nils-herrmann/clean_scirepeval huggingface dataset:
Using multi-instance enrollment to improve performance of 3D face recognition

This paper explores the use of multi-instance enrollment as a means to improve the performance of 3D face recognition. Experiments are performed using the ND-2006 3D face data set which contains 13,450 scans of 888 subjects. This is the largest 3D face data set currently available and contains a substantial amount of varied facial expression. Results indicate that the multi-instance enrollment approach outperforms a state-of-the-art component-based recognition approach, in which the face to be recognized is considered as an independent set of regions. ! 2008 Elsevier Inc. All rights reserved.
A Pragmatic AI Approach to Creating Artistic Visual Variations by Neural Style Transfer

On a constant quest for inspiration, designers can become more effective with tools that facilitate their creative process and let them overcome design fixation. This paper explores the practicality of applying neural style transfer as an emerging design tool for generating creative digital content. To this aim, the present work explores a well-documented neural style transfer algorithm (Johnson 2016) in four experiments on four relevant visual parameters: number of iterations, learning rate, total variation, content vs. style weight. The results allow a pragmatic recommendation of parameter configuration (number of iterations: 200 to 300, learning rate: 2e-1 to 4e-1, total variation: 1e-4 to 1e-8, content weights vs. style weights: 50:100 to 200:100) that saves extensive experimentation time and lowers the technical entry barrier. With this rule-of-thumb insight, visual designers can effectively apply deep learning to create artistic visual variations of digital content. This could enable designers to leverage AI for creating design works as state-of-the-art.
A One-Stage Correction of the Blepharophimosis Syndrome Using a Standard Combination of Surgical Techniques

The aim of this study was to evaluate the efficacy of a one-stage treatment for the blepharophimosis-ptosis-epicanthus inversus syndrome (BPES) using a combination of standard surgical techniques. This is a retrospective interventional case series study of 21 BPES patients with a 1-year minimum follow-up period. The one-stage intervention combined three different surgical procedures in the following order: Z-epicanthoplasty for the epicanthus, transnasal wiring of the medial canthal ligaments for the telecanthus, and a bilateral fascia lata sling for ptosis correction. Preoperative and postoperative measurements of the horizontal lid fissure length (HFL), vertical lid fissure width (VFW), nasal intercanthal distance (ICD), and the ratio between the intercanthal distance and the horizontal fissure length (ICD/HFL) were analyzed using Student’s t test for paired variables. The mean preoperative measurements were 4.95 ± 1.13 mm for the VFW, 20.90 ± 2.14 mm for the HFL, 42.45 ± 2.19 mm for the ICD, and 2.04 ± 0.14 mm for the ICD/HFL ratio. The mean postoperative measurements were 7.93 ± 1.02 mm for the VFW, 26.36 ± 1.40 mm for the HFL, 32.07 ± 1.96 mm for the ICD, and 1.23 ± 0.09 mm for the ICD/HFL ratio. All these values and their differences were statistically significant (P < 0.0001). All of the patients developed symmetric postoperative inferior version lagophthalmus, a complication that tended to decrease over time. One-stage correction of BPES is safe and efficient with the surgical techniques described.
Intelligent Maze Solving Robot Based on Image Processing and Graph Theory Algorithms

The most important task for maze solving robots is the fast and reliable finding of its shortest path from its initial point to its final destination point. This paper proposes an intelligent maze solving robot that can determine its shortest path on a line maze based on image processing and artificial intelligence algorithms. The image of the line maze is captured by a camera and sent to the computer to be analyzed and processed by a program developed using Visual C++ and OpenCV libraries and based on graph theory algorithms. The developed program solves the captured maze by examining all possible paths exist in the maze that could convey the robot to the required destination point. After that, the best shortest path is determined and then the instructions that guide the car-like robot to reach its desired destination point are sent to the robot through Bluetooth. The robot follows the received guide path to reach its destination. The proposed approach works faster than the traditional methods which push the robot to move through the maze cell by cell in order to find its destination point. Moreover, the proposed method allows the maze solving robot to avoid trapping and falling in infinity loops. Applications of maze solving systems include intelligent traffic control that helps ambulances, fire fighters, or rescuing robots to find their shortest path to their destination.
Acupuncture and electro-acupuncture for people diagnosed with subacromial pain syndrome: A multicentre randomized trial.

Musculoskeletal disorders have been identified globally as the second most common healthcare problem for 'years lived with disability', and of these shoulder conditions are amongst the most common, frequently associated with substantial pain and morbidity. Exercise and acupuncture are often provided as initial treatments for musculoskeletal shoulder conditions but their clinical effectiveness is uncertain. This study compared group exercise with group exercise plus either acupuncture or electro-acupuncture in patients with subacromial pain syndrome.



Two hundred and twenty-seven participants were recruited to a three-arm parallel-group randomized clinical trial. The primary outcome measure was the Oxford Shoulder Score. Follow-up was post treatment, and at 6 and 12 months. Between-group differences (two comparisons: the exercise group versus each of the acupuncture groups) were analysed at 6 months. A similar comparison across all follow-up time points was also conducted. Data were analysed on intention-to-treat principles with imputation of missing values.



Treatment groups were similar at baseline, and all treatment groups demonstrated an improvement over time. Between-group estimates at 6 months were, however, small and non-significant, for both of the comparisons. The analyses across all follow-up time points yielded similar conclusions. There was a high rate of missing values (22% for the Oxford Shoulder Score). A sensitivity analysis using complete data gave similar conclusions to the analysis with missing values imputed.



In the current investigation, neither acupuncture nor electro-acupuncture were found to be more beneficial than exercise alone in the treatment of subacromial pain syndrome. These findings may support clinicians with treatment planning.



Shoulder pain is common and associated with substantial morbidity. Acupuncture is a popular treatment for shoulder pain. The findings suggest that acupuncture and electro-acupuncture offer no additional benefit over exercise in the treatment of shoulder pain of musculoskeletal origin.
Modeling urban dynamics through GIS-based cellular automata

In urban systems modeling, there are many elaborate dynamic models based on intricate decision processes whose simulation must be based on customized software if their space±time properties are to be explored eectively. In this paper we present a class of urban models whose dynamics are based on theories of development associated with cellular automata (CA), whose data is ®ne-grained, and whose simulation requires software which can handle an enormous array of spatial and temporal model outputs. We ®rst introduce the generic problem of modeling within GIS, noting relevant CA models before outlining a generalized model based on Xie's (1996, A general model for cellular urban dynamics. Geographical Analysis, 28, 350±373) ``dynamic urban evolutionary modeling'' (DUEM) approach. We present ways in which land uses are structured through their life cycles, and ways in which existing urban activities spawn locations for new activities. We de®ne various decision rules that embed distance and direction, density thresholds, and transition or mutation probabilities into the model's dynamics, and we then outline the software designed to generate eective urban simulations consistent with GIS data inputs, outputs and related functionality. Finally, we present a range of hypothetical urban simulations that illustrate the diversity of model types that can be handled within the framework as a prelude to more realistic applications which will be reported in later papers.
Temporal Readout Noise Analysis and Reduction Techniques for Low-Light CMOS Image Sensors

In this paper, an analytical noise calculation is presented to derive the impact of process and design parameters on 1/f and thermal noise for a low-noise CMOS image sensor (CIS) readout chain. It is shown that dramatic noise reduction is obtained by using a thin-oxide transistor as the source follower of a typical 4T pixel. This approach is confirmed by a test chip designed in a 180-nm CIS process and embedding small arrays of the proposed new pixels together with state-ofthe-art 4T pixels for comparison. The new pixels feature a pitch of 7.5 μm and a fill factor of 66%. A 0.4erms input-referred noise and a 185-μV/econversion gain are obtained. Compared with state-of-the-art pixels, also present onto the test chip, the rms noise is divided by more than 2 and the conversion gain is multiplied by 2.2.
Power Modeling and Optimization for OLED Displays

Emerging organic light-emitting diode (OLED)-based displays obviate external lighting, and consume drastically different power when displaying different colors, due to their emissive nature. This creates a pressing need for OLED display power models for system energy management, optimization as well as energy-efficient GUI design, given the display content or even the graphical-user interface (GUI) code. In this work, we study this opportunity using commercial QVGA OLED displays and user studies. We first present a comprehensive treatment of power modeling of OLED displays, providing models that estimate power consumption based on pixel, image, and code, respectively. These models feature various tradeoffs between computation efficiency and accuracy so that they can be employed in different layers of a mobile system. We validate the proposed models using a commercial QVGA OLED module and a mobile device with a QVGA OLED display. Then, based on the models, we propose techniques that adapt GUIs based on existing mechanisms as well as arbitrarily under usability constraints. Our measurement and user studies show that more than 75 percent display power reduction can be achieved with user acceptance.
Continuous Beam Steering Through Broadside Using Asymmetrically Modulated Goubau Line Leaky-Wave Antennas

Goubau line is a single-conductor transmission line, featuring easy integration and low-loss transmission properties. Here, we propose a periodic leaky-wave antenna (LWA) based on planar Goubau transmission line on a thin dielectric substrate. The leaky-wave radiations are generated by introducing periodic modulations along the Goubau line. In this way, the surface wave, which is slow-wave mode supported by the Goubau line, achieves an additional momentum and hence enters the fast-wave region for radiations. By employing the periodic modulations, the proposed Goubau line LWAs are able to continuously steer the main beam from backward to forward within the operational frequency range. However, the LWAs usually suffer from a low radiation efficiency at the broadside direction. To overcome this drawback, we explore both transversally and longitudinally asymmetrical modulations to the Goubau line. Theoretical analysis, numerical simulations and experimental results are given in comparison with the symmetrical LWAs. It is demonstrated that the asymmetrical modulations significantly improve the radiation efficiency of LWAs at the broadside. Furthermore, the measurement results agree well with the numerical ones, which experimentally validates the proposed LWA structures. These novel Goubau line LWAs, experimentally demonstrated and validated at microwave frequencies, show also great potential for millimeter-wave and terahertz systems.
A Three-Phase Current-Fed DC/DC Converter With Active Clamp for Low-DC Renewable Energy Sources

This paper focuses on a new three-phase high power current-fed DC/DC converter with an active clamp. A three-phase DC/DC converter with high efficiency and voltage boosting capability is designed for use in the interface between a low-voltage fuel-cell source and a high-voltage DC bus for inverters. Zero-voltage switching in all active switches is achieved through using a common active clamp branch, and zero current switching in the rectifier diodes is achieved through discontinuous current conduction in the secondary side. Further, the converter is capable of increased power transfer due to its three-phase power configuration, and it reduces the RMS current per phase, thus reducing conduction losses. Moreover, a delta-delta connection on the three-phase transformer provides parallel current paths and reduces conduction losses in the transformer windings. An efficiency of above 93% is achieved through both improvements in the switching and through reducing conduction losses. A high voltage ratio is achieved by combining inherent voltage boost characteristics of the current-fed converter and the transformer turns ratio. The proposed converter and three-phase PWM strategy is analyzed, simulated, and implemented in hardware. Experimental results are obtained on a 500-W prototype unit, with all of the design verified and analyzed.
LOYALTY AS MEDIATOR ON THE RELATIONSHIP AMONG SERVICE QUALITY , SATISFACTION , CORPORATE IMAGE AND BEHAVIORAL INTENTION OF HEALTH TOURISM CUSTOMERS IN UPPER NORTHERN REGION OF THAILAND

The purpose of this research was to study both direct and indirect relationship factors of loyalty on service quality, satisfaction, corporate image and behavioral intention of health tourism customers in the Upper Northern Region of Thailand. Nowadays the self-care health tourism is currently popular. There are a lot of attractive sites in the northern part of Thailand where the weather is cool and with abundant of natural resources, especially the hot spring. There are 48 out of 112 hot springs scattered in the north. The local custom of the north is very famous such as their dressing, foods and colloquial language which is quite unique. Hot spring health tourism business is the whole health promotion: body, mind, emotion and spirit. It can help the tourist for relaxation and comfort. Using the loyalty in the health tourism business due to its quality service, satisfaction and corporate image give rise to the behavioral intention. There are only a few studies have been carried out with no research on Thailand. So this study will provide benefits to the tour agency to improve their services and physical image for satisfaction which leading to the loyalty and behavioral intention. The government’s policy and strategy emphasizes on health tourism business and spa to advocate Thai tradition and self-care in the near future. This study was the mixed research derived from literature reviews that related to the concept of loyalty, quality service, satisfaction, corporate image and behavioral intention. Studied population was the natural hot spring tourists at 5 provinces in upper north of Thailand which is Chiangrai, Chiangmai, Maehongson, Lampang and Phrae. Calculated sample sizes was provided by parameter derived from Cohen , together with G*power 3.0 program. Total cases were 350 cases selected from the hot spring attractions in the studied provinces. Questionnaires were performed and issued by e-mail, postal mail and interview. Quantitative analysis was performed to find out the relative factors by structural equation from Structure Equation Model (SEM) which formulated by PLS Graph program. Qualitative analysis was performed by interview and analysed the contents to support the quantitative research that concerned to health business spa. KeywordsLoyalty, Service Quality, Satisfaction, Corporate Image, Behavioral Intention, Customer’s Health Tourism, Hot Spring.
Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis.

Glaucoma is the leading cause of global irreversible blindness. Present estimates of global glaucoma prevalence are not up-to-date and focused mainly on European ancestry populations. We systematically examined the global prevalence of primary open-angle glaucoma (POAG) and primary angle-closure glaucoma (PACG), and projected the number of affected people in 2020 and 2040.



Systematic review and meta-analysis.



Data from 50 population-based studies (3770 POAG cases among 140,496 examined individuals and 786 PACG cases among 112 398 examined individuals).



We searched PubMed, Medline, and Web of Science for population-based studies of glaucoma prevalence published up to March 25, 2013. Hierarchical Bayesian approach was used to estimate the pooled glaucoma prevalence of the population aged 40-80 years along with 95% credible intervals (CrIs). Projections of glaucoma were estimated based on the United Nations World Population Prospects. Bayesian meta-regression models were performed to assess the association between the prevalence of POAG and the relevant factors.



Prevalence and projection numbers of glaucoma cases.



The global prevalence of glaucoma for population aged 40-80 years is 3.54% (95% CrI, 2.09-5.82). The prevalence of POAG is highest in Africa (4.20%; 95% CrI, 2.08-7.35), and the prevalence of PACG is highest in Asia (1.09%; 95% CrI, 0.43-2.32). In 2013, the number of people (aged 40-80 years) with glaucoma worldwide was estimated to be 64.3 million, increasing to 76.0 million in 2020 and 111.8 million in 2040. In the Bayesian meta-regression model, men were more likely to have POAG than women (odds ratio [OR], 1.36; 95% CrI, 1.23-1.52), and after adjusting for age, gender, habitation type, response rate, and year of study, people of African ancestry were more likely to have POAG than people of European ancestry (OR, 2.80; 95% CrI, 1.83-4.06), and people living in urban areas were more likely to have POAG than those in rural areas (OR, 1.58; 95% CrI, 1.19-2.04).



The number of people with glaucoma worldwide will increase to 111.8 million in 2040, disproportionally affecting people residing in Asia and Africa. These estimates are important in guiding the designs of glaucoma screening, treatment, and related public health strategies.
Powering the Future with the Integrated Power System

267 ABSTRACT For the past four years, Advanced Surface Machinery Programs (SEA 03R2) has been developing the Integrated Power System (IPS) to reduce ship acquisition and life cycle costs while still meeting all ship performance requirements. IPS provides electrical power to ship service loads and electric propulsion for a wide range of ship applications including surface combatants, aircraft carriers, amphibious ships, auxiliary ships, sealift and high value commercial ships. IPS consists of an architecture and a family of modules from which affordable and high performance configurations can be developed for the full range of ship applications. Two years ago, the initial IPS concepts were presented at ASNE Day 1994. Since then, much has been learned through the Reduced Scale Advanced Development (RSAD) and Full Scale Advanced Development (FSAD) programs. This paper describes the fundamental IPS architecture, details the evolving "family of modules" and their interface standards, and outlines the "Mass Customization" based design process for achieving customer performance requirements with an affordable IPS configuration. Lcdr. Norbert Doerry, USN, Henry Robey, LCdr.
An induction furnace employing with half bridge series resonant inverter

In this paper, an induction furnace employing with half bridge series resonant inverter built around IGBT as its switching devices suitable for melting 500 grams of brass is presented. Melting times of 10 minutes were achieved at a power level of approximately 4 kW. The operating frequency is automatically tracked to maintain a small constant lagging phase angle using dual phase lock loop when brass is melted. The coil voltage is controlled to protect the resonant capacitors. The experimental results are presented.
Making flexible magnetic aerogels and stiff magnetic nanopaper using cellulose nanofibrils as templates.

Nanostructured biological materials inspire the creation of materials with tunable mechanical properties. Strong cellulose nanofibrils derived from bacteria or wood can form ductile or tough networks that are suitable as functional materials. Here, we show that freeze-dried bacterial cellulose nanofibril aerogels can be used as templates for making lightweight porous magnetic aerogels, which can be compacted into a stiff magnetic nanopaper. The 20-70-nm-thick cellulose nanofibrils act as templates for the non-agglomerated growth of ferromagnetic cobalt ferrite nanoparticles (diameter, 40-120 nm). Unlike solvent-swollen gels and ferrogels, our magnetic aerogel is dry, lightweight, porous (98%), flexible, and can be actuated by a small household magnet. Moreover, it can absorb water and release it upon compression. Owing to their flexibility, high porosity and surface area, these aerogels are expected to be useful in microfluidics devices and as electronic actuators.
1 A Weakly Supervised Learning Framework For Detecting Social Anxiety And Depression ASIF

Although social anxiety and depression are common, they are often underdiagnosed and undertreated, in part due to difficulties identifying and accessing individuals in need of services. Current assessments rely on client self-report and clinician judgment, which are vulnerable to social desirability and other subjective biases. Identifying objective, nonburdensome markers of these mental health problems, such as features of speech, could help advance assessment, prevention, and treatment approaches. Prior research examining speech detection methods has focused on fully supervised learning approaches employing strongly labeled data. However, strong labeling of individuals high in symptoms or state affect in speech audio data is impractical, in part because it is not possible to identify with high confidence which regions of a long speech indicate the person’s symptoms or affective state. We propose a weakly supervised learning framework for detecting social anxiety and depression from long audio clips. Specifically, we present a novel feature modeling technique named NN2Vec that identifies and exploits the inherent relationship between speakers’ vocal states and symptoms/affective states. Detecting speakers high in social anxiety or depression symptoms using NN2Vec features achieves F-1 scores 17% and 13% higher than those of the best available baselines. In addition, we present a new multiple instance learning adaptation of a BLSTM classifier, named BLSTM-MIL. Our novel framework of using NN2Vec features with the BLSTM-MIL classifier achieves F-1 scores of 90.1% and 85.44% in detecting speakers high in social anxiety and depression symptoms.