nils-herrmann/clean_scirepeval huggingface dataset:
Metal additive manufacturing in the commercial aviation industry: A review
Venue: Journal of Manufacturing Systems
Year: 2019

The applications of Additive Manufacturing (AM) have been grown up rapidly in various industries in the past few decades. Among them, aerospace has been attracted more attention due to heavy investment of the principal aviation companies for developing the AM industrial applications. However, many studies have been going on to make it more versatile and safer technology and require making development in novel materials, technologies, process design, and cost efficiency. As a matter of fact, AM has a great potential to make a revolution in the global parts manufacturing and distribution while offering less complexity, lower cost, and energy consumption, and very highly customization. The current paper aims to review the last updates on AM technologies, material issues, post processes, and design aspects, particularly in the aviation industry. Moreover, the AM process is investigated economically including various cost models, spare part digitalization and environmental consequences. This review would be helpfully applied in both academia and industry as well.
Prevalence and antibiotic resistance of Salmonella Enteritidis and Salmonella Typhimurium in raw chicken meat at retail markets in Malaysia.
Venue: Poultry science
Year: 2016

Salmonellosis is one of the major food borne diseases in many countries. This study was carried out to determine the occurrence of Salmonella spp. Salmonella Enteritidis, and Salmonella Typhimurium in raw chicken meat from wet markets and hypermarkets in Selangor, as well as to determine the antibiotic susceptibility profile of S. Enteritidis and S. Typhimurium. The most probable number (MPN) in combination with multiplex polymerase chain reaction (mPCR) method was used to quantify the Salmonella spp. S. Enteritidis, and S. Typhimurium in the samples. The occurrence of Salmonella spp. S. Enteritidis, and S. Typhimurium in 120 chicken meat samples were 20.80% 6.70% and 2.50% respectively with estimated quantity varying from <3 to 15 MPN/g. The antibiogram testing revealed differential multi drug resistance among S. Enteritidis and S. Typhimurium isolates. All the isolates were resistance to erythromycin, penicillin, and vancomycin whereas sensitivity was recorded for Amoxicillin/Clavulanic acid, Gentamicin, Tetracycline, and Trimethoprim. Our findings demonstrated that the retail chicken meat could be a source of multiple antimicrobial resistance Salmonella and may constitute a public health concern in Malaysia.
Towards Privacy Preserving Ego Motion Estimation Using an Extremely Low Resolution Camera
Venue: IEEE Robotics and Automation Letters
Year: 2020

Ego motion estimation is a core task in robotic systems as well as in augmented and virtual reality applications. It is often solved using visual inertial odometry, which involves using one or more always on cameras on mobile robots and wearable devices. As consumers increasingly use such devices in their homes and workplaces, which are filled with sensitive details, the role of privacy in such camera based approaches is of ever increasing importance. In this letter, we introduce the first solution to perform privacy preserving ego motion estimation. We recover camera ego motion from an extremely low resolution monocular camera by estimating dense optical flow at a higher spatial resolution (i.e. 4x super resolution) We propose SRFNet for directly estimating Super Resolved Flow, a novel convolutional neural network model that is trained in a supervised setting using ground truth optical flow. We also present a weakly supervised approach for training a variant of SRFNet on real videos where ground truth flow is unavailable. On image pairs with known relative camera orientations, we use SRFNet to predict the auto epipolar flow that arises from pure camera translation, from which we robustly estimate the camera translation direction. We evaluate our super resolved optical flow estimates and camera translation direction estimates on the Sintel and KITTI odometry datasets, where our methods outperform several baselines. Our results indicate that robust ego motion recovery from extremely low resolution images can be viable when camera orientations and metric scale is recovered from inertial sensors and fused with the estimated translations.
Analysis of Special Interference Methodologies in Satellite Networks
Venue: 2006 7th International Symposium on Antennas, Propagation EM Theory
Year: 2006

In this paper the effects of interference of non geostationary orbit (GSO) satellite with GSO satellite services is calculated. As these effects are calculated in frequencies up to 30 GHz, the interference with the assumption of given GSO satellite parameters (such as BER C/N) is determined considering rain fade. For calculation of C/I in this paper, we first introduce various methodologies which are used to calculate maximum allowable level of interference. Then using these methodologies, EPFD (the equivalent power flow density) is calculated. Finally, a computer program is developed using one of these methodologies and comparison is made with an ITU (International Telecommunication Union) model which shows good agreement.
Hybrid Digital and Analog Beamforming Design for Large Scale Antenna Arrays
Venue: IEEE Journal of Selected Topics in Signal Processing
Year: 2016

The potential of using of millimeter wave (mmWave) frequency for future wireless cellular communication systems has motivated the study of large scale antenna arrays for achieving highly directional beamforming. However, the conventional fully digital beamforming methods which require one radio frequency (RF) chain per antenna element is not viable for large scale antenna arrays due to the high cost and high power consumption of RF chain components in high frequencies. To address the challenge of this hardware limitation, this paper considers a hybrid beamforming architecture in which the overall beamformer consists of a low dimensional digital beamformer followed by an RF beamformer implemented using analog phase shifters. Our aim is to show that such an architecture can approach the performance of a fully digital scheme with much fewer number of RF chains. Specifically, this paper establishes that if the number of RF chains is twice the total number of data streams, the hybrid beamforming structure can realize any fully digital beamformer exactly, regardless of the number of antenna elements. For cases with fewer number of RF chains, this paper further considers the hybrid beamforming design problem for both the transmission scenario of a point to point multiple input multiple output (MIMO) system and a downlink multi user multiple input single output (MU MISO) system. For each scenario, we propose a heuristic hybrid beamforming design that achieves a performance close to the performance of the fully digital beamforming baseline. Finally, the proposed algorithms are modified for the more practical setting in which only finite resolution phase shifters are available. Numerical simulations show that the proposed schemes are effective even when phase shifters with very low resolution are used.
TGAN: Deep Tensor Generative Adversarial Nets for Large Image Generation
Venue: ArXiv
Year: 2019

Deep generative models have been successfully applied to many applications. However, existing works experience limitations when generating large images (the literature usually generates small images, e.g. 32 32 or 128 128) In this paper, we propose a novel scheme, called deep tensor adversarial generative nets (TGAN) that generates large high quality images by exploring tensor structures. Essentially, the adversarial process of TGAN takes place in a tensor space. First, we impose tensor structures for concise image representation, which is superior in capturing the pixel proximity information and the spatial patterns of elementary objects in images, over the vectorization preprocess in existing works. Secondly, we propose TGAN that integrates deep convolutional generative adversarial networks and tensor super resolution in a cascading manner, to generate high quality images from random distributions. More specifically, we design a tensor super resolution process that consists of tensor dictionary learning and tensor coefficients learning. Finally, on three datasets, the proposed TGAN generates images with more realistic textures, compared with state of the art adversarial autoencoders. The size of the generated images is increased by over 8.5 times, namely 374 374 in PASCAL2.
Sociological characteristics of biofilms
Year: 2017

Biofilms are a kind of biological structure with high complexity and self organization, composed of a variety of microorganisms (bacteria, archaea, algae, and micro eukaryotes) and biological substrates (polysaccharides, proteins, fatty acids, etc. They own special structures and ecological functions, and play important roles in microbial colonization, niche construction and environmental adaptability. Many microorganisms' behaviors, such as pathogenic infection, toxin production, drug resistance, biofouling and pipe blockage, are related with biofilms. The formation of these events is full of various microbial behaviors, including signal communication, cooperation/competition, division of labor, as well as "bacteria intelligence" under the adverse circumstances. These features offer further indication of the sociological attributes of biofilms, which also provide a new insight into them. Thus, based on the 3D structure of biofilms, we took the communication language, collaboration, and intelligent resistance (environmental stress, co evolution) inside biofilms as the core to elaborate their social characteristics, in order to get a better understanding of their nature and sociomicrobiology.
Automated Robotic Process Automation: A Self Learning Approach
Venue: OTM Conferences
Year: 2019

Robotic Process Automation (RPA) recently gained a lot of attention, in both industry and academia. RPA embodies a collection of tools and techniques that allow business owners to automate repetitive manual tasks. The intrinsic value of RPA is beyond dispute, e.g. automation reduces errors and costs and thus allows us to increase the overall business process performance. However, adoption of current generation RPA tools requires a manual effort w.r.t. identification, elicitation and programming of the to be automated tasks. At the same time, several techniques exist that allow us to track the exact behavior of users in the front end, in great detail. Therefore, in this paper, we present a novel end to end approach that allows for completely automated, algorithmic RPA rule deduction, on the basis of captured user behavior. Furthermore, our proposed approach is accompanied by a publicly available proof of concept implementation.
Model Checking Embedded Control Software using OS in the Loop CEGAR
Venue: 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE)
Year: 2019

Verification of multitasking embedded software requires taking into account its underlying operating system w.r.t. its scheduling policy and handling of task priorities in order to achieve a higher degree of accuracy. However, such comprehensive verification of multitasking embedded software together with its underlying operating system is very costly and impractical. To reduce the verification cost while achieving the desired accuracy, we propose a variant of CEGAR, named OiL CEGAR (OS in the Loop Counterexample Guided Abstraction Refinement) where a composition of a formal OS model and an abstracted application program is used for comprehensive verification and is successively refined using the counterexamples generated from the composition model. The refinement process utilizes the scheduling information in the counterexample, which acts as a mini OS to check the executability of the counterexample trace on the concrete program. Our experiments using a prototype implementation of OiL CEGAR show that OiL CEGAR greatly improves the accuracy and efficiency of property checking in this domain. It automatically removed all false alarms and accomplished property checking within an average of 476 seconds over a set of multitasking programs, whereas model checking using existing approaches over the same set of programs either showed an accuracy of under 11.1% or was unable to finish the verification due to timeout.
Psychopathic traits affect the visual exploration of facial expressions
Venue: Biological Psychology
Year: 2016

Deficits in emotional reactivity and recognition have been reported in psychopathy. Impaired attention to the eyes along with amygdala malfunctions may underlie these problems. Here, we investigated how different facets of psychopathy modulate the visual exploration of facial expressions by assessing personality traits in a sample of healthy young adults using an eye tracking based face perception task. Fearless Dominance (the interpersonal emotional facet of psychopathy) and Coldheartedness scores predicted reduced face exploration consistent with findings on lowered emotional reactivity in psychopathy. Moreover, participants high on the social deviance facet of psychopathy 'Self Centered Impulsivity' showed a reduced bias to shift attention towards the eyes. Our data suggest that facets of psychopathy modulate face processing in healthy individuals and reveal possible attentional mechanisms which might be responsible for the severe impairments of social perception and behavior observed in psychopathy.
Analisa dan perancangan sistem aplikasi pengaduan tindak kriminalitas kepada kepolisian berbasis android (studi kasus Polsek Kembangan)
Year: 2019

Abstrak Di era globalisasi sekarang ini, kepolisian dituntut untuk meningkatkan kinerjanya. Kepolisian harus merumuskan kebijakan kebijakan strategis antara lain efisiensi serta harus mampu secara cepat dan tepat dalam mengambil keputusan untuk peningkatan pelayanan kepada masyarakat. Inti permasalahan yang dibahas adalah tentang sulitnya masyarakat mengadu kekepolisian. Karena semakin maraknya kriminalitas disekitar masyarakat, aplikasi ini dibuat dan dirancang untuk memudahkan masyarakat melakukan pengaduan terhadap kriminalisasi yang terjadi didalam lingkungan masyarakat. Informasi dan pengaduan pada kepolisian yang berjalan masih dilakukan dengan cara mendatangi langsung instansi tersebut, hal ini merupakan suatu kendala bagi masyarakat sehingga terdapat beberapa kelemahan diantaranya waktu pengaduan tidak cepat, sistem monitoring pengaduan informasi yang kurang efisien dan bagian unit kerja terlambat menanggulangi kasus karena berkaitan dengan penerimaan informasi yang lambat. Aplikasi informasi pengaduan berbasis android adalah sebuah aplikasi untuk para user sebagai pelapor yang memanfaatkan sistem operasi android pada perangkat pintar seperti telepon selular atau tablet yang sudah memasyarakat, bersifat mobile karena bisa dilakukan dimanapun mereka berada. Aplikasi ini diharapkan mampu membuat kinerja kepolisian semakin efektif dan efisien serta mampu mengurangi angka kriminalitas yang terjadi dimasyarakat. Kata kunci Android, Kepolisian, Kriminalitas, Masyarakat
The Work Family Conflict Scale (WAFCS) Development and Initial Validation of a Self report Measure of Work Family Conflict for Use with Parents
Venue: Child psychiatry and human development
Year: 2015

This paper outlines the development and validation of the Work Family Conflict Scale (WAFCS) designed to measure work to family conflict (WFC) and family to work conflict (FWC) for use with parents of young children. An expert informant and consumer feedback approach was utilised to develop and refine 20 items, which were subjected to a rigorous validation process using two separate samples of parents of 2 12 year old children (n 305 and n 264) As a result of statistical analyses several items were dropped resulting in a brief 10 item scale comprising two subscales assessing theoretically distinct but related constructs: FWC (five items) and WFC (five items) Analyses revealed both subscales have good internal consistency, construct validity as well as concurrent and predictive validity. The results indicate the WAFCS is a promising brief measure for the assessment of work family conflict in parents. Benefits of the measure as well as potential uses are discussed.
Barra Tatimore Ne Shqiperi, 2017 (Tax Burden in Albania, 2017)
Year: 2017

Ne serine e publikimeve qe tashme jane bere nje tradite per barren tatimore, ashtu si edhe publikimi tjeter mbi boshllekun tatimor, Qendra ALTAX prezanton edhe kete vit, edicionin e peste Barra tatimore ne Shqiperi, 2017, per secilin qark ne Shqiperi, regjion ne Kosove duke bere edhe klasifikimin per barren me te ulet dhe barren tatimore me te larte, sipas peshes qe ato mbajne ne raport me buxhetin dhe prodhimin e brendshem rajonal. Me qellimin per te pare nje vleresim me global te barres tatimore, ne studim prezantohet edhe barra tatimore ne vendet e rajonit ballkanik. Nje vend te vecante dhe per here te pare mban barra tatimore edhe per Kosoven duke e trajtuar ne nivel shteti dhe regjionesh. Qellimi i studimit eshte terheqja e vemendjes se politikes dhe studiuesve, medias fiskale, politikes fiskale dhe administrimit, si dhe kritikeve qe mund te rezervojne komente per vleresimin apo kane pyetje ne lidhje me llogaritjet dhe faktet e prezantuara ne dokument. Te dhenat e perdorura per llogaritjet jane marre nga burime statistikore zyrtare, nga financat, tatimet dhe organizata qe mbajne te baza te dhenash dhe publikojne, si brenda dhe jashte Shqiperise. Nje pjese e te dhenave jane perpunuar dhe perdorur nga ekspertet e ALTAX per te krahasuar dhe sherbyer si reference kryesore per prezantimin.  In a series of publications that have already become a tradition for the tax burden in Albania, as well as other publication on the tax gap, ALTAX Center presents this year, the fifth edition of the tax burden in Albania, in 2017, for each region in Albania, Kosovo region presenting the classification to lower the burden and the high tax burden, the share they have in relation to the regional budget and regional internal production. With a view to the assessment of the tax burden for the balkan area, the study presents the tax burden for ten countries of Balkans. A special place and for the first time holds the tax burden for Kosovo being treated at the country level and regions. The purpose of the study is to attract the attention of policymakers and researchers, economic and fiscal media, tax policy experts and tax administration, as well as critics who can book reviews to assess or have questions about calculations and facts presented in the document. The data used for the calculations are taken from official statistical sources of finance, taxation and organizations that maintain databases and publish data, both local and foreigner ones. A part of the data are processed and used by ALTAX experts to compare and to serve them as the main reference for the presentation.
Cumulative live birth rates and perinatal outcomes with the use of time lapse imaging incubators for embryo culture: a retrospective cohort study of 1882 ART cycles
Venue: BJOG an international journal of obstetrics and gynaecology
Year: 2019

Comparison of live birth rates and the perinatal outcomes after fresh and frozen embryo transfer between time lapse imaging (TLI) and standard culture (SC) incubators.
THE EFFECT OF GUESSING GAMES ON THE EIGHT YEAR STUDENTS' VOCABULARY ACHIEVEMENT AT SMPN 03 BALUNG JEMBER IN THE 2012/2013 ACADEMIC YEAR
Year: 2013

This article is intended to describe the research result on the use of guessing games on the eight year students' vocabulary achievement. The research problem was the students' difficulties in mastering the vocabularies of the target language. To solve this problem, guessing games in the form of crossword puzzle and riddle was used to know whether or not there is a significant effect of using guessing games on the eight year students' vocabulary achievement. The research design was experimental research with posttest only control group design. The primary data were collected by vocabulary posttest. The result of the research showed that the use of guessing games effected the students' vocabulary achievement.  teaching vocabulary, guessing games, vocabulary achievement
Visual Relation Detection with Multi Level Attention
Venue: ACM Multimedia
Year: 2019

Visual relations, which describe various types of interactions between two objects in the image, can provide critical information for comprehensive semantic understanding of the image. Multiple cues related to the objects can contribute to visual relation detection, which mainly include appearances, spacial locations and semantic meanings. It is of great importance to represent different cues and combine them effectively for visual relation detection. However, in previous works, the appearance representation is simply realized by global visual representation based on the bounding boxes of objects, which may not capture salient regions of the interaction between two objects, and the different cue representations are equally concatenated without considering their different contributions for different relations. In this work, we propose a multi level attention visual relation detection model (MLA VRD) which generates salient appearance representation via a multi stage appearance attention strategy and adaptively combine different cues with different importance weighting via a multi cue attention strategy. Extensive experiment results on two widely used visual relation detection datasets, VRD and Visual Genome, demonstrate the effectiveness of our proposed model which significantly outperforms the previous state of the arts. Our proposed model also achieves superior performance under the zero shot learning condition, which is an important ordeal for testing the generalization ability of visual relation detection models.
Diet and nutrition reverse Type 3 diabetes and accelerated aging linked to global chronic diseases
Year: 2016

The acceleration in the rate of chronic diseases that involve insulin resistance has become of global concern. The rate of the most prevalent chronic disease such as cardiovascular disease is linked to the metabolic syndrome, non alcoholic fatty liver disease (NAFLD) and other chronic diseases that include obesity, diabetes and neurodegenerative diseases. The gene environment interaction in Western countries indicates that with urbanization access to food and its content may lead to induction of epigenetic alterations and identify the gene Sirtuin 1 (Sirt 1) to be responsible for the increased risk for insulin resistance and NAFLD relevant to Type 1, Type 2 and Type 3 diabetes in these countries. Nutrigenomics is linked to neuron and liver telomere maintenance, cell division and tissue growth and has become important with essential nutrients that regulate Sirt 1 function important to prevent NAFLD in individuals with diabetes. Nutrigenomic diets, exercise, drugs and lifestyle changes regulate Type 3 diabetes with neuron Sirt 1 transcriptional responses associated with DNA modifications that regulate brain insulin resistance relevant to NAFLD and diabetes.