nils-herrmann/clean_scirepeval huggingface dataset:
Outcomes of Conservative Treatment of 134 Cases of Umbilical Pilonidal Sinus

There are different opinions about the treatment of umbilical pilonidal sinus. The aim of the present study was to evaluate the outcome of conservative treatment of this disease. All patients with umbilical pilonidal sinus who attended our private surgical clinic in Erbil, Kurdistan, from January 1997 to August 2011, were treated by conservative treatment. Umbilectomy was performed for those who did not respond to the conservative treatment after three sessions. A total of 134 patients were seen; 121 (90.3 %) were men. Only 105 (78.35 %) patients came back for the second visit. Eighty of them (76.19 %) responded to the treatment. The other 25 (23.8 %) patients were retreated by a second session of conservative treatment. Of these 25 patients, 19 (76 %) came back for the third visit and only three (15.78 %) patients did not respond to the treatment. One patient insisted on umbilectomy. The other two patients were treated but did not respond to the third session treatment. Umbilectomy was performed for them. Hair was found in the sinus after excision in these three patients. The follow-up period ranged from 9 months to 6.5 years for 46 (34.32 %) patients and revealed no recurrence. Conservative treatment should be regarded as the first choice and the main method of treatment in the management of umbilical pilonidal sinus. Improper extraction of hair is the main cause of failure of conservative treatment. Recurrence can be prevented by giving the patients instructions on preventive measures.
Depth enhancement via non-local means filter

The depth image captured by a RGB-D camera is noisy and usually misses the values at some pixels, especially around the object boundaries. There are many methods take advantage of the corresponding color images to enhance the depth images. Most of them bring the texture of the color image into the depth image. In this paper, an adaptive double non-local means (ADNLM) method of depth enhancement is proposed. First, ADNLM pre-inpaint the depth image via a color-guided non-local means method; second, a depth-based non-local means method is used to denoise the pre-inpainted depth image. Experiments on the public benchmarks show that, ADNLM can avoid the color texture, and effectively enhance the depth image, especially when there are several large missing regions in the depth image. Also, the performance in terms of PSNR of ADNLM is slightly better than that of the state of the arts.
Divide and Fuse: A Re-ranking Approach for Person Re-identification

As re-ranking is a necessary procedure to boost person re-identification (re-ID) performance on large-scale datasets, the diversity of feature becomes crucial to person reID for its importance both on designing pedestrian descriptions and re-ranking based on feature fusion. However, in many circumstances, only one type of pedestrian feature is available. In this paper, we propose a “Divide and Fuse” re-ranking framework for person re-ID. It exploits the diversity from different parts of a high-dimensional feature vector for fusion-based re-ranking, while no other features are accessible. Specifically, given an image, the extracted feature is divided into sub-features. Then the contextual information of each sub-feature is iteratively encoded into a new feature. Finally, the new features from the same image are fused into one vector for re-ranking. Experimental results on two person re-ID benchmarks demonstrate the effectiveness of the proposed framework. Especially, our method outperforms the state-of-the-art on the Market-1501 dataset.
The effects of cosmetics on person perception.

(1)The use of cosmetics (facial make-up and hair care) leads to more favourable appearance ratings by others (both males and females). For make-up there were more favourable ratings on all of the six appearance scales, and for hair care there were more favourable ratings on four of the six appearance scales. (2)The use of cosmetics leads to more favourable ratings of personality as perceived by others (both males and females). Facial make-up enhanced ratings on eight of the fourteen personality dimensions tested and hair treatment led to more favourable ratings on ten of the scales.
Quality Questions Need Quality Code: Classifying Code Fragments on Stack Overflow

Stack Overflow (SO) is a question and answers (Q&A) web platform on software development that is gaining in popularity. With increasing popularity often comes a very unwelcome side effect: A decrease in the average quality of a post. To keep Q&A websites like SO useful it is vital that this side effect is countered. Previous research proved to be reasonably successful in using properties of questions to help identify low quality questions to be later reviewed and improved.
 We present an approach to improve the classification of high and low quality questions based on a novel source of information: the analysis of the code fragments in SO questions. We show that we get similar performance to classification based on a wider set of metrics thus potentially reaching a better overall classification.
Practical Implementation of Private Cloud Based on Open Source ownCloud for Small Teams - Case Study

Various companies in the manufacturing, but also in non-manufacturing sector, research and public organization use technology based on Internet to share data among staff but also with customers or in collaboration with other companies. Depending on the requirements of individual companies widely differing demands are placed on the technology in terms of features, administration, as well as security and the cost of the solution usually considered as one of the key issues. Cloud promises lower costs, high availability and scalability and that in the long term. The essence of any choice in selecting cloud solutions for corporate environment is to recognize its purpose, scope of use and content that will be uploaded to the storage. The paper discusses the project of setting up your own private cloud solution based on the open software ownCloud.
Midfrontal theta and pupil dilation parametrically track subjective conflict (but also surprise) during intertemporal choice

Many everyday choices are based on personal, subjective preferences. When choosing between two options, we often feel conflicted, especially when trading off costs and benefits occurring at different times (e.g., saving for later versus spending now). Although previous work has investigated the neurophysiological basis of conflict during inhibitory control tasks, less is known about subjective conflict resulting from competing subjective preferences. In this pre-registered study, we investigated subjective conflict during intertemporal choice, whereby participants chose between smaller immediate versus larger delayed rewards (e.g., $15 today vs. $22 in 30 days). We used economic modeling to parametrically vary eleven different levels of conflict, and recorded EEG data and pupil dilation. Midfrontal theta power, derived from EEG, correlated with pupil responses, and our results suggest that these signals track different gradations of subjective conflict. Unexpectedly, both signals were also maximally enhanced when decisions were surprisingly easy. Therefore, these signals may track events requiring increased attention and adaptive shifts in behavioral responses, with subjective conflict being only one type of such event. Our results suggest that the neural systems underlying midfrontal theta and pupil responses interact when weighing costs and benefits during intertemporal choice. Thus, understanding these interactions might elucidate how individuals resolve self-control conflicts.
Electrostatic Energy Harvester Employing Conductive Droplet and Thin-Film Electret

This paper presents detailed investigations on an electrostatic energy harvester using conductive droplet/marble rolling across a charged electret film. Both mercury droplets and ionic liquid marbles were used as the working medium. With a 1.2-mm mercury droplet rolling across the electret film of the prototype, a maximum output power was obtained at 0.18 μW and the peak value of the output voltage was 1.5 V. A semi-empirical model was developed to understand the output waveforms. Applied to the test data, it shows that the transducer short-circuit charge is mainly a function of droplet position in the pattern. Several factors influencing the output performance are discussed. Such droplet-based electrostatic energy harvesters are especially suitable for very low frequency vibration up to a few Hz.
Key issues in domestic violence

Domestic violence is traditionally associated with cases of physical violence occurring within intimate relationships and in a domestic setting. It is most commonly perpetrated by a male against a female partner, but it also includes violence against men. Domestic violence occurs in both heterosexual and homosexual relationships and includes married, de facto and separated adolescents and adults (Flood & Fergus 2008). Domestic violence is also commonly referred to as relationship violence, intimate partner violence and gender-based violence. In Indigenous communities, ‘family violence’ is often the preferred term as it encapsulates the broader issue of violence within extended families (Stanley, Tomison & Pocock 2003).
A Survey of Intrusion Detection Systems for Mobile Ad Hoc Networks

Tactical Mobile Ad-hoc Networks (MANETs) are widely deployed in military organizations that have critical needs of communication even with the absence of fixed infrastructure. The lack of communication infrastructure and dynamic topology makes MANETs vulnerable to a wide range attacks. Tactical military operations are among the prime users of ad-hoc networks. The military holds higher standards of security requirements and thus require special intrusion detection applications. Conventional Intrusion Detection System (IDS) require central control and monitoring entities and thus cannot be applied to MANETs. Solutions to secure these networks are based on distributed and cooperative security. This paper presents a survey of IDS specifically for MANETs and also highlights the strengths and weakness of each model. We present a unique evaluation matrix for measuring the effectiveness of IDS for MANETs in an emergency response scenario.
A Dual-Broadband Dual-Polarized Fylfot-Shaped Antenna for Mobile Base Stations Using MIMO Over-Lapped Antenna Subarrays

This paper proposes a novel design of a dual-broadband dual-polarized antenna for mobile communication base stations. The proposed antenna is Fylfot-shaped and covers 0.7–0.96 and 1.7–2.7 GHz simultaneously (with S11 ≤ −10 dB), which are the two common frequency bands for mobile communication systems. Three resonant frequencies are produced in the proposed design where two of them are independently controlled to achieve the dual-broadband performance. A prototype of the proposed antenna has been developed and tested. The results demonstrate that the antenna has high isolation between its ports, high polarization purity, and stable radiation patterns across both the frequency bands. A new linear array is proposed and implemented. Unlike reported dual-band base station antenna arrays, the proposed array uses a novel technique of two MIMO overlapped subarrays with shared radiating antenna elements. The overlapped subarrays have excellent frequency diversity performance with low envelope correlation coefficients. The array has been found to have the same performance as a standard conventional base station antenna but with 25% less number of antenna elements, which leads to a smaller size and lower cost. The simple antenna structure and the novel smart MIMO overlapped antenna subarrays technique give the design the privilege to be an ideal candidate for a low-cost directive base station antenna.
QoS-Aware Service Composition for Converged Network-Cloud Service Provisioning

The crucial role of networking in Cloud computing calls for federated management of both computing and networking resources for end-to-end service provisioning. Application of the Service-Oriented Architecture (SOA) in both Cloud computing and networking enables a convergence of network and Cloud service provisioning. One of the key challenges to network -- Cloud convergence lies in QoS-aware composition of network and Cloud services. In this paper, we propose a QoS-aware service composition method to tackle this challenging issue. We first present a system model for network -- Cloud service composition and formulate the service composition problem as a variant of Multi-Constrained Optimal Path (MCOP) problem. We then develop an algorithm to solve the problem and give theoretical analysis on properties of the algorithm to show its effectiveness and efficiency for QoS-aware network-Cloud service composition. Performance of the proposed algorithm is evaluated through extensive simulation experiments and the obtained results indicate that the proposed method achieves better performance in service composition than the best currently available MCOP approach.
UWB antenna for brain stroke and brain tumour detection

UWB Pentagon antenna is designed to detect brain stroke and brain tumour. It is operating at a band from 3.3568– 12.604 GHz in free space and from 3.818 to 9.16 GHz on the normal head model. The antenna has dimensions of 44×30mm2. It is fabricated on FR4-substrate with relative permittivity 4.4 and thickness 1.5mm. The antenna is simulated on the CST Microwave Studio and measured using the network analyser. There is a good agreement between the measured and simulated results of the return loss of the antenna on human's head and head phantom.
Internet-based e-shopping and consumer attitudes: an empirical study

This paper analyses consumer attitudes towards Internet-based e-shopping. It aims to provide a theoretically and empirically grounded initial reference position, against which later research can explore and interpret the effects of changes in variables representing consumer preferences and shifts in these preferences on the success or failure of B2C e-commerce over the Internet. Because of the opportunity to sample at the outset and of ceteris paribus conditions following from the tendency for other factors such as e-transactions cost to remain small and constant, Singapore data were employed. Regression analysis shows that the life content of products, transactions security, price, vendor quality, IT education and Internet usage signi®cantly affect the initial willingness of Singaporeans to e-shop on the Internet. Generalising, we suggest that Internetbased B2C e-commerce can pro®tably be introduced or promoted along similar dimensions in socio-geographically and technologically similar situations.
An Improved Topology of SEPIC Converter With Reduced Output Voltage Ripple

An improved version of a single-ended primary inductor converter (SEPIC) is presented. The converter consists of a conventional SEPIC converter plus an additional high-frequency transformer and diode to maintain a freewheeling mode of the DC inductor currents during the switch on state. The voltage conversion ratio characteristics and semiconductor device voltage and current stresses are characterized. The main advantages of this converter are the continuous output current, smaller output voltage ripple, and lower semiconductors current stress compared with the conventional SEPIC converter. The design and simulation of the concept is verified by an experiment with a 48-V input and 12-V/3.75-A output converter.
Baseline Mechanisms for Enterprise Governance of IT in SMEs

Information Technology (IT) has become fundamental for most organizations since it is vital to their sustainability, development and success. This pervasive use led organizations to a critical dependency on IT. Despite the benefits, it exposes organizations to several risks. Hence, a significant focus on Enterprise Governance of IT (EGIT) is required. EGIT involve the definition and implementation of processes, structures and relational mechanisms to support the business/IT alignment and the creation of business value from IT investments. These mechanisms act as a mean to direct and operationalize IT-related decision-making. However, identifying the appropriate mechanisms is a complex task since there are internal and external contingency factors that influence the design and implementation of EGIT. Small and Medium Enterprises (SMEs) are considered key elements to promote economic growth, job creation, social integration and innovation. The use of IT in these organizations can imply severe consequences on survival and growth in highly competitive markets, becoming critical in this globalization era. Several studies were developed to investigate and identify EGIT mechanisms in different contingencies but very few focused on the organization' size criterion. However, SMEs have particular characteristics that require further investigation. Therefore, our goal in this research is to evaluate EGIT mechanisms in a SME's context and identify a baseline of mechanisms for SMEs using semi-structured interviews with IT experts that have experience in SMEs. The article ends by presenting contributions, limitations and future work.
Outlier Detection over Massive-Scale Trajectory Streams

The detection of abnormal moving objects over high-volume trajectory streams is critical for real-time applications ranging from military surveillance to transportation management. Yet this outlier detection problem, especially along both the spatial and temporal dimensions, remains largely unexplored. In this work, we propose a rich taxonomy of novel classes of neighbor-based trajectory outlier definitions that model the anomalous behavior of moving objects for a large range of real-time applications. Our theoretical analysis and empirical study on two real-world datasets—the Beijing Taxi trajectory data and the Ground Moving Target Indicator data stream—and one generated Moving Objects dataset demonstrate the effectiveness of our taxonomy in effectively capturing different types of abnormal moving objects. Furthermore, we propose a general strategy for efficiently detecting these new outlier classes called the <underline>m</underline>inimal <underline>ex</underline>amination (MEX) framework. The MEX framework features three core optimization principles, which leverage spatiotemporal as well as the predictability properties of the neighbor evidence to minimize the detection costs. Based on this foundation, we design algorithms that detect the outliers based on these classes of new outlier semantics that successfully leverage our optimization principles. Our comprehensive experimental study demonstrates that our proposed MEX strategy drives the detection costs 100-fold down into the practical realm for applications that analyze high-volume trajectory streams in near real time.
A multivariate time series clustering approach for crime trends prediction

In recent past, there is an increased interest in time series clustering research, particularly for finding useful similar trends in multivariate time series in various applied areas such as environmental research, finance, and crime. Clustering multivariate time series has potential for analyzing large volume of crime data at different time points as law enforcement agencies are interested in finding crime trends of various police administration units such as states, districts and police stations so that future occurrences of similar incidents can be overcome. Most of the traditional time series clustering algorithms deals with only univariate time series data and for clustering high dimensional data, it has to be transformed into single dimension using a dimension reduction technique. The conventional time series clustering techniques do not provide desired results for crime data set, since crime data is high dimensional and consists of various crime types with different weight age. In this paper, a novel approach based on dynamic time wrapping and parametric Minkowski model has been proposed to find similar crime trends among various crime sequences of different crime locations and subsequently use this information for future crime trends prediction. Analysis on Indian crime records show that the proposed technique generally outperforms the existing techniques in clustering of such multivariate time series data.
Applying QR code in augmented reality applications

In this paper we present an augmented reality (AR) application based on the QR Code. The system can extract the information embedded in a QR Code and show the information in an extended 3D form with the QR Code being the traditional AR marker. Traditional AR systems often use a particularly designed pattern (the marker) to recover the 3D scene structure and identify the object to be displayed on the scene. In these systems, the marker is used only for tracking and identification. They do not convey any other information. Consequently, the applications of these systems are limited and often a registration procedure is required for a new marker.
 QR Code has the advantage of large information capacity and is similar to an AR marker in appearance. Thus, more interesting and useful applications can be developed by combining the QR Code with the traditional AR system. In this paper, we combine these two techniques to develop a product demo system. A QR Code is pasted on the package of a product and then a 3D virtual object is displayed on the QR Code. This system allows the customer to visualize the product via a more direct and interactive way. Our system demonstrates the success of using QR Code as the AR marker to a particular application and we believe it can bring more convenient to our life in the future.
An integrated approach for risk-based life cycle assessment and multi-criteria decision-making: Selection, design and evaluation of cleaner and greener processes

Cleaner and greener technologies for process and product selection and design have gained popularity in recent years. Life cycle assessment (LCA) is a systematic approach that enables selection of cleaner and greener products and processes. Recently, significant progress has been made for the use of LCA for product/process evaluation and selection, however, its use in process design and environmental decision-making has not been fully exploited. There are challenging activities which require trade-offs among conflicting attributes like cost, technical feasibility and environmental impacts. These attributes can be analysed at the early design stage by considering the full life cycle of a process (and/or a product). A cleaner and greener process referred economical, technically feasible and environmental friendly alternative. This paper proposes an integrated methodology for design by combining LCA with multi-criteria decisionmaking. This methodology is simple and applicable at the early design stage and guide decisionmaking under uncertainty. Application of the methodology is demonstrated through a case study of urea production.