nils-herrmann/clean_scirepeval huggingface dataset:
CW Broad-Band Spatial Power Combiner Using Dense Finline Arrays

This paper presents a broad-band spatial powercombining system based on tapered-slot antenna arrays integrated in a standard WR-90 waveguide environment. The system is designed using a modular tray architecture, providing full waveguide-band frequency coverage and an excellent thermal environment for a set of monolithic-microwave integrated-circuit (MMIC) amplifiers. The shape of the tapered-slot or finline structures was optimized to minimize return loss and provide a broad-band impedance transformation from the waveguide mode to the MMIC amplifiers. A prototype eight-element array using commercial GaAs MMIC power amplifiers yielded a maximum of 41-W output power (continuous wave) with a gain variation less than 1.2 dB within the entire band of interest. The average combining efficiency over the operating band was estimated at 73%. The results suggest the efficacy of the design and a strong potential for higher powers by moving toward a greater number of MMIC’s per tray and a larger number of trays. Should the 100-W system be realized in the near future, our combiner system will become a promising candidate to challenge the dominant position currently claimed by the traveling-wave tube amplifiers.
Attribution versus persuasion as a means for modifying behavior.

The present research compared the relative effectiveness of an attribution strategy with a persuasion strategy in changing behavior. Study 1 attempted to teach fifth graders not to litter and to clean up after others. An attribution group was repeatedly told that they were neat and tidy people, a persuasion group was repeatedly told that they should be neat and tidy, and a control group received no treatment. Attribution proved considerably more effective in modifying behavior. Study 2 tried to discover whether similar effects would hold for a more central aspect of school performance, math achievement and self-esteem, and whether an attribution of ability would be as effective as an attribution of motivation. Repeatedly attributing to second graders either the ability or the motivation to do well in math proved more effective than comparable persuasion or no-treatment control groups, although a group receiving straight reinforcement for math problem-solving behavior also did well. It is suggested that persuasion often suffers because it involves a negative attribution (a person should be what he is not), while attribution generally gains because it disguises persuasive intent.
Image Stitching using Watersheds and Graph Cuts

Image stitching is commonly used in many different applications. One such application could be creating panoramas or high resolution images. To create seamless images is often very computationally demanding. On the other hand, the technological evolution of the latest years has created a customer demand for these algorithms to be used in handheld devices, such as cameras and cell phones. The methods need therefore to be faster in order to work in near real-time on mobile devices. Using one of the simpler algorithms often results in degrading artifacts, such as artificial seams or blurred regions. To favor seamless blending and clarity in the blending areas, while keeping a low computational cost, is the main motivation for this report. In this report the implementation of a fast image blending algorithm, based on the watershed algorithm and graph cuts, is presented [5]. The images are first aligned using SURF-matches.
Limits to compliance and the role of tactile sensing in grasping

Grasping and manipulation in unstructured environments must handle a wide range of object properties and significant sensing errors. Underactuation and compliance have been shown to be an effective way to improve grasping performance under such uncertainty, but the degree of compliance plays an important role in both gently adapting to sensing errors and maintaining stable grasps of heavy objects. These demands limit the range of objects that can be grasped. We consider the role and required characteristics of tactile sensing as a compensation method when compliance alone is insufficient. By strategic use of contact sensing, it is possible to expand the capabilities of a hand to grasp effectively under a wide range of positioning errors using simple position-driven motors and low-cost hardware.
Configurations of Manufacturing Strategy , Business Strategy , Environment and Structure

By developing strategic configurations which describe commonly used paths to competitive advantage for manufacturers, this paper reconciles some basic concepts from competitive strategy and manufacturing strategy. Four basic strategic configurations are identified: niche diflerentiator, broad differentiator, cost leader, and lean competitor. The configurations are traced conceptually through competitive strategy, organizational structure, environment, and a strategic framework of manufacturing capabilities and decisions. Examples from the major home appliance industry are provided for each configuration.
A Learning Machine: Part I

Machines would be more useful if they could learn to perform tasks for which they were not given precise methods. Difficulties that attend giving a machine this ability are discussed. It i s proposed that the program of a stored-program computer be gradually improved by a learning procedure which tries many programs and chooses, from the instructions that may occupy a given location, the one most often associated with a successful result. An experimental test of this principle i s described in detail. Preliminary results, which show limited success, are reported and interpreted. Further results and conclusions will appear in the second part of the paper.
Development of Network Gateway Between CAN and FlexRay Protocols For ECU Embedded Systems

This paper presents a network gateway between the CAN and FlexRay protocols for ECU embedded systems. Flexible gateways are necessary for implementing several functions to avoiding the need for increased clock speed. This gateway system is based on a second internal control unit, which can be implemented as a RISC or a specialized finite state machine and use combined message buffer RAM. The control unit is used to lessen the interrupt burden of the main CPU and to reduce the required CPU performance, while message buffer RAM is used to store all messages transmitted and received. It requires a high system frequency to guarantee the transfer of data between two or more networks in real-time and to assure data integrity. To compensate for the limited functionality of the modules, the control unit requires greater program memory capacity, for storing the complex routing information. This gateway system is based on proven communication controllers, expanded with a gateway interface. These communication controllers are linked by an independent CPU data bus structure that enables the transfer of messages. The data flow between the modules is controlled by an application specific gateway unit that provides all control signals. This unit consists of special function registers or of an independent CPU finite state machine. Due to the special gateway interfaces, which allows concurrent CPU and gateway unit request to the same cell, semaphores and flags are not necessary. This maximizes the flexibility of the module. These Gateways play and will continue to play a major role in automotive networks such as CAN, and FlexRay
Two Efficient Lattice Rescoring Methods Using Recurrent Neural Network Language Models

An important part of the language modelling problem for automatic speech recognition (ASR) systems, and many other related applications, is to appropriately model long-distance context dependencies in natural languages. Hence, statistical language models (LMs) that can model longer span history contexts, for example, recurrent neural network language models (RNNLMs), have become increasingly popular for state-of-the-art ASR systems. As RNNLMs use a vector representation of complete history contexts, they are normally used to rescore N-best lists. Motivated by their intrinsic characteristics, two efficient lattice rescoring methods for RNNLMs are proposed in this paper. The first method uses an n-gram style clustering of history contexts. The second approach directly exploits the distance measure between recurrent hidden history vectors. Both methods produced 1-best performance comparable to a 10 k-best rescoring baseline RNNLM system on two large vocabulary conversational telephone speech recognition tasks for US English and Mandarin Chinese. Consistent lattice size compression and recognition performance improvements after confusion network (CN) decoding were also obtained over the prefix tree structured N-best rescoring approach.
Weighted Local Binary Pattern Infrared Face Recognition Based on Weber's Law

The traditional LBP Histogram representation extracts the local micro-patterns and assigns the same weight all local micro-patterns. To combine the different contribution to face recognition, this paper proposes a weighted LBP histogram based on Weber's law. Firstly, inspired by psychological Weber's law, intensity of local micro-pattern is defined by the ratio between two terms: one is relative intensity differences of a central pixel against its neighbors, the other is intensity of local central pixel. Secondly, regarding the intensity of local micro-pattern as its weight, the weighted LBP histogram is constructed with the defined weight. Finally, to make full use of the space location information and lessen the complexity of recognition, the partitioning and uniform patterns are applied to get final features. The experiment results demonstrate that the proposed method outperforms the methods based on traditional LBP.
A Survey of MAC Protocols for Mission-Critical Applications in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are generally designed to support applications in long-term deployments, and thus WSN protocols are primarily designed to be energy efficient. However, the research community has recently explored new WSN applications such as industrial process automation. These mission-critical applications demand not only energy efficient operation but also strict data transport performance. In particular, data must be transported to a sink in a timely and reliable fashion. Both WSN's data transport performance and energy consumption pattern are mainly defined by the employed medium access control (MAC) protocol. Therefore, this survey paper explores to what extent existing MAC protocols for WSNs can serve mission-critical applications. The reviewed protocols are classified according to data transport performance and suitability for mission-critical applications. The survey reveals that the existing solutions have a number of limitations and only a few recently developed MAC protocols are suitable for this application domain.
A Wideband Omnidirectional Horizontally Polarized Antenna for 4G LTE Applications

An innovative wideband omnidirectional horizontally polarized (HP) antenna is presented for 4G Long Term Evolution (LTE) wireless communication and networking systems. The proposed planar antenna consists of four pairs of flag-shaped radiators, a balun for balance-unbalance transformation, and four parasitical strips for bandwidth enhancement. Such a design enables in-phase and axially symmetric current flowing along the radiators. The measurements show that the proposed HP antenna exhibits a relative bandwidth of 41% with the return loss greater than or equal to 10 dB; it covers the frequency band of 1.76-2.68 GHz, including PCS, UMTS/LTE, Bluetooth, ISM, and WLAN bands. With an omnidirectional radiation pattern in E-plane, the proposed antenna has a peak gain of 3.6-4.2 dBi across the operational band and a radiation efficiency of 83%. The low profile and compact design, along with the omnidirectional radiation pattern, makes it ideal for ceiling or surface-mounted indoor and automobile 4G applications.
Block sparse representations of tensors using Kronecker bases

In this paper, we consider sparse representations of multidimensional signals (tensors) by generalizing the one-dimensional case (vectors). A new greedy algorithm, namely the Tensor-OMP algorithm, is proposed to compute a block-sparse representation of a tensor with respect to a Kronecker basis where the non-zero coefficients are restricted to be located within a sub-tensor (block). It is demonstrated, through simulation examples, the advantage of considering the Kronecker structure together with the block-sparsity property obtaining faster and more precise sparse representations of tensors compared to the case of applying the classical OMP (Orthogonal Matching Pursuit).
Control of a Quadrotor Using a Smart Self-Tuning Fuzzy PID Controller

This paper deals with the modelling, simulation-based controller design and path planning of a four rotor helicopter known as a quadrotor. All the drags, aerodynamic, coriolis and gyroscopic effect are neglected. A Newton-Euler formulation is used to derive the mathematical model. A smart self-tuning fuzzy PID controller based on an EKF algorithm is proposed for the attitude and position control of the quadrotor. The PID gains are tuned using a self-tuning fuzzy algorithm. The self-tuning of fuzzy parameters is achieved based on an EKF algorithm. A smart selection technique and exclusive tuning of active fuzzy parameters is proposed to reduce the computational time. Dijkstra’s algorithm is used for path planning in a closed and known environment filled with obstacles and/or boundaries. The Dijkstra algorithm helps avoid obstacle and find the shortest route from a given initial position to the final position.
A new “smart parking” system based on optimal resource allocation and reservations

We propose a new “smart parking” system for an urban environment. The system assigns and reserves an optimal resource (parking space) for a user (driver) based on the user's objective function that combines proximity to destination and parking cost, while also ensuring that the overall parking capacity is efficiently utilized. Our approach solves a Mixed Integer Linear Program (MILP) problem at each decision point in a time-driven sequence. The solution of each MILP is an optimal allocation based on current state information and subject to random events such as new user requests or parking spaces becoming available. The allocation is updated at the next decision point ensuring that there is no resource reservation conflict and that no user is ever assigned a resource with higher than the current cost function value. Simulated case studies are included based on parking at part of the Boston University campus showing that we can achieve significant improvement over uncontrolled parking processes or state-of-the-art guidance-based systems. We also describe a laboratory setting where this system has been tested in real time.
Cryptography and cryptanalysis for embedded systems

A growing number of devices of daily use are equipped with computing capabilities. Today, already more than 98 % of all manufactured microprocessors are employed in embedded applications , leaving less than 2 % to traditional computers. Many of these embedded devices are enabled to communicate amongst each other and form networks. A side effect of the rising interconnectedness is a possible vulnerability of these embedded systems. Attacks that have formerly been restricted to PCs can suddenly be launched against cars, tickets, ID cards or even pacemakers. At the same time the security awareness of users and manufacturers of such systems is much lower than in classical PC environments. This renders security one key aspect of embedded systems design and for most pervasive computing applications. As embedded systems are usually deployed in large numbers, costs are a main concern of system developers. Hence embedded security solutions have to be cheap and efficient. Many security services such as digital signatures can only be realized by public key cryptography. Yet, public key schemes are in terms of computation orders of magnitude more expensive than private key cryptosystems. At the same time the prevailing schemes rely on very similar security assumptions. If one scheme gets broken, almost all cryptosystems employing asymmetric cryptography become useless. The first part of this work explores alternatives to the prevailing public key cryptosystems. Two alternative signature schemes and one public key encryption scheme from the family of post quantum cryptosystems are explored. Their security relies on different assumptions so that a break of one of the prevailing schemes does not affect the security of the studied alternatives. The main focus lies on the implementational aspects of these schemes for embedded systems. One actual outcome is that, contrary to common belief, the presented schemes provide similar and in some cases even better performance than the prevailing schemes. The presented solutions include a highly scalable software implementation of the Merkle signature scheme aimed at low-cost microprocessors. For signatures in hardware an FPGA framework for implementing a family of signature schemes based on multivariate quadratic equations is presented. Depending on the chosen scheme, multivariate quadratic signatures show better performance than elliptic curves in terms of area consumption and performance. The McEliece cryptosystem is an alternative public key encryption scheme which was believed to be infeasible on embedded platforms due to its large key size. This work shows that by applying certain …
Design of Wireless Sensor System for Neonatal Monitoring

In this paper, we present the application of wireless sensor technology and the advantages it will inherently have for neonatal care and monitoring at Neonatal Intensive Care Units (NICU). An electrocardiography (ECG) readout board and a wireless transceiver module developed by IMEC at the Holst Centre in the Netherlands are embedded in the proposed wireless sensor systems in combination with the signal processing and software interface developed at the Department of Industrial Design, Eindhoven University of Technology (TU/e). Through development of this prototype system, we opt to ensure correct data transmission, detection and display. The wireless system is designed to be suitable for integration into non-invasive monitoring platforms such as a smart neonatal jacket developed at TU/e. Experiments at Maxima Medical Centre (MMC) in Veldhoven, the Netherlands demonstrate the wireless transmission of ECG data from the smart jacket integrated with textile electrodes.
Spine dynamics as a computational resource in spine-driven quadruped locomotion

Recent results suggest that compliance and non-linearity in physical bodies of soft robots may not be disadvantageous properties with respect to control, but rather of advantage. In the context of morphological computation one could see such complex structures as potential computational resources. In this study, we implement and exploit this view point in a spine-driven quadruped robot called Kitty by using its flexible spine as a computational resource. The spine is an actuated multi-joint structure consisting of a sequence of soft silicone blocks. Its complex dynamics are captured by a set of force sensors and used to construct a closed-loop to drive the motor commands. We use simple static, linear readout weights to combine the sensor values to generate multiple gait patterns (bounding, trotting, turning behavior). In addition, we demonstrate the robustness of the setup by applying strong external perturbations in form of additional loads. The system is able to fully recover to its nominal gait patterns (which are encoded in the linear readout weights) after the perturbation has vanished.
Active Vision via Extremum Seeking for Robots in Unstructured Environments: Applications in Object Recognition and Manipulation

In this paper, a novel active vision strategy is proposed for optimizing the viewpoint of a robot’s vision sensor for a given success criterion. The strategy is based on extremum seeking control (ESC), which introduces two main advantages: 1) Our approach is model free: It does not require an explicit objective function or any other task model to calculate the gradient direction for viewpoint optimization. This brings new possibilities for the use of active vision in unstructured environments, since a priori knowledge of the surroundings and the target objects is not required. 2) ESC conducts continuous optimization backed up with mechanisms to escape from local maxima. This enables an efficient execution of an active vision task. We demonstrate our approach with two applications in the object recognition and manipulation fields, where the model-free approach brings various benefits: for object recognition, our framework removes the dependence on offline training data for viewpoint optimization, and provides robustness of the system to occlusions and changing lighting conditions. In object manipulation, the model-free approach allows us to increase the success rate of a grasp synthesis algorithm without the need of an object model; the algorithm only uses continuous measurements of the objective value, i.e., the grasp quality. Our experiments show that continuous viewpoint optimization can efficiently increase the data quality for the underlying algorithm, while maintaining the robustness. Note to Practitioners—Vision sensors provide robots flexibility and robustness both in industrial and domestic settings by supplying required data to analyze the surroundings and the state of the task. However, the quality of these data can be very high or poor depending on the viewing angle of the vision sensor. For example, if the robot aims to recognize an object, images taken from certain angles (e.g., feature rich surfaces) can be more descriptive than the others, or if the robot’s goal is to manipulate an object, observing it from a viewpoint that reveals easy-to-grasp “handles” makes the task simpler to execute. The algorithm presented in this paper aims to provide the robot high quality visual data relative to the task at hand by changing vision sensors’ viewpoint. Different from other methods in the literature, our method does not require any task models (therefore, it is model free), and only utilizes a quality value that can be measured from the current viewpoint (e.g., object recognition success rate for the current image). The viewpoint of the sensor is changed continuously for increasing the quality value until the robot is confident enough about the success of the execution. We demonstrate the application of the algorithm in the object recognition and manipulation domains. Nevertheless, it can be applied to many other robotics tasks, where viewing angle of the scene affects the robot’s performance.
The Hidden Image of the City: Sensing Community Well-Being from Urban Mobility

A key facet of urban design, planning, and monitoring is measuring communities’ well-being. Historically, researchers have established a link between well-being and visibility of city neighbourhoods and have measured visibility via quantitative studies with willing participants, a process that is invariably manual and cumbersome. However, the influx of the world’s population into urban centres now calls for methods that can easily be implemented, scaled, and analysed. We propose that one such method is offered by pervasive technology: we test whether urban mobility—as measured by public transport fare collection sensors—is a viable proxy for the visibility of a city’s communities. We validate this hypothesis by examining the correlation between London urban flow of public transport and census-based indices of the well-being of London’s census areas. We find that not only are the two correlated, but a number of insights into the flow between areas of varying social standing can be uncovered with readily available transport data. For example, we find that deprived areas tend to preferentially attract people living in other deprived areas, suggesting a segregation effect.