nils-herrmann/clean_scirepeval huggingface dataset:
3D visual SLAM with a Time of Flight camera
Venue: 2015 IEEE Workshop on Signal Processing Systems (SiPS)
Year: 2015

Location and mapping are fundamental problems for a mobile robot to implement a series of high level applications. Traditional solutions to Simultaneous Location and Mapping (SLAM) are probabilistic reasoning. This paper proposes an analytic solution to 3D visual SLAM with a Time of Flight (TOF) camera. According to the visual registration, 3D visual SLAM problem is decomposed into such steps as environment sensing, data matching, motion estimation, as well as location update and registration of new landmarks. First, TOF range camera enables the robot to capture images of distance and intensity of a scene. Scale Invariant feature transform (SIFT) algorithms for visual feature extraction is applied to the captured intensity images. These visual features combined with the corresponding distance information give a full measurement of 3D landmarks. Then, the process of data association and match is developed through SIFT and the Iterative Closest Point (ICP) to minimize the relative and global error in SLAM process, while obtaining motion estimation. Finally, based on the visual theory of structure from motion (SFM) an analytic solution to location and mapping is presented to 3D Visual SLAM, instead of conventional probabilistic reasoning. We provide 3D visual SLAM experimental results from simulation and the indoor environment. It turns out that the proposed scheme is feasible.
Review of the Opus Codec in a WebRTC Scenario for Audio and Speech Communication
Venue: SPECOM
Year: 2015

The Internet Engineering Task Force (IETF) the open Internet standards development body considers the Opus codec as a highly versatile audio codec for interactive voice and music transmission. In this review we survey the dynamic functioning of the Opus codec within a Web Real Time Communication (WebRTC) framework based on the Google Chrome browser. The codec behavior and the effectively utilized features during the active communication process are tested and analyzed under various testing conditions. In the experiments, we verify the Opus performance and interactivity. Relevant codec parameters can easily be adapted in application development. In addition, WebRTC framework coded speech achieves a similar MOS assessment compared to stand alone Opus coding.
Non invasive Ultrasonographic Score for Assessment of the Severity of Inflammatory Bowel Disease.
Venue: Ultrasound in medicine biology
Year: 2020

Intestinal ultrasound and shear wave elastography have gained increasing interest because of their promising results in the assessment of inflammatory bowel disease. The aim of this study was to find an ultrasonographic score to replace invasive endoscopic procedures for the management of these patients. The score includes ultrasound parameters that correlate well with clinical severity scales and inflammatory markers: bowel wall thickness, the Limberg score, disease extension and acoustic radiation force impulse measurements. The score proved to be well correlated with the Harvey Bradshaw Index, the Mayo score, C reactive protein and fecal calprotectin. For Crohn's disease, a cutoff value of 8 points could identify active disease with 81.81% sensitivity and 83% specificity, while for ulcerative colitis, a cutoff value of 7 points could discriminate between remission and relapse with 86.85% sensitivity and 94% specificity. In conclusion, our ultrasonographic score can differentiate relapse from remission in inflammatory bowel disease.
Learning From Fails in Crisis Management: Case of Stress Impact
Venue: 2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC FSKD)
Year: 2018

A crisis is a complex situation, which actors have some difficulties to manage it. They are under stress to deal with problems that they cannot predict consequences. The human conditions (familial and life) and, the influence of the environment (politic, economic, media) pushes the actors to lose control of the crisis situation. The question we face in this paper is: "is it possible to predict fails action under the impact of the stress in this type of situation and to correct it?" Our main hypothesis to answer is representing fails actions using the experience feedback and the knowledge management. To model the crisis management as systemic system emphasizing regulation loops, and the collaboration activity by showing the dimension of the communication, coordination, and cooperation. This modeling is illustrated on a terrorist attack situation in Algeria. To predict actions consequence of the stress and their corrective, Fuzzy set principle is adopted, based on experience feedback and situations modeling.
Knowledge about Hepatitis B and Vaccination Status among Healthcare Workers in a Tertiary Care Teaching Hospital, Mysuru.
Year: 2016

Hepatitis B is a major infectious disease of mankind. It is the most common cause of chronic hepatitis, liver cirrhosis and hepato cellular carcinoma worldwide. Health professionals are at the most risk. Vaccination against Hepatitis B can prevent this deadly disease.  This study was conducted to assess the knowledge and status of Hepatitis B vaccination among technicians, nurses and group D workers.  A cross sectional study was conducted among 150 members and the data was analyzed by cross tabulation and Chi square tests.  The Knowledge regarding hepatitis b among group D workers was found to be low with a mean score of 2.66. The attitude and practices to prevent transmission of Hepatitis B infection was low among group D workers when compared to nurses and technicians in the hospital.  The, Knowledge, Practices and vaccination status among group D workers was poor when compared to technicians and nurses. A considerable amount of improvement in practice is required among health care workers to prevent hepatitis B infection.
Structure and Function of the Nicotinic Arm of Acetylcholine Regulatory Axis in Human Leukemic T Cells
Venue: International journal of immunopathology and pharmacology
Year: 2009

Although acetylcholine (ACh) is widely known as a neurotransmitter, it also functions as a local humoral factor translating environmental stimuli into alterations in T cell development and function. The cholinergic components present in neurons are expressed in T cells where they constitute an independent cholinergic system. Both non immunologic and immunologic stimulations can alter expression and function of cholinergic elements in T cells. Recent studies have convincingly demonstrated regulation of immune system by auto/paracrine ACh, which provides a basis for development of new immunomodulatory therapies with nicotinic agonists. The purpose of our research is to integrate information about the structure and activity of the ACh regulatory axis with the phenotypic and functional alterations of T cells during their development and commitment. In this study, we used the ACh producing human leukemic T cell line CCRF CEM (CEM) to investigate auto/paracrine mechanisms of T cell regulation through the nicotinic class of ACh receptors (nAChRs) The intact CEM expressed a3, a5, a6, a7, a9, b2 and b4 nAChR subunits. Stimulation of CEM with 10 mg/ml of phytohemagglutinin (PHA) for 16 h upregulated expression of the a3, a5, a7, a9 and b2 and downregulated that of a6 and b4 subunits, indicating that TCR activation leads to overexpression of high Ca2+ permeable ACh gated ion channels. Activation of a7 and a3 nAChRs predominantly abrogated PHA dependent upregulation of the pro inflammatory cytokine TNF a and IFN g receptors, respectively, at the mRNA and protein levels. Signaling through a7 and a3 nAChRs also significantly (p<0.05) altered expression of the cell state regulators p21 and Bcl 2, respectively, suggesting that downregulation of inflammation via nAChRs includes effects on the T cell cycle progression and apoptosis. These findings indicate that constant stimulation of a7 and a3 nAChRs by endogenously released ACh controls T cell activation and that signaling downstream of distinct nAChR subtypes targets specific inflammatory and cell cycle genes. Learning the cholinergic pharmacology of inflammation should allow to regulate specific types of immune reactions by selectively activating or blocking the types of nAChRs expressed by the immune cells mediating specific immune reactions.
Multi Adversarial Partial Transfer Learning With Object Level Attention Mechanism for Unsupervised Remote Sensing Scene Classification
Venue: IEEE Access
Year: 2020

In recent years, deep learning methods have been widely applied in remote sensing image classification tasks, providing valuable information for natural monitoring and spatial planning. In an actual application like this, acquiring massive labeled data for deep convolutional networks is costly and difficult especially in the situation that the data sources are diverse and the requirements are changing. Transfer learning methods have already shown superior performance on exploiting domain invariance features in existing data for deep network based categorization tasks. However, the data imbalance between source and target domains may bring negative transfer and weaken the classifier's ability. Moreover, it is still a difficult problem to extract object level visual features among easy mixed categories. In this context, Multi adversarial Object level Attention Network (MOAN) is proposed for partial transfer learning and selecting useful features. On the one hand, we present an improved object level attention proposal network (OANet) for perceiving structural features of the main object in the picture, and weakening the unrelated regions. On the other hand, the extracted features are further enhanced by multi adversarial framework in order to promote positive transfer, selecting and mapping valuable cross domain features from shared categories and suppressing others. This adversarial learning module can also generate pseudo tags for the samples in target domain so as to perceive integral visual signals, similar to the process in source domain. In addition, virtual adversarial training method is introduced in MOAN so as to regularize the model and maintain stability. Experimental analyses show that our MOAN can significantly promote positive transfer and restrain negative transfer in unsupervised classification problems. MOAN has good performances such as higher accuracies and lower loss values on several benchmark data sets.
Coexistence Performance of IEEE 802.15.4 Wireless Sensor Networks Under IEEE 802.11b/g Interference
Venue: Wirel. Pers. Commun.
Year: 2013

are often collocated, causing a coexistence issue since these networks share the same 2.4GHz Industrial, Scientific, and Medical band. In our previous work, we built a coexistence model of IEEE 802.15.4 WSNs and IEEE 802.11b/g WLANs. By identifying three distinct coexistence regions, the model explained the coexistence behavior of IEEE 802.15.4 WSNs and IEEE 802.11b/g WLANs, and the model was experimentally validated. In this paper, we improve the model by introducing two important implementation factors: the transceiver's Rx to Tx turnaround time and the Clear Channel Assessment partial detection effect. The enhanced model significantly improves the accuracy on explaining and predicting the coexistence performance of IEEE 802.15.4 WSNs in the real life environment. Furthermore, under the guidance of the model, the coexistence performance of IEEE 802.15.4 WSNs is extensively investigated in various coexistence scenarios by analysis, simulation and experiments, respectively. The simulation and experimental results agree with our analysis. The coexistence model is believed to be helpful in resolving the coexistence issue.
Yin Pin Duan 1.34 mmYa Suo Tai Guang Chang De Shi Yan Zhi Bei
Year: 2018

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Three dimensional non stationary geometry based stochastic model for UAV MIMO Ricean fading channels
Venue: IET Commun.
Year: 2019

In this study, the authors propose a novel three dimensional (3D) non stationary geometry based stochastic model (GBSM) and the corresponding deterministic and stochastic simulation models for non isotropic unmanned aerial vehicle (UAV) multiple input multiple output (MIMO) Ricean fading channels. The proposed GBSM employs a two cylinder model, where the signal is a superposition of line of sight component, single bounced rays around the UAV, single bounced rays around the ground station (GS) single bounced rays on the ground, and double bounced rays. The non stationarity is reflected on the time varying angles of departure and angles of arrival. Since the authors consider the GS to be mobile, the proposed 3D GBSM is general and suitable for UAV aided vehicular communication scenarios. Based on the proposed model, some important channel statistical properties are derived and thoroughly investigated, including the space time correlation function, Doppler power spectral density, envelope level crossing rate and average fade duration. Moreover, the proposed model has the ability to investigate the influence of some unique UAV related parameters on channel characteristics and non stationarity. Finally, excellent agreement is achieved between the reference model and simulation models, demonstrating the feasibility of simulation models as well as the correctness of theoretical derivations.
Stock Price Index and Exchange Rate Nexus in African Markets
Year: 2017

This paper examines the relationship between stock price index and exchange rate in six African markets using monthly data for the period January 2007 to October 2015. A quantile regression approach is used. This methodology is shown to perform better than the ordinary least squares estimators, particularly when the conditional distribution is heterogeneous. Our empirical evidence reveals an interesting pattern in the association of these two financial markets in Africa, which shows that the negative relationship between stock and foreign exchange markets is more apparent when exchange rates are extremely low or high. The negative relationship between the two variables is in line with the portfolio balance effect.
Power and performance analysis of scalable photonic networks for exascale architecture
Venue: 2015 Sixth International Green and Sustainable Computing Conference (IGSC)
Year: 2015

As bandwidth demands from high performance computing (HPC) applications have increased, scalable topology and power efficiency of network technology are becoming critical parameters for exascale design. Dragonfly topology provides low diameter for exascale networks however, fewer global links reduce the bisection bandwidth while high radix routers increase the router complexity and area overhead. Further, performance/watt delivered by metallic interconnects significantly increases the power consumed by the network. In this paper, we propose multiple level topologies that utilize scalable HPC topologies such as k ary n cube, flattened butterfly and dragonfly for intra cabinet and inter cabinet levels that can lead to higher bisection, manageable radix, and reduced link costs, although at higher packet latency due to increased diameter. As photonic technology offers higher bandwidth density, better power efficiency, and higher performance/watt, our proposed exascale network is designed with photonic transceivers such as vertical cavity surface emitting lasers (VCSELs) and photodiodes, and complementary metal oxide semiconductor (CMOS) routers. Our analytical and simulation studies show that multiple level topologies can achieve 10 15% more throughput while consuming 40% less power when compared to single level topologies, and VCSEL based transceivers can deliver the injection bandwidth of 256 GB/sec/direction while consuming 2 3MW in an exascale systems.
Providers' perspectives on inbound medical tourism in Central America and the Caribbean: factors driving and inhibiting sector development and their health equity implications.
Venue: Global health action
Year: 2016

Many governments and health care providers worldwide are enthusiastic to develop medical tourism as a service export. Despite the popularity of this policy uptake, there is relatively little known about the specific local factors prospectively motivating and informing development of this sector.  To identify common social, economic, and health system factors shaping the development of medical tourism in three Central American and Caribbean countries and their health equity implications.  In depth, semi structured interviews were conducted in Mexico, Guatemala, and Barbados with 150 health system stakeholders. Participants were recruited from private and public sectors working in various fields: trade and economic development, health services delivery, training and administration, and civil society. Transcribed interviews were coded using qualitative data management software, and thematic analysis was used to identify cross cutting issues regarding the drivers and inhibitors of medical tourism development.  Four common drivers of medical tourism development were identified: 1) unused capacity in existing private hospitals, 2) international portability of health insurance, vis a vis international hospital accreditation, 3) internationally trained physicians as both marketable assets and industry entrepreneurs, and 4) promotion of medical tourism by public export development corporations. Three common inhibitors for the development of the sector were also identified: 1) the high expense of market entry, 2) poor sector wide planning, and 3) structural socio economic issues such as insecurity or relatively high business costs and financial risks.  There are shared factors shaping the development of medical tourism in Central America and the Caribbean that help explain why it is being pursued by many hospitals and governments in the region. Development of the sector is primarily being driven by public investment promotion agencies and the private health sector seeking economic benefits with limited consideration and planning for the health equity concerns medical tourism raises.
Towards cross modal organ translation and segmentation: A cycle and shape consistent generative adversarial network
Venue: Medical Image Anal.
Year: 2019

HighlightsThis paper shows extensive experiments to validate our method, including CT and MRI translation for pancreas segmentation and domain adaptation for mammogram X rays for breast lesion segmentation.This paper validates our method using a variety of advanced segmentation networks and show that our method performs generally well and consistently boosts medical 2D/3D image segmentation performance.This paper systemically analyzes the effect of synthetic data on segmentation, with the goal to investigate the limitation of synthetic data, and inspire new scopes.   Synthesized medical images have several important applications. For instance, they can be used as an intermedium in cross modality image registration or used as augmented training samples to boost the generalization capability of a classifier. In this work, we propose a generic cross modality synthesis approach with the following targets: 1) synthesizing realistic looking 2D/3D images without needing paired training data, 2) ensuring consistent anatomical structures, which could be changed by geometric distortion in cross modality synthesis and 3) more importantly, improving volume segmentation by using synthetic data for modalities with limited training samples. We show that these goals can be achieved with an end to end 2D/3D convolutional neural network (CNN) composed of mutually beneficial generators and segmentors for image synthesis and segmentation tasks. The generators are trained with an adversarial loss, a cycle consistency loss, and also a shape consistency loss (supervised by segmentors) to reduce the geometric distortion. From the segmentation view, the segmentors are boosted by synthetic data from generators in an online manner. Generators and segmentors prompt each other alternatively in an end to end training fashion. We validate our proposed method on three datasets, including cardiovascular CT and magnetic resonance imaging (MRI) abdominal CT and MRI, and mammography X rays from different data domains, showing both tasks are beneficial to each other and coupling these two tasks results in better performance than solving them exclusively.
Understanding crowd conflict: social context, psychology and policing.
Venue: Current opinion in psychology
Year: 2020

This review draws together articles from a range of different disciplines to highlight the central role played by social context and policing in the dynamics of crowd conflict. Accordingly, the review highlights the importance and value of interdisciplinary dialogue both in attempts to advance theoretical understanding of the dynamics through which crowd events become violent but also in using knowledge to advance and defend democratic and human rights based forms of state intervention into crowd events.
Seed crystal free growth of high quality double cation double halide perovskite single crystals for optoelectronic applications
Venue: Journal of Materials Chemistry C
Year: 2020

We developed a seed crystal free re fill crystallization method (RFCM) to grow high quality (FAPbI3)0.9(MAPbBr3)0.1 perovskite single crystals for optoelectronic applications.
Virgin Coconut Oil: Extraction, Physicochemical Properties, Biological Activities and Its Authentication Analysis
Year: 2019

Virgin coconut oil (VCO) has emerged as functional food oil due to its capability to provide some biological activities which are beneficial to human health. This is due to the fact that some minor components like tocopherols and phenolics compounds are retained. VCO is prepared from fresh, mature kernel of the coconuts by mechanical or natural means, with or without the use of heat, but specifically without any chemical refining, bleaching and deodorizing (RBD) As a consequence, VCO has slight difference in terms of some physico chemical properties with RBD coconut oil. Due to phenolics compounds contained, VCO exhibited several pharmacological activities including antioxidant, anti inflammatory and immunomodulatory, anti hyperlipidemia, anticancer, antidiabetic, anti bacterial and neuroprotective activities. VCO has commanded high price value in the fats and oils industry, hence, VCO can be target of adulteration with low priced oils. Fourier transform infrared (FTIR) spectroscopy and chromatographic techniques combined with multivariate analysis has been successfully reported for analysis of adulteration practice involving the substitution or replacement VCO with other oils. This review highlights some techniques for VCO extraction, physicochemical (characterization) biological activities and authentication analysis of VCO.