nils-herrmann/clean_scirepeval huggingface dataset:
Students' Perceptions of Edmodo and Mobile Learning and Their Real Barriers towards Them.

The present research aims to investigate the students' perceptions levels of Edmodo and Mobile learning and to identify the real barriers of them at Taibah University in KSA. After implemented Edmodo application as an Mlearning platform, two scales were applied on the research sample, the first scale consisted of 36 statements was constructed to measure students' perceptions towards Edmodo and M-learning, and the second scale consisted of 17 items was constructed to determine the barriers of Edmodo and M-learning. The scales were distributed on 27 students during the second semester of the academic year 2013/2014. Findings indicated that students' perceptions of Edmodo and Mobile learning is in “High” level in general, and majority of students have positive perceptions towards Edmodo and Mobile learning since they think that learning using Edmodo facilitates and increases effectiveness communication of learning, and they appreciate Edmodo because it save time. Regarding the barriers of Edmodo and Mobile learning that facing several students seem like normal range, however, they were facing a problem of low mobile battery, and storing large files in their mobile phones, but they do not face any difficulty to enter the information on small screen size of mobile devices. Finally, it is suggested adding a section for M-learning in the universities to start application of M-learning and prepare a visible and audible guide for using of M-learning in teaching and learning.
Learning in Particle Swarm Optimization

This paper presents particle swarm optimization based on learning from winner particle. (PSO-WS). Instead of considering gbest and pbest particle for position update, each particle considers its distance from immediate winner to update its position. Only winner particle follow general velocity and position update equation. If this strategy performs well for the particle, then that particle updates its position based on this strategy, otherwise its position is replaced by its immediate winner particle’s position. Dimension dependant swarm size is used for better exploration. Proposed method is compared with CSO and CCPSO2, which are available to solve large scale optimization problems. Statistical results show that proposed method performs well for separable as well as non separable problems.
Combining Deep Facial and Ambient Features for First Impression Estimation

First impressions influence the behavior of people towards a newly encountered person or a human-like agent. Apart from the physical characteristics of the encountered face, the emotional expressions displayed on it, as well as ambient information affect these impressions. In this work, we propose an approach to predict the first impressions people will have for a given video depicting a face within a context. We employ pre-trained Deep Convolutional Neural Networks to extract facial expressions, as well as ambient information. After video modeling, visual features that represent facial expression and scene are combined and fed to Kernel Extreme Learning Machine regressor. The proposed system is evaluated on the ChaLearn Challenge Dataset on First Impression Recognition, where the classification target is the ”Big Five” personality trait labels for each video. Our system achieved an accuracy of 90.94% on the sequestered test set, 0.36% points below the top system in the competition.
Stock market prediction using Hidden Markov Model

Stock market is the most popular investment scheme promising high returns albeit some risks. An intelligent stock prediction model would thus be desirable. So, this paper aims at surveying recent literature in the area of Neural Network, Hidden Markov Model and Support Vector Machine used to predict the stock market fluctuation. Neural networks and SVM are identified to be the leading machine learning techniques in stock market prediction area. Also, a model for predicting stock market using HMM is presented. Traditional techniques lack in covering stock price fluctuations and so new approaches have been developed for analysis of stock price variations. Markov Model is one such recent approach promising better results. In this paper a predicting method using Hidden Markov Model is proposed to provide better accuracy and a comparison of the existing techniques is also done.
Sensor Guardian: prevent privacy inference on Android sensors

Privacy inference attacks based on sensor data is an emerging and severe threat on smart devices, in which malicious applications leverage data from innocuous sensors to infer sensitive information of user, e.g., utilizing accelerometers to infer user’s keystroke. In this paper, we present Sensor Guardian, a privacy protection system that mitigates this threat on Android by hooking and controlling applications’ access to sensors. Sensor Guardian inserts hooks into applications by statically instrumenting their APK (short for Android Package Kit) files and enforces control policies in these hooks at runtime. Our evaluation shows that Sensor Guardian can effectively and efficiently mitigate the privacy inference threat on Android sensors, with negligible overhead during both static instrumentation and runtime control.
Identifying and addressing vaccine hesitancy.

In the 20th century, the introduction of multiple vaccines significantly reduced childhood morbidity, mortality, and disease outbreaks. Despite, and perhaps because of, their public health impact, an increasing number of parents and patients are choosing to delay or refuse vaccines. These individuals are described as "vaccine hesitant." This phenomenon has developed due to the confluence of multiple social, cultural, political, and personal factors. As immunization programs continue to expand, understanding and addressing vaccine hesitancy will be crucial to their successful implementation. This review explores the history of vaccine hesitancy, its causes, and suggested approaches for reducing hesitancy and strengthening vaccine acceptance.
A modified Artificial Bee Colony algorithm for real-parameter optimization

Swarm intelligence is a research field that models the collective intelligence in swarms of insects or animals. Many algorithms that simulates these models have been proposed in order to solve a wide range of problems. The Artificial Bee Colony algorithm is one of the most recent swarm intelligence based algorithms which simulates the foraging behaviour of honey bee colonies. In this work, modified versions of the Artificial Bee Colony algorithm are introduced and applied for efficiently solving real-parameter optimization problems.
Document-based Recommender System for Job Postings using Dense Representations

Job boards and professional social networks heavily use recommender systems in order to better support users in exploring job advertisements. Detecting the similarity between job advertisements is important for job recommendation systems as it allows, for example, the application of item-to-item based recommendations. In this work, we research the usage of dense vector representations to enhance a large-scale job recommendation system and to rank German job advertisements regarding their similarity. We follow a two-folded evaluation scheme: (1) we exploit historic user interactions to automatically create a dataset of similar jobs that enables an offline evaluation. (2) In addition, we conduct an online A/B test and evaluate the best performing method on our platform reaching more than 1 million users. We achieve the best results by combining job titles with full-text job descriptions. In particular, this method builds dense document representation using words of the titles to weigh the importance of words of the full-text description. In the online evaluation, this approach allows us to increase the click-through rate on job recommendations for active users by 8.0%.
Coverage and capacity of millimeter-wave cellular networks

The millimeter-wave (mmWave) band offers the potential for high-bandwidth communication channels in cellular networks. It is not clear, however, whether both high data rates and coverage in terms of signal-to-noise-plus-interference ratio can be achieved in interference-limited mmWave cellular networks due to the differences in propagation conditions and antenna topologies. This article shows that dense mmWave networks can achieve both higher data rates and comparable coverage relative to conventional microwave networks. Sum rate gains can be achieved using more advanced beamforming techniques that allow multiuser transmission. The insights are derived using a new theoretical network model that incorporates key characteristics of mmWave networks.
Still happy after all these years: research frontiers on subjective well-being in later life.

OBJECTIVES. Understanding the factors that promote quality of life in old age has been a staple of social gerontology since its inception and remains a significant theme in aging research. The purpose of this article was to review the state of the science with regard to subjective well-being (SWB) in later life and to identify promising directions for future research.



This article is based on a review of literature on SWB in aging, sociological, and psychological journals. Although the materials reviewed date back to the early 1960s, the emphasis is on publications in the past decade.



Research to date paints an effective portrait of the epidemiology of SWB in late life and the factors associated with it. Although the research base is large, causal inferences about the determinants of SWB remain problematic. Two recent contributions to the research base are highlighted as emerging issues: studies of secular trends in SWB and cross-national studies.  The review ends with discussion of priority issues for future research.
Supplier integration into new product development : coordinating product , process and supply chain design

In many industries, firms are seeking to cut concept to customer development time, improve quality, reduce the cost of new products and facilitate the smooth launch of new products. Prior research has indicated that the integration of material suppliers into the new product development (NPD) cycle can provide substantial benefits towards achieving these goals. This involvement may range from simple consultation with suppliers on design ideas to making suppliers fully responsible for the design of components or systems they will supply. Moreover, suppliers may be involved at different stages of the new product development process. Early supplier involvement is a key coordinating process in supply chain design, product design and process design. Several important questions regarding supplier involvement in new product development remain unanswered. Specifically, we look at the issue of what managerial practices affect new product development team effectiveness when suppliers are to be involved. We also consider whether these factors differ depending on when the supplier is to be involved and what level of responsibility is to be given to the supplier. Finally, we examine whether supplier involvement in new product development can produce significant improvements in financial returns and/or product design performance. We test these proposed relationships using survey data collected from a group of global organizations and find support for the relationships based on the results of a multiple regression analysis.
Interfaces That Heal: Coupling Real and Virtual Objects to Treat Spider Phobia

Tactile augmentation is a simple, safe, inexpensive interaction technique for adding physical texture and force feedback cues to virtual objects. This study explored whether virtual reality (VR) exposure therapy reduces fear of spiders and whether giving patients the illusion of physically touching the virtual spider increases treatment effectiveness. Eight clinically phobic students were randomly assigned to one of 3 groups—(a) no treatment, (b) VR with no tactile cues, or (c) VR with a physically “touchable” virtual spider—as were 28 nonclinically phobic students. Participants in the 2 VR treatment groups received three 1-hr exposure therapy sessions resulting in clinically significant drops in behavioral avoidance and subjective fear ratings. The tactile augmentation group showed the greatest progress on behavioral measures. On average, participants in this group, who only approached to 5.5 ft of a live spider on the pretreatment Behavioral Avoidance Test (Garcia-Palacios, 2002), were able to approach to 6 in. of the spider after VR exposure treatment and did so with much less anxiety (see www.vrpain.com for details). Practical implications are discussed.
A Quantitative Model of the British Industrial Revolution , 1780-1850

A simple quantitative model is presented that is consistent with the available evidence about the British economy during the early phase of the Industrial Revolution. The basic model is a variant of a standard growth model, calibrated to data from Great Britain for the period 1780-1850. The model is used to study the importance of foreign trade and the role of the declining cost of power during this period. The British Industrial Revolution was an amazing episode, with economic consequences that changed the world. But our understanding of the economic events of this ¤Research Department, Federal Reserve Bank of Minneapolis, and Department of Economics, University of Chicago. I am grateful to Matthias Doepke for many stimulating conversations, as well as several useful leads on data sources. I also owe more than the ususal thanks to Joel Mokyr for many helpful comments, including several that changed the direction of the paper in a fundamental way. Finally, I am grateful to the Research Division of Federal Reserve Bank of Minneapolis for support while much of this work was done. This paper is being prepared for the Carnegie-Rochester conference in November, 2000.
Defense Against Adversarial Attacks with Saak Transform

Deep neural networks (DNNs) are known to be vulnerable to adversarial perturbations, which imposes a serious threat to DNN-based decision systems. In this paper, we propose to apply the lossy Saak transform to adversarially perturbed images as a preprocessing tool to defend against adversarial attacks. Saak transform is a recently-proposed state-of-the-art for computing the spatial-spectral representations of input images. Empirically, we observe that outputs of the Saak transform are very discriminative in differentiating adversarial examples from clean ones. Therefore, we propose a Saak transform based preprocessing method with three steps: 1) transforming an input image to a joint spatial-spectral representation via the forward Saak transform, 2) apply filtering to its high-frequency components, and, 3) reconstructing the image via the inverse Saak transform. The processed image is found to be robust against adversarial perturbations. We conduct extensive experiments to investigate various settings of the Saak transform and filtering functions. Without harming the decision performance on clean images, our method outperforms state-of-the-art adversarial defense methods by a substantial margin on both the CIFAR10 and ImageNet datasets. Importantly, our results suggest that adversarial perturbations can be effectively and efficiently defended using state-of-the-art frequency analysis.
Randomised, Double-Blind, Parallel, Placebo-Controlled Study of Oral Glucosamine, Methylsulfonylmethane and their Combination in Osteoarthritis.

Glucosamine, classified as a slow-acting drug in osteoarthritis (SADOA), is an efficacious chondroprotective agent. Methylsulfonylmethane (MSM), the isoxidised form of dimethyl-sulfoxide (DSMO), is an effective natural analgesic and anti-inflammatory agent. The aim of this study was to compare the efficacy and safety of oral glucosamine (Glu), methylsulfonylmethane (MSM), their combination and placebo in osteoarthritis of the knee.



A total of 118 patients of either sex with mild to moderate osteoarthritis were included in the study and randomised to receive either Glu 500mg, MSM 500mg, Glu and MSM or placebo capsules three times daily for 12 weeks. Patients were evaluated at 0 (before drug administration), 2, 4, 8 and 12 weeks post-treatment for efficacy and safety. The efficacy parameters studied were the pain index, the swelling index, visual analogue scale pain intensity, 15m walking time, the Lequesne index, and consumption of rescue medicine.



Glu, MSM and their combination significantly improved signs and symptoms of osteoarthritis compared with placebo. There was a statistically significant decrease in mean (+/- SD) pain index from 1.74 +/- 0.47 at baseline to 0.65 +/- 0.71 at week 12 with Glu (p < 0.001). MSM significantly decreased the mean pain index from 1.53 +/- 0.51 to 0.74 +/- 0.65, and combination treatment resulted in a more significant decrease in the mean pain index (1.7 +/- 0.47 to 0.36 +/- 0.33; p < 0.001). After 12 weeks, the mean swelling index significantly decreased with Glu and MSM, while the decrease in swelling index with combination therapy was greater (1.43 +/- 0.63 to 0.14 +/- 0.35; p < 0.05) after 12 weeks. The combination produced a statistically significant decrease in the Lequesne index. All treatments were well tolerated.



Glu, MSM and their combination produced an analgesic and anti-inflammatory effect in osteoarthritis. Combination therapy showed better efficacy in reducing pain and swelling and in improving the functional ability of joints than the individual agents. All the treatments were well tolerated. The onset of analgesic and anti-inflammatory activity was found to be more rapid with the combination than with Glu. It can be concluded that the combination of MSM with Glu provides better and more rapid improvement in patients with osteoarthritis.
Wideband Dual-Polarized Patch Antenna With Low Cross Polarization and High Isolation

A coax-feed wideband dual-polarized patch antenna with low cross polarization and high port isolation is presented in this letter. The proposed antenna contains two pairs of T-shaped slots on the two bowtie-shaped patches separately. This structure changes the path of the current and keeps the cross polarization under -40 dB. By introducing two short pins, the isolation between the two ports remains more than 38 dB in the whole bandwidth with the front-to-back ratio better than 19 dB. Moreover, the proposed antenna achieving a 10-dB return loss bandwidth of 1.70-2.73 GHz has a compact structure, thus making it easy to be extended to form an array, which can be used as a base station antenna for PCS, UMTS, and WLAN/WiMAX applications.
Dynamic vehicle routing using genetic algorithms

Many difficult combinatorial optimization problems have been modeled as static problems. However, in practice, many problems are dynamic and changing, while some decisions have to be made before all the design data are known. For example, in the Dynamic Vehicle Routing Problem (DVRP), new customer orders appear over time, and new routes must be reconfigured while executing the current solution. Montemanni et al.  considered a DVRP as an extension to the standard vehicle routing problem (VRP) by decomposing a DVRP as a sequence of static VRPs, and then solving them with an ant colony system (ACS) algorithm. This paper presents a genetic algorithm (GA) methodology for providing solutions for the DVRP model employed in . The effectiveness of the proposed GA is evaluated using a set of benchmarks found in the literature. Compared with a tabu search approach implemented herein and the aforementioned ACS, the proposed GA methodology performs better in minimizing travel costs.
Conceptual Metaphor Theory : in defence or on the fence ?

Conceptual Metaphor Theory is a promising model that despite its deficiencies can be used to account for a number of phenomena in figurative language use. The paper reviews the arguments in favour of and against Conceptual Metaphor Theory in terms of the data, methodology and content. Since the model focuses on regularities, it is less useful in the study of idioms, where irregularities are also found. It has, however, enormous potential as it integrates corpusand discourse-driven findings.
Privacy Leakage in Mobile Online Social Networks

Mobile Online Social Networks (mOSNs) have recently grown in popularity. With the ubiquitous use of mobile devices and a rapid shift of technology and access to OSNs, it is important to examine the impact of mobile OSNs from a privacy standpoint. We present a taxonomy of ways to study privacy leakage and report on the current status of known leakages. We find that all mOSNs in our study exhibit some leakage of private information to third parties. Novel concerns include combination of new features unique to mobile access with the leakage in OSNs that we had examined earlier.
Androgenetic alopecia: an evidence-based treatment update.

Androgenetic alopecia (AGA) is one of the most common chronic problems seen by dermatologists worldwide. It is characterized by progressive hair loss, especially of scalp hair, and has distinctive patterns of loss in women versus men, but in both genders the central scalp is most severely affected. It often begins around puberty and is known to effect self-esteem and the individual's quality of life. In contrast to the high prevalence of AGA, approved therapeutic options are limited. In addition to the scarce pharmacologic treatments, there are numerous nonprescription products claimed to be effective in restoring hair in androgenetic alopecia.



The purpose of this paper is to review published medical and non-medical treatments for male and female AGA using the American College of Physicians evidence assessment methods. MEDLINE, EMBASE and Cochrane Library were searched for systematic reviews, randomized controlled trials, open studies, case reports and relevant studies of the treatment of male and female AGA. The relevant articles were classified according to grade and level of evidence.



The medical treatments with the best level of evidence classification for efficacy and safety for male AGA are oral finasteride and topical minoxidil solution. For female AGA, topical minoxidil solution appears to be the most effective and safe treatment. The medical treatments corresponding to the next level of evidence quality are some commonly used therapeutic non-FDA-approved options including oral and topical anti-hormonal treatments. Surgical treatment of follicular unit hair transplantation is an option in cases that have failed medical treatment although there is high variation in outcomes.



Some articles, especially those concerning traditional herbs claimed to promote hair regrowth, were published in non-English, local journals.



An assessment of the evidence quality of current publications indicates that oral finasteride (for men only) and topical minoxidil (for men and women) are the best treatments of AGA.