nils-herrmann/clean_scirepeval huggingface dataset:
4.5 GHz Lithium Niobate MEMS Filters With 10% Fractional Bandwidth for 5G Front Ends
Venue: Journal of Microelectromechanical Systems
Year: 2019

This paper presents a new class of micro electro mechanical system (MEMS) C band filters for 5G front ends. The filter is comprised of resonators based on the first order asymmetric Lamb wave (A1) mode in thin film lithium niobate. Two filters have been demonstrated at 4.5 GHz with sharp roll off, flat in band group delay, and spurious free response over a wide frequency range. The first design shows a 3 dB fractional bandwidth (FBW) of 10% an insertion loss (IL) of 1.7 dB, an out of band (OoB) rejection of 13 dB, and a compact footprint of 0.36 mm2, while the second design shows a 3 dB FBW of 8.5% an IL of 2.7 dB, an OoB rejection of 25 dB, and a footprint of 0.9 mm2. The demonstrations herein mark the largest FBW achieved for acoustic only filters at 5G frequencies.
PENILAIAN RETURN DAN RISIKO SISTEMATIS SAHAM MENGGUNAKAN CAPITAL ASSET PRICING MODEL
Year: 2020

ABSTRAK Tujuan dilakukannya penelitian ini adalah: (1) Agar investor dapat mengetahui saham mana yang memberikan return yang optimal sesuai dengan risiko yang berani ditanggung oleh investor, (2) Agar investor dapat mengetahui saham mana yang termasuk efisien dan tidak efisien untuk menghindari adanya kesalahan investasi, (3) Agar investor dapat memahami metode Capital Asset Pricing Model untuk membantu para investor menentukan keputusan investasi yang terbaik. Teknik pengambilan sampel yang digunakan adalah purposive sampling, dengan kriteria (1) Perusahaan yang terdaftar di Bursa Efek Indonesia yang tergolong ke dalam Jakarta Islamic Index, (2) Perusahaan yang sahamnya konsisten masuk dalam Jakarta Islamic Index periode Januari 2014 Desember 2016, (3) Data yang tersedia lengkap periode Januari 2014 Desember 2016. Periode penelitian yang digunakan adalah dari periode Desember 2013 Desember 2016. Kriteria pemilihan saham dalam penelitian ini adalah memilih saham efisien dimana return individu expected return [E(R) E(R) CAPM] Hasil penelitian ini menunjukkan bahwa: (1) Terdapat hubungan yang negatif atau tidak searah antara risiko sistematis beta dengan tingkat keuntungan yang diharapkan. (2) Terdapat 12 saham yang termasuk saham efisien yaitu ADRO, AKRA, ASII, BSDE, INDF, KLBF, LSIP, SMRA, TLKM, UNTR, UNVR dan WIKA. Saham saham tersebut memiliki nilai E(R) E(R) CAPM, Keputusan investasi yang harus dilakukan investor adalah membeli saham efisien.
StarGAN: Unified Generative Adversarial Networks for Multi domain Image to Image Translation
Venue: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
Year: 2018

Recent studies have shown remarkable success in image to image translation for two domains. However, existing approaches have limited scalability and robustness in handling more than two domains, since different models should be built independently for every pair of image domains. To address this limitation, we propose StarGAN, a novel and scalable approach that can perform image to image translations for multiple domains using only a single model. Such a unified model architecture of StarGAN allows simultaneous training of multiple datasets with different domains within a single network. This leads to StarGAN's superior quality of translated images compared to existing models as well as the novel capability of flexibly translating an input image to any desired target domain. We empirically demonstrate the effectiveness of our approach on a facial attribute transfer and a facial expression synthesis tasks.
A prescription fraud detection model
Venue: Comput. Methods Programs Biomed.
Year: 2012

Prescription fraud is a main problem that causes substantial monetary loss in health care systems. We aimed to develop a model for detecting cases of prescription fraud and test it on real world data from a large multi center medical prescription database. Conventionally, prescription fraud detection is conducted on random samples by human experts. However, the samples might be misleading and manual detection is costly. We propose a novel distance based on data mining approach for assessing the fraudulent risk of prescriptions regarding cross features. Final tests have been conducted on adult cardiac surgery database. The results obtained from experiments reveal that the proposed model works considerably well with a true positive rate of 77.4% and a false positive rate of 6% for the fraudulent medical prescriptions. The proposed model has the potential advantages including on line risk prediction for prescription fraud, off line analysis of high risk prescriptions by human experts, and self learning ability by regular updates of the integrative data sets. We conclude that incorporating such a system in health authorities, social security agencies and insurance companies would improve efficiency of internal review to ensure compliance with the law, and radically decrease human expert auditing costs.
Vacuum Assisted Wound Closure for Management of Different Types of Wounds
Year: 2013

The aim of this study is to compare the effectiveness of Vacuum assisted closure with routine wound dressings for different types of wounds like traumatic wounds, specially open fractures of the lower limbs, post surgical wound dehiscence, gunshot wounds, diabetic foot wounds, deep burn wounds, pressure ulcers and chronic fistula wounds.  Forty one patients with different types of acute, subacute and chronic wounds were treated by routine wound dressings and VAC therapy. We used 4 Vacuum assisted closure machines and the study lasted for about 2 years in the Dammam Medical Complex, Dammam, Saudi Arabia.  The Vacuum assisted closure dressing is an important effective tool in the treatment of acute, sub acute and chronic wounds. Vacuum assisted closure effectiveness was found to be better than the usual routine dressings, resources were better utilized and costs were decreased.  Despite the significant costs involved, the Vacuum assisted closure technique has proved to be more effective and better in financial terms when compared to conventional treatments in the management of difficult to heal acute traumatic, sub acute and chronic wounds.
Fibroblasts Derived From Human Adipose Stem Cells Produce More Effective Extracellular Matrix and Migrate Faster Compared to Primary Dermal Fibroblasts.
Venue: Aesthetic surgery journal
Year: 2019

The efficacy of adipose derived stem cells (ASCs) to improve wound healing has been extensively investigated. Unfortunately, there have been no consistent reports describing significant improvements in healing time or outcomes in large scale clinical trials using human ASCs. Primarily, these studies examined undifferentiated ASCs as opposed to specific cells differentiated from ASCs.  Here, we examine the properties of fibroblasts differentiated from human ASCs (dFib cells) in comparison to those of primary dermal fibroblasts.  ASCs were isolated from healthy female patients, differentiated into dFib cells, and compared with intra patient primary dermal fibroblasts for morphology, extracellular matrix marker expression, and cell migration using qPCR, western blot, and scratch test assays.  De novo differentiated fibroblasts produce higher levels of the healthy extracellular matrix (ECM) markers elastin, fibronectin, and collagen 1, when compared to primary fibroblasts. In contrast, dFib cells have reduced expression of the scar tissue markers aSMA, Collagen 3, and MMP 1. Further, dFib cells close scratch defects more quickly than primary dermal fibroblasts (32 12.85 hours vs. 64 13.85 hours, p<0.01) in a scratch test assay.  These data suggest that fibroblasts newly differentiated from human ASCs migrate well and produce a robust ECM the combination of which may contribute to improved wound healing and thus should be further investigated.
Unsupervised Sentence Compression using Denoising Auto Encoders
Venue: CoNLL
Year: 2018

In sentence compression, the task of shortening sentences while retaining the original meaning, models tend to be trained on large corpora containing pairs of verbose and compressed sentences. To remove the need for paired corpora, we emulate a summarization task and add noise to extend sentences and train a denoising auto encoder to recover the original, constructing an end to end training regime without the need for any examples of compressed sentences. We conduct a human evaluation of our model on a standard text summarization dataset and show that it performs comparably to a supervised baseline based on grammatical correctness and retention of meaning. Despite being exposed to no target data, our unsupervised models learn to generate imperfect but reasonably readable sentence summaries. Although we underperform supervised models based on ROUGE scores, our models are competitive with a supervised baseline based on human evaluation for grammatical correctness and retention of meaning.
Narrating the story of a failed national transition: discourses on the Greek crisis, 2010 2014
Year: 2015

This article traces the construction of the dominant, promemorandum discourse that has been propagated by the political establishment and mainstream media in Greece interpreting the current crisis as a crisis of the national identity: Greece failed to reform where necessary due to the domination of the traditional political culture that is to be blamed for the failed transition since 1974 to postwar European modernity. This narrative is examined within broader narratives and discourses that have attempted in different periods to conceptualise and prescribe the transition to modernity followed not only by Greece, but by other societies the world over. This brief study enables us to think of this exceptional "failed transition" as a not so exceptional or failed transition, while at the same time to observe how societies in crisis turn to history so as to make sense of their present.
Research Analysis of Cyber Attacks in Cloud Computing Domains with Suitable Solutions
Year: 2016

The last few years will surely enter in the history of IT Security. The period highlighted the introduction of STUXNET, the first malware able to take the control of low level industrial devices. STUXNET was conceived to take the control of a particular device which is a centrifuge of nuclear power plants. This fact made everybody reflect on the fact that cyber security was not anymore a matter of securing servers and software, company data and continuity, but a matter of citizen safety. In a few days, the world understood that all our critical infrastructures (electric grids, water grids, gas and oil pipelines, air traffic control systems, hospital networks etc. are indeed vulnerable to cyber attacks. It is the need of the hour to combat all forms of cyber attacks with a professional bent of mind and by utilizing effective control measures to retaliate cyber attacks in cloud computing environments in particular.  STUXNET; Distributed Denial of Service; Managed Service Providers (MSPs) Video Game Attacks; Host Security; Network Availibility; Health Insurance Portability and Accountability Act (HIPAA) Cyber Threat Intelligence
Characterization and mechanical response of novel Al (Mg TiFe SiC) metal matrix composites developed by stir casting technique
Venue: Journal of Composite Materials
Year: 2019

This study was conducted to investigate the synthesis, characterization and mechanical properties of aluminium reinforced with ferrotitanium and silicon carbide via stir casting technique. Microstructures of as cast samples were analysed using optical and scanning electron microscopes equipped with energy dispersive X ray spectroscopy. The mechanical properties in terms of hardness, tensile, tribological behaviour and fracture were assessed. Results showed that the homogeneous dispersion of reinforcement was within the metal matrix composite. Tribological study revealed a decrease in frictional coefficient of the composites with lowest frictional coefficient observed in composite with addition of silicon carbide as reinforcement. Morphology of fractured surface displayed a reduction in the size of dimples formed in reinforced aluminium composites when compared with larger dimple sizes observed in as cast aluminium alloy.
Decision model for identity management product selection using fuzzy AHP
Venue: 2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)
Year: 2017

Identity management (IDM) refers to a security discipline that employs technologies to manage information about the identity of users and control their access to organization resources. Various IDM products are in the market to offer corporate customers productivity and security while lowering costs of identity management. System integrators who implement the IDM solutions for their corporate customers often face problems when choosing the right IDM products for integrating with the customers' enterprise systems. This paper proposes a decision model for IDM product selection which is used in evaluating and ranking IDM products based on the proposed customer requirements questionnaire. The model is comprehensive in that its decision criteria comprise not only the technical specifications of the products but also other important aspects including price and accountability of system integrators and product vendors. Based on the decision model, product selection is conducted using a multi criteria decision making technique called fuzzy analytic hierarchy process (fuzzy AHP) In an evaluation, a leading system integrator company in Thailand applies the proposed approach to IDM product selection for its customer and the result is quite satisfactory.
Biomarkers associated with idiopathic frozen shoulder: a systematic review
Venue: Connective tissue research
Year: 2019

The pathophysiology of idiopathic frozen shoulder (FS) remains poorly described. There is a lack of differentiation between idiopathic and secondary cause. The aim of this systematic review was to summarize the evidence regarding the pathophysiology of idiopathic FS on a molecular level and emphasize the clinical relevance.  A database search of Medline, EMBASE and Cochrane Central Register of Controlled Trials from inception to April 2018 was performed. Participants who underwent previous injections or surgeries were excluded. A thorough selection and quality assessment process using the Cochrane Risk of Bias assessment tool and the Joanna Briggs Institute Critical Appraisal Checklist was conducted by two reviewers independently.  A total of 15 studies analyzing 333 study subjects were included. Twelve studies evaluated capsular tissue and three studies investigated blood samples. The tissue samples revealed increased expression of various inflammatory cytokines including interleukins, cyclooxygenase and tumor necrosis factor. Several types of acid sensing ion channels (ASIC1 and ASIC3) were associated with disturbed neurogenesis and melatonin regulated pain mechanism. The blood samples showed prevalence of specific interleukin and metalloproteinase genotypes. A decreased matrix metalloproteinase/tissue inhibitor of metalloproteinase ratio was found both in tissue and blood.  The findings indicate an abnormal local neurogenesis with possible regulation through melatonin. The disturbance in remodeling of the extracellular matrix and in collagen translation, together with a persistent inflammation and an impaired healing, all interact in the process that leads to persistent fibrosis. There is global fibroplasia with localized anterior capsule contracture.
A delay prediction model for high speed railway: an extreme learning machine tuned via particle swarm optimization
Venue: 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)
Year: 2020

Train delay prediction is a significant part of railway delay management, which is key to timetable optimization of Highspeed Railways (HSRs) In this paper, an extreme learning machine (ELM) tuned via particle swarm optimization (PSO) is proposed to predict train arrival delays of HSR lines. First, five characteristics (e.g. the plan running time between the present station and the next station, stations) are selected from nine characteristics as input variables for ELM by correlation coefficient matrix. Next, PSO algorithm is implemented to effectively resolve the hyperparameter adjustment of ELM, which overcomes tedious manual regulation for the number of hidden neurons. Finally, a case study of fifteen stations on Beijing Kowloon (B K) HSR line in China is proposed using the ELM tuned via PSO (ELM PSO) The prediction performance of the proposed method is verified by comparison with six benchmark models. The results indicate that our method is superior to these baseline models in prediction accuracy.
Development of Open source Software and Gaze Data Repositories for Performance Evaluation of Eye Tracking Systems
Venue: Vision
Year: 2019

In this paper, a range of open source tools, datasets, and software that have been developed for quantitative and in depth evaluation of eye gaze data quality are presented. Eye tracking systems in contemporary vision research and applications face major challenges due to variable operating conditions such as user distance, head pose, and movements of the eye tracker platform. However, there is a lack of open source tools and datasets that could be used for quantitatively evaluating an eye tracker's data quality, comparing performance of multiple trackers, or studying the impact of various operating conditions on a tracker's accuracy. To address these issues, an open source code repository named GazeVisual Lib is developed that contains a number of algorithms, visualizations, and software tools for detailed and quantitative analysis of an eye tracker's performance and data quality. In addition, a new labelled eye gaze dataset that is collected from multiple user platforms and operating conditions is presented in an open data repository for benchmark comparison of gaze data from different eye tracking systems. The paper presents the concept, development, and organization of these two repositories that are envisioned to improve the performance analysis and reliability of eye tracking systems.
Un cas d'anevrisme dissequant de l'artere carotide interne secondaire a une dysplasie focale en Afrique sub Saharienne cas clinique et revue de la litterature
Year: 2018

Nous rapportons le cas d'un AVC du sujet jeune, secondaire a un anevrisme dissequant du bulbe carotidien, chez lequel l'aspect angioscannographique est evocateur d'une dysplasie focale atypique. Cette pathologie rare, decrite preferentiellement chez le sujet de race noire, n'a jamais ete decrite en Afrique sub saharienne. A partir d'une revue de litterature, nous en rappelons les arguments du diagnostic clinique et radiologique. Son potentiel de recidive eleve sous traitement medical et l'efficacite averee du traitement chirurgical necessite donc qu'elle soit connue et diagnostiquee par les praticiens exercant dans cette zone geographique. Mots cles: AVC dissection dysplasie Race noire Afrique English Title: Dissecting aneurysm of the internal carotid artery due to focal dysplasia in sub Saharan Africa: a case report and literature review English Abstract We report a case of ischemic stroke in a 38 year old patient, related to a dissecting aneurysm of the carotid bulb, in which the angioscannographic aspect is evocative of an atypical focal dysplasia. This rare disease, described preferentially in black subjects, has never been reported in sub Saharan Africa. Through a literature review, we recall the arguments of the clinical and radiological diagnosis. Its high potential for recurrence with medical treatment only and the proven effectiveness of surgical treatment therefore requires that it should be known and diagnosed by practitioners working in this geographical area.  Stroke dissection dysplasia black race Africa
Noise induced topological transformations of vortex solitons in optical fibers filled with a cold atomic gas
Year: 2013

We consider the influence of optical and temperature dependent atomic fluctuations on the formation and propagation of optical vortex solitons in dense media realized as hollow core optical fibers filled with a cold atomic gas in presence of optical pumping. We show different perturbation induced scenaria of complete destruction and smooth transformation of the topological characteristics of localized optical patterns in hollow core fiber. The maximum levels of optical and atomic fluctuations at which the soliton regime can be maintained has been determined. The estimates for these levels show that it is possible to observe the optical vortex solitions in the core filling gas of the fiber for temperatures smaller than the critical temperature of Bose Einstein condensate.
Language Models are Unsupervised Multitask Learners
Year: 2019

Natural language processing tasks, such as question answering, machine translation, reading comprehension, and summarization, are typically approached with supervised learning on taskspecific datasets. We demonstrate that language models begin to learn these tasks without any explicit supervision when trained on a new dataset of millions of webpages called WebText. When conditioned on a document plus questions, the answers generated by the language model reach 55 F1 on the CoQA dataset matching or exceeding the performance of 3 out of 4 baseline systems without using the 127,000+ training examples. The capacity of the language model is essential to the success of zero shot task transfer and increasing it improves performance in a log linear fashion across tasks. Our largest model, GPT 2, is a 1.5B parameter Transformer that achieves state of the art results on 7 out of 8 tested language modeling datasets in a zero shot setting but still underfits WebText. Samples from the model reflect these improvements and contain coherent paragraphs of text. These findings suggest a promising path towards building language processing systems which learn to perform tasks from their naturally occurring demonstrations.
Community structure of Anaeromyxobacter in Fe(III) reducing enriched cultures of paddy soils
Venue: Journal of Soils and Sediments
Year: 2019

Anaeromyxobacter is a typical representative genus of dissimilatory metal reducing microbes. However, the community structure and metabolic function of Anaeromyxobacter have rarely been reported because of the limited number of Anaeromyxobacter isolations. Therefore, this study aimed to investigate the community structure and succession of Anaeromyxobacter in a Fe(III) reducing enriched culture of paddy soils. A 40 day anaerobic incubation of paddy soils enriched with ferrihydrite and goethite was conducted to investigate the response of the community structure and succession of Anaeromyxobacter to iron oxide addition. The dominant Anaeromyxobacter in paddy soils were potentially capable of Fe(III) reduction. Ferrihydrite enrichment increased the absolute abundance of Anaeromyxobacter by 0.01 x 108 to 3.2 x 108 copies g 1 soil, while goethite enrichment increased the absolute abundance of Anaeromyxobacter by 0.004 x 108 to 1.8 x 108 copies g 1 soil. Iron oxide enrichment significantly influenced the richness of Anaeromyxobacter during the later stages of incubation but had a negligible influence on the evenness. Nonetheless, Fe(II) accumulation was stimulated by ferrihydrite enrichment after paddy soil was incubated for 5 days, whereas goethite had a negligible effect on Fe(II) accumulation. Redundancy analysis revealed that Anaeromyxobacter community succession was closely correlated with the processes of Fe(III) reduction. Exogenous ferrihydrite addition showed a greater influence than goethite on the Anaeromyxobacter community during anaerobic incubation of paddy soils. The difference in inherent amorphous iron oxide content in paddy soils was also decisive in the distinct community structure and succession of Anaeromyxobacter in paddy soils.