bluuebunny/crossref_metadata_2025 huggingface dataset:
The metric dimension of annihilator graphs of commutative rings
Authors: Soleymanivarniab V. , Tehranian A. , Nikandish R.
Published: April 2019

Let [Formula: see text] be a commutative ring with nonzero identity. The annihilator graph of [Formula: see text], denoted by [Formula: see text], is the (undirected) graph whose vertex set is the set of all nonzero zero-divisors of [Formula: see text] and two distinct vertices [Formula: see text] and [Formula: see text] are adjacent if and only if [Formula: see text]. In this paper, we study the metric dimension of annihilator graphs associated with commutative rings and some metric dimension formulae for annihilator graphs are given.
BIOMECHANICAL PERFORMANCE OF A MODIFIED DESIGN OF DYNAMIC CERVICAL IMPLANT COMPARED TO CONVENTIONAL BALL AND SOCKET DESIGN OF AN ARTIFICIAL INTERVERTEBRAL DISC IMPLANT: A FINITE ELEMENT STUDY
Authors: BHATTACHARYA SHAMBO , ROY SANDIPAN , RANA MASUD , BANERJEE SREERUP , KARMAKAR SANTANU KUMAR , BISWAS JAYANTA KUMAR
Published: April 2019

Most of the implants used for total disc replacement (TDR) surgery are designed as a ball and socket pair aimed at providing a three-dimensional unconstrained motion. However, one of the major concerns with ball and socket design is the wear of the implant which limits its life. In this study the biomechanical performance of two types of implant designs is compared — a conventional ball and socket type (Prodisc-C) and a modified design of dynamic cervical implant (DCI) using FE analysis. A 3-dimensional geometrical model of cervical spine (C1–T1) was developed using CT scan data of a middle-aged healthy male. Subsequently, using FE analysis, the ROM values were validated with the existing literature using a compressive load in combination with different physiological motions of the neck. Furthermore, FE analysis on the two implants, fitted at C5–C6 segment, showed a significant increase in the ROM of implanted segment using Prodisc and decrease in the ROM of inferior segment, but modified-DCI restored the motion of the implanted and adjacent segments. Analysis of average bone strains adjacent to the implant showed a possibility of stress shielding for Prodisc. However, higher stress distribution on the modified-DCI limited its clinical use.
Silicon p+–p−–n Diodes with Embedded β-FeSi2 and CrSi2 Nanocrystals: Morphology, Crystal Structure and Photoelectric Properties
Authors: Galkin N. G. , Goroshko D. L. , Chusovitin E. A. , Shevlyagin A. V. , Galkin K. N. , Gutakovskii A. K.
Published: April 2019

The [Formula: see text]–[Formula: see text]–[Formula: see text] diode structures with a variable number of [Formula: see text]-FeSi2 and CrSi2 nanocrystal (NC) bilayer were studied at room and liquid nitrogen temperatures. The high crystal quality of Si and embedded NCs was determined by HRTEM cross-sectional data. This diode demonstrated a photoresponse in the IR region (1.02–0.8[Formula: see text]eV) which was associated with a decrease in recombination losses with the main contribution coming from CrSi2 NCs. Calculations of photoyield and its extrapolation to zero resulted in band gap values of 0.35[Formula: see text]eV at 300[Formula: see text]K and 0.46[Formula: see text]eV at 90[Formula: see text]K. The spectral sensitivity of [Formula: see text][Formula: see text]A/W and specific detectivity of [Formula: see text][Formula: see text](cm Hz[Formula: see text]/W) were determined at [Formula: see text][Formula: see text][Formula: see text]m and T=300[Formula: see text]K.
Total Roman domatic number of a graph
Authors: Amjadi J. , Nazari-Moghaddam S. , Sheikholeslami S. M.
Published: April 2019

A total Roman dominating function on a graph [Formula: see text] is a labeling [Formula: see text] such that every vertex with label 0 has a neighbor with label 2 and the subgraph of [Formula: see text] induced by the set of all vertices of positive weight has no isolated vertex. A set [Formula: see text] of total Roman dominating functions on [Formula: see text] with the property that [Formula: see text] for each [Formula: see text], is called a total Roman dominating family (of functions) on [Formula: see text]. The maximum number of functions in a total Roman dominating family on [Formula: see text] is the total Roman domatic number of [Formula: see text], denoted by [Formula: see text]. In this paper, we investigate the properties of total Roman domatic number in graphs. In particular, we present some sharp bounds for [Formula: see text] and we determine the total Roman domatic number of some special graphs.
On the stable implicit finite differences approximation of diffusion equation with the time fractional derivative without singular kernel
Authors: Taghavi Ali , Babaei Afshin , Mohammadpour Alireza
Published: April 2019

In this paper, we give a numerical approximation to the Caputo–Fabrizio time fractional diffusion equation. The implicit finite differences method is applied to solve a time-fractional diffusion equation with this new fractional derivative. We present the stability and convergence analysis of the proposed numerical scheme. Some numerical problems will be presented to show the accuracy and effectiveness of the method.
New result of existence of periodic solutions for a generalized p-Laplacian Liénard type differential equation with a variable delay
Authors: Eswari R. , Piramanantham V.
Published: April 2019

In this paper, we propose a generalized [Formula: see text]-Laplacian Liénard type differential equation with a variable delay. By applying the Mawhin continuation theorem, we established a set of sufficient conditions on the existence of at least one periodic solution with period [Formula: see text]. It is significant that the growth degree with respect to the variables [Formula: see text] imposed on [Formula: see text] is allowed to be greater than [Formula: see text] and the growth degree with respect to the variables [Formula: see text] imposed on [Formula: see text] is allowed to be greater than [Formula: see text] so the result not only improves but also generalizes. Some examples are provided to illustrate the results.
Nonhomogeneous polyharmonic elliptic problems involving GJMS operator on Riemannian manifold
Authors: Tahri Kamel
Published: April 2019

Let [Formula: see text] be a closed Riemannian manifold, under some assumptions on [Formula: see text] and [Formula: see text] by applying a method used in [Tarantello, On nonhomogeneous elliptic equations involving critical Sobolev exponent, Ann. Inst. Henri Poincaré 9 (1992) 281–304], we show the existence and multiplicity of solutions of the semi-linear elliptic equation: [Formula: see text]. When [Formula: see text] is an Einsteinian manifold of positive scalar curvature, under additional conditions, we obtain the existence of positive solutions.
Hermitian energy and Hermitian Estrada index of digraphs
Authors: Jahanbani Akbar
Published: April 2019

Let [Formula: see text] be a digraph of order [Formula: see text], and [Formula: see text] be spectrum of the Hermitian adjacency matrix. The main purpose of this paper is to introduce the Hermitian energy and Hermitian Estrada index of a digraph, both based on the eigenvalues of the Hermitian matrix. Moreover, we establish upper and lower bounds for these new digraph invariants, and relations between them.
Oblique dual frames in Hilbert spaces
Authors: Javanshiri Hossein , Fattahi Abdolmajid , Sargazi Mojtaba
Published: April 2019

In this paper, we consider oblique dual frames and particularly, we obtain some of their characterizations. Among other things, special attention is devoted to the study of the effect of perturbations of frame sequences on their oblique duals. In particular, as a surprising result, we show that a frame sequence is uniquely determined by the set of its oblique dual.
A Unified Model for the Mobile-Edge-Cloud Continuum
Authors: Baresi L. , Mendonça D. F. , Garriga M. , Guinea S. , Quattrocchi G.
Published: April 2019

Technologies such as mobile, edge, and cloud computing have the potential to form a computing continuum for new, disruptive applications. At runtime, applications can choose to execute parts of their logic on different infrastructures that constitute the continuum, with the goal of minimizing latency and battery consumption and maximizing availability. In this article, we propose A3-E, a unified model for managing the life cycle of continuum applications. In particular, A3-E exploits the Functions-as-a-Service model to bring computation to the continuum in the form of microservices. Furthermore, A3-E selects where to execute a certain function based on the specific context and user requirements. The article also presents a prototype framework that implements the concepts behind A3-E. Results show that A3-E is capable of dynamically deploying microservices and routing the application’s requests, reducing latency by up to 90% when using edge instead of cloud resources, and battery consumption by 74% when computation has been offloaded.
Fog Computing for the Internet of Things
Authors: Puliafito Carlo , Mingozzi Enzo , Longo Francesco , Puliafito Antonio , Rana Omer
Published: April 2019

Research in the Internet of Things (IoT) conceives a world where everyday objects are connected to the Internet and exchange, store, process, and collect data from the surrounding environment. IoT devices are becoming essential for supporting the delivery of data to enable electronic services, but they are not sufficient in most cases to host application services directly due to their intrinsic resource constraints. Fog Computing (FC) can be a suitable paradigm to overcome these limitations, as it can coexist and cooperate with centralized Cloud systems and extends the latter toward the network edge. In this way, it is possible to distribute resources and services of computing, storage, and networking along the Cloud-to-Things continuum. As such, FC brings all the benefits of Cloud Computing (CC) closer to end (user) devices. This article presents a survey on the employment of FC to support IoT devices and services. The principles and literature characterizing FC are described, highlighting six IoT application domains that may benefit from the use of this paradigm. The extension of Cloud systems towards the network edge also creates new challenges and can have an impact on existing approaches employed in Cloud-based deployments. Research directions being adopted by the community are highlighted, with an indication of which of these are likely to have the greatest impact. An overview of existing FC software and hardware platforms for the IoT is also provided, along with the standardisation efforts in this area initiated by the OpenFog Consortium (OFC).
Tight Bounds on the Asymptotic Descriptive Complexity of Subgraph Isomorphism
Authors: Verbitsky Oleg , Zhukovskii Maksim
Published: April 2019

Let
v
(
F
) denote the number of vertices in a fixed connected pattern graph
F
. We show an infinite family of patterns
F
such that the existence of a subgraph isomorphic to
F
is expressible by a first-order sentence of quantifier depth 2/3
v
(
F
) + 1, assuming that the host graph is sufficiently large and connected. However, this is impossible for any
F
using less than 2/3
v
(
F
) - 2 first-order variables.
Passages
Authors: Groce Alex
Published: April 2019

In every larger-scale endeavor, or at least in most larger-scale endeavors, there comes a time to evaluate progress, solicit opinion, ask your public, survey your customers -- in short, to find out if what you are doing is actually worth doing. In some cases, this step may be omitted, or the results ignored: it is possible that if Herman Melville had shown people Moby Dick when he was half-done with it, everyone except Nathaniel Hawthorne would have said "Er, we're not sure what this is all about. Where's the nice adventure of Omoo? Just what are you up to, Sir?" He should not have therefore ditched the manuscript and gone on to something else; also, Nathaniel Hawthorne gets 50,000 votes. However, in general, you (and I) are not Melville writing Moby Dick. Scientific projects tend to publish some papers before they are "complete" and if these are universally derided and rejected, or receive no citations, it is often the case that they are doing nothing of much interest. There are exceptions, but they are rarer, perhaps, than we might think. Most things that are ignored are ignored for a good reason.
Using Natural Language Processing and Graph Mining to Explore Inter- Related Requirements in Software Artefacts
Authors: Singh Maninder
Published: April 2019

Software development is prone to software faults due to the involvement of multiple stakeholders especially during the fuzzy phases (requirements and design). Software inspections are commonly used in industry to detect and fix problems in requirements and design artifacts thereby mitigating the fault propagation to later phases. The requirements documented in natural language (NL) are prone to contain faults because of different vocabularies among stakeholders. This research employs various NL processing with semantic analysis (SA) and mining solutions from graph theory to NL requirements to develop inter-related requirements (IRRs) that can help identify requirements that may need similar fixes. Additionally, our approach aims at aiding requirements' engineers with fault-prone regions both pre and post inspection. Pre-inspection, our approach using IRRs help removing redundant and extraneous faults within related requirements while post-inspection, it aids engineers analyse the impact of a change in one requirement on another related requirements. So, this research aims at developing a graph of inter-related requirements using natural language processing and semantic analysis approaches on a given requirements document that can be used to aid various decisions pre and post-inspections.
Engineering Multi-Agent Systems
Authors: Mascardi Viviana , Weyns Danny , Ricci Alessandro
Published: April 2019

The continuous integration of software-intensive systems together with the ever-increasing computing power offer a breeding ground for intelligent agents and multi-agent systems (MAS) more than ever before. Over the past two decades, a wide variety of languages, models, techniques and methodologies have been proposed to engineer agents and MAS. Despite this substantial body of knowledge and expertise, the systematic engineering of large-scale and open MAS still poses many challenges. Researchers and engineers still face fundamental questions regarding theories, architectures, languages, processes, and platforms for designing, implementing, running, maintaining, and evolving MAS. This paper reports on the results of the 6th International Workshop on Engineering Multi-Agent Systems (EMAS 2018, 14th-15th of July, 2018, Stockholm, Sweden), where participants discussed the issues above focusing on the state of affairs and the road ahead for researchers and engineers in this area.
Summary of the 5th International Workshop on Requirements Engineering and Testing (RET 2018)
Authors: Unterkalmsteiner Michael , Yu Tingting , Gay Gregory , Bjarnason Elizabeth , Borg Markus , Felderer Michael
Published: April 2019

The RET (Requirements Engineering and Testing) workshop series provides a meeting point for researchers and practitioners from the two separate elds of Requirements Engineering (RE) and Testing. The goal is to improve the connection and alignment of these two areas through an exchange of ideas, challenges, practices, experiences and results. The long term aim is to build a community and a body of knowledge within the intersection of RE and Testing, i.e. RET. The 5th workshop was held in colocation with ICSE 2018 in Gothenburg, Sweden. The workshop continued in the same interactive vein as the predecessors. We introduced a new format for the presentations in which the paper authors had the opportunity to interact extensively with the audience. Each author was supported by a member of the organization committee to prepare either an extensive demo, collect more data in form of a questionnaire or perform a hands-on tutorial. We named this new format \X-ray session". In order to create an RET knowledge base, this cross-cutting area elicits contributions from both RE and Testing, and from both researchers and practitioners. A range of papers were presented from short positions papers to full research papers that cover connections between the two elds. The workshop attracted 27 participants and the positive feedback on the new format encourages us to organize the workshop the next year again.
mORAL
Authors: Akther Sayma , Saleheen Nazir , Samiei Shahin Alan , Shetty Vivek , Ertin Emre , Kumar Santosh
Published: April 2019

We address the open problem of reliably detecting oral health behaviors passively from wrist-worn inertial sensors. We present our model named mORAL (pronounced em oral) for detecting brushing and flossing behaviors, without the use of instrumented toothbrushes so that the model is applicable to brushing with still prevalent manual toothbrushes. We show that for detecting rare daily events such as toothbrushing, adopting a model that is based on identifying candidate windows based on events, rather than fixed-length timeblocks, leads to significantly higher performance. Trained and tested on 2,797 hours of sensor data collected over 192 days on 25 participants (using video annotations for ground truth labels), our brushing model achieves 100% median recall with a false positive rate of one event in every nine days of sensor wearing. The average error in estimating the start/end times of the detected event is 4.1% of the interval of the actual toothbrushing event.
Deep Multi-Task Learning Based Urban Air Quality Index Modelling
Authors: Chen Ling , Ding Yifang , Lyu Dandan , Liu Xiaoze , Long Hanyu
Published: April 2019

Obtaining comprehensive air quality information can help protect human health from air pollution. Existing spatially fine-grained estimation methods and forecasting methods have the following problems: 1) Only a part of data related to air quality is considered. 2) Features are defined and extracted artificially. 3) Due to the lack of training samples, they usually cannot achieve good generalization performance. Therefore, we propose a deep multi-task learning (MTL) based urban air quality index (AQI) modelling method (PANDA). On one hand, a variety of air quality-related urban big data (meteorology, traffic, factory air pollutant emission, point of interest (POI) distribution, road network distribution, etc.) are considered. Deep neural networks are used to learn the representations of these relevant spatial and sequential data, as well as to build the correlation between AQI and these representations. On the other hand, PANDA solves spatially fine-grained AQI level estimation task and AQI forecasting task jointly, which can leverage the commonalities and differences between these two tasks to improve generalization performance. We evaluate PANDA on the dataset of Hangzhou city. The experimental results show that our method can yield a better performance compared to the state-of-the-art methods.
Identifying and Planning for Individualized Change
Authors: Chung Chia-Fang , Wang Qiaosi , Schroeder Jessica , Cole Allison , Zia Jasmine , Fogarty James , Munson Sean A.
Published: April 2019

Identifying and planning strategies that support a healthy lifestyle or manage a chronic disease often require patient-provider collaboration. For example, people with healthy eating goals often share everyday food, exercise, or sleep data with health coaches or nutritionists to find opportunities for change, and patients with irritable bowel syndrome (IBS) often gather food and symptom data as part of working with providers to diagnose and manage symptoms. However, a lack of effective support often prevents health experts from reviewing large amounts of data in time-constrained visits, prevents focusing on individual goals, and prevents generating correct, individualized, and actionable recommendations. To examine how to design photo-based diaries to help people and health experts exchange knowledge and focus on collaboration goals when reviewing the data together, we designed and developed Foodprint, a photo-based food diary. Foodprint includes three components: (1) A mobile app supporting lightweight data collection, (2) a web app with photo-based visualization and quantitative visualizations supporting collaborative reflection, and (3) a pre-visit note communicating an individual's expectations and questions to experts. We deployed Foodprint in two studies: (1) with 17 people with healthy eating goals and 7 health experts, and (2) with 16 IBS patients and 8 health experts. Building upon the lens of boundary negotiating artifacts and findings from two field studies, our research contributes design principles to (1) prepare individuals to collect data relevant to their health goals and for collaboration, (2) help health experts focus on an individual's eating context, experiences, and goals in collaborative review, and (3) support individuals and experts to develop individualized, actionable plans and strategies.
Towards Reliable, Automated General Movement Assessment for Perinatal Stroke Screening in Infants Using Wearable Accelerometers
Authors: Gao Yan , Long Yang , Guan Yu , Basu Anna , Baggaley Jessica , Ploetz Thomas
Published: April 2019

Perinatal stroke (PS) is a serious condition that, if undetected and thus untreated, often leads to life-long disability, in particular Cerebral Palsy (CP). In clinical settings, Prechtl's General Movement Assessment (GMA) can be used to classify infant movements using a Gestalt approach, identifying infants at high risk of developing PS. Training and maintenance of assessment skills are essential and expensive for the correct use of GMA, yet many practitioners lack these skills, preventing larger-scale screening and leading to significant risks of missing opportunities for early detection and intervention for affected infants. We present an automated approach to GMA, based on body-worn accelerometers and a novel sensor data analysis method--Discriminative Pattern Discovery (DPD)--that is designed to cope with scenarios where only coarse annotations of data are available for model training. We demonstrate the effectiveness of our approach in a study with 34 newborns (21 typically developing infants and 13 PS infants with abnormal movements). Our method is able to correctly recognise the trials with abnormal movements with at least the accuracy that is required by newly trained human annotators (75%), which is encouraging towards our ultimate goal of an automated PS screening system that can be used population-wide.
GoalKeeper
Authors: Kim Jaejeung , Jung Hayoung , Ko Minsam , Lee Uichin
Published: April 2019

Many people often experience difficulties in achieving behavioral goals related to smartphone use. Most of prior studies approached this problem with various behavior change strategies such as self-reflection and social support. However, little is known about the effectiveness and user experiences of restrictive and coercive interventions such as blocking. In this work, we developed "GoalKeeper," a smartphone intervention app that locks the user into the self-defined daily use time limit with restrictive intervention mechanisms. We conducted a four-week field experiment with 36 participants to investigate the effects and user experiences of varying intensities of restrictive interventions. The results showed that restrictive mechanisms are more effective than non-restrictive mechanisms such as warning. However, we found that restrictive mechanisms caused more frustration and pressure to the users, mainly due to diversity of usage contexts and needs. Based on our study results, we extracted practical implications for designing restrictive mechanisms that balance the intervention effectiveness for behavioral changes and the flexibility for user acceptability.
Audio-Based Activities of Daily Living (ADL) Recognition with Large-Scale Acoustic Embeddings from Online Videos
Authors: Liang Dawei , Thomaz Edison
Published: April 2019

Over the years, activity sensing and recognition has been shown to play a key enabling role in a wide range of applications, from sustainability and human-computer interaction to health care. While many recognition tasks have traditionally employed inertial sensors, acoustic-based methods offer the benefit of capturing rich contextual information, which can be useful when discriminating complex activities. Given the emergence of deep learning techniques and leveraging new, large-scale multimedia datasets, this paper revisits the opportunity of training audio-based classifiers without the onerous and time-consuming task of annotating audio data. We propose a framework for audio-based activity recognition that can make use of millions of embedding features from public online video sound clips. Based on the combination of oversampling and deep learning approaches, our framework does not require further feature processing or outliers filtering as in prior work. We evaluated our approach in the context of Activities of Daily Living (ADL) by recognizing 15 everyday activities with 14 participants in their own homes, achieving 64.2% and 83.6% averaged within-subject accuracy in terms of top-1 and top-3 classification respectively. Individual class performance was also examined in the paper to further study the co-occurrence characteristics of the activities and the robustness of the framework.
W!NCE
Authors: Rostaminia Soha , Lamson Alexander , Maji Subhransu , Rahman Tauhidur , Ganesan Deepak
Published: April 2019

The ability to unobtrusively and continuously monitor one's facial expressions has implications for a variety of application domains ranging from affective computing to health-care and the entertainment industry. The standard Facial Action Coding System (FACS) along with camera based methods have been shown to provide objective indicators of facial expressions; however, these approaches can also be fairly limited for mobile applications due to privacy concerns and awkward positioning of the camera. To bridge this gap, W!NCE re-purposes a commercially available Electrooculography-based eyeglass (J!NS MEME) for continuously and unobtrusively sensing of upper facial action units with high fidelity. W!NCE detects facial gestures using a two-stage processing pipeline involving motion artifact removal and facial action detection. We validate our system's applicability through extensive evaluation on data from 17 users under stationary and ambulatory settings, a pilot study for continuous pain monitoring and several performance benchmarks. Our results are very encouraging, showing that we can detect five distinct facial action units with a mean F1 score of 0.88 in stationary and 0.82 in ambulatory settings, and that we can accurately detect facial gestures that due to pain.
Modeling Spatio-Temporal App Usage for a Large User Population
Authors: Wang Huandong , Li Yong , Zeng Sihan , Wang Gang , Zhang Pengyu , Hui Pan , Jin Depeng
Published: April 2019

With the wide adoption of mobile devices, it becomes increasingly important to understand how users use mobile apps. Knowing when and where certain apps are used is instrumental for app developers to improve app usability and for Internet service providers (ISPs) to optimize their network services. However, modeling spatio-temporal patterns of app usage has been a challenging problem due to the complicated usage behavior and the very limited personal data. In this paper, we propose a Bayesian mixture model to capture when, where and what apps are used and predict future app usage. To solve the challenge of data sparsity, we apply a hierarchical Dirichlet process to leverage the shared spatio-temporal patterns to accurately model users with insufficient data. We then evaluate our model using a large dataset of app usage traces involving 1.7 million users over 3503 apps. Our analysis shows a clear correlation between the user's location and the apps being used. Extensive evaluations show that our model can accurately predict users' future locations and app usage, outperforming the state-of-the-art algorithms by 11.7% and 11.1%, respectively. In addition, our model can be used to synthesize app usage traces that do not leak user privacy while preserving the key data statistical properties.
LeakDoctor
Authors: Wang Xiaolei , Continella Andrea , Yang Yuexiang , He Yongzhong , Zhu Sencun
Published: April 2019

With the enormous popularity of smartphones, millions of mobile apps are developed to provide rich functionalities for users by accessing certain personal data, leading to great privacy concerns. To address this problem, many approaches have been proposed to detect privacy disclosures in mobile apps, but they largely fail to automatically determine whether the privacy disclosures are necessary for the functionality of apps. As a result, security analysts may easily face with a large number of false positives when directly adopting such approaches for app analysis. In this paper, we propose LeakDoctor, an analysis system seeking to automatically diagnose privacy leaks by judging if a privacy disclosure from an app is necessary for some functionality of the app. Functionality-irrelevant privacy disclosures are not justifiable, so considered as potential privacy leak cases. To achieve this goal, LeakDoctor integrates dynamic response differential analysis with static response taint analysis. In addition, it employs a novel technique to locate the program statements of each privacy disclosure. We implement a prototype of LeakDoctor and evaluate it against 1060 apps, which contain 2,095 known disclosure cases. Our experimental results show that LeakDoctor can automatically determine that 71.9% of the privacy disclosure cases indeed serve apps' functionalities and are justifiable. Hence, with the diagnosis results of LeakDoctor, analysts may avoid analyzing many justifiable privacy disclosures and only focus on the those unjustifiable cases.
RF-Focus
Authors: Wang Zhongqin , Xu Min , Ye Ning , Wang Ruchuan , Huang Haiping
Published: April 2019

Capturing RFID tags in the region of interest (ROI) is challenging. Many issues, such as multipath interference, frequency-dependent hardware characteristics and phase periodicity, make RF phase difficult to accurately indicate the tag-to-antenna distance for RFID tag localization. In this paper, we propose a comprehensive solution, called RF-Focus, which fuses RFID and computer vision (CV) techniques to recognize and locate moving RFID-tagged objects within ROI. Firstly, we build a multipath propagation model and propose a dual-antenna solution to minimize the impact of multipath interference on RF phase. Secondly, by extending the multipath model, we estimate phase shifts due to hardware characteristics at different operating frequencies. Thirdly, to minimize the tag position uncertainty due to RF phase periodicity, we leverage CV to extract image regions of being likely to contain ROI RFID-tagged objects, and then associate them with the processed RF phase after the removal of the phase shifts due to multipath interference and hardware characteristics for recognition and localization. Our experiments demonstrate the effectiveness of multipath modelling and hardware-related phase shift estimation. When five RFID-tagged objects are moving in the ROI, RF-Focus achieves the average recognition accuracy of 91.67% and localization accuracy of 94.26% given a false positive rate of 10%.
ShoesLoc
Authors: Yu Tuo , Jin Haiming , Nahrstedt Klara
Published: April 2019

Currently, in-shoe force sensors have been widely used for step counting and gait analysis. However, it has not been realized that in-shoe force sensors are also capable of tracking walking paths. In this paper, we present ShoesLoc, an indoor walking path tracking method based on in-shoe force sensors. We show that, based on the force signals from a user's shoes, it is possible to estimate the walking direction change and the stride length of each step with machine learning techniques. We further apply a particle filter to combine this information with the constraint of barriers in floor maps, and thus can determine the walking path and the current position of the user. To solve the problem of the low accuracy caused by cumulative walking direction errors, we improve the particle filter by designing the direction correction algorithm. Moreover, we propose the weight normalization method to handle the impact of handbags and backpacks. Our experimental results show that, after a convergence phase, ShoesLoc achieves the average location error of 0.9-1.3 m. Compared with traditional indoor tracking technologies, ShoesLoc does not require the installation of wireless anchors, and has good robustness to environment changes such as the magnetic interference.
Towards a Diffraction-based Sensing Approach on Human Activity Recognition
Authors: Zhang Fusang , Niu Kai , Xiong Jie , Jin Beihong , Gu Tao , Jiang Yuhang , Zhang Daqing
Published: April 2019

In recent years, wireless sensing has been exploited as a promising research direction for contactless human activity recognition. However, one major issue hindering the real deployment of these systems is that the signal variation patterns induced by the human activities with different devices and environmental settings are neither stable nor consistent, resulting in unstable system performance. The existing machine learning based methods usually take the "black box" approach and fails to achieve consistent performance. In this paper, we argue that a deep understanding of radio signal propagation in wireless sensing is needed, and it may be possible to develop a deterministic sensing model to make the signal variation patterns predictable.

With this intuition, in this paper we investigate: 1) how wireless signals are affected by human activities taking transceiver location and environment settings into consideration; 2) a new deterministic sensing approach to model the received signal variation patterns for different human activities; 3) a proof-of-concept prototype to demonstrate our approach and a case study to detect diverse activities. In particular, we propose a diffraction-based sensing model to quantitatively determine the signal change with respect to a target's motions, which eventually links signal variation patterns with motions, and hence can be used to recognize human activities. Through our case study, we demonstrate that the diffraction-based sensing model is effective and robust in recognizing exercises and daily activities. In addition, we demonstrate that the proposed model improves the recognition accuracy of existing machine learning systems by above 10%.
What Web Template Extractor Should I Use? A Benchmarking and Comparison for Five Template Extractors
Authors: Alarte Julián , Silva Josep , Tamarit Salvador
Published: April 2019

A Web template is a resource that implements the structure and format of a website, making it ready for plugging content into already formatted and prepared pages. For this reason, templates are one of the main development resources for website engineers, because they increase productivity. Templates are also useful for the final user, because they provide uniformity and a common look and feel for all webpages. However, from the point of view of crawlers and indexers, templates are an important problem, because templates usually contain irrelevant information, such as advertisements, menus, and banners. Processing and storing this information leads to a waste of resources (storage space, bandwidth, etc.). It has been measured that templates represent between 40% and 50% of data on the Web. Therefore, identifying templates is essential for indexing tasks. There exist many techniques and tools for template extraction, but, unfortunately, it is not clear at all which template extractor should a user/system use, because they have never been compared, and because they present different (complementary) features such as precision, recall, and efficiency. In this work, we compare the most advanced template extractors. We implemented and evaluated five of the most advanced template extractors in the literature. To compare all of them, we implemented a workbench, where they have been integrated and evaluated. Thanks to this workbench, we can provide a fair empirical comparison of all methods using the same benchmarks, technology, implementation language, and evaluation criteria.
Hazardous Air Pollutants Associated with Upstream Oil and Natural Gas Development: A Critical Synthesis of Current Peer-Reviewed Literature
Authors: Garcia-Gonzales Diane A. , Shonkoff Seth B.C. , Hays Jake , Jerrett Michael
Published: April 2019

Increased energy demands and innovations in upstream oil and natural gas (ONG) extraction technologies have enabled the United States to become one of the world's leading producers of petroleum and natural gas hydrocarbons. The US Environmental Protection Agency (EPA) lists 187 hazardous air pollutants (HAPs) that are known or suspected to cause cancer or other serious health effects. Several of these HAPs have been measured at elevated concentrations around ONG sites, but most have not been studied in the context of upstream development. In this review, we analyzed recent global peer-reviewed articles that investigated HAPs near ONG operations to ( a) identify HAPs associated with upstream ONG development, ( b) identify their specific sources in upstream processes, and ( c) examine the potential for adverse health outcomes from HAPs emitted during these phases of hydrocarbon development.
Introduction to the Symposium: Causal Inference and Public Health
Authors: Aiello Allison E. , Green Lawrence W.
Published: April 2019

Assessing the extent to which public health research findings can be causally interpreted continues to be a critical endeavor. In this symposium, we invited several researchers to review issues related to causal inference in social epidemiology and environmental science and to discuss the importance of external validity in public health. Together, this set of articles provides an integral overview of the strengths and limitations of applying causal inference frameworks and related approaches to a variety of public health problems, for both internal and external validity.
Theories of the Causes of Poverty
Authors: Brady David
Published: April 2019

There has been a lack of debate between and frameworks for theories of the causes of poverty. This article proposes that most theories of poverty can be productively categorized into three broader families of theories: behavioral, structural, and political. Behavioral theories concentrate on individual behaviors as driven by incentives and culture. Structural theories emphasize the demographic and labor market context, which causes both behavior and poverty. Political theories contend that power and institutions cause policy, which causes poverty and moderates the relationship between behavior and poverty. I review each theory's arguments, contributions, and challenges. Furthermore, I explain how to integrate, classify studies into, and distinguish between theories. Ultimately, I argue that poverty research would benefit from more explicit theory and theoretical debate, as well as greater interdisciplinarity and integration between studies of the United States, rich democracies, and developing countries.
LncRNA BLACAT1 May Serve as a Prognostic Predictor in Cancer: Evidence from a Meta-Analysis
Authors: Lu Hongyan , Liu Haoran , Yang Xiaoqi , Ye Tao , Lv Peng , Wu Xiaoliang , Ye Zhangqun
Published: April 2019

Background. As a newly discovered lncRNA, bladder cancer-associated transcript 1 (BLACAT1) has been reported to correlate with poor clinical outcomes in several different cancers. This study aimed to evaluate its generalized predictive value for cancer prognosis. Materials and Methods. We thoroughly searched PubMed, Embase, and Web of Science databases for eligible studies published until November 11, 2018, in which the relationship between BLACAT1 expression and cancer prognosis was explored. The analyses were performed using Review Manager Version 5.3 and Stata SE 12.0. The primary endpoints included overall survival (OS), pathological characteristics (TNM stage and tumor grade), lymph node metastasis (LNM), and distant metastasis. Results. Ten studies containing 861 patients with 7 different cancerous diseases were eventually included. The results demonstrated that patients with high lncRNA BLACAT1 expression had a significantly shorter OS (HR: 1.82, 95% CI: 1.44-2.30, p < 0.00001) than patients with low lncRNA BLACAT1 expression. Moreover, elevated BLACAT1 expression was significantly associated with advanced TNM stage (OR: 2.29, 95% CI: 1.15-4.56, p = 0.005), high tumor grade (OR: 1.67, 95% CI: 1.11-2.53, p = 0.01), and lymph node metastasis (OR: 2.53, 95% CI: 1.80-3.57, p < 0.00001). Meanwhile, the expression of BLACAT1 had no significant association with age (p = 0.92), gender (p = 0.55), and smoking (p = 0.62). Conclusion. High expression of lncRNA BLACAT1 may predict a poor prognosis in OS, TNM stage, tumor grade, and LNM. Its predictive roles were not significantly affected by age, gender, or smoking. Therefore, lncRNA BLACAT1 may serve as a promising predictor in cancer prognosis.
Secure Multiparty Computation and Trusted Hardware: Examining Adoption Challenges and Opportunities
Authors: Choi Joseph I. , Butler Kevin R. B.
Published: April 2019

When two or more parties need to compute a common result while safeguarding their sensitive inputs, they use secure multiparty computation (SMC) techniques such as garbled circuits. The traditional enabler of SMC is cryptography, but the significant number of cryptographic operations required results in these techniques being impractical for most real-time, online computations. Trusted execution environments (TEEs) provide hardware-enforced isolation of code and data in use, making them promising candidates for making SMC more tractable. This paper revisits the history of improvements to SMC over the years and considers the possibility of coupling trusted hardware with SMC. This paper also addresses three open challenges: (1) defeating malicious adversaries, (2) mobile-friendly TEE-supported SMC, and (3) a more general coupling of trusted hardware and privacy-preserving computation.
Biological Amnion Prevents Flexor Tendon Adhesion in Zone II: A Controlled, Multicentre Clinical Trial
Authors: Liu Chunjie , Bai Jiangbo , Yu Kunlun , Liu Guoli , Tian Siyu , Tian Dehu
Published: April 2019

Introduction. Tendon adhesion to surrounding tissues is the most common complication reported after tendon repair. To date, effective solutions to prevent tendon injury are still lacking. Materials and Methods. A total of 89 patients with flexor tendon injury in zone II were recruited. The patients were divided into a control group, a poly-DL-lactic acid (PDLLA) group, and an amnion group according to the different tendon treatments applied. The control group was not subjected to other treatments. PDLLA and bioamniotic membranes were, respectively, used to wrap broken ends in the PDLLA and amnion membrane groups. The patients were followed at 1, 2, 3, 6, and 12 months after surgery and the ranges of active flexion and extension lag in the proximal and distal interphalangeal joints were evaluated. Results. The means of total active ranges of motion of the interphalangeal joints (excluding rupture cases) in the PDLLA and amnion groups did not significantly differ between each other but significantly differed from that of the control group. Statistical analysis showed a significant difference in the clinical grades of the outcomes among the control, PDLLA, and amnion groups. The incidence of complications in the control and PDLLA groups was found to be significantly higher than that in the amniotic membrane group; no significant difference was observed between the control and PDLLA groups. Conclusion. In this study, freeze-dried amniotic membrane transplantation was applied to promote healing of the flexor tendon in zone II and prevent adhesion. This technique presents a new method to solve the issue of tendon adhesion after repair. Clinical Trial Registration. The trial was registered by identifier ChiCTR1900021769.
Potentiometric Stripping Analysis of Cadmium and Lead with Constant Inverse Current in the Analytical Step Using an Open Tubular Mercury-Coated Glassy Carbon Electrode
Authors: Suturović Zvonimir J. , Kravić Snežana Ž. , Stojanović Zorica S. , Đurović Ana D. , Brezo-Borjan Tanja Ž.
Published: April 2019

The most important experimental parameters of the flow potentiometric stripping analysis (PSA) with oxygen as an oxidant were investigated and optimised. A simple, homemade flow system consisting of glassy carbon tubes, which served as a working and auxiliary electrode, was used. By applying a rest period before the stripping step (the flow stop mode) and by imposing a constant reductive current simultaneously with the interruption of potentiostatic control, significant increase of the flow PSA sensitivity was achieved. In the determination of cadmium and lead, quantitation limits of 0.11 and 0.82 μg/L were obtained. The precision of the method was evaluated in terms of repeatability and reproducibility, with values of relative standard deviation lower than 4.0% for cadmium and 4.2% for lead. This modified technique was applied for simultaneous determination of cadmium and lead in milk, after a simple pretreatment of the samples by dilution and acidification. The method accuracy was confirmed by analysing the certified reference material of skimmed milk powder (ERM-BD151).
Modulation of Corneal FAK/PI3K/Akt Signaling Expression and of Metalloproteinase-2 and Metalloproteinase-9 during the Development of Herpes Simplex Keratitis
Authors: Ke Lan , Yang Yanning , Li Jing wei , Wang Bo , Wang Yujing , Yang Wanju , Yan Jiangbo
Published: April 2019

To observe the expression of MMP-2 and MMP-9 and of the FAK/PI3K/Akt signaling pathway in HSK. Fifty BALB/c mice were infected to establish the model and killed on days 0, 2, 7, 14, and 28. The cornea samples were prepared, respectively. Slit lamp examination, immunofluorescence staining, reverse transcription PCR, and Western blot were used to detect the index. After HSV-1 infection, different degrees of epithelial or stromal damage and corneal opacity were observed. Immunofluorescence staining showed that the expressions of MMP-2 and MMP-9 at different levels of corneal tissue were observed on the 0d, 2d, 7d, 14d, and 28d. Compared with 0d, the relative expression levels of MMP-2 and MMP-9 mRNA at 2d, 7d, 14d, and 28d were significantly increased (all P< 0.05). Compared with 14d, the relative expression of MMP-2 and MMP-9 mRNA decreased on the 2d, 7d, and 28d (all P< 0.05). Western blot showed that the protein expressions of p-FAK, p-PI3K, p-Akt, MMP-2, and MMP-9 at 2d, 14d, and 28d were all significantly higher than 0d (all P< 0.05). At 14 d, the expressions of p-FAK, p-PI3K, p-Akt, and MMP-2 were significantly higher than those at 2d, 7d, and 28d (all P< 0.05). The protein expression of FAK, PI3K, and Akt in corneal of mice in each time period had no significant (all P> 0.05). These data suggest that FAK/PI3K/Akt signaling pathway and MMP-2 and MMP-9 may be involved in the development of HSK.