nils-herrmann/clean_scirepeval huggingface dataset:
Mobile-Based Location Tracking without Internet Connectivity Using Cloud Computing Environment

With emergence of the smartphone, peoplegain access to several applications that make their workeasier. Likewise, one of the top trended app searcheswhich we do is location tracking or accessing location ofthe other user in the cloud computing environment. Inrecent past, these accesses are done without user'sknowledge and accord. In this paper, we present thestudy about runtime location access of users in the cloudcomputing environment. With this, we have thepossibility of the location accessibility of users both viaonline as well as offline. Our main goal is to get users'location for safety purpose. Through the online, we haveseveral apps which show the user's location but not mucheffective. We introduce the novel Mobile-Based LocationTracking without Internet (MLTWI). Our approachtracks the location of the user by applying latitude andlongitude information. The latitude and longitudeinformation are collected using our designed latitude andlongitude (LL) algorithm. Based on the realexperimental tests and simulation results, we validatedthat our scheme outperforms to known approaches.
K-nearest correlated neighbor classification for Indian sign language gesture recognition using feature fusion

A sign language recognition system is an attempt to bring the speech and the hearing impaired community closer to more regular and convenient forms of communication. Thus, this system requires to recognize the gestures from a sign language and convert them to a form easily understood by the hearing. The model that has been proposed in this paper recognizes static images of the signed alphabets in the Indian Sign Language. Unlike the alphabets in other sign languages like the American Sign Language and the Chinese Sign language, the ISL alphabet are both single-handed and double-handed. Hence, to make recognition easier the model first categorizes them as single-handed or double-handed. For both categories two kinds of features, namely HOG and SIFT, are extracted for a set of training images and are combined in a single matrix. After which, HOG and SIFT features for the input test image are combined with the HOG and SIFT feature matrices of the training set. Correlation is computed for these matrices and is fed to a K-Nearest Neighbor Classifier to obtain the resultant classification of the test image.
Analysis and optimization of software requirements prioritization techniques

Prioritizing requirements helps the project team to understand which requirements are most important and most urgent. Based on this finding a software engineer can decide what to develop/implement in the first release and what on the coming releases. Prioritization is also a useful activity for decision making in other phases of software engineering like development, testing, and implementation. There are a number of techniques available to prioritize the requirements with their associated strengths and limitations. In this paper we will examine state of the art techniques and analyze their applicability on software requirements domain. At the end we present a framework that will help the software engineer of how to perform prioritization process by combining existing techniques and approaches.
Tests enhance the transfer of learning.

Numerous learning studies have shown that if the period of time devoted to studying information (e.g., casa-house) includes at least 1 test (casa-?), performance on a final test is improved-a finding known as the testing effect. In most of these studies, however, the final test is identical to the initial test. If the final test requires a novel demonstration of learning (i.e., transfer), prior studies suggest that a greater degree of transfer reduces the size of the testing effect. The authors tested this conjecture. In 2 experiments, 4th- or 5th-grade students learned to assign regions or cities to map locations and returned 1 day later for 2 kinds of final tests. One final test required exactly the same task seen during the learning session, and the other final test consisted of novel, more challenging questions. In both experiments, testing effects were found for both kinds of final tests, and the testing effect was no smaller, and actually slightly larger, for the final test requiring transfer.
Software radios: Survey, critical evaluation and future directions

A software radio is defined as a set of digital signal processing (DSP) primitives, a metalevel system for combining the primitives into communication system functions (transmitter, channel model, receiver, etc.), and a set of target processors on which the software radio is hosted for real-time communications. The performance of enabling hardware technologies is related to software radio requirements, portending a decade of shift from hardware radios toward software intensive approaches. Computational models and architecture are discussed, stressing the need for topological consistency of radio functions and host architectures. A layered topology-oriented design approach encapsulated in a canonical open architecture software radio model is presented. The model provides a unified mathematical framework for quantitative analysis of algorithm structures, host architectures, and system performance for CAD.<<ETX>>
Diaphragmatic Eventration in Sisters with Asparagine Synthetase Deficiency: A Novel Homozygous ASNS Mutation and Expanded Phenotype.

Asparagine Synthetase Deficiency (ASNSD; OMIM #615574) is a newly described rare autosomal recessive neurometabolic disorder, characterised by congenital microcephaly, severe psychomotor delay, encephalopathy and progressive cerebral atrophy. To date, seven families and seven missense mutations in the ASNSD disease causing gene, ASNS, have been published.



We report two further affected infant sisters from a consanguineous Indian family, who in addition to the previously described features had diaphragmatic eventration. Both girls died within the first 6 months of life. Whole exome sequencing (WES) was performed for both sisters to identify the pathogenic mutation. The clinical and biochemical parameters of our patient are compared to previous reports.



WES demonstrated a homozygous novel missense ASNS mutation, c.1019G > A, resulting in substitution of the highly conserved arginine residue by histidine (R340H).



This report expands the phenotypic and mutation spectrum of ASNSD, which should be considered in neonates with congenital microcephaly, seizures and profound neurodevelopmental delay. The presence of diaphragmatic eventration suggests extracranial involvement of the central nervous system in a disorder that was previously thought to exclusively affect the brain. Like all previously reported patients, these cases were diagnosed with WES, highlighting the clinical utility of next generation sequencing in the diagnosis of rare, difficult to recognise disorders.
Assessing the vulnerability of supply chains using graph theory

In today’s business environment, harsher and more frequent natural and man-made disasters make supply chains more vulnerable. Supply chain disruptions now seem to occur more frequently and with more serious consequences. During and after supply chain disruptions, companies may lose revenue and incur high recovery costs. If supply chain managers were more capable of measuring and managing supply chain vulnerability, they could reduce the number of disruptions and their impact. In this research we developed an approach based on graph theory to quantify and hence mitigate supply chain vulnerability. Quantification of supply chain vulnerability aids managers in assessing the vulnerability of their supply chains (e.g., across and between supply chains, or over time) and in comparing the effectiveness of different risk mitigation strategies. & 2009 Elsevier B.V. All rights reserved.
A Tabu Search/Path Relinking Algorithm to Solve the Job Shop Scheduling Problem

We present an algorithm that incorporates a tabu search procedure into the framework of path relinking to tackle the job shop scheduling problem (JSP). This tabu search/path relinking (TS/PR) algorithm comprises several distinguishing features, such as a specific relinking procedure and a reference solution determination method. To test the performance of TS/PR, we apply it to tackle almost all of the benchmark JSP instances available in the literature. The test results show that TS/PR obtains competitive results compared with state-of-the-art algorithms for JSP in the literature, demonstrating its efficacy in terms of both solution quality and computational efficiency. In particular, TS/PR is able to improve the upper bounds for 49 out of the 205 tested instances and it solves a challenging instance that has remained unsolved for over 20 years.
Image Captioning as Neural Machine Translation Task in SOCKEYE

Image captioning is an interdisciplinary research problem that stands between computer vision and natural language processing. The task is to generate a textual description of the content of an image. The typical model used for image captioning is an encoder-decoder deep network, where the encoder captures the essence of an image while the decoder is responsible for generating a sentence describing the image. Attention mechanisms can be used to automatically focus the decoder on parts of the image which are relevant to predict the next word. In this paper, we explore different decoders and attentional models popular in neural machine translation, namely attentional recurrent neural networks, self-attentional transformers, and fully-convolutional networks, which represent the current state of the art of neural machine translation. The image captioning module is available as part of SOCKEYE [11] at https://github.com/awslabs/sockeye which tutorial can be found at https://awslabs.github.io/sockeye/image_captioning.html.
Solid lipid nanoparticles: production, characterization and applications.

Solid lipid nanoparticles (SLN) have attracted increasing attention during recent years. This paper presents an overview about the selection of the ingredients, different ways of SLN production and SLN applications. Aspects of SLN stability and possibilities of SLN stabilization by lyophilization and spray drying are discussed. Special attention is paid to the relation between drug incorporation and the complexity of SLN dispersions, which includes the presence of alternative colloidal structures (liposomes, micelles, drug nanosuspensions, mixed micelles, liquid crystals) and the physical state of the lipid (supercooled melts, different lipid modifications). Appropriate analytical methods are needed for the characterization of SLN. The use of several analytical techniques is a necessity. Alternative structures and dynamic phenomena on the molecular level have to be considered. Aspects of SLN administration and the in vivo fate of the carrier are discussed.
Ruminating Reader: Reasoning with Gated Multi-Hop Attention

To answer the question in machine comprehension (MC) task, the models need to establish the interaction between the question and the context. To tackle the problem that the single-pass model cannot reflect on and correct its answer, we present Ruminating Reader. Ruminating Reader adds a second pass of attention and a novel information fusion component to the Bi-Directional Attention Flow model (BIDAF). We propose novel layer structures that construct a query aware context vector representation and fuse encoding representation with intermediate representation on top of BIDAF model. We show that a multi-hop attention mechanism can be applied to a bi-directional attention structure. In experiments on SQuAD, we find that the Reader outperforms the BIDAF baseline by 2.1 F1 score and 2.7 EM score. Our analysis shows that different hops of the attention have different responsibilities in selecting answers.
Automating extract class refactoring: an improved method and its evaluation

During software evolution the internal structure of the system undergoes continuous modifications. These continuous changes push away the source code from its original design, often reducing its quality, including class cohesion. In this paper we propose a method for automating the Extract Class refactoring. The proposed approach analyzes (structural and semantic) relationships between the methods in a class to identify chains of strongly related methods. The identified method chains are used to define new classes with higher cohesion than the original class, while preserving the overall coupling between the new classes and the classes interacting with the original class. The proposed approach has been first assessed in an artificial scenario in order to calibrate the parameters of the approach. The data was also used to compare the new approach with previous work. Then it has been empirically evaluated on real Blobs from existing open source systems in order to assess how good and useful the proposed refactoring solutions are considered by software engineers and how well the proposed refactorings approximate refactorings done by the original developers. We found that the new approach outperforms a previously proposed approach and that developers find the proposed solutions useful in guiding refactorings.
An Inmarsat BGAN Terminal Patch Antenna Array With Unequal Input Impedance Elements and Conductor-Backed ACPW Series-Feed Network

A novel 2 × 2 sequentially rotated patch antenna array with unequal input impedance elements and a conductor-backed asymmetric coplanar waveguide (ACPW) series-feed network is proposed. The corner truncated patch element is fed by a three-dimensional meander strip, which can easily control the input impedance and has slight effects on the radiation performance. Compared to microstrip-line feed networks, the radiation loss of the proposed feed network is lower. Furthermore, the maximum characteristic impedance of transmission lines in the proposed feed network is 91.2 Ohm. As a result, it can be easily realized with printed circuit board (PCB) techniques. The measured results show that the proposed antenna array has an impedance bandwidth (VSWR <; 1.5) of about 40.5% (1244-1876 MHz), a 3-dB axial ratio (AR) bandwidth of about 25.6% (1412-1826 MHz), and a gain-level larger than 11.6 dBi across the broadband global area network (BGAN) operating bands. Therefore, the proposed antenna array can be a good candidate for Inmarsat BGAN portable terminal applications.
Handover decision using fuzzy MADM in heterogeneous networks

In the next generation heterogeneous wireless networks, a user with a multi-interface terminal may have a network access from different service providers using various technologies. It is believed that handover decision is based on multiple criteria as well as user preference. Various approaches have been proposed to solve the handover decision problem, but the choice of decision method appears to be arbitrary and some of the methods even give disputable results. In this paper, a new handover criteria is introduced along with a new handover decision strategy. In addition, handover decision is identified us a fuzzy multiple attribute decision making (MADM) problem, and fuzzy logic is applied to deal with the imprecise information of some criteria and user preference. After a systematic analysis of various fuzzy MADM methods, a feasible approach is presented. In the end, examples are provided illustrating the proposed methods and the sensitivity of the methods is also analysed.
Software-defined network virtualization: an architectural framework for integrating SDN and NFV for service provisioning in future networks

SDN and NFV are two significant innovations in networking. The evolution of both SDN and NFV has shown strong synergy between these two paradigms. Recent research efforts have been made toward combining SDN and NFV to fully exploit the advantages of both technologies. However, integrating SDN and NFV is challenging due to the variety of intertwined network elements involved and the complex interaction among them. In this article, we attempt to tackle this challenging problem by presenting an architectural framework called SDNV. This framework offers a clear holistic vision of integrating key principles of both SDN and NFV into unified network architecture, and provides guidelines for synthesizing research efforts toward combining SDN and NFV in future networks. Based on this framework, we also discuss key technical challenges to realizing SDN-NFV integration and identify some important topics for future research, with a hope to arouse the research community's interest in this emerging area.
Optimizing memory transactions

Atomic blocks allow programmers to delimit sections of code as 'atomic', leaving the language's implementation to enforce atomicity. Existing work has shown how to implement atomic blocks over word-based transactional memory that provides scalable multi-processor performance without requiring changes to the basic structure of objects in the heap. However, these implementations perform poorly because they interpose on all accesses to shared memory in the atomic block, redirecting updates to a thread-private log which must be searched by reads in the block and later reconciled with the heap when leaving the block.This paper takes a four-pronged approach to improving performance: (1) we introduce a new 'direct access' implementation that avoids searching thread-private logs, (2) we develop compiler optimizations to reduce the amount of logging (e.g. when a thread accesses the same data repeatedly in an atomic block), (3) we use runtime filtering to detect duplicate log entries that are missed statically, and (4) we present a series of GC-time techniques to compact the logs generated by long-running atomic blocks.Our implementation supports short-running scalable concurrent benchmarks with less than 50\% overhead over a non-thread-safe baseline. We support long atomic blocks containing millions of shared memory accesses with a 2.5-4.5x slowdown.
Child sexual abuse in sub-Saharan Africa: a literature review.

This article reviews the English-language literature on child sexual abuse in sub-Saharan Africa (SSA). The focus is on the sexual abuse of children in the home/community, as opposed to the commercial sexual exploitation of children.



English language, peer-reviewed papers cited in the Social Sciences Citation Index (SSCI) are examined. Reports from international and local NGOs and UN agencies are also examined.



Few published studies on the sexual abuse of children have been conducted in the region, with the exception of South Africa. Samples are predominantly clinical or University based. A number of studies report that approximately 5% of the sample reported penetrative sexual abuse during their childhood. No national survey of the general population has been conducted. The most frequent explanations for the sexual abuse of children in SSA include rapid social change, AIDS/HIV avoidance strategies and the patriarchal nature of society. Child sexual abuse is most frequently perpetrated by family members, relatives, neighbors or others known to the child.



There is nothing to support the widely held view that child sexual abuse is very rare in SSA-prevalence levels are comparable with studies reported from other regions. The high prevalence levels of AIDS/HIV in the region expose sexually abused children to high risks of infection. It is estimated that, approximately.6-1.8% of all children in high HIV-incidence countries in Southern Africa will experience penetrative sexual abuse by an AIDS/HIV infected perpetrator before 18 years of age.
Effective Large-Scale Online Influence Maximization

In this paper, we study a highly generic version of influence maximization (IM), one of optimizing influence campaigns by sequentially selecting "spread seeds" from a set of candidates, a small subset of the node population, under the hypothesis that, in a given campaign, previously activated nodes remain "persistently" active throughout and thus do not yield further rewards. We call this problem online influence maximization with persistence. We introduce an estimator on the candidates' missing mass – the expected number of nodes that can still be reached from a given seed candidate – and justify its strength to rapidly estimate the desired value. We then describe a novel algorithm, GT-UCB, relying on upper confidence bounds on the missing mass. We show that our approach leads to high-quality spreads on classic IM datasets, even though it makes almost no assumptions on the diffusion medium. Importantly, it is orders of magnitude faster than state-of-the-art IM methods.
The measure of face-lift patient satisfaction: the Owsley Facelift Satisfaction Survey with a long-term follow-up study.

Patient satisfaction is a major factor in determining success in aesthetic surgery. To the authors' knowledge, a long-term study measuring patient satisfaction with face-lift surgery has not been published. The authors' study was designed to measure patient satisfaction with the overall experience of a face lift and to assess the patient's level of satisfaction 10 to 15 years after surgery.



Three hundred ninety-four consecutive patients were identified who had face lifts performed by the senior author (J.Q.O.) between January 1, 1994, and January 1, 1999. Contact was achieved with 146 patients (37 percent), and 131 patients (90 percent) agreed to participate by completing a four-page survey. Eighty-nine patients (68 percent) returned the survey.



One year after face-lift surgery, 87 patients (97.8 percent) described the improvement of their facial appearance as very good or beyond expectations. After an average follow-up of 12.6 years, 61 patients (68.5 percent) rated their current degree of improvement as very good or beyond expectations, and 61 patients (68.5 percent) felt 10 or more years had been added to their youthful appearance. Thirty-four patients (31 percent) indicated disappointment in some aspect of the face lift.



This work assesses the long-term satisfaction of face-lift patients who had a superficial musculoaponeurotic system-platysma face lift. The results suggest a high degree of satisfaction following face-lift surgery at short-term and long-term follow-up. The authors recognize that recall bias may be present when recalling the satisfaction at 1 year postoperatively. We present the survey questionnaire as a template for future research in face-lift patients.
Ubiquitous Monitoring of Electrical Household Appliances

The number of appliances at home is increasing continuously, mainly because they make our lives easier. Currently, technology is integrated in all objects of our daily life. TCP/IP let us monitor our home in real time and check ubiquitously if something is happening at home. Bearing in mind this idea, we have developed a low-cost system, which can be used in any type of electrical household appliance that takes information from the appliance and posts the information to the Twitter Social network. Several sensors placed in the household appliances gather the sensed data and send them wired or wirelessly, depending on the case, using small and cheap devices to a gateway located in the home. This gateway takes decisions, based on the received data, and sends notifications to Twitter. We have developed a software application that takes the values and decides when to issue an alarm to the registered users (Twitter friends of our smart home). The performance of our system has been measured taking into account the home network (using IEEE 802.3u and IEEE 802.11g) and the data publishing in Twitter. As a result, we have generated an original product and service for any electrical household appliance, regardless of the model and manufacturer, that helps home users improve their quality of life. The paper also shows that there is no system with the same innovative features like the ones presented in this paper.