nils-herrmann/clean_scirepeval huggingface dataset:
Broadcast Encryption

We introduce new theoretical measures for the qualitative and quantitative assessment of encryption schemes designed for broadcast transmissions. The goal is to allow a central broadcast site to broadcast secure transmissions to an arbitrary set of recipients while minimizing key management related transmissions. We present several schemes that allow a center to broadcast a secret to any subset of privileged users out of a universe of size so that coalitions of users not in the privileged set cannot learn the secret. The most interesting scheme requires every user to store keys and the center to broadcast messages regardless of the size of the privileged set. This scheme is resilient to any coalition of users. We also present a scheme that is resilient with probability against a random subset of users. This scheme requires every user to store keys and the center to broadcast messages.  1994, pp. 480–491. Dept. of Computer Science, School of Mathematics, Tel Aviv University, Tel Aviv, Israel, and Algorithmic Research Ltd. E-mail fiat@math.tau.ac.il. Incumbent of the Morris and Rose Goldman Career Development Chair, Dept. of Applied Mathematics and Computer Science, Weizmann Institute of Science, Rehovot 76100,  Research supported by an Alon Fellowship and a grant from the Israel Science Foundation administered by the Israeli Academy of Sciences. E-mail: naor@wisdom.weizmann.ac.il.
A Batteryless Sensor ASIC for Implantable Bio-Impedance Applications

The measurement of the biological tissue's electrical impedance is an active research field that has attracted a lot of attention during the last decades. Bio-impedances are closely related to a large variety of physiological conditions; therefore, they are useful for diagnosis and monitoring in many medical applications. Measuring living tissues, however, is a challenging task that poses countless technical and practical problems, in particular if the tissues need to be measured under the skin. This paper presents a bio-impedance sensor ASIC targeting a battery-free, miniature size, implantable device, which performs accurate 4-point complex impedance extraction in the frequency range from 2 kHz to 2 MHz. The ASIC is fabricated in 150 nm CMOS, has a size of 1.22 mm × 1.22 mm and consumes 165 μA from a 1.8 V power supply. The ASIC is embedded in a prototype which communicates with, and is powered by an external reader device through inductive coupling. The prototype is validated by measuring the impedances of different combinations of discrete components, measuring the electrochemical impedance of physiological solution, and performing ex vivo measurements on animal organs. The proposed ASIC is able to extract complex impedances with around 1 Ω resolution; therefore enabling accurate wireless tissue measurements.
Trajectory planning for car-like vehicles: A modular approach

We consider the problem of trajectory planning with geometric constraints for a car-like vehicle. The vehicle is described by its dynamic model, considering such effects as lateral slipping and aerodynamic drag. We propose a modular solution, where three different problems are identified and solved by specific modules. The execution of the three modules can be orchestrated in different ways in order to produce efficient solutions to a variety of trajectory planning problems (e.g., obstacle avoidance, or overtake). As a specific example, we show how to generate the optimal lap on a specified racing track. The numeric examples provided in the paper are good witnesses of the effectiveness of our strategy.
Design of an ex-proof untethered in-pipe inspection robot

In this work, the design of a natural gas pipeline inspection robot that generates energy from gas flow, performs onboard image processing and handles propulsion through biometal fiber (BMF) driven arms is presented. For an in-pipe inspection of an explosive gas filled pipe to be performed properly in real operational conditions, the robot should be free of external cable to prevent gas leakage from the pipe, ex-proof to prevent any spark that can lead to a fire or explosion, and adaptive to highly varying pipe diameters and tight curvatures on L and T joints. Novel solutions that address the mentioned requirements are proposed for systems of propulsion, energy source, data acquisition and communication. Design of robot that combines all these solutions is explained in detail.
Mechanical design of a novel Hand Exoskeleton for accurate force displaying

This paper deals with the mechanical design of a novel haptic Hand Exoskeleton (HE) that allows exerting controlled forces on the fingertip of the index and thumb of the operator. The proposed device includes several design solutions for optimizing the accuracy and mechanical performances. Remote Centers of Motion mechanisms have been adopted for delocalizing the encumbrance of linkages of the structure away from the operator's fingers. An improved stiffness of the transmission and reduced requirements for the actuators have been achieved thanks to a novel Patent Pending principle for integrating speed reduction ratio with the transmission system.
Adaptive Estimation Approach for Parameter Identification of Photovoltaic Modules

This paper presents a novel identification technique for estimation of unknown parameters in photovoltaic (PV) systems. A single-diode model is considered for the PV system, which consists of five unknown parameters. Using information about standard test conditions, three unknown parameters are written as functions of the other two parameters in a reduced model. An objective function and a set of inequality constraints are defined for the reduced model, considering limitations of the physical system. It is shown that the nonconvex optimization problem of PV systems is converted to a convex optimization one. The constraints are enforced using a modified barrier function that generates an augmented convex objective function. An adaptive identification technique is utilized to find the optimal values of the augmented cost. Unlike most identification techniques, the proposed algorithm has a precise and unique solution, which is easy to implement. The effectiveness of the proposed approach is confirmed using some simulation and experiments.
SnakeFighter - Development of a Water Hydraulic Fire Fighting Snake Robot

This paper presents the SnakeFighter concept and describes the generic element within this concept in the form of a water hydraulic snake robot. Applications of a SnakeFighter system are presented with focus on fire intervention tasks. The development of a water hydraulic snake robot that demonstrates the concept is described. The robot is the first water hydraulic snake robot ever constructed. The paper identifies design challenges of a complete SnakeFighter system and describes future research on this concept
Pruning ConvNets Online for Efficient Specialist Models

Convolutional neural networks (CNNs) excel in various computer vision related tasks but are extremely computationally intensive and power hungry to run on mobile and embedded devices. Recent pruning techniques can reduce the computation and memory requirements of CNNs, but a costly retraining step is needed to restore the classification accuracy of the pruned model. In this paper, we present evidence that when only a subset of the classes need to be classified, we could prune a model and achieve reasonable classification accuracy without retraining. The resulting specialist model will require less energy and time to run than the original full model. To compensate for the pruning, we take advantage of the redundancy among filters and class-specific features. We show that even simple methods such as replacing channels with mean or with the most correlated channel can boost the accuracy of the pruned model to reasonable levels.
Designing core ontologies

One of the key factors that hinders integration of distributed, heterogeneous information systems is the lack of a formal basis for modeling the complex, structured knowledge that is to be exchanged. To alleviate this situation, we present an approach based on core ontologies. Core ontologies are characterized by a high degree of axiomatization and formal precision. This is achieved by basing on a foundational ontology. In addition, core ontologies should follow a pattern-oriented design approach. By this, they are modular and extensible. Core ontologies allow for reusing the structured knowledge they define as well as integrating existing domain knowledge. The structured knowledge of the core ontologies is clearly separated from the domain-specific knowledge. Such core ontologies allow for both formally conceptualize their particular fields and to be flexibly combined to cover the needs of concrete, complex application domains. Over the last years, we have developed three independent core ontologies for events and objects, multimedia annotations, and personal information management. In this paper, we present the simultaneous use and integration of our core ontologies at the example of a complex, distributed socio-technical system of emergency response. We describe our design approach for core ontologies and discuss the lessons learned in designing them. Finally, we elaborate on the beauty aspects of our core ontologies.
Safety of Machine Learning Systems in Autonomous Driving

Machine Learning, and in particular Deep Learning, are extremely capable tools for solving problems which are difficult, or intractable to tackle analytically. Application areas include pattern recognition, computer vision, speech and natural language processing. With the automotive industry aiming for increasing amount of automation in driving, the problems to solve become increasingly complex, which appeals to the use of supervised learning methods from Machine Learning and Deep Learning. With this approach, solutions to the problems are learned implicitly from training data, and inspecting their correctness is not possible directly. This presents concerns when the resulting systems are used to support safety-critical functions, as is the case with autonomous driving of automotive vehicles. This thesis studies the safety concerns related to learning systems within autonomous driving and applies a safety monitoring approach to a collision avoidance scenario. Experiments are performed using a simulated environment, with a deep learning system supporting perception for vehicle control, and a safety monitor for collision avoidance. The related operational situations and safety constraints are studied for an autonomous driving function, with potential faults in the learning system introduced and examined. Also, an example is considered for a measure that indicates trustworthiness of the learning system during operation.
Compact Representation of Dynamic Driving Environments for ADAS by Parametric Free Space and Dynamic Object Maps

We present a novel parametric representation of general dynamic driving environments. It is particularly suitable for near-future Advanced Driver Assistance Systems due to its compactness, inherent consistency between static and dynamic entities, suppression of irrelevant details, as well as its sensor-independent, real-time capable generation. By building upon a common occupancy grid map-based environment representation, cells belonging to dynamic objects are simultaneously extracted, classified, and tracked in an object-based manner via an Interacting-MultipleModel-Unscented-Kalman-Probabilistic-Data-Association (IMM-UK-PDA) filter and cleared from the grid. The remaining static environment grid is subsequently processed by methods from the image analysis domain, followed by an Information Filter-based contour tracking of relevant free space boundaries to create a spatiotemporally smooth compact Parametric Free Space (PFS) map. The PFS map represents the static part of the traffic scene with modest bandwidth requirements. The system runs in real time on an experimental vehicle equipped with an automotive radar and a stereo camera and is evaluated within real traffic environments.
Deep EndoVO: A Recurrent Convolutional Neural Network (RCNN) based Visual Odometry Approach for Endoscopic Capsule Robots

Ingestible wireless capsule endoscopy is an emerging minimally invasive diagnostic technology for inspection of the GI tract and diagnosis of a wide range of diseases and pathologies. Medical device companies and many research groups have recently made substantial progresses in converting passive capsule endoscopes to active capsule robots, enabling more accurate, precise, and intuitive detection of the location and size of the diseased areas. Since a reliable real time pose estimation functionality is crucial for actively controlled endoscopic capsule robots, in this study, we propose a monocular visual odometry (VO) method for endoscopic capsule robot operations. Our method lies on the application of the deep Recurrent Convolutional Neural Networks (RCNNs) for the visual odometry task, where Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) are used for the feature extraction and inference of dynamics across the frames, respectively. Detailed analyses and evaluations made on a real pig stomach dataset proves that our system achieves high translational and rotational accuracies for different types of endoscopic capsule robot trajectories.
A wearable fingertip haptic device with 3 DoF asymmetric 3-RSR kinematics

A novel wearable haptic device for modulating skin stretch at the fingertip is presented. Rendering of skin stretch in 3 degrees of freedom (DoF), with contact - no contact capabilities, was implemented through rigid parallel kinematics. The novel asymmetrical three revolute-spherical-revolute (3-RSR) configuration allowed compact dimensions with minimum encumbrance of the hand workspace and minimum inter-finger interference. A differential method for solving the non-trivial inverse kinematics is proposed and implemented in real time for controlling the position of the skin tactor. Experiments involving the grasping of a virtual object were conducted using two devices (thumb and index fingers) in a group of 4 subjects: results showed that participants performed the grasping task more precisely and with grasping forces closer to the expected natural behavior when the proposed device provided haptic feedback.
The role of physical embodiment in human-robot interaction

Autonomous robots are agents with physical bodies that share our environment. In this work, we test the hypothesis that physical embodiment has a measurable effect on performance and perception of social interactions. Support of this hypothesis would suggest fundamental differences between virtual agents and robots from a social standpoint and have significant implications for human-robot interaction. We measure task performance and perception of a robot's social abilities in a structured but open-ended task based on the Towers of Hanoi puzzle. Our experiment compares aspects of embodiment by evaluating: (1) the difference between a physical robot and a simulated one; (2) the effect of physical presence through a co-located robot versus a remote tele-present robot. We present data from a pilot study with 12 subjects showing interesting differences in perception of remote physical robot's and simulated agent's attention to the task, and task enjoyment
Designing Media Architecture: Tools and Approaches for Addressing the Main Design Challenges

Media Architecture is reaching a level of maturity at which we can identify tools and approaches for addressing the main challenges for HCI practitioners working in this field. While previous influential contributions within Media Architecture have identified challenges for designers and offered case studies of specific approaches, here, we (1) provide guidance on how to tackle the domain-specific challenges of Media Architecture design -- pertaining to the interface, integration, content, context, process, prototyping, and evaluation -- on the basis of the development of numerous installations over the course of seven years, and thorough studies of related work, and (2) present five categories of tools and approaches -- software tools, projection, 3D models, hardware prototyping, and evaluation tools -- developed to address these challenges in practice, exemplified through six concrete examples from real-life cases.
Mutual Information Based Semi-Global Stereo Matching on the GPU

Real-time stereo matching is necessary for many practical applications, including robotics. There are already many real-time stereo systems, but they typically use local approaches that cause object boundaries to be blurred and small objects to be removed. We have selected the Semi-Global Matching (SGM) method for implementation on graphics hardware, because it can compete with the currently best global stereo methods. At the same time, it is much more efficient than most other methods that produce a similar quality. In contrast to previous work, we have fully implemented SGM including matching with mutual information, which is partly responsible for the high quality of disparity images. Our implementation reaches 4.2 fps on a GeForce 8800 ULTRA with images of 640×480 pixel size and 128 pixel disparity range and 13 fps on images of 320×240 pixel size and 64 pixel disparity range.
A Novel Self-Reference Technique for STT-RAM Read and Write Reliability Enhancement

Spin-transfer torque random access memory (STT-RAM) has demonstrated great potential in embedded and stand-alone applications. However, process variations and thermal fluctuations greatly influence the operation reliability of STT-RAM and limit its scalability. In this paper, we propose a new field-assisted access scheme to improve the read/write reliability and performance of STT-RAM. During read operations, an external magnetic field is applied to a magnetic tunneling junction (MTJ) device, generating a resistive sense signal without referring to other devices. Such a self-reference scheme offers a very promising alternative approach to overcome the severe cell-to-cell variations at highly scaled technology node. Furthermore, the external magnetic field can be used to assist the MTJ switching during write operations without introducing extra hardware overhead.
A critical review of blockchain and its current applications

Blockchain technology has been known as a digital currency platform since the emergence of Bitcoin, the first and the largest of the cryptocurrencies. Hitherto, it is used for the decentralization of markets more generally, not exclusively for the decentralization of money and payments. The decentralized transaction ledger of blockchain could be employed to register, confirm, and send all kinds of contracts to other parties in the network. In this paper, we thoroughly review state-of-the-art blockchain-related applications emerged in the literature. A number of published works were carefully included based on their contributions to the blockchain's body of knowledge. Several remarks are explored and discussed in the last section of the paper.
1 Coherence and Structure in Text and Discourse

Textual coherence versus discourse structure Coherence is one of the most general and most widely discussed concepts in the study of text and discourse In spite or perhaps because of its central status the concept of coherence has many di erent and often incompatible de nitions and connotations For text linguistics or psycholinguistics with their focus on the representation and processing of information in written texts coherence is predominantly a matter of semantics and domain knowledge while various brands of speech act and dialogue analysis describe coherence in terms of inten tions and interactional structures I will argue in subsection that the focus on and restriction to rather extreme discourse genres such as exposition on the one hand or highly interactive dialogues on the other causes an overemphasis on genre speci c characteristics at the expense of general properties common to all kinds of discourse Theories of discourse coherence then should be built and tested for a su ciently diverse variety of discourse types especially discourse that combines monologue and dialogue features In sections and of this paper I will present a framework for such a theory and two corpus analytical studies that support the notion that coherence should be thought of as con sisting of three parallel components ideational semantic structure rhetorical structure and sequential or segment structure
Uninvited Connections: A Study of Vulnerable Devices on the Internet of Things (IoT)

The Internet of Things (IoT) continues to grow as uniquely identifiable objects are added to the internet. The addition of these devices, and their remote connectivity, has brought a new level of efficiency into our lives. However, the security of these devices has come into question. While many may be secure, the sheer number creates an environment where even a small percentage of insecure devices may create significant vulnerabilities. This paper evaluates some of the emerging vulnerabilities that exist and puts some figures to the scale of the threat.
A Ka-Band CMOS Wilkinson Power Divider Using Synthetic Quasi-TEM Transmission Lines

This work presents a Ka-band two-way 3 dB Wilkinson power divider using synthetic quasi-transverse electromagnetic (TEM) transmission lines (TLs). The synthetic quasi-TEM TL, also called complementary-conducting-strip TL (CCS TL), is theoretically analyzed. The equivalent TL model, whose production is based on the extracted results, is applied to the power divider design. The prototype is fabricated by the standard 0.18 mum 1P6M CMOS technology, showing the circuit size of 210.0 mumtimes390.0 mum without contact pads. The measurement results, which match the 50 Omega system, reveal perfect agreements with those of the simulations. The comparison reveals the following characteristics. The divider exhibits an equal power-split with the insertion losses (S21 and S31) of 3.65 dB. The return losses (S11, S22 and S33) of the prototype are higher than 10.0 dB from 30.0 to 40.0 GHz.
PLC based DC drive control using Modbus RTU communication for selected applications of sugar mill

DC Drives are serving in industries with their efficient motion control ability. These Drives can operate in Local Mode as well as in Overriding Control mode. In Local Mode the Drive is controlled by its control panel where as in Overriding Control mode, it can be controlled remotely by a Programmable Logic Controller (PLC). This PLC based control of Drive is essential for process control in industries like Sugar Mill. Further, this control can be employed using any of the industrial communication protocols which reduce the wiring complexity. Modbus Remote Terminal Unit (RTU) is one such protocol which is open, robust and widely used in industries because of its simplicity. Therefore the same protocol has been implemented in the presented work. This paper depicts initially about configuring a DC Drive (DCS800 of ABB) for Modbus RTU communication and a preliminary test to verify the proper working of intermediate components and cables by communicating the Drive with PC using Modscan32 software. Later, the PLC and Drive communication details and development of ladder program are presented. Further, the results obtained from testing PLC-Drive communication considering the two applications of Sugar Mill are put forth. These ensure the successful implementation of PLC-Drive communication. The applications considered are; speed raise and lower of a DC motor by PLC and secondly, achieving a speed pattern (speed versus time graph) required by a process of Centrifugal Machine in Sugar Mill.