nils-herrmann/clean_scirepeval huggingface dataset:
Face detection techniques: a review

With the marvelous increase in video and image database there is an incredible need of automatic understanding and examination of information by the intelligent systems as manually it is getting to be plainly distant. Face plays a major role in social intercourse for conveying identity and feelings of a person. Human beings have not tremendous ability to identify different faces than machines. So, automatic face detection system plays an important role in face recognition, facial expression recognition, head-pose estimation, human–computer interaction etc. Face detection is a computer technology that determines the location and size of a human face in a digital image. Face detection has been a standout amongst topics in the computer vision literature. This paper presents a comprehensive survey of various techniques explored for face detection in digital images. Different challenges and applications of face detection are also presented in this paper. At the end, different standard databases for face detection are also given with their features. Furthermore, we organize special discussions on the practical aspects towards the development of a robust face detection system and conclude this paper with several promising directions for future research.
Analysing Cloud Services Reviews Using Opining Mining

There is increasing interest in sharing the experience of products and services on the web platform, and social media has opened a way for product and service providers to understand their consumers needs and expectations. This paper explores reviews by cloud consumers that reflect consumers experiences with cloud services. The reviews of around 6,000 cloud service users were analysed using sentiment analysis to identify the attitude of each review, and to determine whether the opinion expressed was positive, negative, or neutral. The analysis used two data mining tools, KNIME and RapidMiner, and the results were compared. We developed four prediction models in this study to predict the sentiment of users reviews. The proposed model is based on four supervised machine learning algorithms: K-Nearest Neighbour (k-NN), Nave Bayes, Random Tree, and Random Forest. The results show that the Random Forest predictions achieve 97.06% accuracy, which makes this model a better prediction model than the other three.
A Colonel Blotto Game for Anti-Jamming in the Internet of Things

The Internet of Things (IoT) is envisioned to be a large-scale system that interconnects sensors, mundane objects, and other physical devices via an effective communication infrastructure. Given the heterogeneous and large-scale nature of the IoT, security has emerged as a key challenge. This challenge is further exacerbated by the fact that security solutions for the IoT must account for the limited computational capabilities of the IoT's nodes. That makes enhancing the security at the physical layer level an attractive solution for IoT networks. In this paper, a novel anti- jamming mechanism is proposed to enable a fusion center to defend the IoT from a malicious radio jamming attack. The problem is formulated as a Colonel Blotto game in which the fusion center, acting as defender, aims to detect the jamming attack by increasing the number of bits allocated to certain nodes for reporting their measured interference level, while the jammer aims to disturb the network performance and still be undetected. To solve this game, an algorithm based on fictitious play is proposed to reach the equilibrium of the game. Simulation results show that the proposed mechanism outperforms the mechanism of allocating the available bits in a random manner for two different cases of network architecture.
Dynamic life table model for Aedes aegypti (diptera: Culicidae): simulation results and validation.

The container-inhabiting mosquito simulation model (CIMSiM) is a weather-driven, dynamic life table simulation model of Aedes aegypti (L.) and similar nondiapausing Aedes mosquitoes that inhabit artificial and natural containers. This paper presents a validation of CIMSiM simulating Ae. aegypti using several independent series of data that were not used in model development. Validation data sets include laboratory work designed to elucidate the role of diet on fecundity and rates of larval development and survival. Comparisons are made with four field studies conducted in Bangkok, Thailand, on seasonal changes in population dynamics and with a field study in New Orleans, LA, on larval habitat. Finally, predicted ovipositional activity of Ae. aegypti in seven cities in the southeastern United States for the period 1981-1985 is compared with a data set developed by the U.S. Public Health Service. On the basis of these comparisons, we believe that, for stated design goals, CIMSiM adequately simulates the population dynamics of Ae. aegypti in response to specific information on weather and immature habitat. We anticipate that it will be useful in simulation studies concerning the development and optimization of control strategies and that, with further field validation, can provide entomological inputs for a dengue virus transmission model.
Who Uses Mobile Phone Health Apps and Does Use Matter? A Secondary Data Analytics Approach

Mobile phone use and the adoption of healthy lifestyle software apps ("health apps") are rapidly proliferating. There is limited information on the users of health apps in terms of their social demographic and health characteristics, intentions to change, and actual health behaviors.



The objectives of our study were to (1) to describe the sociodemographic characteristics associated with health app use in a recent US nationally representative sample; (2) to assess the attitudinal and behavioral predictors of the use of health apps for health promotion; and (3) to examine the association between the use of health-related apps and meeting the recommended guidelines for fruit and vegetable intake and physical activity.



Data on users of mobile devices and health apps were analyzed from the National Cancer Institute's 2015 Health Information National Trends Survey (HINTS), which was designed to provide nationally representative estimates for health information in the United States and is publicly available on the Internet. We used multivariable logistic regression models to assess sociodemographic predictors of mobile device and health app use and examine the associations between app use, intentions to change behavior, and actual behavioral change for fruit and vegetable consumption, physical activity, and weight loss.



From the 3677 total HINTS respondents, older individuals (45-64 years, odds ratio, OR 0.56, 95% CI 0.47-68; 65+ years, OR 0.19, 95% CI 0.14-0.24), males (OR 0.80, 95% CI 0.66-0.94), and having degree (OR 2.83, 95% CI 2.18-3.70) or less than high school education (OR 0.43, 95% CI 0.24-0.72) were all significantly associated with a reduced likelihood of having adopted health apps. Similarly, both age and education were significant variables for predicting whether a person had adopted a mobile device, especially if that person was a college graduate (OR 3.30). Individuals with apps were significantly more likely to report intentions to improve fruit (63.8% with apps vs 58.5% without apps, P=.01) and vegetable (74.9% vs 64.3%, P<.01) consumption, physical activity (83.0% vs 65.4%, P<.01), and weight loss (83.4% vs 71.8%, P<.01). Individuals with apps were also more likely to meet recommendations for physical activity compared with those without a device or health apps (56.2% with apps vs 47.8% without apps, P<.01).



The main users of health apps were individuals who were younger, had more education, reported excellent health, and had a higher income. Although differences persist for gender, age, and educational attainment, many individual sociodemographic factors are becoming less potent in influencing engagement with mobile devices and health app use. App use was associated with intentions to change diet and physical activity and meeting physical activity recommendations.
Embodiment or Envatment ? : Reflections on the Bodily Basis of Consciousness

Suppose that a team of neurosurgeons and bioengineers were able to remove your brain from your body, suspend it in a life-sustaining vat of liquid nutrients, and connect its neurons and nerve terminals by wires to a supercomputer that would stimulate it with electrical impulses exactly like those it normally receives when embodied. According to this brain-in-a-vat thought experiment, your envatted brain and your embodied brain would have subjectively indistinguishable mental lives. For all you know—so one argument goes—you could be such a brain in a vat right now. Daniel Dennett calls this sort of philosophical thought experiment an “intuition pump” (1995). An intuition pump is designed to elicit certain intuitive convictions, but is not itself a proper argument: “Intuition pumps are fine if they’re used correctly, but they can also be misused. They’re not arguments, they’re stories. Instead of having a conclusion, they pump an intuition. They get you to say ‘Aha! Oh, I get it!’” (Dennett 1995, 182). Philosophers have used the brain-in-a-vat story mainly to raise the problem of radical skepticism and to elicit various intuitions about meaning and knowledge (Putnam 1981). The basic intuition the story tries to pump is that the envatted brain, though fully conscious, has systematically false beliefs about the world, including itself. Some philosophers reject this intuition. They propose that the envatted brain’s beliefs are really about its artificial environment or that it has no real beliefs at all. According to these proposals, the mental lives of the two brains do not match, despite their being subjectively indistinguishable. Dennett (1978) tells a classic variant of the brain-in-a-vat story, one in which he sees his own envatted brain and knows that it remotely controls his own body, but still cannot experience himself as located where his brain is located. Here the thought experiment serves to raise questions about the locus of the self in the physical world.
Marchand balun with connecting segment designed with the use of multi-technique compensation

In this paper, a single-layer compensated Marchand balun with arbitrarily chosen connecting line segment has been presented. It has been shown that the utilization of connecting line compensation technique together with the method of capacitive and inductive coupling coefficients' equalization in coupled-lines allows for reduction of the required number of compensating elements. The theoretical investigation has been verified by electromagnetic simulations and measurements of Marchand balun designed in a microstrip technique, operating at f0 = 1.3 GHz and terminated at the input and output with 70 Ω and 100 Ω, respectively.
Pressure ulcer prevention and healing using alternating pressure mattress at home: the PARESTRY project.

Specialised pressure-relieving supports reduce or relieve the interface pressure between the skin and the support surface. The comparative effectiveness of dynamic support surfaces is debated. The aim of this study is to examine the impact of using an alternating pressure air mattress (APAM) on pressure ulcer (PU) incidence in patients receiving home-based care. A second aim was to determine the level of patient/family satisfaction with comfort and gain the views of the care team that used the APAM.



The PARESTRY study was a prospective observational study conducted in patients with a high risk of PUs (Braden score <15), discharged to hospital-care at home. The primary prevention groups consisted of patients with no PU at baseline who were in bed for at least 20 hours a day. Patients at baseline with a category 3 or 4 PU or a category 1 or 2 PU in association with poor general health or end-of-life status were included in the secondary prevention group. All patients were laid on an APAM. The primary end point was the % of patients with a worsening skin condition in the pressure area (heel, sacrum, ischium) at day 90 or at the end of the study. The primary analysis was done on the full analysis set (patients included with at least a second assessment), using the last observation carried forward technique to handle missing data, at day 90. A 95% confidence interval was calculated.



Analysis was performed on 92 patients (30 in primary prevention and 62 in secondary prevention). The average time spent in bed was 22.7 (SD 2.7) hours a day and 22.6 (SD 2.2) hours in the primary and secondary prevention groups, respectively. At baseline, in the secondary group, 77% of patients had a sacral PU, 63% a heel PU, 8% an ischial tuberosity PU and 45% a PU in another area, a number of patients having multiple PUs. In the primary prevention group, 63% (19/30) of patients dropped out of the study (5 were hospitalised, 9 died, 5 other causes). In the secondary prevention group, 61% (38/62) dropped out (7 were hospitalised, 23 died, 8 others causes). In the primary prevention group, only one patient had worsening skin condition. In the secondary prevention group, 17.7% (11/62: 95% CI: 8.3-27.2) of patients had worsening skin condition. The number of PUs decreased regardless of location. At the end of follow-up, 49% (45/92) of patients had a PU versus 67% (62/92) at baseline



This work provides data on the incidence of PUs in patients at high risk, who are using APAMs, and, following inpatient hospitalisation, are taken into home health-care centres. The results of the study highlight the importance of continuity of care across transitions between care settings.
A Snapback Suppressed Reverse-Conducting IGBT With a Floating p-Region in Trench Collector

A novel reverse-conducting insulated-gate bipolar transistor (RC-IGBT) featuring an oxide trench placed between the n-collector and the p-collector and a floating p-region (p-float) sandwiched between the n-drift and n-collector is proposed. First, the new structure introduces a high-resistance collector short resistor at low current density, which leads to the suppression of the snapback effect. Second, the collector short resistance can be adjusted by varying the p-float length without increasing the collector cell length. Third, the p-float layer also acts as the base of the n-collector/p-float/n-drift transistor which can be activated and offers a low-resistance current path at high current densities, which contributes to the low on-state voltage of the integrated freewheeling diode and the fast turnoff. As simulations show, the proposed RC-IGBT shows snapback-free output characteristics and faster turnoff compared with the conventional RC-IGBT.
Dense 3D face alignment from 2D videos in real-time

To enable real-time, person-independent 3D registration from 2D video, we developed a 3D cascade regression approach in which facial landmarks remain invariant across pose over a range of approximately 60 degrees. From a single 2D image of a person's face, a dense 3D shape is registered in real time for each frame. The algorithm utilizes a fast cascade regression framework trained on high-resolution 3D face-scans of posed and spontaneous emotion expression. The algorithm first estimates the location of a dense set of markers and their visibility, then reconstructs face shapes by fitting a part-based 3D model. Because no assumptions are required about illumination or surface properties, the method can be applied to a wide range of imaging conditions that include 2D video and uncalibrated multi-view video. The method has been validated in a battery of experiments that evaluate its precision of 3D reconstruction and extension to multi-view reconstruction. Experimental findings strongly support the validity of real-time, 3D registration and reconstruction from 2D video. The software is available online at http://zface.org.
Model-based adaptive user interface based on context and user experience evaluation

Personalized services have greater impact on user experience to effect the level of user satisfaction. Many approaches provide personalized services in the form of an adaptive user interface. The focus of these approaches is limited to specific domains rather than a generalized approach applicable to every domain. In this paper, we proposed a domain and device-independent model-based adaptive user interfacing methodology. Unlike state-of-the-art approaches, the proposed methodology is dependent on the evaluation of user context and user experience (UX). The proposed methodology is implemented as an adaptive UI/UX authoring (A-UI/UX-A) tool; a system capable of adapting user interface based on the utilization of contextual factors, such as user disabilities, environmental factors (e.g. light level, noise level, and location) and device use, at runtime using the adaptation rules devised for rendering the adapted interface. To validate effectiveness of the proposed A-UI/UX-A tool and methodology, user-centric and statistical evaluation methods are used. The results show that the proposed methodology outperforms the existing approaches in adapting user interfaces by utilizing the users context and experience.
A graphene-based electrochemical sensor for sensitive detection of paracetamol.

An electrochemical sensor based on the electrocatalytic activity of functionalized graphene for sensitive detection of paracetamol is presented. The electrochemical behaviors of paracetamol on graphene-modified glassy carbon electrodes (GCEs) were investigated by cyclic voltammetry and square-wave voltammetry. The results showed that the graphene-modified electrode exhibited excellent electrocatalytic activity to paracetamol. A quasi-reversible redox process of paracetamol at the modified electrode was obtained, and the over-potential of paracetamol decreased significantly compared with that at the bare GCE. Such electrocatalytic behavior of graphene is attributed to its unique physical and chemical properties, e.g., subtle electronic characteristics, attractive pi-pi interaction, and strong adsorptive capability. This electrochemical sensor shows an excellent performance for detecting paracetamol with a detection limit of 3.2x10(-8)M, a reproducibility of 5.2% relative standard deviation, and a satisfied recovery from 96.4% to 103.3%. The sensor shows great promise for simple, sensitive, and quantitative detection and screening of paracetamol.
When did Mozart Become a Mozart ? Neurophysiological Insight Into Behavioral Genetics

The prevailing concept in modern cognitive neuroscience is that cognitive functions are performed predominantly at the network level, whereas the role of individual neurons is unlikely to extend beyond forming the simple basic elements of these networks. Within this conceptual framework, individuals of outstanding cognitive abilities appear as a result of a favorable configuration of the microarchitecture of the cognitive-implicated networks, whose final formation in ontogenesis may occur in a relatively random way. Here I suggest an alternative concept, which is based on neurological data and on data from human behavioral genetics. I hypothesize that cognitive functions are performed mainly at the intracellular, probably at the molecular level. Central to this hypothesis is the idea that the neurons forming the networks involved in cognitive processes are complex elements whose functions are not limited to generating electrical potentials and releasing neurotransmitters. According to this hypothesis, individuals of outstanding abilities are so due to a ‘lucky’ combination of specific genes that determine the intrinsic properties of neurons involved in cognitive functions of the brain.
Graph-Based Clustering for Computational Linguistics: A Survey

In this survey we overview graph-based clustering and its applications in computational linguistics. We summarize graph-based clustering as a five-part story: hypothesis, modeling, measure, algorithm and evaluation. We then survey three typical NLP problems in which graph-based clustering approaches have been successfully applied. Finally, we comment on the strengths and weaknesses of graph-based clustering and envision that graph-based clustering is a promising solution for some emerging NLP problems.
A Novel Security-Enhanced Agile Software Development Process Applied in an Industrial Setting

A security-enhanced agile software development process, SEAP, is introduced in the development of a mobile money transfer system at Ericsson Corp. A specific characteristic of SEAP is that it includes a security group consisting of four different competences, i.e., Security manager, security architect, security master and penetration tester. Another significant feature of SEAP is an integrated risk analysis process. In analyzing risks in the development of the mobile money transfer system, a general finding was that SEAP either solves risks that were previously postponed or solves a larger proportion of the risks in a timely manner. The previous software development process, i.e., The baseline process of the comparison outlined in this paper, required 2.7 employee hours spent for every risk identified in the analysis process compared to, on the average, 1.5 hours for the SEAP. The baseline development process left 50% of the risks unattended in the software version being developed, while SEAP reduced that figure to 22%. Furthermore, SEAP increased the proportion of risks that were corrected from 12.5% to 67.1%, i.e., More than a five times increment. This is important, since an early correction may avoid severe attacks in the future. The security competence in SEAP accounts for 5% of the personnel cost in the mobile money transfer system project. As a comparison, the corresponding figure, i.e., For security, was 1% in the previous development process.
A Compact High-Performance Orthomode Transducer for the Atacama Large Millimeter Array (ALMA) Band 1 (31–45 GHz)

This paper describes a compact high-performance orthomode transducer (OMT) with a circular waveguide input and two rectangular waveguide outputs based on the superimposition of three aluminum blocks. Several prototypes operating in the band 1 (31-45 GHz) of the atacama large millimeter array have been fabricated and measured. The design is based on the use of a turnstile junction that is machined in a single block, requiring neither alignment nor a high degree of mechanical tolerances. Thus, a high repeatability of the design is possible for mass production. Across the 31-45 GHz band, the isolation is better than 50 dB and the return losses at the input and outputs of the OMT are better than -25 dB.
Remote Detection of Photoplethysmographic Systolic and Diastolic Peaks Using a Digital Camera

We present a new method for measuring photoplethysmogram signals remotely using ambient light and a digital camera that allows for accurate recovery of the waveform morphology (from a distance of 3 m). In particular, we show that the peak-to-peak time between the systolic peak and diastolic peak/inflection can be automatically recovered using the second-order derivative of the remotely measured waveform. We compare measurements from the face with those captured using a contact fingertip sensor and show high agreement in peak and interval timings. Furthermore, we show that results can be significantly improved using orange, green, and cyan color channels compared to the tradition red, green, and blue channel combination. The absolute error in interbeat intervals was 26 ms and the absolute error in mean systolic-diastolic peak-to-peak times was 12 ms. The mean systolic-diastolic peak-to-peak times measured using the contact sensor and the camera were highly correlated, ρ = 0.94 (p <; 0.001). The results were obtained with a camera frame-rate of only 30 Hz. This technology has significant potential for advancing healthcare.