nils-herrmann/clean_scirepeval huggingface dataset:
Enhanced device performance using lightly doped channel junctionless accumulation-mode FinFET

Recently, junctionless transistor architectures with improved short channel characteristics have been extensively studied. JLTs, unlike inversion mode transistors (IMT), do not require precise control of doping profile in sub-20nm technology nodes. However, due to its highly doped channel, it faces several other challenges that limit its usage. To overcome these challenges, we present a lightly doped channel junctionless accumulation-mode (LDC-JAM) FinFET that provides excellent electrostatic integrity as well as reduction in short channel effects (SCEs) in comparison to the conventional junctionless FETs (conv-JLT). It is observed that the drive current and the channel mobility is enhanced using the proposed LDC-JAM FinFET. The effect of equivalent oxide thickness, fin thickness, and source/drain doping concentration on the overall device performance is analyzed and compared.
Object-Based Classification of Urban Areas Using VHR Imagery and Height Points Ancillary Data

Land cover classification of very high resolution (VHR) imagery over urban areas is an extremely challenging task. Impervious land covers such as buildings, roads, and parking lots are spectrally too similar to be separated using only the spectral information of VHR imagery. Additional information, therefore, is required for separating such land covers by the classifier. One source of additional information is the vector data, which are available in archives for many urban areas. Further, the object-based approach provides a more effective way to incorporate vector data into the classification process as the misregistration between different layers is less problematic in object-based compared to pixel-based image analysis. In this research, a hierarchical rule-based object-based classification framework was developed based on a small subset of QuickBird (QB) imagery coupled with a layer of height points called Spot Height (SH) to classify a complex urban environment. In the rule-set, different spectral, morphological, contextual, class-related, and thematic layer features were employed. To assess the general applicability of the rule-set, the same classification framework and a similar one using slightly different thresholds applied to larger subsets of QB and IKONOS (IK), respectively. Results show an overall accuracy of 92% and 86% and a Kappa coefficient of 0.88 and 0.80 for the QB and IK Test image, respectively. The average producers’ accuracies for impervious land cover types were also 82% and 74.5% for QB and IK. OPEN ACCESS Remote Sens. 2012, 4 2257
A Novel Rectangular Ring Planar Monopole Antennas for Ultra-Wideband Applications

This paper proposes two rectangular ring planar monopole antennas for wideband and ultra-wideband applications. Simple planar rectangular rings are used to design the planar antennas. These rectangular rings are designed in a way to achieve the wideband operations. The operating frequency band ranges from 1.85 GHz to 4.95 GHz and 3.12 GHz to 14.15 GHz. The gain varies from 1.83 dBi to 2.89 dBi for rectangular ring wideband antenna and 1.89 dBi to 5.2 dBi for rectangular ring ultra-wideband antenna. The design approach and the results are discussed.
Dimensional synthesis of three-fingered robot hands for maximal precision manipulation workspace

This paper applies dimensional synthesis to explore the geometric design of dexterous three-fingered robotic hands for maximizing precision manipulation workspace, in which the hand stably moves an object with respect to the palm of the hand, with contacts only on the fingertips. We focus primarily on the tripod grasp, which is the most commonly used grasp for precision manipulation. We systematically explore the space of design parameters, with two main objectives: maximize the workspace of a fully actuated hand and explore how under-actuation modifies it. We use a mathematical framework that models the hand-plus-object system and examine how the workspace varies with changes in nine hand and object parameters such as link length and finger arrangement on the palm. Results show that to achieve the largest workspaces the palm radius should be approximately half of a finger length larger than the target object radius, that the distal link of the two-link fingers should be around 1–1.2 times the length of the proximal link, and that fingers should be arranged symmetrically about the palm with object contacts also symmetric. Furthermore, a proper parameter design for an under-actuated hand can achieve up to 50% of the workspace of a fully actuated hand. When compared to the system parameters of existing popular hand designs, larger palms and longer distal links are needed to maximize the manipulation workspace of the studied design.
Designing 8 Degrees of Freedom Humanoid Robotic Arm

This study presents the processes undertaken in the design and development of an intelligent 8 degrees of freedom (DOF) humanoid robotic arm using specified-made parts. The robotic arm imitates a human arm and able to grasp many objects of different shapes and sizes ranging from a small pen to a large ball. The robotic arm consists of a shoulder, an elbow, a wrist and five fingers and each finger is designed with three moveable sections except only two for the thumb. The sections in each finger will either be pushed or pulled synchronously using internal linkages and controlled by a 18F4431 microcontroller. Basic movement is pre-programmed to ensure that all the movement is within the allowable constrains, and can be controlled by human operator or automatically controlled by a computer. The 8 DOFs humanoid robotic arm provides wide trajectory coverage over the three-dimensional space around the base. The specified trajectory of each finger, wrist and arm are bio-inspired and carefully designed to resemble the humanpsilas arm movement.
Program proving using intermediate verification languages (IVLs) like boogie and why3

A program verifier is a complex piece of software. To deal with this complexity, a standard architecture of a modern program verifier consists of two basic parts: a front end and a back end, separated by an intermediate verification language (IVL). The separation of concerns obtained by this architecture is analogous to that in compilers: the front end is concerned with breaking down the semantics of given source-language programs into the more primitive operations of the intermediate language, and the back end is concerned with encoding the meaning of the intermediate program as efficient theorem-prover input.
 Two prevalent IVLs today are Boogie~2 and Why3. In this invited talk, I will give a tour of the Boogie language. Through a set of examples, I will illustrate how a verifier may translate common source-program features into an IVL. A verification engine for the IVL is then applied to perform the actual verification. In this way, you can obtain a program verifier for your own language by building a new front end and reusing an existing verification engine.
Core Services for Smart Products

The increasing complexity and diversity of technical products plus the massive amount of product-related data overwhelms humans dealing with them at all stages of the life-cycle. We present a novel architecture for building smart products that are able to interact with humans in a natural and proactive way, and assist and guide them in performing their tasks. Further, we show how communication capabilities of smart products are used to account for the limited resources of individual products by leveraging resources provided by the environment or other smart products for storage and natural interaction.
The Effects of Employee Recognition , Pay , and Benefits on Job Satisfaction : Cross Country Evidence

This paper analyzes the effect of employee recognition, pay, and benefits on job satisfaction. In this cross-sectional study, survey responses from university students in the U.S. (n = 457), Malaysia (n = 347) and Vietnam (n = 391) were analyzed. Employee recognition, pay, and benefits were found to have a significant impact on job satisfaction, regardless of home country income level (high, middle or low income) and culture (collectivist or individualist). However, the effect of benefits on job satisfaction was significantly more important for U.S. respondents than for respondents from Malaysia and Vietnam. The authors conclude that both financial and nonfinancial rewards have a role in influencing job satisfaction, which ultimately impacts employee performance. Theoretical and practical implications for developing effective recruitment and retention policies for employees are also discussed.
β-Alanine supplementation and military performance

During sustained high-intensity military training or simulated combat exercises, significant decreases in physical performance measures are often seen. The use of dietary supplements is becoming increasingly popular among military personnel, with more than half of the US soldiers deployed or garrisoned reported to using dietary supplements. β-Alanine is a popular supplement used primarily by strength and power athletes to enhance performance, as well as training aimed at improving muscle growth, strength and power. However, there is limited research examining the efficacy of β-alanine in soldiers conducting operationally relevant tasks. The gains brought about by β-alanine use by selected competitive athletes appears to be relevant also for certain physiological demands common to military personnel during part of their training program. Medical and health personnel within the military are expected to extrapolate and implement relevant knowledge and doctrine from research performed on other population groups. The evidence supporting the use of β-alanine in competitive and recreational athletic populations suggests that similar benefits would also be observed among tactical athletes. However, recent studies in military personnel have provided direct evidence supporting the use of β-alanine supplementation for enhancing combat-specific performance. This appears to be most relevant for high-intensity activities lasting 60–300 s. Further, limited evidence has recently been presented suggesting that β-alanine supplementation may enhance cognitive function and promote resiliency during highly stressful situations.
Forensic Image Analyses of Skin and Underlying Muscles as a Tool for Postmortem Interval Delimitation: Histopathologic Examination.

One of the biggest challenges for forensic pathologists is to diagnose the postmortem interval (PMI) delimitation; therefore, the aim of this study was to use a routine histopathologic examination and quantitative analysis to obtain an accurate diagnosis of PMI. The current study was done by using 24 adult male albino rats divided into 8 groups based on the scarification schedule (0, 8, 16, 24, 32, 40, 48, and 72 hours PMI). Skin specimens were collected and subjected to a routine histopathologic processing. Examination of hematoxylin-eosin-stained sections from the skin, its appendages and underlying muscles were carried out. Morphometric analysis of epidermal nuclear chromatin intensities and area percentages, reticular dermis integrated density, and sebaceous gland nuclei areas and chromatin condensation was done. Progressive histopathologic changes could be detected in epidermis, dermis, hypodermis, underlying muscles including nerve endings, and red blood cells in relation to hours PMI. Significant difference was found in epidermal nuclear chromatin intensities at different-hours PMI (at P < 0.001). The highest intensity was detected 40 hours PMI. Quantitative analysis of measurements of dermal collagen area percentages revealed a high significant difference between 0 hours PMI and 24 to 72 hours PMI (P < 0.001). As the PMI increases, sebaceous gland nuclei and nuclear chromatin condensation showed a dramatic decrease. Significant differences of sebaceous gland nuclei areas between 0 hours and different-hours PMI (P < 0.001) were obtained. A combination between routine histopathologic examination and quantitative and morphometric analysis of the skin could be used to evaluate the time of death in different-hours PMI.
Collecting complex activity datasets in highly rich networked sensor environments

We deployed 72 sensors of 10 modalities in 15 wireless and wired networked sensor systems in the environment, in objects, and on the body to create a sensor-rich environment for the machine recognition of human activities. We acquired data from 12 subjects performing morning activities, yielding over 25 hours of sensor data. We report the number of activity occurrences observed during post-processing, and estimate that over 13000 and 14000 object and environment interactions occurred. We describe the networked sensor setup and the methodology for data acquisition, synchronization and curation. We report on the challenges and outline lessons learned and best practice for similar large scale deployments of heterogeneous networked sensor systems. We evaluate data acquisition quality for on-body and object integrated wireless sensors; there is less than 2.5% packet loss after tuning. We outline our use of the dataset to develop new sensor network self-organization principles and machine learning techniques for activity recognition in opportunistic sensor configurations. Eventually this dataset will be made public.
Comparative Study of Simulators for Vehicular Ad-hoc Networks ( VANETs )

Vehicular Ad hoc Networks (VANETs) are classified as an application of Mobile Ad-hoc Networks (MANETs) that has the potential in improving road safety and providing Intelligent Transportation System (ITS). Vehicular communication system facilitates communication devices for exchange of information among vehicles and vehicles and Road Side Units (RSUs).The era of vehicular adhoc networks is now gaining attention and momentum. Researchers and developers have built VANET simulation tools to allow the study and evaluation of various routing protocols, various emergency warning protocols and others VANET applications. Simulation of VANET routing protocols and its applications is fundamentally different from MANETs simulation because in VANETs, vehicular environment impose new issues and requirements, such as multi-path fading, roadside obstacles, trip models, traffic flow models, traffic lights, traffic congestion, vehicular speed and mobility, drivers behaviour etc. This paper presents a comparative study of various publicly available VANET simulation tools. Currently, there are network simulators, VANET mobility generators and VANET simulators are publicly available. In particular, this paper contrast their software characteristics, graphical user interface, accuracy of simulation, ease of use, popularity, input requirements, output visualization capabilities etc. Ad-hoc network, ITS (Intelligent Transportation System), MANET, Simulation, VANET.
A new algorithm for Boolean operations on general polygons

A new algorithm for Boolean operations on general planar polygons is presented. It is available for general planar polygons (manifold or non-manifold, with or without holes). Edges of the two general polygons are subdivided at the intersection points and touching points. Thus, the boundary of the Boolean operation resultant polygon is made of some whole edges of the polygons after the subdivision process. We use the simplex theory to build the basic mathematical model of the new algorithm. The subordination problem between an edge and a polygon is reduced to a problem of determining whether a point is on some edges of some simplices or inside the simplices, and the associated simplicial chain of the resultant polygon is just an assembly of some simplices and their coefficients of the two polygons after the subdivision process. Examples show that the running time required by the new algorithm is less than one-third of that by the Rivero and Feito algorithm.
PixNet: interference-free wireless links using LCD-camera pairs

Given the abundance of cameras and LCDs in today's environment, there exists an untapped opportunity for using these devices for communication. Specifically, cameras can tune to nearby LCDs and use them for network access. The key feature of these LCD-camera links is that they are highly directional and hence enable a form of interference-free wireless communication. This makes them an attractive technology for dense, high contention scenarios. The main challenge however, to enable such LCD-camera links is to maximize coverage, that is to deliver multiple Mb/s over multi-meter distances, independent of the view angle. To do so, these links need to address unique types of channel distortions, such as perspective distortion and blur.
 This paper explores this novel communication medium and presents PixNet, a system for transmitting information over LCD-camera links. PixNet generalizes the popular OFDM transmission algorithms to address the unique characteristics of the LCD-camera link which include perspective distortion, blur, and sensitivity to ambient light. We have built a prototype of PixNet using off-the-shelf LCDs and cameras. An extensive evaluation shows that a single PixNet link delivers data rates of up to 12 Mb/s at a distance of 10 meters, and works with view angles as wide as 120 degree°.
An Airborne Wireless Sensor System for Near-Real Time Air Pollution Monitoring

Over the last decades with the rapid growth of industrial zones, manufacturing plants and the substantial urbanization, environmental pollution has become a crucial health, environmental and safety concern. In particular, due to the increased emissions of various pollutants caused mainly by human sources, the air pollution problem is elevated in such extent where significant measures need to be taken. Towards the identification and the qualification of that problem, we present in this paper an airborne wireless sensor network system for automated monitoring and measuring of the ambient air pollution. Our proposed system is comprised of a pollution-aware wireless sensor network and unmanned aerial vehicles (UAVs). It is designed for monitoring the pollutants and gases of the ambient air in three-dimensional spaces without the human intervention. In regards to the general architecture of our system, we came up with two schemes and algorithms for an autonomous monitoring of a three-dimensional area of interest. To demonstrate our solution, we deployed the system and we conducted experiments in a real environment measuring air pollutants such as: NH3, CH4, CO2, O2 along with temperature, relative humidity and atmospheric pressure. Lastly, we experimentally evaluated and analyzed the two proposed schemes.
Distributed traffic light control at uncoupled intersections with real-world topology by deep reinforcement learning

This work examines the implications of uncoupled intersections with local realworld topology and sensor setup on traffic light control approaches. Control approaches are evaluated with respect to: Traffic flow, fuel consumption and noise emission at intersections. The real-world road network of Friedrichshafen is depicted, preprocessed and the present traffic light controlled intersections are modeled with respect to state space and action space. Different strategies, containing fixed-time, gap-based and time-based control approaches as well as our deep reinforcement learning based control approach, are implemented and assessed. Our novel DRL approach allows for modeling the TLC action space, with respect to phase selection as well as selection of transition timings. It was found that real-world topologies, and thus irregularly arranged intersections have an influence on the performance of traffic light control approaches. This is even to be observed within the same intersection types (n-arm, m-phases). Moreover we could show, that these influences can be efficiently dealt with by our deep reinforcement learning based control approach.
Retrieving Smith-Waterman Alignments with Optimizations for Megabase Biological Sequences Using GPU

In Genome Projects, biological sequences are aligned thousands of times, in a daily basis. The Smith-Waterman algorithm is able to retrieve the optimal local alignment with quadratic time and space complexity. So far, aligning huge sequences, such as whole chromosomes, with the Smith-Waterman algorithm has been regarded as unfeasible, due to huge computing and memory requirements. However, high-performance computing platforms such as GPUs are making it possible to obtain the optimal result for huge sequences in reasonable time. In this paper, we propose and evaluate CUDAlign 2.1, a parallel algorithm that uses GPU to align huge sequences, executing the Smith-Waterman algorithm combined with Myers-Miller, with linear space complexity. In order to achieve that, we propose optimizations which are able to reduce significantly the amount of data processed, while enforcing full parallelism most of the time. Using the NVIDIA GTX 560 Ti board and comparing real DNA sequences that range from 162 KBP (Thousand Base Pairs) to 59 MBP (Million Base Pairs), we show that CUDAlign 2.1 is scalable. Also, we show that CUDAlign 2.1 is able to produce the optimal alignment between the chimpanzee chromosome 22 (33 MBP) and the human chromosome 21 (47 MBP) in 8.4 hours and the optimal alignment between the chimpanzee chromosome Y (24 MBP) and the human chromosome Y (59 MBP) in 13.1 hours.
What Psycholinguists Know About Chemistry: Aligning Wiktionary and WordNet for Increased Domain Coverage

By today, no lexical resource can claim to be fully comprehensive or perform best for every NLP task. This caused a steep increase of resource alignment research. An important challenge is thereby the alignment of differently represented word senses, which we address in this paper. In particular, we propose a new automatically aligned resource of Wiktionary and WordNet that has (i) a very high domain coverage of word senses and (ii) an enriched sense representation, including pronunciations, etymologies, translations, etc. We evaluate our alignment both quantitatively and qualitatively, and explore how it can contribute to practical tasks.
Ultrasound evaluation of the fetal nasal bone: what is the most appropriate first-trimester cut-off point for aneuploidy screening?

To establish fetal nasal bone length cut-off points for first trimester aneuploidy screening based on a normal curve of a Brazilian population. The following tests were proposed: presence or absence of the nasal bone (NB); 2.5 and 5.0 NB percentiles relative to the normal curve; and 0.70, 0.75 and 0.80 multiples of the median (MoM) values defined in the receiver operating characteristic (ROC) curve. Nasal Bone tests were based on positive and negative likelihood ratio value detection rates (LR); the confidence interval was 95% in all tests. Cases in which ultrasonographic images of the NB were absent were not taken into account when evaluating the 2.5 and 5.0 percentiles and the 0.70, 0.75 and 0.80 MoM. The sample consisted of 571 fetuses (10–14 weeks). After exclusions (11) and loss of follow-up (53), the study sample was reduced to 507 patients. There were 23 Down syndrome patients among 41 aneuploid fetuses. The sensitivity of the qualitative NB test (absent vs. present) was 34.1%, and the specificity was 99.1% (+LR 37.89, −LR 0.66). An image of the nasal bone was absent in 52.2% of fetuses with the Down syndrome (+LR 58.00, −LR 0.48). The best tool for aneuploidy screening was the qualitative NB test (absent vs. present). Ultrasonography of the NB is a component of aneuploidy screening, and should not be used alone.