nils-herrmann/clean_scirepeval huggingface dataset:
Multi user shared access in massive machine type communication systems via superimposed waveforms
Venue: Phys. Commun.
Year: 2019

With the development of the mobile internet and Internet of things (IoT) the number of connected devices is increasing exponentially. Services that are required to support a large number of users, such as massive machine type communications (mMTC) suffer from limited radio resources. Non orthogonal multiple access (NOMA) is a promising access scheme for mMTC systems to meet the massive connectivity and heterogeneous network demands with low latency and high throughput. Motivated by the problems of an mMTC system, we propose a novel waveform that superimposes the users on the same resources with a family of orthogonal functions. The proposed model, which we call superimposed multi user shared access (MUSA) is able to support more users than the conventional MUSA scheme. Furthermore, we combine the superimposed MUSA scheme with generalized frequency division multiplexing (GFDM) technique to achieve low latency with high overloading ratio. The performances of the superimposed MUSA and superimposed MUSA with GFDM are investigated over Rayleigh fading channel model. It is shown that the overloading ratio with three layers of superimposed orthogonal functions becomes three times that of the conventional MUSA scheme with low latency by using the GFDM structure.
A Typology of Perceived Triggers for End User Security and Privacy Behaviors
Venue: SOUPS USENIX Security Symposium
Year: 2019

What triggers end user security and privacy (S&P) behaviors? How do those triggers vary across individuals? When and how do people share their S&P behavior changes? Prior work, in usable security and persuasive design, suggests that answering these questions is critical if we are to design systems that encourage pro S&P behaviors. Accordingly, we asked 852 online survey respondents about their most recent S&P behaviors (n 1947) what led up to those behaviors, and if they shared those behaviors. We found that social "triggers" where people interacted with or observed others, were most common, followed by proactive triggers, where people acted absent of an external stimulus, and lastly by forced triggers, where people were forced to act. People from different age groups, nationalities, and levels of security behavioral intention (SBI) all varied in which triggers were dominant. Most importantly, people with low to medium SBI most commonly reported social triggers. Furthermore, participants were four times more likely to share their behavior changes with others when they, themselves, reported a social trigger.
GAN based synthetic brain MR image generation
Venue: 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)
Year: 2018

In medical imaging, it remains a challenging and valuable goal how to generate realistic medical images completely different from the original ones; the obtained synthetic images would improve diagnostic reliability, allowing for data augmentation in computer assisted diagnosis as well as physician training. In this paper, we focus on generating synthetic multi sequence brain Magnetic Resonance (MR) images using Generative Adversarial Networks (GANs) This involves difficulties mainly due to low contrast MR images, strong consistency in brain anatomy, and intra sequence variability. Our novel realistic medical image generation approach shows that GANs can generate 128 kh 128 brain MR images avoiding artifacts. In our preliminary validation, even an expert physician was unable to accurately distinguish the synthetic images from the real samples in the Visual Turing Test.
On Learning Cluster Coefficient of Private Networks
Venue: ASONAM 2012
Year: 2012

Enabling accurate analysis of social network data while preserving differential privacy has been challenging since graph features such as clustering coefficient or modularity often have high sensitivity, which is different from traditional aggregate functions (e.g. count and sum) on tabular data. In this paper, we treat a graph statistics as a function f and develop a divide and conquer approach to enforce differential privacy. The basic procedure of this approach is to first decompose the target computation f into several less complex unit computations f1, fm connected by basic mathematical operations (e.g. addition, subtraction, multiplication, division) then perturb the output of each fi with Laplace noise derived from its own sensitivity value and the distributed privacy threshold i, and finally combine those perturbed fi as the perturbed output of computation f. We examine how various operations affect the accuracy of complex computations. When unit computations have large global sensitivity values, we enforce the differential privacy by calibrating noise based on the smooth sensitivity, rather than the global sensitivity. By doing this, we achieve the strict differential privacy guarantee with smaller magnitude noise. We illustrate our approach by using clustering coefficient, which is a popular statistics used in social network analysis. Empirical evaluations show the developed divide and conquer approach outperforms the direct approach.
Transfer Learning for Activity Recognition in Mobile Health
Venue: ArXiv
Year: 2020

While activity recognition from inertial sensors holds potential for mobile health, differences in sensing platforms and user movement patterns cause performance degradation. Aiming to address these challenges, we propose a transfer learning framework, TransFall, for sensor based activity recognition. TransFall's design contains a two tier data transformation, a label estimation layer, and a model generation layer to recognize activities for the new scenario. We validate TransFall analytically and empirically.
The rolling circle amplification and next generation sequencing approaches reveal genome wide diversity of Kenyan cassava mosaic geminivirus
Year: 2016

Rolling circle amplification is a simple approach of enriching populations of single stranded DNA plant begomovirus genomes (genus, Begomovirus; family, Geminiviridae) This is an innovative approach that utilizes the robustness of the bacteriophage phi29 DNA polymerase used in circle amplification, together with deep sequencing using Illumina Miseq and bioinformatics to assess population diversity of begomoviruses in naturally infected cassava. The approach is suitable for detecting rare members in a population in begomoviral populations in situation where mixtures of isolates, strains, and multiple species occur. The main objectives were to increase the sensitivity of detection of next generation sequencing by enriching it using rolling circle amplification then determination of the diversity of the cassava mosaic geminivirus. This was done by total nucleic acids isolated from sy mptomatic, field cassava infected plants, then using rolling circle amplification to multiply the less abundant viral sequences. Enriched and non enriched virus libraries were subjected to deep sequencing using Illumina Miseq. Using bioinformatic CLC Genomics 5.5.1 software programs the quality assessment of reads and contig assembly of viral sequences. This was done through de novo and reference guided assembly. The identity and diversities of the begomoviral sequences were compared with sequences in Sanger sequencing of viral components deposited in the NCBI Gene Bank. In this study we have demonstrated that RCA increases the chances of detecting the virus by approximately 10 to 1000 fold and wide genome diversity of cassava mosaic geminivirus in various cassava growing zones in Kenya were detected. In conclusion, this approach described herein is simple and will enhance the exploration of begomovirus diversities from cassava infected plants, irrespective of their viral abundance. This will make it possible for routine screening of field samples as the cost of deep sequencing NGS is decreasing and the advances of bioinformatic software development become enhanced. This is the first report of the RCA Illumina NGS approach to explore cassava infected with begomoviruses under field conditions and their diversities. Key words Illumina Miseq sequencing, geminivirus, ssDNA viruses, viral sequence enrichment, de novo genome assembly, rolling cycle amplification (RCA)
Recent advances in developing organic electrode materials for multivalent rechargeable batteries
Year: 2020

Due to the low cost and abundance of multivalent metallic resources (Mg/Al/Zn/Ca) multivalent rechargeable batteries (MRBs) are promising alternatives to Li ion and Pb acid batteries for grid scale stationary energy storage applications. However, the high performance of inorganic electrode materials in Li ion batteries does not extend to MRBs, because the high charge density of multivalent cations dramatically reduces their diffusivity in the crystal lattice of inorganic materials. To achieve high performance MRBs, organic electrode materials (OEMs) with abundant structural diversity and high structural tunability offer opportunities. This review presents an overview of the state of the art OEMs in MRBs, including non aqueous rechargeable Mg/Al/Zn and aqueous rechargeable Mg/Al/Zn/Ca batteries. The advantages, challenges, development, mechanism, structure, and performance of OEMs in MRBs are discussed in detail. To provide a comprehensive and thorough understanding of OEMs in MRBs, the correlation between molecular structure and electrochemical behavior is also summarized and discussed. This review offers insights for the rational structure design and performance optimization of advanced OEMs in MRBs.
CAR T cell therapy: Full speed ahead
Venue: Hematological oncology
Year: 2019

Chimeric antigen receptor (CAR) T cell therapy has dramatically shifted the landscape of treatment for lymphoid malignancies, especially diffuse large B cell lymphoma (DLBCL) and acute lymphoblastic leukemia (ALL) However, there continue to be significant limitations of this therapy, such as incomplete or nonsustained responses and severe toxicities in a subset of patients. Furthermore, expanding the role of CAR T cell therapy to new disease types is an important next step. In this review, we will highlight landmark trials for anti CD19 CAR T cells and first in human trials of novel CARs, as well as discuss promising innovative CAR designs that are still undergoing preclinical development. Lastly, we will discuss toxicity and mechanisms of CAR T cell resistance and failure, as well as potential future treatment approaches to these common issues.
Formation Control of UAVs and Mobile Robots Using Self organized Communication Topologies
Year: 2020

Formation control in a robot swarm targets the overall swarm shape and relative positions of individual robots during navigation. Existing approaches often use a global reference or have limited topology flexibility. We propose a novel approach without these constraints, by extending the concept of 'mergeable nervous systems' to establish distributed asymmetric control via a self organized wireless communication network. In simulated experiments with UAVs and mobile robots, we present a proof of concept for three sub tasks of formation control: formation establishment, maintenance during motion, and deformation. We also assess the fault tolerance and scalability of our approach.
Ficusdeltoidea (Jack) Moraceae Varietal Identification Using Statistical Recognition Approach
Year: 2017

Plant species identification is one of important application in pattern recognition. Selection of relevant features for classification is a classical problem in statistical pattern recognition and data mining. There are two main branches in solving this problem which is by using feature selection or feature extraction. Currently, in statistical plant species recognition domain, researchers focus mainly on providing an automatic system using feature extraction method such as Principal Component Analysis. This paper presents a hybrid of filter and wrapper in feature selection as well as an empirical comparison of feature selection wrapper method using Sequential Forward Selection and feature extraction method using Principal Component Analysis on a benchmark of 420 images of Ficus deltoidea leaf with 6 varieties. At first, the leaf images are processed using image pre processing techniques. Then, 23 leaf features are extracted such as shape, texture and vein. Finally, in classification process, different feature selection and feature extraction techniques are computed using Support Vector Machine and Nearest Neighbor classifiers. The recognition results reveal that a combination of filter and wrapper approach in feature selection outperformed the other approaches for F. deltoidea varietal identification.
Topological Properties of Multigranular Rough sets on Fuzzy Approximation Spaces
Venue: Int. J. Rough Sets Data Anal.
Year: 2019

One of the extensions of the basic rough set model introduced by Pawlak in 1982 is the notion of rough sets on fuzzy approximation spaces. It is based upon a fuzzy proximity relation defined over a Universe. As is well known, an equivalence relation provides a granularization of the universe on which it is defined. However, a single relation defines only single granularization and as such to handle multiple granularity over a universe simultaneously, two notions of multigranulations have been introduced. These are the optimistic and pessimistic multigranulation. The notion of multigranulation over fuzzy approximation spaces were introduced recently in 2018. Topological properties of rough sets are an important characteristic, which along with accuracy measure forms the two facets of rough set application as mentioned by Pawlak. In this article, the authors introduce the concept of topological property of multigranular rough sets on fuzzy approximation spaces and study its properties.
Experimental Demonstration of Electromagnetically Induced Transparency in a Conductively Coupled Flexible Metamaterial with Cheap Aluminum Foil
Venue: Nanoscale Research Letters
Year: 2019

We propose a conductively coupled terahertz metallic metamaterial exhibiting analog of electromagnetically induced transparency (EIT) in which the bright and dark mode antennae interact via surface currents rather than near field coupling. Aluminum foil, which is very cheap and often used in food package, is used to fabricate our metamaterials. Thus, our metamaterials are also flexible metamaterials. In our design, aluminum bar resonators and aluminum split ring resonators (SRRs) are connected (rather than separated) in the form of a fork shaped structure. We conduct a numerical simulation and an experiment to analyze the mechanism of the proposed metamaterial. The surface current due to LSP resonance (bright mode) flows along different paths, and a potential difference is generated at the split gaps of the SRRs. Thus, an LC resonance (dark mode) is induced, and the bright mode is suppressed, resulting in EIT. The EIT like phenomenon exhibited by the metamaterial is induced by surface conducting currents, which may provide new ideas for the design of EIT metamaterials. Moreover, the process of fabricating microstructures on flexible substrates can provide a reference for producing flexible microstructures in the future.
Low Density Insulation of Inorganic Powder with Supporting Structure Using Expended Perlite, its Manufacturing Method and Making Machine
Year: 2012

The invention method of producing low density inorganic powder insulating material having a low density molded structure with a binder (binder) expansion peorayiteu (perlite) without the use of and relates to its molding machine, particularly by using the expansion peorayiteu the irregularly shaped glass particles to evenly distribute the peorayiteu particle shape for improved molding strength at low density to form a structural frame (framework) between synthetic silica according to the low density and increased specific surface area (conduction and convection block) is to generate the heat conductivity reduction. Through In low specific gravity and the specific surface area is large laminated material to compression molding, or compression roller with a molding machine with a plate and a filter of perforated structure mounted to remove the pressure and the air in the molded product generated upon compression of the use of raw material in the production method of the heat insulating material It made of a laminated material, by compressed economical and physical properties to the preparation method thereof and a molding machine of low density inorganic insulator powder having a forming structure using a high expansion peorayiteu.
A developed nearly analytic discrete method for forward modeling in the frequency domain
Year: 2018

High efficiency forward modeling methods play a fundamental role in full waveform inversion (FWI) In this paper, the developed nearly analytic discrete (DNAD) method is proposed to accelerate frequency domain forward modeling processes. We first derive the discretization of frequency domain wave equations via numerical schemes based on the nearly analytic discrete (NAD) method to obtain a linear system. The coefficients of numerical stencils are optimized to make the linear system easier to solve and to minimize computing time. Wavefield simulation and numerical dispersion analysis are performed to compare the numerical behavior of DNAD method with that of the conventional NAD method. The results demonstrate the superiority of our proposed method. Finally, the DNAD method is implemented in frequency domain FWI, and high resolution inverse results are obtained.
Thickness Dependence of Domain Wall Patterns in BiFeO3 Thin Films
Year: 2015

Unique properties of domain walls in ferroelectrics have been recently discovered but methods of their controlled engineering remain underdeveloped. Here we investigate the domain structure of Bi0.9La0.1FeO3 epitaxial thin films with piezoelectric force microscopy and transmission electron microscopy. We show that with increasing Bi0.9La0.1FeO3 thickness, a transition from randomly oriented 71deg domain walls to 109deg domain walls stripe occurs. At intermediate thicknesses, 71deg and 109deg domain walls coexist together with non ferroelastic 180deg domain walls. TEM cross section images show complex domain structure due to the interplay between electrostatic constrains imposed by the SrRuO3 electrode and mechanical constrains imposed by the DyScO3 substrate.
TEXT SUMMARIZATION EVALUATION BASED ON SENTENCE SCORING AND CLUSTERING
Year: 2018

A summary system comprises a subtraction of text document contents to generate a new form that delivers the essentials contents of the text documents. Due to the hassle of documents overload, getting the right information and effectivelydeveloped summaries are essential in retrieving information. Reduction of information allows users to find the information needed quickly without the need to read the full document collection. The purpose of this paper is to evaluate the performance of sentence scoring and clustering in the process of generating text summaries. Adaptive Neuro Fuzzy Inference System (ANFIS) has been used to score the sentences and clustering were performed using K Means and Hierarchical Clustering (HC) approaches. From the experimental findings, it was found that no improvements in the quality of the generated summaries obtained by simply performing clustering. This paper proposes some recommendations to improve text summarization.
Use of Evidence Based Decision Making in Comprehensive Dental Treatment of a Patient with Meth Mouth A Case Report.
Year: 2017

This case report illustrates the use of evidence based practice in formulating a comprehensive dental treatment plan for a patient who presented himself with signs of oral health debilitation accompanying methamphetamine (MA) abuse called "meth mouth" with the goal of providing dental care practitioners in Saudi Arabia with an insight into the global problem of MA abuse and its impact on oral health.  This report documents the case of a 22 year old male patient who reported to the clinic with rampant caries caused due to MA abuse exacerbated by poor oral hygiene and smoking habit.  The treatment plan of this present case was formulated on the lines of the evidence based dentistry approach. A clinical question was composed based on the Problem, Intervention, Comparison, and Outcome format to identify past studies and case reports on meth mouth. A standard search was conducted on PubMed Central. Standard guidelines on the treatment of meth mouth were extracted from the Web site of the American Dental Association.  A total of 2 systematic reviews, 7 review articles, 4 epidemiologic studies, 5 case reports, and 1 American Dental Association guideline were found.  Accelerated dental decay leading to rampant caries in young and middle aged adults is a characteristic oral finding in MA abusers. The most important factor that affects the prognosis of dental care is complete cessation of MA use by the patient.
Traffic type Assignment for TSN based Mixed criticality Cyber physical Systems
Venue: ACM Trans. Cyber Phys. Syst.
Year: 2020

This article focuses on mixed criticality applications with functions that have different timing requirements, i.e. hard real time (HRT) soft real time (SRT) and functions that are not time critical (NC) The applications are implemented on distributed cyber physical systems that use IEEE Time sensitive Networking (TSN) TSN is the product of an IEEE effort to bring deterministic real time capabilities to IEEE 802.3 Ethernet. TSN supports the convergence of multiple traffic types, i.e. critical, real time, and regular "best effort" traffic within a single network: Time triggered (TT) where the messages are transmitted based on static schedule tables, Audio video Bridging (AVB) for dynamically scheduled messages with a guaranteed bandwidth and bounded delays, and Best Effort (BE) for which no timing guarantees are provided. The HRT messages have deadlines, whereas we capture the quality of service for the SRT messages using "utility functions." Given the network topology, the set of application messages, including their routing, and the set of available AVB classes, we are interested in determining the traffic type of each message, such that all the HRT messages are schedulable and the total utility for the SRT messages is maximized. We propose a Tabu Search based metaheuristic to solve this optimization problem. The proposed proof of concept tool has been evaluated using several benchmarks, including two realistic test cases.
An ocean view of African climate change during the last 620,000 years
Year: 2020

It has been a long standing and passionately discussed hypothesis that important developments in human origins over the last 6 8 Ma coincided with environmental change, including cooling, drying, and wider climate fluctuations. However, testing these hypotheses is difficult as both high resolution climate records and fossil records of early human populations are often incomplete and poorly dated. Thus, to better understand the role that past African climate changes might have played in the evolution and dispersal of our ancestors, in particular Homo sapiens, we have developed a ~620,000 year record of humidity variability from the Chew Bahir basin situated in southern Ethiopia. This 293 m composite lacustrine sediment succession was compiled from two parallel cores HSPDP CHB14 2A and 2B collected as part of the Hominin Sites and Paleolakes Drilling Project (HSPDP) in 2014. We utilized the log(K/Zr) ratio determined by micro X ray fluorescence (mXRF) scanning to analyse past moisture changes in the Chew Bahir basin. By placing our results into the existing framework of marine and terrestrial proxy records from various parts of Africa and its surrounding oceans we document a close coupling between the spatio temporal distribution of African rainfall and sea surface temperature changes in the Indo Pacific realm on orbital time scales. We argue that this coupling is facilitated by shifts in the Walker and Hadley circulations in response to insolation variability at the same time.