) at the package- and system-level

In this paper, package-level thermal modeling of the embedded micro-wafer-level-packaging (EMWLP) package has been performed to extract the parametric trends for thermal design guidelines of an eccentric single active die embedded alongside an integrated passive device (IPD), as shown in Fig.1 (with optional heat sink as a cooling solution). Exploratory thermal resistance modeling of an embedded two-die-stack has also been conducted. The effect of the mold compound used in the thermal models is further considered under the following parameters: mold thickness and thermal conductivity (0.4 W/mK to 2.5 W/mK). The effects of heat spreaders and heat sinks on the package thermal resistance are also studied, with due consideration paid to the above mold parameters. Furthermore, experimental characterization has been conducted to validate the package-level simulation for the single active die model, conforming to the JEDEC JESD 51-2A Thermal Measurements in Natural Convection standard. Finally, simulation results for a general system-level thermal modeling in both cellphone as well as laptop systems are also performed. Thermal management solutions for both scenarios, such as thermal vias and heat spreaders, are studied, with an optimal cooling solution proposed.
Design of 3 stage low noise operational amplifier

In this paper a high gain low noise Op-Amp has been designed. In designing of a high gain Op-Amp, for large values of coupling capacitor, gain will decrease. Since our requirement was to increase the gain, so we have designed a three stage Op-Amp. Our designed circuit provides gain of 78.4 dB, which is very much larger than two stage Op-Amp. There is a trade-off between various parameters like Phase margin, gain, slew rate etc. For example, to achieve larger values of GBW, PM will decrease. We have compared the results for two values of input common mode range. Improvement in the designed circuit is done to achieve the desired GBW by recalculating the transistor's W/L ratios and then simulating the results. Gain Bandwidth product of 176.9 MHz and Phase Margin greater than 60 degrees is achieved but at the cost of power dissipation and area. The Op-Amp is designed in gpdk 180 nm CMOS technology.
End-to-End Channel Assurance for Communication over Open Voice Channels

Voice channels are commonly utilized in a wide variety of communication and control scenarios that span the gamut of applications ranging from military and commercial aviation to emergency response applications. Often the existing equipment for these applications utilizes openly accessible voice communication systems that offer no assurance of data security or integrity. It is possible to secure the systems with encryption but this would require significant new investments and introduce interoperability problems with existing equipment. As an alternative, we propose an in-band methodology for end-to-end channel assurance in these scenarios based on speech watermarking. Our speech watermark is resilient to low-bit rate coding standards commonly used in these voice communication applications and in mobile telephony and digital voice-over-IP (VoIP).
Q-SIFT: Efficient feature descriptors for distributed camera calibration

We consider camera self-calibration, i.e. the estimation of parameters for camera sensors, in the setting of a visual sensor network where the sensors are distributed and energy-constrained. With the objective of reducing the communication burden and thereby maximizing network lifetime, we propose an energy-efficient approach for self-calibration where feature points are extracted locally at the cameras and efficient descriptions for these features are transmitted to a central processor that performs the self-calibration. Specifically, in this work we use reduced-dimensionality quantized approximations as efficient feature descriptors. The effectiveness of the proposed technique is validated through feature matching, and epipolar geometry estimation which enable self-calibration of the network.
Comparison of Flooding and Directed Diffusion for Wireless Sensor Network

A Wireless Sensor Network (WSN) is a collection of thousands of tiny sensor nodes having the capability of wireless communication, limited computation and sensing. In this paper, all the components of a sensor node are discussed in brief. Also, a comparison of two routing protocols Flooding and Directed Dif- fusion on the basis of throughput, energy consumption and net- work lifetime is presented. Keywords-component; Wireless Sensor Networks; flooding; directed diffusion
Numerical analysis of flow field over compound delta wing at subsonic and supersonic speeds

A great number of supersonic aircrafts use delta wings. Since 1950, delta wings have been studied well and it has been observed that there appear two large counter-rotating leading edge vortices when delta wing structure flies at high angles of attack. These vortices are responsible for additional lift and they also provide a very high stall incidence to the wing. At high Mach numbers, compressibility advances leading edge separation and also expands the magnitude of the primary vortex. Shock waves appearing due to high-speed flow over the delta wing result in drastic changes in the flow characteristics. Although supersonic jets use delta wing configurations but most of the time they fly at subsonic speeds and hence the focus of present study is on both subsonic as well as supersonic regimes. The present study consist of numerical simulations of the flow-field over a compound delta wing at various Mach numbers ranging from 0.3 to 2.0 and angles of attack ranging from 0° to 15° using the computational model established in previous research . Reynolds Averaged Navier-Stokes (RANS) based steady-state computations were carried out. Spalart Allmaras (SA) turbulence model is considered due to its less computational cost and good performance for simulating external flows. Since the study involves supersonic Mach numbers, compressibility was also incorporated in the computational model. The study with various freestream Mach numbers shows that there is a sudden change in flow fields with an increase in the Mach number for the range of 0.8 to 1.3. The flow near to the delta wing surface beneath the primary vortex becomes completely supersonic and shock waves appear when the flow reaches Mach number 0.85. Due to this shock wave formation, flow fields become more complex. At high Mach number because of the stronger magnitude of the primary vortex which prevents the evolution of the inner separation, the secondary vortex disappears. The results also confirm the hypothesis of vortex breakdown which is also responsible for the nonlinear behavior of flow characteristics over the wing when there is an increase in Mach number.
A joint learning approach for cross domain age estimation

We propose a novel joint learning method for cross domain age estimation, a domain adaptation problem. The proposed method learns a low dimensional projection along with a re-gressor, in the projection space, in a joint framework. The projection aligns the features from two different domains, i.e. source and target, to the same space, while the regressor predicts the age from the domain aligned features. After this alignment, a regressor trained with only a few examples from the target domain, along with more examples from the source domain, can predict very well the ages of the target domain face images. We provide empirical validation on the largest publicly available dataset for age estimation i.e. MORPH-II. The proposed method improves performance over several strong baselines and the current state-of-the-art methods.
Characterization of DAF tape for embedded micro wafer level packaging

The requirements of new packaging technologies for smaller, thinner and lighter electronics products have resulted in electronics industry moving towards wafer level packaging. Some of the main advantages of wafer level packaging are suitability for very fine pitch interconnection, low assembly cost and smaller form factor. This is because the package formed through wafer level technology has the same size as the die itself. Wafer level packaging is in demand especially for portable products such as mobile phone and digital camera. With wafers thinned to 100µm, conventional die attach process may not be suitable as the control of bleed out of the die attached paste becomes critical. New generation of die attach material such as the Dicing Die attach film (DDAF) is introduced to control the paste bleed at the die edge as well as to have a consistent bondline thickness. This paper presents the results of DDAF tape lamination on 100µm thin wafer, DDAF tape dicing process characterization and materials characterization in terms of die shear test of 2 DDAF tapes after die attach process and after subjecting to Moisture Sensitivity test Level 3. A three-factor D.O.E (bonding pressure, bonding temperature and bonding time) adopted to understand the dominant contributing factors on DDAF tape bonding process and to understand the effects of bonding parameters on the DDAF bondline thickness and DDAF voids (Table 1). The 3 selected bond forces range from 0.5kg to 2.5kg. Reliability of the DDAF assembly will also be studied and reported in this work.
Localization Technique for Lost Node in Geo-Location

The use of location based authentication services has seen a sudden boom with the reduced cost of GPS hardware and small size-factors. However, the drawbacks associated with the GPS related services makes it infeasible to incorporate GPS in all the mobile nodes (MN) and subject to availability of GPS signals. This demands for alternatives that can be used directly or indirectly in place of GPS for geo-localization of a lost node or a mobile node with no GPS capability. A number of such techniques has been proposed for non-GPS dependent localization of wireless nodes. Some of these can be used directly or indirectly for geo-localizing lost nodes. We present a comparative study of these techniques on the basis of several metrics such as complexity, additional hardware requirement, efficiency, operative field etc.
Design and validation of a robotic subsea winch with minimal sensor feedback

Teledyne SeaBotix is developing a robotic subsea winch to be used in deep deployments of an observation class (20kg) ROV to 4000 m depths. The subsea winch system can be incorporated in a self-contained launch and recovery system or via larger vehicles like work class ROVs or submarines. High reliability is an underlying design objective in subsea systems due to the very high cost of downtime or system failure. These objectives translate into a design criteria to minimize potential system failure points including: connectors, cables, and housings. Particularly of concern are connectors that have a high risk of being misused, damaged, or worn-out causing catastrophic failures. Advancements in sensor technology and related monitoring algorithms can be used to reduce if not eliminate the need of electromechanical sensors for feedback. This paper discusses a system design which incorporates novel sensing techniques to remove numerous sensors on the subsea winch while maintaining the same performance as if they were still there. The system benefits from size reduction, cost reduction and an increase in reliability, while maintaining equal performance.
Watermark Synchronization for Feature-Based Embedding: Application to Speech

We propose a novel framework for synchronization in feature-based data embedding systems. The framework is tolerant to de-synchronizing errors in feature estimates, which have hitherto crippled feature-based embedding methods. The method uses a concatenated coding system comprising of an outer q-ary LDPC code and an inner insertion-deletion code to recover from both de-synchronization caused by feature estimation discrepancies between the transmitter and receiver; and errors in estimated symbols arising from other channel perturbations. We illustrate the framework in a speech watermarking application employing pitch modification for data-embedding. We show that the method indeed allows recovery of watermark data even in the presence of de-synchronization errors in the underlying pitch-based embedding. The resilience of the method is also demonstrated over channels employing low bit rate speech encoders
Adaptive decoding for halftone orientation-based data hiding

Halftone image watermarking techniques that allow automated extraction of the embedded watermark data are useful in a variety of document security and workflow applications. The print-scan process inherent in these applications introduces distortions whose characteristics exhibit a strong spatial dependence on the cover image in which the data is embedded. In this paper, we demonstrate that a characterization of this channel dependence and the use of error correction coding that exploits this dependence via image adaptive decoding offers a significant performance gain. We show this advantage in the specific context of a high rate data embedding method that utilizes orientation modulation for data embedding in clustered dot halftones and moment based detection at the receiver. Channel coding for this scenario utilizing convolutional codes and Repeat Accumulate (RA) codes highlights the advantage of the proposed adaptive decoding methodology. The performance for the RA codes with adaptive decoding also reveals that the resulting system has significantly higher operational rates than prior schemes.
Improved Low-Density Parity Check Accumulate (LDPCA) Codes

We present improved constructions for Low-Density Parity-Check Accumulate (LDPCA) codes, which are rate-adaptive codes commonly used for distributed source coding (DSC) applications. Our proposed constructions mirror the traditional LDPCA approach; higher rate codes are obtained by splitting the check nodes in the decoding graph of lower rate codes, beginning with a lowest rate mother code. In a departure from the uniform splitting strategy adopted by prior LDPCA codes, however, the proposed constructions introduce non-uniform splitting of the check nodes at higher rates. Codes are designed by a global minimization of the average rate gap between the code operating rates and the corresponding theoretical lower bounds evaluated by density-evolution. In the process of formulating the design framework, the paper also contributes a formal definition of LDPCA codes. Performance improvements provided by the proposed non-uniform splitting strategy over the conventional uniform splitting approach used in prior work are substantiated via density evolution based analysis and DSC codec simulations. Optimized designs for our proposed constructions yield codes with a lower average rate gap than conventional designs and alleviate the trade-off between the performance at different rates inherent in conventional designs. A software implementation is provided for the codec developed.
Multichannel Attention Network for Analyzing Visual Behavior in Public Speaking

We investigate the importance of human centered visual cues for predicting the popularity of a public lecture. We construct a large database of more than 1800 TED talk videos and leverage the corresponding (online) viewers' ratings from YouTube for a measure of popularity of the TED talks. Visual cues related to facial and physical appearance, facial expressions, and pose variations are learned using convolutional neural networks (CNN) connected to an attention-based long short-term memory (LSTM) network to predict the video popularity. The proposed overall network is end-to-end-trainable, and achieves state-of-the-art prediction accuracy indicating that the visual cues alone contain highly predictive information about the popularity of a talk. We also demonstrate qualitatively that the network learns a human-like attention mechanism, which is particularly useful for interpretability, i.e. how attention varies with time, and across different visual cues as a function of their relative importance.
High Capacity Color Barcodes: Per Channel Data Encoding via Orientation Modulation in Elliptical Dot Arrays

We present a new high capacity color barcode. The barcode we propose uses the cyan, magenta, and yellow (C,M,Y) colorant separations available in color printers and enables high capacity by independently encoding data in each of these separations. In each colorant channel, payload data is conveyed by using a periodic array of elliptically shaped dots whose individual orientations are modulated to encode the data. The orientation based data encoding provides beneficial robustness against printer and scanner tone variations. The overall color barcode is obtained when these color separations are printed in overlay as is common in color printing. A reader recovers the barcode data from a conventional color scan of the barcode, using red, green, and blue (R,G,B) channels complementary, respectively, to the print C, M, and Y channels. For each channel, first the periodic arrangement of dots is exploited at the reader to enable synchronization by compensating for both global rotation/scaling in scanning and local distortion in printing. To overcome the color interference resulting from colorant absorptions in noncomplementary scanner channels, we propose a novel interference minimizing data encoding approach and a statistical channel model (at the reader) that captures the characteristics of the interference, enabling more accurate data recovery. We also employ an error correction methodology that effectively utilizes the channel model. The experimental results show that the proposed method works well, offering (error-free) operational rates that are comparable to or better than the highest capacity barcodes known in the literature.
Hierarchical Origin and Path verification for securing inter-domain routing protocol

Border Gateway Protocol (BGP 4) has emerged as the de facto inter-domain routing protocol used for making the core routing decisions on the Internet. However, it is not a secured protocol and suffers from serious security flaws such as no Origin AS Prefix verification and no AS Path verification. These two flaws in the BGP protocol can result in the attacks such as Prefix Hijacking and AS_PATH Forgery. These flaws are present in BGP due to lack of mechanisms for validating the actual source and path of the BGP UPDATE message. Many alternatives for the BGP such as S-BGP, SoBGP, etc. have been proposed but they are not compatible with the BGP and we need to replace BGP completely with them. The proposed method is a complimentary protocol to the BGP and verifies the Origin AS and the AS_PATH advertised in the BGP UPDATE message. The proposed Hierarchical Origin & Path (HOP) Verification method can be deployed in the current setting and works along with BGP. It can also be deployed in a scalable manner and can also work along with the ASes which do not follow HOP Verification method, thereby, solving all the deployment issues.