nils-herrmann/clean_scirepeval huggingface dataset:
Electrocardiogram signal processing by morphological operators

A new approach to impulsive noise suppression and background normalization for digitized electrocardiogram (ECG) signals is presented. The algorithm makes use of a class of nonlinear signal-processing operators known as morphological operators for processing the ECG data. A brief introduction to these nonlinear self-processing operators and a detailed description of the algorithm are presented. The performance of the algorithm is evaluated by test data made up of a known ECG signal, digitized from an analog simulator and corrupted by impulsive noise and background drift, and by processing clinically required ECG data from a standard set. It is concluded that the algorithm is effective for impulsive noise suppression and background normalization.<<ETX>>
Development and laboratory testing of a 138 kV PPP-insulated joint for commercial application

The design, development, and laboratory testing of a PPP (paper/polypropylene/paper)-insulated joint for commercial application on 1389 kV PPP-insulated cable are presented. The design approach taken is conservative and addresses the typical variations in field conditions and in skill and workmanship of the splicing. Joint construction details, including choice of connector, taping structure, and joint mechanical reinforcement, are discussed. The test criteria are described, and results are presented.
Dynamic tracking of moving objects in microassembly through visual servoing

Precise micropart alignment is a crucial factor in most gripper-based microassembly processes. For the micropart to be grasped or manipulated, these processes require the micropart to be positioned and oriented properly for the microgripper. At present, many of the these processes still rely on operators to monitor and align the micropart manually through visual images provided by the camera on top of the assembly line. However, due to the limited field of view of the microassembly system microscope, the micropart may move outside of the visual monitoring area at some point during the manipulation process. The present work proposes an integrated microassembly algorithm that performs the assembly process regardless of the micropart initial orientation. The algorithm automatically aligns and tracks the micropart during the manipulation process. As the micropart rotates to the required grasping orientation, the algorithm projects the future motion of the micropart, repositions it, and simultaneously, using a PID control algorithm, maintains the micropart within the field of view of the microscope. The proposed algorithm eliminates the need for a manual alignment process, which is time consuming and is subject to error. The algorithm was implemented and evaluated on an in-house 6 DOF microassembly manipulator. Experimental results confirmed that the proposed algorithm successfully tracked and corrected a 45-degree misaligned micropart at a specified location within the camera field of view with a steady-state error of +/−15 pixels.
Vision-Based Surgical Suture Looping Through Trajectory Planning for Wound Suturing

Robot-assisted surgery has revolutionized the field of surgery over the past few decades. Despite many successes, achieving full automation in these surgeries remains a challenging task. In this paper, a dynamic approach is proposed to automate knot tying with an in-house robot vision system. Through efficient path planning and coordination between two grippers, the workspace required for constructing the suture loop can be reduced while issues such as suture slippage and collisions between instruments can be eliminated. Visual images were employed to monitor the two grippers in real time and their positions were evaluated using transformation matrices obtained experimentally. A linear quadratic control scheme was applied to optimize the tracking performance of the two grippers. From the experiments, this visual evaluation method can achieve a position accuracy of 1 mm in the workspace. The proposed algorithm was evaluated and automatic suture looping operation was successfully performed in all six trials. Different parameters in the control scheme were also examined by introducing external impulse disturbances during the knot-tying process. This proposed knot-tying approach demonstrates a simple and efficient way to construct a suture knot in a minimal workspace. Note to Practitioners—A surgical operation usually takes several hours to complete, which is a test of surgeon’s endurance. To better assist surgeons, several repetitive surgical tasks can be performed automatically with a robotic system. This paper presents a new method for robot-assisted surgical knot tying in a confined environment. Through simultaneous manipulation and trajectory planning of the two surgical grippers, suture loops were constructed while keeping the suture in tension. Images were employed to guide the gripers in completing the knot-tying process with high precision. Experiments were conducted to demonstrate the automated suture looping operation with the system and the proposed method. The robustness of the method was also examined by introducing impulse disturbances and occlusions during the experiments. This proposed method does not require complicated hardware setup, allowing easy implementations on various surgical systems.
Sinusoidal responses of nonlinear signal processing operators

The response of morphological operators to sinusoidal input is studied and compared to that of the standard median filter. It is shown that the morphological operators have performance characteristics that are comparable to those of finite impulse response hybrid median filters. It is further shown that for both the morphological operators and the median filter, a sampling rate significantly higher than the Nyquist rate is needed for the input sine wave to avoid being severely attenuated.<<ETX>>
Pattern classification by geometrical learning of binary neural networks

This paper considers the use of binary neural networks for pattern classification. An expand-and-truncate learning (ETL) algorithm is used to determine the required number of neurons as well as the connecting weights in a three-layered feedforward network for classifying input patterns. The ETL algorithm is guaranteed to find a network for any binary-to-binary mappings. The ETL algorithm's performance in pattern classification is tested using a breast cancer database that have been used for benchmarking performance other machine learning methods.
Characterization of a Honeycomb-Like Scaffold With Dielectrophoresis-Based Patterning for Tissue Engineering

Seeding and patterning of cells with an engineered scaffold is a critical process in artificial tissue construction and regeneration. To date, many engineered scaffolds exhibit simple intrinsic designs, which fail to mimic the geometrical complexity of native tissues. In this study, a novel scaffold that can automatically seed cells into multilayer honeycomb patterns for bone tissue engineering application was designed and examined.  The scaffold incorporated dielectrophoresis for noncontact manipulation of cells and intrinsic honeycomb architectures were integrated in each scaffold layer. When a voltage was supplied to the stacked scaffold layers, three-dimensional electric fields were generated, thereby manipulating cells to form into honeycomb-like cellular patterns for subsequent culture.  The biocompatibility of the scaffold material was confirmed through the cell viability test. Experiments were conducted to evaluate the cell viability during DEP patterning at different voltage amplitudes, frequencies, and manipulating time. Three different mammalian cells were examined and the effects of the cell size and the cell concentration on the resultant cellular patterns were evaluated.  Results showed that the proposed scaffold structure was able to construct multilayer honeycomb cellular patterns in a manner similar to the natural tissue.  This honeycomb-like scaffold and the dielectrophoresis-based patterning technique examined in this study could provide the field with a promising tool to enhance seeding and patterning of a wide range of cells for the development of high-quality artificial tissues.
Data compression by multiresolution wavelet packet tree search

The standard wavelet transform can be considered to be a subtree of a complete multiresolution binary tree, in which each branch corresponds to a decomposition step. Any subtree of this multiresolution tree which covers all leaves is a valid wavelet packet processing tree, which specifies the processing steps for a wavelet decomposition of the original data. This paper describes an adaptation scheme for configuring a wavelet packet processing tree using a genetic algorithm search of the complete multiresolution tree. Data compression is used as the target signal processing task, and performance is measured based on the reconstruction distortion.
Contour shape matching by a constraint satisfaction network

The contour shape-matching task is formulated as a constraint satisfaction problem and solved using a Hopfield net. Constraints that are intrinsic to the shape-matching task are coded in the network interconnection weights. Direct evidence obtained from the observed data, as gauged by a local shape measure, are provided as the external input to the network. The local shape measure used is based on an affine transformation model, which is a general class of mappings that includes the rigid body motion. Empirical results demonstrate the performance of this network when applied to match contours that have undergone rotation, scale change, translation, or combinations of these transformations. The network is shown to be capable of handling noisy data, as well as a reasonable amount of deformation resulting from object rotation in the three-dimensional space. The affine transformation can be generalized to match entire contour segments; hence the network is not confined to matching point patterns.<<ETX>>
3D building reconstruction from LiDAR data

Airborne LiDAR data can be used to create 3D terrain models useful in augmented or virtual reality in which real-world landscapes are incorporated. Automatic generation of 3D models of man-made structures such as buildings is essential for creating these detailed models. We present a method that builds a 3D mesh, segments the triangles, and forms planar facets that correspond to a roof structure of a target building. We illustrate our method with real-world data sets.
The configuration of stack filters by probabilistic search

An efficient search method for the configuration of stack filters is presented. Nonlinear digital filters such as these are known to be flexible and effective in applications where it is difficult to characterize the noise type. An open problem associated with designing stack filters is finding the right configuration for a given noise type and the signal characteristics which need to be preserved. The problem of finding the right configuration is modeled as a combinatorial search problem. An efficient search method is developed which considers the probability distribution of the objective function values. Based on this, the number of steps needed to come up with a good configuration is established. The required number of steps can be carried out in parallel in any type of parallel computer. The method is empirically verified, and the performance of the stack filters found by the search method is compared to the performance of the median filter.<<ETX>>
Robotic knot tying through a spatial trajectory with a visual servoing system

Robot assisted surgery has become increasingly popular with the rapid development of more sophisticated robotic systems. Nevertheless, there are still many tedious surgical tasks that remain to be performed manually by surgeons with high supervisions. One example is to tie a surgical knot during the surgery, which includes the processes of needle threading, suture looping, suture tail grasping and suture pulling. In this research, we present a new method for robotic suture looping process. This method is based on a spatial trajectory planning for the surgical instruments, where challenges such as suture slippage and potential collisions between the instruments could be eliminated. In contrast to conventional looping process, a dynamic control scheme is proposed to optimize the time and workspace required to complete the process. Vision information is incorporated in order to enable closed loop control of the robotic system with Linear Quadratic (LQ) controller. A series of experiments were conducted in order to examine the performance of the proposed control scheme and the results confirmed that surgical knots can be successfully tied robotically, offering new insights to the field of automated robotassisted surgery.
Detection and Location of Dielectric Fluid Leaks on Pipe-Type Cable Systems

In the late 1940's high voltage pipe-type feeders were first installed in the United States. Since that time, over 2360 circuit miles of underground high voltage pipe-type cables have been installed throughout the country. Con Edison has approximately 652 circuit miles of high pressure pipe-type cable on its system, operating at 69, 138 or 345 kV. The typical pipe-type cable system is comprised of a steel pipe, containing 3 cables, with splices located at intervals of approximately 2000 feet. The pipe is filled with dielectric fluid which is maintained at a nominal operating pressure of 200 psig. Pressurization on the feeder is maintained automatically by pumping plants. For the 345 kV system, these plants sometimes include cooling capability. As the pipe type cable system grows older, leaks of dielectric fluid develop. The major causes of leaks are corrosion, contractor damages, effects of stray currents and localized pipe wear due to vibration. Quick detection and location of dielectric fluid leaks, particularly without the need to deenergize the feeder, is of prime importance to the utility industry. Raychem Corporation has been involved with the development of sensor cables for the detection and location of fluid leaks such as water and gasoline. This technology has been enhanced to address the problem of pipe type cable dielectric fluid leaks and a new system has been developed. The new system uses a sensor cable which is buried in the trench with the pipe type cable.
Development of 138 kV transition joint between HPPT cable and extruded cable

The authors describe the successful development of a 138 kV transition joint between high-pressure dielectric-fluid-filled cable with paper insulation and cable with extruded insulation, such as cross-linked polyethylene or ethylene propylene rubber. Such a joint must have adequate electrical and mechanical properties and contain the high-pressure dielectric fluid normally at 1400 kPa. For evaluation of the transition joint, the IEEE standard 404-1986 for laminar-to-laminar cable joints and extruded-to-extruded cable joints was considered, along with many of the specified types of tests included, such as high-voltage AC and DC, hot impulse to BIL, cyclic aging, and corona. The test results are reported.
Fault-tolerance inclusion in neural networks by a concurrent training algorithm

A learning algorithm, referred to as concurrent training, based on genetic algorithms for a neural network with connected modules is described. The algorithm does not require the knowledge of training sets for each module so that all modules can be trained concurrently. For an N module system, N separate pools of chromosomes are maintained and updated. The concurrent training algorithm is applied to train multilayered feedforward networks by considering each layer of connections to be a 1-layer network module. The algorithm is tested using the 4-bit parity problem and a linearly nonseparable classification problem. Experiment results are presented and the learning behavior and performance is analyzed.<<ETX>>
Visualizing association mining results through hierarchical clusters

We propose a new methodology for visualizing association mining results. Inter-item distances are computed from combinations of itemset supports. The new distances retain a simple pairwise structure, and are consistent with important frequently occurring itemsets. Thus standard tools of visualization, e.g. hierarchical clustering dendrograms can still be applied, while the distance information upon which they are based is richer. Our approach is applicable to general association mining applications, as well as applications involving information spaces modeled by directed graphs, e.g. the Web. In the context of collections of hypertext documents, the inter-document distances capture the information inherent in a collection's link structure, a form of link mining. We demonstrate our methodology with document sets extracted from the Science Citation Index, applying a metric that measures consistency between clusters and frequent itemsets.
Automatic interpretation of echocardiograms-a computer vision approach

Cardiac function is often evaluated quantitatively using two-dimensional echocardiography to analyze shape attributes, such as the heart wall thickness or the shape change of the heart wall boundaries. A review of previous work in detecting the heart wall boundaries is presented, along with how this problem can be viewed from a computer vision perspective. The principles of echo image sequence analysis and high-level analysis are described. It is suggested that one promising approach is to use multiple-resolution processing by using a large window smoothed image for the initial detection of major edge segments, followed by smaller and smaller windows until a complete boundary is found.<<ETX>>
Pressure surge testing of pothead and joint for pipe type cable circuits

The development and testing of a pressure surge accumulator (PSA) suitable for field installation on high pressure fluid filled pipe cable circuits is described. A prototype full stop joint was designed and built for Con Edison. Pressure surge testing was performed on the complete joint to assure that the design would withstand the pressure surges developed during an electrical fault. Test results show that installation of PSAs will reduce the electrical fault pressure surge to a level low enough to prevent the pothead porcelain from rupturing.<<ETX>>
Design of a high sensitivity capacitive force sensor

This paper presents the design and development of a MEMS based, capacitive sensor for micro-force measurement. The sensor has an overall dimension of 3600 mum times 1000 mum times 10 mum and was fabricated using the Micragem fabrication process. A displacement reduction mechanism is incorporated in this sensor design to increase the sensitivity of the sensor. Analysis from Finite Element software, COMSOL, confirms that a 10:1 displacement reduction ratio is achievable with this mechanism. Simulation results show that the sensor is capable of measuring a maximum force input of 11 milli-Newton, resulting from a 20-mum displacement on the sensing structure. A 6-DOF manipulator and an evaluation board were used to experimentally verify the performance the sensor. Experimental results show that a capacitance change of approximately 175 to 200 fF can be observed from a 20-mum displacement.
Meeting Cardinality Constraints in Role Mining

Role mining is a critical step for organizations that migrate from traditional access control mechanisms to role based access control (RBAC). Additional constraints may be imposed while generating roles from a given user-permission assignment relation. In this paper we consider two such constraints which are the dual of each other. A role-usage cardinality constraint limits the maximum number of roles any user can have. Its dual, the permission-distribution cardinality constraint, limits the maximum number of roles to which a permission can belong. These two constraints impose mutually contradictory requirements on user to role and role to permission assignments. An attempt to satisfy one of the constraints may result in a violation of the other. We show that the constrained role mining problem is NP-Complete and present heuristic solutions. Two distinct frameworks are presented in this paper. In the first approach, roles are initially mined without taking the constraints into account. The user-role and role-permission assignments are then checked for constraint violation in a post-processing step, and appropriately re-assigned, if necessary. In the second approach, constraints are enforced during the process of role mining. The methods are first applied on problems that consider the two constraints individually, and then with both considered together. Both methods are evaluated over a number of real-world data sets.
Minimum user requirement in Role Based Access Control with Separation of Duty constraints

Constraints, specifically Separation of Duty (SoD) constraints, constitute an essential component for specifying Role Based Access Control (RBAC) policies. While it has been shown earlier that SoD constraints can be effectively represented using a set of t - t Statically Mutually Exclusive Roles (SMER) constraints, this paper presents a method for finding minimum number of users under multiple SMER constraints. We show that one way of solving the problem is to evaluate chromatic numbers for a set of graphs. However, since exhaustive search is computationally quite expensive, we present a genetic algorithm formulation of the problem. Each chromosome is a string of positive integers within a certain range and its length equals the number of t-t SMER constraints in the system. We report our results for different values of the number of roles and the number of constraints and also for different values of t.
Frontal Gait Recognition From Incomplete Sequences Using RGB-D Camera

Frontal gait recognition using partial cycle information has not received significant attention to date in spite of its many potential applications. In this paper, we propose a hierarchical classification strategy that combines front and back view features captured by RGB-D (Red Green Blue - Depth) cameras. Airport security check points are considered as a typical application scenario, where two depth cameras mounted on top of a metal detector gate positioned beyond a yellow line, respectively, record front and back views of a subject as he goes through the check-in process. Due to the short distance of the surveillance zone between the yellow line and point of exit, it is often not possible to capture a full gait cycle independently from the front view or back view. An initial stage of anthropometric feature-based classification followed by motion feature extraction from the front view is used to restrict the potential set of matched subjects. A final classification is then applied on this reduced set of subjects using depth features extracted from the back view. The method is computationally efficient with a much higher rate of accuracy compared with existing gait recognition approaches.