nils-herrmann/clean_scirepeval huggingface dataset:
Optimal Extrinsic Calibration Between a Stereoscopic System and a LIDAR

Current perception systems of intelligent vehicles not only make use of visual sensors, but also take advantage of depth sensors. Extrinsic calibration of these heterogeneous sensors is required for fusing information obtained separately by vision sensors and light detection and ranging (LIDARs). In this paper, an optimal extrinsic calibration algorithm between a binocular stereo vision system and a 2-D LIDAR is proposed. Most extrinsic calibration methods between cameras and a LIDAR proceed by calibrating separately each camera with the LIDAR. We show that by placing a common planar chessboard with different poses in front of the multisensor system, the extrinsic calibration problem is solved by a 3-D reconstruction of the chessboard and geometric constraints between the views from the stereovision system and the LIDAR. Furthermore, our method takes sensor noise into account that it provides optimal results under Mahalanobis distance constraints. To evaluate the performance of the algorithm, experiments based on both computer simulation and real datasets are presented and analyzed. The proposed approach is also compared with a popular camera/LIDAR calibration method to show the benefits of our method.
Evaluation of background subtraction algorithms for video surveillance

This paper presents a comparative study of several state of the art background subtraction (BS) algorithms. The goal is to provide brief solid overview of the strengths and weaknesses of the most widely applied BS methods. Approaches ranging from simple background subtraction with global thresholding to more sophisticated statistical methods have been implemented and tested with ground truth. The interframe difference, approximate median filtering and Gaussian mixture models (GMM) methods are compared relative to their robustness, computational time, and memory requirement. The performance of the algorithms is tested in public datasets. Interframe difference and approximate median filtering are pretty fast, almost five times faster than GMM. Moreover, GMM occupies five times more memory than simpler methods. However, experimental results of GMM are more accurate than simple methods.
Prospective forecasts of annual dengue hemorrhagic fever incidence in Thailand, 2010–2014

Dengue hemorrhagic fever (DHF), a severe manifestation of dengue viral infection that can cause severe bleeding, organ impairment, and even death, affects between 15,000 and 105,000 people each year in Thailand. While all Thai provinces experience at least one DHF case most years, the distribution of cases shifts regionally from year to year. Accurately forecasting where DHF outbreaks occur before the dengue season could help public health officials prioritize public health activities. We develop statistical models that use biologically plausible covariates, observed by April each year, to forecast the cumulative DHF incidence for the remainder of the year. We perform cross-validation during the training phase (2000-2009) to select the covariates for these models. A parsimonious model based on preseason incidence outperforms the 10-y median for 65% of province-level annual forecasts, reduces the mean absolute error by 19%, and successfully forecasts outbreaks (area under the receiver operating characteristic curve = 0.84) over the testing period (2010-2014). We find that functions of past incidence contribute most strongly to model performance, whereas the importance of environmental covariates varies regionally. This work illustrates that accurate forecasts of dengue risk are possible in a policy-relevant timeframe.
The Utility of Hello Messages for Determining Link Connectivity

Future wireless applications will take advantage of rapidly deployable, self-configuring multihop ad hoc networks. Because of the difficulty of obtaining IEEE 802.11 feedback about link connectivity in real networks, many multihop ad hoc networks utilize hello messages to determine local connectivity. This paper uses an implementation of the Ad hoc On-demand Distance Vector (AODV) routing protocol to examine the effectiveness of hello messages for monitoring link status. In this study, it is determined that many factors influence the utility of hello messages, including allowed hello message loss settings, discrepancy between data and hello message size and 802.11b packet handling. This paper examines these factors and experimentally evaluates a variety of approaches for improving the accuracy of hello messages as an indicator of local connectivity.
High-frequency modeling and signal integrity analysis of high-density silicone rubber socket

In this paper, we propose and analyze an equivalent RLGC model of silicone rubber socket with single-ended signaling. A silicone rubber socket consists of highly dense metal powders in elastic silicone rubber. When the silicone rubber is compressed, metal powders form a column which corresponds to a pad of package. Thus, it can be modeled as a pair of cylinders. We have successfully verified the proposed model using a 3D electromagnetic (EM) solver in frequency domain and the eye diagram measurement in time domain. As a result, the verified model can be used to determine whether socket is applicable to the test system in the simulation level concurrently with offering physical insight and reducing time spent 3D EM simulating socket.
Generating Music from Text : Mapping Embeddings to a VAEâ€ TM s Latent Space

Music has always been used to elevate the mood in movies and poetry, adding emotions which might not have been without the music. Unfortunately only the most musical people are capable of creating music, let alone the appropriate music. This paper proposes a system that takes as input a piece of text, the representation of that text is consequently transformed into the latent space of a VAE capable of generating music. The latent space of the VAE contains representations of songs and the transformed vector can be decoded from it as a song. An experiment was performed to test this system by presenting a text to seven experts, along with two pieces of music from which one was created from the text. On average the music generated from the text was only recognized in half of the examples, but the poems gave significant results in their recognition, showing a relation between the poems and the generated music.
The Applicability of Internal Marketing Factors to Boost Internal Service Quality

The purpose of this paper is to examine the applicability of Internal Marketing (IM) factors in relation to the Internal Service Quality (ISQ) of the company. In this study, Pos Malaysia Berhad, a Malaysian postal company, was selected to investigate how the Internal Marketing element and the anticipated Internal Service Quality was implemented in the company. The research applies six internal marketing practices namely, employee motivation, effective communication, employee selection, employment development, support system and healthy work environment A total of 103 respondents were surveyed as well as a series of interviews were conducted. The data collected was analysed quantitatively by using the factor analysis and multiple regression analysis. The results indicated that there was a positive relationship between the elements of the Internal Marketing and the anticipated Internal Service Quality in variable magnitude. Research findings showed that the support system brought about the most changes in Internal Service Quality.
Icariin protects against intestinal ischemia-reperfusion injury.

This study investigated the role of Sirtuin 1 (SIRT1)/forkhead box O3 (FOXO3) pathway, and a possible protective function for Icariin (ICA), in intestinal ischemia-reperfusion (I/R) injury and hypoxia-reoxygenation (H/R) injury.



Male Sprague-Dawley rats were pretreated with different doses of ICA (30 and 60 mg/kg) or olive oil as control 1 h before intestinal I/R. Caco-2 cells were pretreated with different concentrations of ICA (25, 50, and 100 μg/mL) and then subjected to H/R-induced injury.



The in vivo results demonstrated that ICA pretreatment significantly improved I/R-induced tissue damage and decreased serum tumor necrosis factor α and interleukin-6 levels. Changes of manganese superoxide dismutase, Bcl-2, and Bim were also reversed by ICA, and apoptosis was reduced. Importantly, the protective effects of ICA were positively associated with SIRT1 activation. Increased SIRT1 expression, as well as decreased acetylated FOXO3 expression, was observed in Caco-2 cells pretreated with ICA. Additionally, the protective effects of ICA were abrogated in the presence of SIRT1 inhibitor nicotinamide. This suggests that ICA exerts a protective effect upon H/R injury through activation of SIRT1/FOXO3 signaling pathway. Accordingly, the SIRT1 activator resveratrol achieved a similar protective effect as ICA on H/R injury, whereas cellular damage resulting from H/R was exacerbated by SIRT1 knockdown and nicotinamide.



SIRT1, activated by ICA, protects intestinal epithelial cells from I/R injury by inducing FOXO3 deacetylation both in vivo and in vitro These findings suggest that the SIRT1/FOXO3 pathway can be a target for therapeutic approaches intended to minimize injury resulting from intestinal dysfunction.
Better to organize personal information by folders or by tags?: The devil is in the details

People can organize information items by placing them into folders or by tagging them with labels. Over the years there has been considerable discussion on the relative merits of folders vs. labels. But there is relatively little empirical data directly comparing people’s experiences with each model of organization on comparable sets of information.. We compared participants’ experiences organizing information with both folders and labels over time. Results indicate that each model has its strengths and weaknesses when assessed with respect to basic activities of personal information management (PIM) such as keeping, organizing and re-finding. Results afford a deeper, more detailed understanding of each model in practice. This understanding is achieved by engaging participants in an active, “hands-on” comparison of models over a period of time. Study results point to syntheses in tool support for organizing information that might combine strengths of folders and labels while avoiding the inadvertent introduction of weaknesses from these models.
Air quality data clustering using EPLS method

Nowadays air quality data can be easily accumulated by sensors around the world. Analysis on air quality data is very useful for society decision. Among five major air pollutants which are calculated for AQI (Air Quality Index), PM2.5 data is the most concerned by the people. PM2.5 data is also cross-impacted with the other factors in the air and which has properties of non-linear nonstationary including high noise level and outlier. Traditional methods cannot solve the problem of PM2.5 data clustering very well because of their inherent characteristics. In this paper, a novel model-based feature extraction method is proposed to address this issue. The EPLS model includes 1) Mode Decomposition, in which EEMD algorithm is applied to the aggregation dataset; 2) Dimension Reduction, which is carried out for a more significant set of vectors; 3) Least Squares Projection, in which all testing data are projected to the obtained vectors. Synthetic dataset and air quality dataset are applied to different clustering methods and similarity measures. Experimental results demonstrate IFully documented templates are available in the elsarticle package on CTAN. ∗Corresponding author at: Department of Computer Science, China University of Geosciences, Wuhan, China. ∗∗Corresponding author at: Department of Computer Science, China University of Geosciences, Wuhan, China. Email addresses: lizhewang@icloud.com (Lizhe Wang), lfy_cug@hotmail.com (Fangyuan Li) 1Email address: Cyl king@hotmail.com.  Templates December 1, 2016
Correction of Stahl's Ear

Stahl's ear is a rare congenital anomaly difficult to correct surgically. This report presents the experience of the Division of Plastic Surgery, University of São Paulo Medical School for managing this anomaly. From January 1994 to September 1999, 15 patients underwent surgery (17 ears). Ages ranged from 7 to 22 (mean 15 years). Six patients were female. Four subjects were of Oriental descent, four were Negroes, and seven were Caucasians. Deformities included two bilateral, four on the left ear, and nine on the right one. Different methods were utilized for correction depending on the elasticity of the cartilage. In the presence of an elastic cartilage, sutures only are employed, otherwise the cartilage is repositioned, as described by Sugino et al. No standard characteristics were noted regarding gender or race, however, there were more unilateral cases and more on the right ear. The results were adequately satisfactory, with the two methods enabling us to recommend these surgical techniques for correction of Stahl's ear.
Cloud-based Wireless Network: Virtualized, Reconfigurable, Smart Wireless Network to Enable 5G Technologies

In recent years, information communication and computation technologies are deeply converging, and various wireless access technologies have been successful in deployment. It can be predicted that the upcoming fifthgeneration mobile communication technology (5G) can no longer be defined by a single business model or a typical technical characteristic. 5G is a multi-service and multitechnology integrated network, meeting the future needs of a wide range of big data and the rapid development of numerous businesses, and enhancing the user experience by providing smart and customized services. In this paper, we propose a cloud-based wireless network architecture with four components, i.e., mobile cloud, cloud-based radio access network (Cloud RAN), reconfigurable network and big data centre, which is capable of providing a virtualized, reconfigurable, smart wireless network.
Controllable WLAN band rejection of ultra wideband monopole antenna using PIN diodes and two C-shaped conductor

In this paper, an ultra-wideband circular printed monopole antenna is presented. The antenna performance will be studied using the two-readymade software package IE3D and CST. The regular monopole antenna will be tuning by adding two C-shaped conductors near the antenna feeder to control the rejection band inside the WLAN frequency range (5.15–5.825GHz). The simulation results using the two software packages will be compared to each other. An empirical formula for the variation of the rejection band frequency against the mean length of C-shaped conductors is derived. The effect of the variation of the C-shaped conductor mean lengths on the center frequency of the rejection band will be discussed. The WLAN band rejection will be controlled by using two groups of PIN diodes. The circuit will be designed on RT/Duriod substrate (εr=2.2, h=1.57 mm, tanδ = 0.00019), where the simulations results using IE3D and CST are in good agreement with measurement results.
Towards dense volumetric pancreas segmentation in CT using 3D fully convolutional networks

Pancreas segmentation in computed tomography imaging has been historically difficult for automated methods because of the large shape and size variations between patients. In this work, we describe a custom-build 3D fully convolutional network (FCN) that can process a 3D image including the whole pancreas and produce an automatic segmentation. We investigate two variations of the 3D FCN architecture; one with concatenation and one with summation skip connections to the decoder part of the network. We evaluate our methods on a dataset from a clinical trial with gastric cancer patients, including 147 contrast enhanced abdominal CT scans acquired in the portal venous phase. Using the summation architecture, we achieve an average Dice score of 89.7 ± 3.8 (range [79.8, 94.8])% in testing, achieving the new state-of-the-art performance in pancreas segmentation on this dataset.
Solving constraint satisfaction problems with SAT modulo theories

Due to significant advances in SAT technology in the last years, its use for solving constraint satisfaction problems has been gaining wide acceptance. Solvers for satisfiability modulo theories (SMT) generalize SAT solving by adding the ability to handle arithmetic and other theories. Although there are results pointing out the adequacy of SMT solvers for solving CSPs, there are no available tools to extensively explore such adequacy. For this reason, in this paper we introduce a tool for translating FLATZINC (MINIZINC intermediate code) instances of CSPs to the standard SMT-LIB language. We provide extensive performance comparisons between state-of-the-art SMT solvers and most of the available FLATZINC solvers on standard FLATZINC problems. The obtained results suggest that state-of-the-art SMT solvers can be effectively used to solve CSPs.
Psychiatric Issues in Cosmetic Plastic Surgery

The objective of cosmetic surgery is increased patient self-esteem and confidence. Most patients undergoing a procedure report these results post-operatively. The success of any procedure is measured in patient satisfaction. In order to optimize patient satisfaction, literature suggests careful pre-operative patient preparation including a discussion of the risks, benefits, limitations and expected results for each procedure undertaken. As a general rule, the patients that are motivated to surgery by a desire to align their outward appearance to their body-image tend to be the most satisfied. There are some psychiatric conditions that can prevent a patient from being satisfied without regard aesthetic success. The most common examples are minimal defect/Body Dysmorphic Disorder, the patient in crisis, the multiple revision patient, and loss of identity. This paper will familiarize the audience with these conditions, symptoms and related illnesses. Case examples are described and then explored in terms of the conditions presented. A discussion of the patient’s motivation for surgery, goals pertaining to specific attributes, as well as an evaluation of the patient’s understanding of the risks, benefits, and limitations of the procedure can help the physician determine if a patient is capable of being satisfied with a cosmetic plastic surgery procedure. Plastic surgeons can screen patients suffering from these conditions relatively easily, as psychiatry is an integral part of medical school education. If a psychiatric referral is required, then the psychiatrist needs to be aware of the nuances of each of these conditions.
Next Generation Backscatter Communication: Systems, Techniques and Applications

The Internet-of-Things (IoT) is an emerging concept of network connectivity anytime and anywhere for billions of everyday objects, which has recently attracted tremendous attention from both the industry and academia. The rapid growth of IoT has been driven by recent advancements in consumer electronics, wireless network densification, 5G communication technologies, and cloud-computing enabled bigdata analytics. One of the key challenges for IoT is the limited network lifetime due to massive IoT devices being powered by batteries with finite capacities. The low-power and low-complexity backscatter communications (BackCom), which simply relies on passive reflecting and modulation an incident radiofrequency (RF) wave, has emerged to be a promising technology for tackling this challenge. However, the contemporary BackCom has several major limitations, such as short transmission range, low data rate and uni-directional information transmission. In this article, we present an overview of the next generation BackCom by discussing basic principles, system and network architectures and relevant techniques. Lastly, we describe the IoT application scenarios with the next generation BackCom.
Variational Memory Encoder-Decoder

Introducing variability while maintaining coherence is a core task in learning to generate utterances in conversation. Standard neural encoder-decoder models and their extensions using conditional variational autoencoder often result in either trivial or digressive responses. To overcome this, we explore a novel approach that injects variability into neural encoder-decoder via the use of external memory as a mixture model, namely Variational Memory Encoder-Decoder (VMED). By associating each memory read with a mode in the latent mixture distribution at each timestep, our model can capture the variability observed in sequential data such as natural conversations. We empirically compare the proposed model against other recent approaches on various conversational datasets. The results show that VMED consistently achieves significant improvement over others in both metricbased and qualitative evaluations.
E-Service Quality and its Impact on Customer Satisfaction and Trust : An Empirical Study on Greek Customers of Internet Shops

The use of Internet as a mean of shopping goods and services is growing over the past decade. Businesses in the e-commerce sector realize that the key factors for success are not limited to the existence of a website and low prices but must also include high standards of e-quality. Research indicates that the attainment of customer satisfaction brings along plenty of benefits. Furthermore, trust is of paramount importance, in ecommerce, due to the fact that that its establishment can diminish the perceived risk of using an internet service. The purpose of this study is to investigate the impact of customer perceived quality of an internet shop on customers’ satisfaction and trust. In addition, the possible effect of customer satisfaction on trust is also examined. An explanatory research approach was adopted in order to identify causal relationships between e-quality, customer satisfaction and trust. This was accomplished through field research by utilizing an interviewer-administered questionnaire. The questionnaire was largely based on existing constructs in relative literature. E-quality was divided into 5 dimensions, namely ease of use, e-scape, customization, responsiveness, and assurance. After being successfully pilot-tested by the managers of 3 Greek companies developing ecommerce software, 4 managers of Greek internet shops and 5 internet shoppers, the questionnaire was distributed to internet shoppers in central Greece. This process had as a result a total of 171 correctly answered questionnaires. Reliability tests and statistical analyses were performed to both confirm scale reliability and test research hypotheses. The findings indicate that all the examined e-quality dimensions expose a significant positive influence on customer satisfaction, with ease of use, e-scape and assurance being the most important ones. One the other hand, rather surprisingly, the only e-quality dimension that proved to have a significant positive impact on trust was customization. Finally, satisfaction was revealed to have a significant positive relation with trust.