nils-herrmann/clean_scirepeval huggingface dataset:
The Design and Implementation of the NDN Protocol Stack for RIOT OS
Venue: 2016 IEEE Globecom Workshops (GC Wkshps)

The Named Data Networking (NDN) architecture has been proposed as a promising solution for supporting communications in IoT environments. An important class of IoT platform is the constrained devices that have limited computing resources and are connected by constrained networks. This paper presents the design and implementation of the NDN protocol stack for RIOT OS, a popular operating system for constrained IoT platforms. We succeeded in integrating the core NDN packet forwarding logic into the RIOT OS kernel together with a high level application interface with data security support. Our results demonstrated the feasibility of using NDN protocol stack to support applications on constrained devices with only 10s of KB of RAM and flash memory.
Border surveillance: Testing the territorial control of the Andalusian defense network in center south Iberia through GIS

The Middle Ages were a high conflictive period in the Iberian Peninsula that left indelible traces in the landscape translated in defensive networks which still extend hundreds of kilometers. However, it is not clearly defined yet the operation of this fortified network in the Andalusian territory. In this paper we set out a series of GIS analyses in order to help solving the existing questions. Thus, we will check the territorial control capabilities of this network over a vast area of central south Iberia. To do this, it will be key to model two factors: the visibility of the study sample and the general human displacement through the territory. After obtaining these products the corresponding statistical analyses will be performed to try to integrate the results into the existing archaeological discourse.
Assessment of the Effective total quality management on performance at selective colleges in Tigray regional administrative State, Ethiopia,

This study attempted to fill a gap in the literature regarding the study of relationships among specific variables, or building blocks, associated with TQM and their use within selective TVET colleges of Tigray state particularly, the eastern zone of Tigray. The study was focused on the TQM and some measuring constructs of TQM. TQM is one of management system like QFD, Six Sigma, ISO 9001, the MBNQA, CQI, Strategic Planning, and the BSC; those are often met with skepticism among leaders of higher educations.  The main aim of this study was assessment of the effective TQM on performance at selective TVET colleges in Tigray, Ethiopia and assessment of associated measuring and affecting factors. Because of time and financial limitations, the study was delimited only on the selective TVET colleges of Eastern zone of Tigray.  Both qualitative and quantitative analysis was conducted passing many procedures through different sources of data. Stratified sampling was employed. Out of Total 7189, sample of 365 was selected. Binary logistic and multiple linear regressions were modeled to measure the relationship among different constructs of TQM.  54.9% of variability in product/service quality and 61.4% of variability in satisfaction were explained by the independent variables altogether and overall multiple regression models were statistically significant (p value<0.001) Besides of multiple linear regressions, the Hosmer Lemeshow
Understanding the potential impact of skills recognition systems on labour markets: Research report

Formal education and training systems are not the only ways in which people develop skills. In many cases, this happens through informal or non formal learning or people acquire them outside the country in which they work. Employers may not easily recognize skills attained this way, and individuals possessing such uncertified skills are at a disadvantage while finding a job, progressing in their careers or securing a wage increase. The fact that these skills are invisible magnifies the challenge of skills under utilization and mismatch, and contributes to higher unemployment, poverty and inequality. The task of skills recognition systems is to make such uncertified skills visible. This research focuses on analysing whether skills recognition improves skills utilization, reduces skills mismatch and alleviates unemployment, poverty and inequality. The development of skills recognition systems gives rise to a number of challenges that may have a negative impact on effectiveness and a return on investment in these systems. The research brings numerous examples on how can these challenges be addressed in the design, implementation or upgrading of skills recognition systems.
Delving Deeper into Convolutional Networks for Learning Video Representations
Venue: ICLR

We propose an approach to learn spatio temporal features in videos from intermediate visual representations we call "percepts" using Gated Recurrent Unit Recurrent Networks (GRUs).Our method relies on percepts that are extracted from all level of a deep convolutional network trained on the large ImageNet dataset. While high level percepts contain highly discriminative information, they tend to have a low spatial resolution. Low level percepts, on the other hand, preserve a higher spatial resolution from which we can model finer motion patterns. Using low level percepts can leads to high dimensionality video representations. To mitigate this effect and control the model number of parameters, we introduce a variant of the GRU model that leverages the convolution operations to enforce sparse connectivity of the model units and share parameters across the input spatial locations. We empirically validate our approach on both Human Action Recognition and Video Captioning tasks. In particular, we achieve results equivalent to state of art on the YouTube2Text dataset using a simpler text decoder model and without extra 3D CNN features.
The Home Literacy Environment as a Predictor of the Early Literacy Development of Children at Family Risk of Dyslexia
Venue: Scientific studies of reading the official journal of the Society for the Scientific Study of Reading

The home literacy environment (HLE) predicts language and reading development in typically developing children; relatively little is known about its association with literacy development in children at family risk of dyslexia. We assessed the HLE at age 4 years, precursor literacy skills at age 5, and literacy outcomes at age 6, in a sample of children at family risk of dyslexia (n 116) and children with no known risk (n 72) Developmental relationships between the HLE and literacy were comparable between the groups; an additional effect of storybook exposure on phoneme awareness was observed in the family risk group only. The effects of socioeconomic status on literacy were partially mediated by variations in the HLE; in turn, effects of the HLE on literacy were mediated by precursor skills (oral language, phoneme awareness, and emergent decoding) in both groups. Findings are discussed in terms of possible gene environment correlation mechanisms underpinning atypical literacy development.
RISK FACTORS FOR THE DEVELOPMENT OF DEEP INFECTION FOLLOWING HIP FRACTURE SURGERY: ANALYSIS OF 2822 CONSECUTIVE PATIENTS

This study aimed to identify risk factors for development of deep periprosthetic joint infection (PJI) in patients following surgical treatment of neck of femur fracture.  This study identified a consecutive series of 2,822 (2,052 female, 73% patients who underwent either hemiarthroplasty (n=1,825, 65% or fixation (DHS) (n=997, 35% for fractured neck of femur performed between January 2009 and June 2015 at our institution. Full patient demographics, co morbidity and peri operative complication data were determined. The majority of patients were either ASA 2 (n=663, 23% or ASA 3 (n=1,521, 54% mean age 81.3 years (SD 10.3) All patients were followed up post operatively by a dedicated surgical site infection (SSI) monitoring team in order to identify patients who developed a PJI within 1 year. A stepwise multivariable logistic regression model was used to identify patient and surgical factors associated with increased risk of infection. Predictors with a p value of <0.20 in the univariate analysis were included in the multivariate analysis.  Thirty nine (39) cases of deep periprosthetic infection were identified (hemiarthroplasty n=35, DHS n=4) representing an overall deep infection rate of 1.4% (hemiarthroplasty 1.9% DHS 0.4% The most common infecting pathogen was a pure growth of coagulase negative Staphylococcus (n=9, 23% followed by a pure growth of Staphylococcus aureus (n=7, 18% An increased risk of PJI was observed in patients who underwent hemiarthroplasty compared to those treated by fixation (odds ratio (OR) 6.50, 95%CI 2.26 18.7, p=0.001) Of patient factors, only blood transfusion within 30 days (OR 3.51, 95%CI 1.72 7.13, p=0.001) and the presence or development of pressure sores on or during admission (OR 2.99, 95%CI 1.24 7.19, p=0.015) were significantly associated with an increased risk of development of PJI. Use of high dose dual antibiotic cement (gentamicin and clindamycin) was associated with a two fold reduction in the risk of PJI (OR 0.39, 95%CI 0.20 0.76, p=0.005) vs standard dose gentamicin antibiotic cement.  This study found: 1) a deep infection rate similar to that reported earlier from large number studies from the UK, 2) a six fold higher deep infection rate in hemiarthroplasties, compared to internal fixations, and 3) a three fold higher infection rate in patients who suffer concomitant pressure sores or receive a blood transfusion up to 30 days post operatively.
Predictors of 30 day mortality following hip/pelvis fractures.
Venue: Orthopaedics traumatology, surgery research OTSR

With the cost of healthcare in the United States reaching $2.9 trillion in 2013 and expected to increase with a growing geriatric population, the Center for Medicare and Medicaid Services (CMS) and Hospital Quality Alliance (HQA) began publicly reporting 30 day mortality rates so that hospitals and physicians may begin to confront clinical problems and promote high quality and patient centered care. Though the 30 day mortality is considered a highly effective tool in measuring hospital performance, little data actually exists that explores the rate and risk factors for trauma related hip and pelvis fractures. Therefore, in this study, we sought to explore the risk factors associated with 30 day mortality in trauma related hip and pelvic fractures.  Utilizing the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) database, 341,062 patients undergoing orthopaedic procedures from 2005 to 2013 were identified through a Current Procedural Terminology (CPT) code search. A second CPT code search identified 24,805 patients who sustained a hip/pelvis fracture. Patient demographics, preoperative comorbidities, operative characteristics and postoperative complications were collected and compared using Chi squared test, Wilcoxon Mann Whitney test and multivariate logistic regression analysis.  Preoperative and postoperative risk factors for 30 day mortality following a hip/pelvis fracture were found: ASA classification, ascites, disseminated cancer, dyspnea, functional status, history of congestive heart failure (CHF) history of chronic obstructive pulmonary disease (COPD) a recent blood transfusion, and the postoperative complications: pneumonia, myocardial infarction, stroke, and septic shock.  Several preoperative patient risk factors and postoperative complications greatly increased the odds for patient mortality following 30 days after initial surgery. Orthopaedic surgeons can utilize these predictive risk factors to better improve patient care.
Risk factors for mortality in geriatric hip fractures: a compressional study of different surgical procedures in 785 consecutive patients
Venue: European Journal of Orthopaedic Surgery Traumatology

BackgroundOnly a little is known about whether type of surgical intervention has an effect on mortality of these patients. Our primary objective was to assess whether different type of surgical procedures has an effect on mortality among elderly patients with hip fracture. A secondary objective was to examine factors that are related to mortality in our patient population. Our hypothesis is that type of surgical procedure, especially external fixation, should have an influence on mortality outcomes.MethodsWe included 785 patients age 65 years or older, with hip fractures. Operative treatment consisted of external fixation, internal fixation, total hip arthroplasty and hip hemiarthroplasty. Age, gender, type of fracture, type of surgery performed, American Society of Anesthesiology (ASA) grade, clinical comorbidities, anesthesia type, blood transfusion requirement, time to surgery, intensive care unit requirement, operation length and length of hospital stay and number of comorbidities were documented.ResultsDuring the study period, 785 patients (262 male, 523 female) were included to study, Overall mortality rate was 37.2 (292/785) Their age ranged between 65 and 100 years (mean 81) Surgery type Kaplan Meier cumulative mortality curves suggested no significant difference between four different types of surgery groups (p 0.064) Transfusion requirement was significantly lower in external fixation group comparing to other groups (p 0.014) Cox regression analysis showed the number of comorbidities 2 and 3 (p 0.0027, p 0.015) transfusion requirement (p 0.0001) ASA 4 (p 0.016) to be significant predictors of mortality.ConclusionsTransfusion requirement, ASA grade 4 and having more than two comorbidities are risk factors for mortality in geriatric hip fractures. Type of surgical intervention and fracture type had similar mortality rates in our patient population.
An Investigation into the Quasi Static Response of Ti6Al4V Lattice Structures Manufactured Using Selective Laser Melting

Ti6Al4 V (Ti64) lattice structures manufactured using selective laser melting (SLM) have been used in fields such as aerospace and medical science due to their exceptional light weight, corrosion resistant capability and biocompatibility. In this study, the mechanical properties of octahedral type Ti64 lattice structures under quasi static loading conditions was investigated. The initial stiffness, ultimate strength and ductility of the structures with different aspect ratios were evaluated and compared using experiments and quasi static finite element analysis (FEA) The results demonstrated that the experimental data and FEA were in good agreement. The initial stiffness and strength of the octahedral lattice structures improved significantly as the strut aspect ratios decreased; however, the poor ductility evident in all the samples showed no obvious relationship to the aspect ratios, which means that the geometrical sizes had little effect on the brittle behaviour of the Ti64 lattice structures fabricated using SLM.
Watertight and 2 manifold Surface Meshes Using Dual Contouring with Tetrahedral Decomposition of Grid Cubes

The Dual Contouring algorithm (DC) is a grid based process used to generate surface meshes from volumetric data. The advantage of DC is that it can reproduce sharp features by inserting vertices anywhere inside the grid cube, as opposed to the Marching Cubes (MC) algorithm that can insert vertices only on the grid edges. However, DC is unable to guarantee 2 manifold and watertight meshes due to the fact that it produces only one vertex for each grid cube. We present a modified Dual Contouring algorithm that is capable of overcoming this limitation. Our method decomposes an ambiguous grid cube into a maximum of twelve tetrahedral cells; we introduce novel polygon generation rules that produce 2 manifold and watertight surface meshes. We have applied our proposed method on realistic data, and a comparison of the results of our proposed method with results from traditional DC shows the effectiveness of our method.
2 manifold Surface Meshing Using Dual Contouring with Tetrahedral Decomposition
Venue: Adv. Eng. Softw.

The Dual Contouring algorithm (DC) is a grid based process used to generate surface meshes from volumetric data. The advantage of DC is that it can reproduce sharp features by inserting vertices anywhere inside the grid cube, as opposed to the Marching Cubes (MC) algorithm that can insert vertices only on the grid edges. However, DC is unable to guarantee 2 manifold and watertight meshes due to the fact that it produces only one vertex for each grid cube. We present a modified Dual Contouring algorithm that is capable of overcoming this limitation. Our method decomposes an ambiguous grid cube into a maximum of twelve tetrahedral cells; we introduce novel polygon generation rules that produce 2 manifold and watertight surface meshes. We have applied our proposed method on realistic data, and a comparison of the results of our proposed method with results from traditional DC shows the effectiveness of our method.
Time to exercise! an aide memoire stroke app for post stroke arm rehabilitation
Venue: MobileHCI

A majority of Stroke survivors have an arm impairment (up to 80% which persists over the long term >12 months) Physiotherapy experts believe that a rehabilitation Aide Memoire could help these patients  Hence, we designed, with the input of physiotherapists, Stroke experts and former Stroke patients, the Aide Memoire Stroke (AIMS) App to help them remember to exercise more frequently. We evaluated its use in a controlled field evaluation on a smartphone, tablet and smartwatch. Since one of the main features of the app is to remind Stroke survivors to exercise we also investigated reminder modalities (i.e. visual, vibrate, audio, speech) One key finding is that Stroke survivors opted for a combination of modalities to remind them to conduct their exercises. Also, Stroke survivors seem to prefer smartphones compared to other mobile devices due to their ease of use, usability, familiarity and being easier to handle with one arm.
Effects of virtual reality training using Nintendo Wii and treadmill walking exercise on balance and walking for stroke patients
Venue: Journal of physical therapy science

The purpose of this study is to investigate the effects of virtual reality training using Nintendo Wii on balance and walking for stroke patients.  Forty stroke patients with stroke were randomly divided into two exercise program groups: virtual reality training (n=20) and treadmill (n=20) The subjects underwent their 40 minute exercise program three times a week for eight weeks. Their balance and walking were measured before and after the complete program. We measured the left/right weight bearing and the anterior/posterior weight bearing for balance, as well as stance phase, swing phase, and cadence for walking.  For balance, both groups showed significant differences in the left/right and anterior/posterior weight bearing, with significant post program differences between the groups. For walking, there were significant differences in the stance phase, swing phase, and cadence of the virtual reality training group.  The results of this study suggest that virtual reality training providing visual feedback may enable stroke patients to directly adjust their incorrect weight center and shift visually. Virtual reality training may be appropriate for patients who need improved balance and walking ability by inducing their interest for them to perform planned exercises on a consistent basis.
Hierarchical Bayesian nonparametric models for knowledge discovery from electronic medical records
Venue: Knowl. Based Syst.

Electronic Medical Record (EMR) has established itself as a valuable resource for large scale analysis of health data. A hospital EMR dataset typically consists of medical records of hospitalized patients. A medical record contains diagnostic information (diagnosis codes) procedures performed (procedure codes) and admission details. Traditional topic models, such as latent Dirichlet allocation (LDA) and hierarchical Dirichlet process (HDP) can be employed to discover disease topics from EMR data by treating patients as documents and diagnosis codes as words. This topic modeling helps to understand the constitution of patient diseases and offers a tool for better planning of treatment. In this paper, we propose a novel and flexible hierarchical Bayesian nonparametric model, the word distance dependent Chinese restaurant franchise (wddCRF) which incorporates word to word distances to discover semantically coherent disease topics. We are motivated by the fact that diagnosis codes are connected in the form of ICD 10 tree structure which presents semantic relationships between codes. We exploit a decay function to incorporate distances between words at the bottom level of wddCRF. Efficient inference is derived for the wddCRF by using MCMC technique. Furthermore, since procedure codes are often correlated with diagnosis codes, we develop the correspondence wddCRF (Corr wddCRF) to explore conditional relationships of procedure codes for a given disease pattern. Efficient collapsed Gibbs sampling is derived for the Corr wddCRF. We evaluate the proposed models on two real world medical datasets PolyVascular disease and Acute Myocardial Infarction disease. We demonstrate that the Corr wddCRF model discovers more coherent topics than the Corr HDP. We also use disease topic proportions as new features and show that using features from the Corr wddCRF outperforms the baselines on 14 days readmission prediction. Beside these, the prediction for procedure codes based on the Corr wddCRF also shows considerable accuracy.
User Initiated Data Plan Trading via a Personal Hotspot Market
Venue: IEEE Transactions on Wireless Communications

Mobile data services are becoming the main driver of a wireless service provider's (WSPs) revenue growth, and two part tariff data plans (each including a lump sum fee and a per unit charge) are usually provided to wireless users. Some users can easily use up their monthly data quota and may pay for costly data over usage. Motivated by users' diverse usage behavior (more or less than the subscribed data quotas) this paper proposes a new type of user initiated network for cellular users to trade data plans by leveraging personal hotspots (PHs) with users' smartphones. A user with data surplus can set up a PH and share the cellular data connection to another user with data deficit in the vicinity. Due to users' randomness in data usage, incentive to trade, and user mobility to enter or leave the PH connection range, the analysis on the secondary trading market is challenging. To overcome these issues, we propose a PH market for users with diverse data usage behaviors and random user mobility to directly trade data as sellers and buyers, by designing a market clearing price. It is shown that the PH market greatly saves all users' expected costs when the existence condition of the PH market is met. Finally, as this PH market will challenge the WSP's revenue collection (especially the surcharge from users' data over usage) we analyze the WSP's response to the PH market and propose two effective countermeasure strategies by either reducing the selling users' data quota in their data plans (the PH market's supply) or increasing the buying users' data quota (the PH market's demand) When we have more than one WSP and they are competitive, we show that one WSP can take advantage of the PH market by indirectly selling more data to the other WSP's users.