nils-herrmann/clean_scirepeval huggingface dataset:
A biomimetic soft fingertip applicable to haptic feedback systems for texture identification

Humans recognize textures using the tactile data obtained from the human somatosensory system. Recognition of textures allows humans discriminate objects and materials. Moreover, by understanding the object's or material's texture, the human intuitively estimates roughness and the friction properties of the object or the material. This ability is necessary for object manipulative tasks. Likewise artificial haptic systems too, should have the ability to encode textures and feedback those data to haptic applications such as haptic displays. In this paper a biomimetic soft fingertip sensor that can be used in above haptic systems is introduced. The fingertip has the ability to detect force and vibration modalities. We propose three features calculated from the covariance signal of two adjacent accelerometers in the fingertip to use in texture identification. The covariance signal is transformed using Discrete Wavelet Transform (DWT) and the three features mentioned below are calculated. The mean and variance of the approximate signal, and the energies of the detailed signal are chosen as features. Then, the proposed features were validate by using those in an Artificial Neural Network (ANN) to classify seven wood samples. The results showed a 65% success rate in classifying wood samples and that the proposed features are acceptable to encode textures.
Minimum Spanning Tree Based Clustering Algorithms

The minimum spanning tree clustering algorithm is known to be capable of detecting clusters with irregular boundaries. In this paper, we propose two minimum spanning tree based clustering algorithms. The first algorithm produces a k-partition of a set of points for any given k. The algorithm constructs a minimum spanning tree of the point set and removes edges that satisfy a predefined criterion. The process is repeated until k clusters are produced. The second algorithm partitions a point set into a group of clusters by maximizing the overall standard deviation reduction, without a given k value. We present our experimental results comparing our proposed algorithms to k-means and EM. We also apply our algorithms to image color clustering and compare our algorithms to the standard minimum spanning tree clustering algorithm
FPGA implementation of real-time Ethernet communication using RMII interface

FPGA-based solutions have become more common in embedded systems these days. These systems need to communicate with external world. Considering high-speed and popularity of Ethernet communication, a reliable real-time Ethernet component inside FPGA is of special value. To that end, this paper presents a new solution for 100 Mb/s FPGA-based Ethernet communications with timing analysis. The solution deals with "Reduced Media-Independent Interface" in its physical layer. UDP is the network protocol which is implemented from physical to transport layer. For getting used in real-time applications, timing analysis is done in the communication system. Component based software engineering is used in the design and development processes. In order to test the components inside FPGA, two different approaches are utilized. Signal measurement in combination with introduced windows based application contributes much in testing and validation phases.
Privacy Preserving Data Publishing: A Classification Perspective

The concept of privacy is expressed as release of information in a controlled way. Privacy could also be defined as privacy decides what type of personal information should be released and which group or person can access and use it. Privacy Preserving Data Publishing (PPDP) is a way to allow one to share anonymous data to ensure protection against identity disclosure of an individual. Data anonymization is a technique for PPDP, which makes sure the published data, is practically useful for processing (mining) while preserving individuals sensitive information. Most works reported in literature on privacy preserving data publishing for classification task handle numerical data. However, most real life data contains both numerical and non-numerical data. Another shortcoming is that use of distributed model called Secure Multiparty Computation (SMC). For this research, a centralized model is used for independent data publication by a single data owner. The key challenge for PPDP is to ensure privacy as well as to keep the data usable for research. Differential privacy is a technique that ensures the highest level of privacy for a record owner while providing actual information of the data set. The aim of this research is to develop a framework that satisfies differential privacy standards and to ensure maximum data usability for a classification tasks such as patient data classification in terms of blood pressure. privacy preserving data publishing; differential privacy
Comparative Study on Vision Based Rice Seed Varieties Identification

This paper presents a system for automated classification of rice variety for rice seed production using computer vision and image processing techniques. Rice seeds of different varieties are visually very similar in color, shape and texture that make the classification of rice seed varieties at high accuracy challenging. We investigated various feature extraction techniques for efficient rice seed image representation. We analyzed the performance of powerful classifiers on the extracted features for finding the robust one. Images of six different rice seed varieties in northern Vietnam were acquired and analyzed. Our experiments have demonstrated that the average accuracy of our classification system can reach 90.54% using Random Forest method with a simple feature extraction technique. This result can be used for developing a computer-aided machine vision system for automated assessment of rice seeds purity.
Guided Procedural Modeling

Procedural methods present one of the most powerful techniques for authoring a vast variety of computer graphics models. However, their massive applicability is hindered by the lack of control and a low predictability of the results. In the classical procedural modeling pipeline, the user usually defines a set of rules, executes the procedural system, and by examining the results attempts to infer what should be changed in the system definition in order to achieve the desired output. We present guided procedural modeling, a new approach that allows a high level of top-down control by breaking the system into smaller building blocks that communicate. In our work we generalize the concept of the environment. The user creates a set of guides. Each guide defines a region in which a specific procedural model operates. These guides are connected by a set of links that serve for message passing between the procedural models attached to each guide. The entire model consists of a set of guides with procedural models, a graph representing their connection, and the method in which the guides interact. The modeling process is performed by modifying each of the described elements. The user can control the high-level description by editing the guides or manipulate the low-level description by changing the procedural rules. Changing the connectivity allows the user to create new complex forms in an easy and intuitive way. We show several examples of procedural structures, including an ornamental pattern, a street layout, a bridge, and a model of trees. We also demonstrate interactive examples for quick and intuitive editing using physics-based mass-spring system.
A Survey On Various Web Template Detection And Extraction Methods

In today’s digital world, reliance on the World Wide Web as a source of information is extensive. Users increasingly rely on web based search engines to provide accurate search results on a wide range of topics that interest them. The search engines, in turn parse the vast repository of web pages searching for relevant information. However, majority of web portals are designed using web templates, which are designed to provide consistent look and feel to end users. The presence of these templates however can influence search results leading to inaccurate results being delivered to the users. Therefore to improve the accuracy and reliability of search results, identification and removal of web templates from the actual content is essential. A wide range of approaches are commonly employed to achieve this, and this paper focuses on the study of the various approaches of template detection and extraction that can be applied across homogenous as well as heterogeneous web pages.
Employee job attitudes and organizational characteristics as predictors of cyberloafing

Cyberloafing is the personal use of the Internet by employees while at work. The purpose of this study is to examine whether employee job attitudes, organizational characteristics, attitudes towards cyberloafing, and other non-Internet loafing behaviors serve as antecedents to cyberloafing behaviors. We hypothesize that the employee job attitudes of job involvement and intrinsic involvement are related to cyberloafing. In addition, we hypothesize that organizational characteristics including the perceived cyberloafing of one’s coworkers and managerial support for internet usage are related to cyberloafing. We also hypothesize that attitudes towards cyberloafing and the extent to which employees participate in non-Internet loafing behaviors (e.g., talking with coworkers, running personal errands) will both be related to cyberloafing. One hundred and forty-three working professional from a variety of industries were surveyed regarding their Internet usage at work. As hypothesized, the employee job attitudes of job involvement and intrinsic involvement were negatively related to cyberloafing. Also as predicted, the organizational characteristics of the perceived cyberloafing of one’s coworkers and managerial support for internet usage were positively related to cyberloafing. Finally, results showed that attitudes towards cyberloafing and participation in non-Internet loafing behaviors were positively related to cyberloafing. Implications for both organizations and employees are discussed.
A structuration analysis of Small and Medium Enterprise (SME) adoption of E-Commerce: The case of Tanzania

There have been several studies on E-Commerce adoption in developing countries. However, few have investigated least developed countries (LDCs). Of those that have, their findings tend to be descriptive in nature – falling short of a theoretical contribution grounded in the sociocultural context. The purpose of this paper is to provide a theoretical analysis of ECommerce adoption in an LDC, Tanzania. Specifically, the study seeks to identify structural practices associated with E-Commerce in Tanzanian SMEs. Using structuration theory and following an interpretivist stance the findings show that Tanzanian SMEs enact three major ecommerce structural practices: (1) Marketing and image-building through use of websites, (2) Transacting through extensive use of mobile technology (3) Technical problem-solving through establishing partnerships. These practices are informed by organizational and environmental factors that define the sociocultural, technological and economic contextual setting. Considerable evidence is found that SMEs use websites in a limited way, as they draw upon their understanding of websites as being incompatible with the Tanzanian cultural bargaining system, which is characterised by cash transactions and face to face bargaining. Websites are viewed primarily as a platform from which SMEs can portray a sophisticated image and advertise/market their products. SMEs use mobile technology extensively, as they draw on the technology’s ability to offer transactive capability, mobility and communication. Findings also point to technological challenges which SMEs face from the environment, mainly from a lack of supporting industry and institutional support. SMEs hence establish partnerships with international organisations that can support them in overcoming technological challenges. Partnerships with large ICT organisations require stringent conditions, such as the requirement for SMEs to have certification in order to be affiliated. The study gives practitioners a better understanding of how SMEs perceive E-Commerce in Tanzania amidst organisational and environmental opportunities and constraints, and in so doing practitioners can better design appropriate E-Commerce context-specific policies and interventions that address SME problems. This will ensure that available resources become utilised in a more effective manner without negative consequences.
Design and Optimization of a 3-Coil Inductive Link for Efficient Wireless Power Transmission

Inductive power transmission is widely used to energize implantable microelectronic devices (IMDs), recharge batteries, and energy harvesters. Power transfer efficiency (PTE) and power delivered to the load (PDL) are two key parameters in wireless links, which affect the energy source specifications, heat dissipation, power transmission range, and interference with other devices. To improve the PTE, a 4-coil inductive link has been recently proposed. Through a comprehensive circuit-based analysis that can guide a design and optimization scheme, we have shown that despite achieving high PTE at larger coil separations, the 4-coil inductive links fail to achieve a high PDL. Instead, we have proposed a 3-coil inductive power transfer link with comparable PTE over its 4-coil counterpart at large coupling distances, which can also achieve high PDL. We have also devised an iterative design methodology that provides the optimal coil geometries in a 3-coil inductive power transfer link. Design examples of 2-, 3-, and 4-coil inductive links have been presented, and optimized for a 13.56-MHz carrier frequency and 12-cm coupling distance, showing PTEs of 15%, 37%, and 35%, respectively. At this distance, the PDL of the proposed 3-coil inductive link is 1.5 and 59 times higher than its equivalent 2- and 4-coil links, respectively. For short coupling distances, however, 2-coil links remain the optimal choice when a high PDL is required, while 4-coil links are preferred when the driver has large output resistance or small power is needed. These results have been verified through simulations and measurements.
Single-image SVBRDF capture with a rendering-aware deep network

Texture, highlights, and shading are some of many visual cues that allow humans to perceive material appearance in single pictures. Yet, recovering spatially-varying bi-directional reflectance distribution functions (SVBRDFs) from a single image based on such cues has challenged researchers in computer graphics for decades. We tackle lightweight appearance capture by training a deep neural network to automatically extract and make sense of these visual cues. Once trained, our network is capable of recovering per-pixel normal, diffuse albedo, specular albedo and specular roughness from a single picture of a flat surface lit by a hand-held flash. We achieve this goal by introducing several innovations on training data acquisition and network design. For training, we leverage a large dataset of artist-created, procedural SVBRDFs which we sample and render under multiple lighting directions. We further amplify the data by material mixing to cover a wide diversity of shading effects, which allows our network to work across many material classes. Motivated by the observation that distant regions of a material sample often offer complementary visual cues, we design a network that combines an encoder-decoder convolutional track for local feature extraction with a fully-connected track for global feature extraction and propagation. Many important material effects are view-dependent, and as such ambiguous when observed in a single image. We tackle this challenge by defining the loss as a differentiable SVBRDF similarity metric that compares the renderings of the predicted maps against renderings of the ground truth from several lighting and viewing directions. Combined together, these novel ingredients bring clear improvement over state of the art methods for single-shot capture of spatially varying BRDFs.
Low Cost Planar Waveguide Technology-Based Dielectric Resonator Antenna (DRA) for Millimeter-Wave Applications: Analysis, Design, and Fabrication

A compact, low cost and high radiation efficiency antenna structure, planar waveguide, substrate integrated waveguide (SIW), dielectric resonator antennas (DRA) is presented in this paper. Since SIW is a high Q- waveguide and DRA is a low loss radiator, then SIW-DRA forms an excellent antenna system with high radiation efficiency at millimeter-waveband, where the conductor loss dominates. The impact of different antenna parameters on the antenna performance is studied. Experimental data for SIW-DRA, based on two different slot orientations, at millimeter-wave band are introduced and compared to the simulated HFSS results to validate our proposed antenna model. A good agreement is obtained. The measured gain for SIW-DRA single element showed a broadside gain of 5.51 dB,-19 dB maximum cross polarized radiation level, and overall calculated (simulated using HFSS) radiation efficiency of greater than 95%.
Working Memory Capacity as Executive Attention

Performance on measures of working memory (WM) capacity predicts performance on a wide range of real-world cognitive tasks. I review the idea that WM capacity (a) is separable from short-term memory, (b) is an important component of general fluid intelligence, and (c) represents a domainfree limitation in ability to control attention. Studies show that individual differences in WM capacity are reflected in performance on antisaccade, Stroop, and dichotic-listening tasks. WM capacity, or executive attention, is most important under conditions in which interference leads to retrieval of response tendencies that conflict with the current task.
A Surface-Growing Approach to Multi-View Stereo Reconstruction

We present a new approach to reconstruct the shape of a 3D object or scene from a set of calibrated images. The central idea of our method is to combine the topological flexibility of a point-based geometry representation with the robust reconstruction properties of scene-aligned planar primitives. This can be achieved by approximating the shape with a set of surface elements (surfels) in the form of planar disks which are independently fitted such that their footprint in the input images matches. Instead of using an artificial energy functional to promote the smoothness of the recovered surface during fitting, we use the smoothness assumption only to initialize planar primitives and to check the feasibility of the fitting result. After an initial disk has been found, the recovered region is iteratively expanded by growing further disks in tangent direction. The expansion stops when a disk rotates by more than a given threshold during the fitting step. A global sampling strategy guarantees that eventually the whole surface is covered. Our technique does not depend on a shape prior or silhouette information for the initialization and it can automatically and simultaneously recover the geometry, topology, and visibility information which makes it superior to other state-of-the-art techniques. We demonstrate with several high-quality reconstruction examples that our algorithm performs highly robustly and is tolerant to a wide range of image capture modalities.
Intelligent active assistive and resistive orthotic device for knee rehabilitation

This paper provides an overview of the state-of-art technology behind existing active assistive / rehabilitative devices, and describes the design and features involved. A novel concept for an active assistive and resistive orthotic device utilizing pneumatic artificial muscles (PAM) is then proposed. The concept design strives to incorporate the advantages inherent in existing devices, enhanced functionalities and features. The key features discussed are portability, compliancy or backdrivability of actuators, compactness, and finally seamless integration with human muscles.
Anti-inflammatory effect of Moringa oleifera Lam. seeds on acetic acid-induced acute colitis in rats

Anti-inflammatory, immuno-modulatory, and antioxidant properties of Moringa oleifera Lam. suggest that it might have beneficial effects on colitis. The present study was performed to investigate the anticolitis effect of Moringa oleifera seeds hydro-alcoholic extract (MSHE) and its chloroform fraction (MCF) on acetic acid-induced colitis in rats.



Both MSHE and MCF with three increasing doses (50, 100, and 200 mg/kg) were administered orally to separate groups of male Wistar rats, 2 h before ulcer induction (using acetic acid 4%) and continued for 5 days. Prednisolone (4 mg/kg) and normal saline (1 ml/kg) were used in reference and control groups, respectively. All rats were sacrificed 24 h after the last dose (at day 6) and tissue injuries were assessed macroscopically and pathologically.



Extracts with three doses mentioned before were effective to reduce weight of distal colon (8 cm) as a marker for inflammation and tissue edema. Three doses of MSHE and two greater doses of MCF (100 and 200 mg/kg) were effective to reduce ulcer severity, area, and index as well as mucosal inflammation severity and extent, crypt damage, invasion involvement, total colitis index, and MPO activity compared with controls. MCF (50 mg/kg) was not significantly effective in reducing evaluated parameters of colitis compared with controls.



It is concluded that MSHE and MCF were both effective to treat experimental colitis and this might be attributed to their similar major components, biophenols and flavonoids. Since the efficacy was evident even in low doses of MSHE, presence of active constituents with high potency in seeds is persuasive.
Challenges in Autonomous Vehicle Testing and Validation

Software testing is all too often simply a bug hunt rather than a wellconsidered exercise in ensuring quality. A more methodical approach than a simple cycle of system-level test-fail-patch-test will be required to deploy safe autonomous vehicles at scale. The ISO 26262 development V process sets up a framework that ties each type of testing to a corresponding design or requirement document, but presents challenges when adapted to deal with the sorts of novel testing problems that face autonomous vehicles. This paper identifies five major challenge areas in testing according to the V model for autonomous vehicles: driver out of the loop, complex requirements, non-deterministic algorithms, inductive learning algorithms, and failoperational systems. General solution approaches that seem promising across these different challenge areas include: phased deployment using successively relaxed operational scenarios, use of a monitor/actuator pair architecture to separate the most complex autonomy functions from simpler safety functions, and fault injection as a way to perform more efficient edge case testing. While significant challenges remain in safety-certifying the type of algorithms that provide high-level autonomy themselves, it seems within reach to instead architect the system and its accompanying design process to be able to employ existing software safety approaches.