nils-herrmann/clean_scirepeval huggingface dataset:
Fast content-based image retrieval using convolutional neural network and hash function

Due to the explosive increase of online images, content-based image retrieval has gained a lot of attention. The success of deep learning techniques such as convolutional neural networks have motivated us to explore its applications in our context. The main contribution of our work is a novel end-to-end supervised learning framework that learns probability-based semantic-level similarity and feature-level similarity simultaneously. The main advantage of our novel hashing scheme that it is able to reduce the computational cost of retrieval significantly at the state-of-the-art efficiency level. We report on comprehensive experiments using public available datasets such as Oxford, Holidays and ImageNet 2012 retrieval datasets.
Theoretical model for continuance use of mobile phone wellness application

Mobile wellness application is widely used for assisting self-monitoring practice to monitor user's daily food intake and physical activities. Although these mostly free downloadable mobile application is easy to use and covers many aspects of wellness routines, there is no proof of prolonged use. Previous research reported that user will stop using the application and turned back into their old attitude of food consumptions. The purpose of this study is to examine the factors that influence the continuance intention to adopt a mobile phone wellness application. Review of Information System Continuance Model in the areas such as mobile health, mobile phone wellness application, social network and web 2.0, were done to examine the existing factors. From the critical review, two external factors namely Social Norm and Perceive Interactivity is believed to have the ability to explain the social perspective behavior and also the effect of perceiving interactivity towards prolong usage of wellness mobile application. These findings contribute to the development of the Mobile Phones Wellness Application Continuance Use theoretical model.
A New 2.5D Representation for Lymph Node Detection using Random Sets of Deep Convolutional Neural Network Observations

Automated Lymph Node (LN) detection is an important clinical diagnostic task but very challenging due to the low contrast of surrounding structures in Computed Tomography (CT) and to their varying sizes, poses, shapes and sparsely distributed locations. State-of-the-art studies show the performance range of 52.9% sensitivity at 3.1 false-positives per volume (FP/vol.), or 60.9% at 6.1 FP/vol. for mediastinal LN, by one-shot boosting on 3D HAAR features. In this paper, we first operate a preliminary candidate generation stage, towards -100% sensitivity at the cost of high FP levels (-40 per patient), to harvest volumes of interest (VOI). Our 2.5D approach consequently decomposes any 3D VOI by resampling 2D reformatted orthogonal views N times, via scale, random translations, and rotations with respect to the VOI centroid coordinates. These random views are then used to train a deep Convolutional Neural Network (CNN) classifier. In testing, the CNN is employed to assign LN probabilities for all N random views that can be simply averaged (as a set) to compute the final classification probability per VOI. We validate the approach on two datasets: 90 CT volumes with 388 mediastinal LNs and 86 patients with 595 abdominal LNs. We achieve sensitivities of 70%/83% at 3 FP/vol. and 84%/90% at 6 FP/vol. in mediastinum and abdomen respectively, which drastically improves over the previous state-of-the-art work.
APPROACHES TO COMMUNITY CRIME PREVENTION by

This paper addresses the topic of community crime prevention. As in many other areas of public policy, there are widely divergent approaches that might be taken to crime prevention focused on local neighbourhoods. In what follows four major forms of prevention relevant to the Australian context will be discussed, with particular emphasis being placed on an approach to crime prevention which enhances the ability of a community to bring together, in an integrative way, divergent groups which can easily become isolated from each other as a result of contemporary economic and urban forces.
Genetic Algorithms for Predicting the Egyptian Stock Market

The purpose of this paper is to discover a semi-optimal set of trading rules and to investigate its effectiveness as applied to Egyptian Stocks. The aim is to mix different categories of technical trading rules and let an automatic evolution process decide which rules are to be used for particular time series. This difficult task can be achieved by using genetic algorithms (GA's), they permit the creation of artificial experts taking their decisions from an optimal subset of the a given set of trading rules. The GA's based on the survival of the fittest, do not guarantee a global optimum but they are known to constitute an effective approach in optimizing non-linear functions. Selected liquid stocks are tested and GA trading rules were compared with other conventional and well known technical analysis rules. The Proposed GA system showed clear better average profit and in the same high sharpe ratio, which indicates not only good profitability but also better risk-reward trade-off
No . 2008 – 02 Framing and Free Riding : Emotional Responses and Punishment in Social Dilemma Games

In this paper, we report an experimental investigation of the effect of framing on social preferences, as revealed in a one-shot linear public goods game. We use two indicators to measure social preferences: self-reported emotional responses; and, as a behavioural indicator of disapproval, punishment. Our findings are that, for a given pattern of contributions, neither punishment nor emotion depends on the Give versus Take framing that we manipulate. To this extent, they suggest that the social preferences we observe are robust to framing effects.
Expression: Visualizing Affective Content from Social Streams

Analysis of social content for understanding people's sentiments towards topics of interest that change over time has become an attractive and challenging research area. Natural Language Processing (NLP) techniques are being adapted to deal with streams of social content. New visualization approaches need also to be proposed to express, in a user friendly and reactive manner, individual as well as collective sentiments. In this paper, we present Expression, an integrated framework that allows users to express their opinions through a social platform and to see others' comments. We introduce the Sentiment Card concept: a live representation of a topic of interest. The Sentiment Card is a space that allows users to express their comments and to understand the trend of selected topics of interest expressed by other users. The design of Expression is presented, describing in particular, the sentiment classification module as well as the sentiment card visualization component. Results of the evaluation of our prototype by a usability study are also discussed and considered for motivating future research.
A big data classification approach using LDA with an enhanced SVM method for ECG signals in cloud computing

Electrocardiographic (ECG) signals often consist of unwanted noises and speckles. In order to remove the noises, various image processing filters are used in various studies. In this paper, FIR and IIR filters are initially used to remove the linear and nonlinear delay present in the input ECG signal. In addition, filters are used to remove unwanted frequency components from the input ECG signal. Linear Discriminant Analysis (LDA) is used to reduce the features present in the input ECG signal. Support Vector Machines (SVM) is widely used for pattern recognition. However, traditional SVM method does not applicable to compute different characteristics of the features of data sets. In this paper, we use SVM model with a weighted kernel function method to classify more features from the input ECG signal. SVM model with a weighted kernel function method is significantly identifies the Q wave, R wave and S wave in the input ECG signal to classify the heartbeat level such as Left Bundle Branch Block (LBBB), Right Bundle Branch Block (RBBB), Premature Ventricular Contraction (PVC) and Premature Atrial Contractions (PACs). The performance of the proposed Linear Discriminant Analysis (LDA) with enhanced kernel based Support Vector Machine (SVM) method is comparatively analyzed with other machine learning approaches such as Linear Discriminant Analysis (LDA) with multilayer perceptron (MLP), Linear Discriminant Analysis (LDA) with Support Vector Machine (SVM), and Principal Component Analysis (PCA) with Support Vector Machine (SVM). The calculated RMSE, MAPE, MAE, R2 and Q2 for the proposed Linear Discriminant Analysis (LDA) with enhanced kernel based Support Vector Machine (SVM) method is low when compared with other approaches such as LDA with MLP, and PCA with SVM and LDA with SVM. Finally, Sensitivity, Specificity and Mean Square Error (MSE) are calculated to prove the effectiveness of the proposed Linear Discriminant Analysis (LDA) with an enhanced kernel based Support Vector Machine (SVM) method.
Choice Architecture and Smartphone Privacy: There's a Price for That

Under certain circumstances, consumers are willing to pay a premium for privacy. We explore how choice architecture affects smartphone users’ stated willingness to install applications that request varying permissions. We performed two experiments to gauge smartphone users’ stated willingness to pay premiums to limit their personal information exposure when installing new applications. We found that when participants were comparison shopping between multiple applications that performed similar functionality, a quarter of our sample responded that they were willing to pay a $1.50 premium for the application that requested the fewest permissions—though only when viewing the requested permissions of each application side-by-side. In a second experiment, we more closely simulated the user experience by asking them to valuate a single application that featured multiple sets of permissions based on five between-subjects conditions. In this scenario, the requested permissions had a much smaller impact on participants’ responses. Our results suggest that many smartphone users are concerned with their privacy and are willing to pay premiums for applications that are less likely to request access to personal information. We propose improvements in choice architecture for smartphone application markets that could result in decreased satisficing and increased rational behavior.
INFORMATION TECHNOLOGY AND BUSINESS-LEVEL STRATEGY : TOWARD AN INTEGRATED THEORETICAL PERSPECTIVE 1

Information technology matters to business success because it directly affects the mechanisms through which they create and capture value to earn a profit: IT is thus integral to a firm’s business-level strategy. Much of the extant research on the IT/strategy relationship, however, inaccurately frames IT as only a functionallevel strategy. This widespread under-appreciation of the business-level role of IT indicates a need for substantial retheorizing of its role in strategy and its complex and interdependent relationship with the mechanisms through which firms generate profit. Using a comprehensive framework of potential profit mechanisms, we argue that while IT activities remain integral to the functional-level strategies of the firm, they also play several significant roles in business strategy, with substantial performance implications. IT affects industry structure and the set of business-level strategic alternatives and value-creation opportunities that a firm may pursue. Along with complementary organizational changes, IT both enhances the firm’s current (ordinary) capabilities and enables new (dynamic) capabilities, including the flexibility to focus on rapidly changing opportunities or to abandon losing initiatives while salvaging substantial asset value. Such digitally attributable capabilities also determine how much of this value, once created, can be captured by the firm—and how much will be dissipated through competition or through the power of value chain partners, the governance of which itself depends on IT. We explore these business-level strategic roles of IT and discuss several provocative implications and future research directions in the converging information systems and strategy domains.
Illuminant estimation and detection using near-infrared

Digital camera sensors are sensitive to wavelengths ranging from the ultraviolet (200-400nm) to the near-infrared (700-100nm) bands. This range is, however, reduced because the aim of photographic cameras is to capture and reproduce the visible spectrum (400-700nm) only. Ultraviolet radiation is filtered out by the optical elements of the camera, while a specifically designed “hot-mirror” is placed in front of the sensor to prevent near-infrared contamination of the visible image. We propose that near-infrared data can actually prove remarkably useful in colour constancy, to estimate the incident illumination as well as providing to detect the location of different illuminants in a multiply lit scene. Looking at common illuminants spectral power distribution show that very strong differences exist between the near-infrared and visible bands, e.g., incandescent illumination peaks in the near-infrared while fluorescent sources are mostly confined to the visible band. We show that illuminants can be estimated by simply looking at the ratios of two images: a standard RGB image and a near-infrared only image. As the differences between illuminants are amplified in the near-infrared, this estimation proves to be more reliable than using only the visible band. Furthermore, in most multiple illumination situations one of the light will be predominantly near-infrared emitting (e.g., flash, incandescent) while the other will be mostly visible emitting (e.g., fluorescent, skylight). Using near-infrared and RGB image ratios allow us to accurately pinpoint the location of diverse illuminant and recover a lighting map.
Human-Computer Interaction: Input Devices

All aspects of human-computer interaction, from the high-level concerns of organizational context and system requirements to the conceptual, semantic, syntactic, and lexical levels of user interface design, are ultimately funneled through physical input and output actions and devices. The fundamental task in computer input is to move information from the brain of the user to the computer. Progress in this discipline attempts to increase the useful bandwidth across that interface by seeking faster, more natural, and more convenient means for a user to transmit information to a computer. This article mentions some of the technical background for this area, surveys the range of input devices currently in use and emerging, and considers future trends in input.
Percentage of Consonants Correct (PCC) in children with and without hearing impairment

To compare the Percentage of Consonants Correct (PCC) index of children with and without hearing loss, and to verify whether the time using hearing aids, the time in therapy, and the time spent until hearing loss was diagnosed influence the performance of deaf children.  Participants were 30 children, 15 with hearing impairment and 15 with normal hearing, paired by gender and age. The PCC index was calculated in three different tasks: picture naming, imitation and spontaneous speech. The phonology tasks of the ABFW – Teste de Linguagem Infantil were used in the evaluation.  Differences were found between groups in all tasks, and normally hearing children had better results. PCC indexes presented by children with hearing loss characterized a moderately severe phonological disorder. Children enrolled in therapy for a longer period had better PCC indexes, and the longer they had been using hearing aids, the better their performances on the imitation task.  Children with hearing loss have lower PCC indexes when compared to normally hearing children. The average performance and imitation are influenced by time in therapy and time using hearing aids.
Clinical achievements of impedance analysis

Various models and derived measures of arterial function have been proposed to describe and quantify pulsatile hemodynamics in humans. A major distinction can be drawn between lumped models based on circuit theory that assume infinite pulse wave velocity versus distributed, propagative models based on transmission line theory that acknowledge finite wave velocity and account for delays, wave reflection, and spatial and temporal pressure gradients within the arterial system. Although both approaches have produced useful insights into human arterial pathophysiology, there are important limitations of the lumped approach. The arterial system is heterogeneous and various segments respond differently to cardiovascular disease risk factors including advancing age. Lumping divergent change into aggregate summary variables can obscure abnormalities in regional arterial function. Analysis of a limited number of summary variables obtained by measuring aortic input impedance may provide novel insights and inform development of new treatments aimed at preventing or reversing abnormal pulsatile hemodynamics.
A Foldable Antagonistic Actuator

We report on an actuator based on dielectric elastomers that is capable of antagonistic actuation and passive folding. This actuator enables foldability in robots with simple structures. Unlike other antagonistic dielectric elastomer devices, our concept uses elastic hinges to allow the folding of the structure, which also provides an additional design parameter. To validate the actuator concept through a specific application test, a foldable elevon actuator with outline size of 70 mm × 130 mm is developed with angular displacement range and torque specifications matched to a 400-mm wingspan micro-air vehicle (MAV) of mass 130 g. A closed-form analytical model of the actuator is constructed, which was used to guide the actuator design. The actuator consists of 125-μm-thick silicone membranes as the dielectric elastomers, 0.2mm-thick fiberglass plate as the frame structure, and 50-μm-thick polyimide as the elastic hinge. We measured voltage-controllable angular displacement up to ±26° and torque of 2720 mN · mm at 5 kV, with good agreement between the model and the measured data. Two elevon actuators are integrated into the MAV, which was successfully flown, with the foldable actuators providing stable and well-controlled flight. The controllability was quantitatively evaluated by calculating the correlation between the control signal and the MAV motion, with a correlation in roll axis of over 0.7 measured during the flights, illustrating the high performance of this foldable actuator.
The nature of selection during plant domestication

Plant domestication is an outstanding example of plant–animal co-evolution and is a far richer model for studying evolution than is generally appreciated. There have been numerous studies to identify genes associated with domestication, and archaeological work has provided a clear understanding of the dynamics of human cultivation practices during the Neolithic period. Together, these have provided a better understanding of the selective pressures that accompany crop domestication, and they demonstrate that a synthesis from the twin vantage points of genetics and archaeology can expand our understanding of the nature of evolutionary selection that accompanies domestication.
Suicidal ligature strangulation utilizing cable ties: a report of three cases.

In 2006 the US National Vital Statistics Report recorded 33,300 suicides in the United States, of which hanging, strangulation and suffocation combined to account for 7,491 (22.5%) of the cases. Self strangulation by ligature is uncommon and in the majority of cases, scarves, belts, neckties and rope are used. We report three instances where cable ties were secured around the neck in order to commit suicide. All had a history of depression. One was a 37-year-old man who used a belt to complete the act after an unsuccessful attempt to use cable ties. The second was a 63-year old woman who used multiple cable ties to accomplish her goal. In the third case a tensioning tool was used by a 54-year old man to tighten a cable tie around his neck during self strangulation. Utilization of a tool to tighten the cable ties has not previously been reported.
Pretend play skills and the child's theory of mind.

Pretend play has recently been of great interest to researchers studying children's understanding of the mind. One reason for this interest is that pretense seems to require many of the same skills as mental state understanding, and these skills seem to emerge precociously in pretense. Pretend play might be a zone of proximal development, an activity in which children operate at a cognitive level higher than they operate at in nonpretense situations. Alternatively, pretend play might be fool's gold, in that it might appear to be more sophisticated than it really is. This paper first discusses what pretend play is. It then investigates whether pretend play is an area of advanced understanding with reference to 3 skills that are implicated in both pretend play and a theory of mind: the ability to represent one object as two things at once, the ability to see one object as representing another, and the ability to represent mental representations.
Responses to intimate partner violence in Kakuma refugee camp: refugee interactions with agency systems.

Intimate partner violence (IPV) has been recognised as a significant problem amongst forcibly displaced communities, and great progress has been made by the United Nations High Commission for Refugees (UNHCR) in responding to IPV and other forms of sexual and gender based violence. However, they have not always effectively engaged refugee communities in these activities, with potentially negative consequences for the health and protection of women. This study was conducted in Kakuma refugee camp, north-west Kenya. Eighteen focus group discussions were conducted with 157 refugees from various nationalities, including Sudanese, Somali, Ethiopian, and Congolese. They focused on the nature and consequences of IPV in Kakuma. The aim of this paper is to explore how refugees in Kakuma talk about the ways that IPV is dealt with, focusing particularly on the ways that community responses are said to interact with formal response systems established by UNHCR and its implementing partners. Refugees talked about using a 'hierarchy of responses' to IPV, with only particularly serious or intransigent cases reaching UNHCR or its implementing agencies. Some male refugees described being mistrustful of agency responses, because agencies were believed to favour women and to prioritise protecting the woman at all costs, even if that means separating her from the family. Whilst community responses to IPV might often be appropriate and helpful, the findings of the current study suggest that in Kakuma they do not necessarily result in the protection of women. Yet women in Kakuma are reported to be reluctant to report their cases to UNHCR and its implementing agencies. A more effective protection response from UNHCR might involve closer co-operation with individuals and structures within the refugee communities to develop a co-ordinated response to IPV.