nils-herrmann/clean_scirepeval huggingface dataset:
Effects of coconut oil pulling and professional toothbrushing on gingivitis
Year: 2019

The purpose of this study was to provide basic data for gingivitis management programs by dental hygienists by evaluating the effect of oral health education, oil pulling, and professional toothbrushing on gingivitis.  A total of 38 subjects were divided into three groups: control group (12 subjects) experimental group 1 (13 subjects) and experimental group 2 (13 subjects) The control and experimental groups were instructed to brush using the rotating method. Distilled water was provided to the control group after training. Coconut oil was provided every morning for about 10 minutes. In the experimental group 2, a professional brushing method was used at each visit.  There were no significant differences in oral health among the three groups, and there was homology between patient hygiene performance (PHP) index (p=0.144) and bleeding rate (p=0.213) The PHP index showed a significant interaction between the group and measurement time. The control and experimental groups showed changes in the PHP index with time (F=3.711; p=0.013) The bleeding rate showed a significant interaction between the group and measurement period. The control and experimental groups showed changes in the bleeding rate with time (F=6.707; p<0.001)  Oral health education, professional toothbrushing, and oil pulling specialists in oral care of gingivitis were effective in managing gingivitis. It is necessary to educate people on self management methods for oral health promotion using gingivitis management programs by dental hygienists.
Donkey milk: An overview on functionality, technology, and future prospects
Year: 2017

Milks from nontraditional animal species (i.e. donkey, camel, and buffalo) are recently gaining momentum mainly due to the fact that they are considered suitable to supplement the needs of special population groups (i.e. infants, the elderly) Research on donkey milk has dramatically increased over the past few years; therefore, this review aims to critically summarize the current research, offering an insight into its unique functional properties, namely, antimicrobial activity, immunomodulation, and hypoallergenicity, especially highlighting their effect on human health. The microbiological and chemical safety, the nutritional profile, and donkey milk's technology are also discussed. Moreover, new promising research grounds are proposed to be explored in order to add to existing knowledge.
Machine Learning in Business Process Monitoring: A Comparison of Deep Learning and Classical Approaches Used for Outcome Prediction
Venue: Bus. Inf. Syst. Eng.
Year: 2021

Predictive process monitoring aims at forecasting the behavior, performance, and outcomes of business processes at runtime. It helps identify problems before they occur and re allocate resources before they are wasted. Although deep learning (DL) has yielded breakthroughs, most existing approaches build on classical machine learning (ML) techniques, particularly when it comes to outcome oriented predictive process monitoring. This circumstance reflects a lack of understanding about which event log properties facilitate the use of DL techniques. To address this gap, the authors compared the performance of DL (i.e. simple feedforward deep neural networks and long short term memory networks) and ML techniques (i.e. random forests and support vector machines) based on five publicly available event logs. It could be observed that DL generally outperforms classical ML techniques. Moreover, three specific propositions could be inferred from further observations: First, the outperformance of DL techniques is particularly strong for logs with a high variant to instance ratio (i.e. many non standard cases) Second, DL techniques perform more stably in case of imbalanced target variables, especially for logs with a high event to activity ratio (i.e. many loops in the control flow) Third, logs with a high activity to instance payload ratio (i.e. input data is predominantly generated at runtime) call for the application of long short term memory networks. Due to the purposive sampling of event logs and techniques, these findings also hold for logs outside this study.
Spatial Attention Fusion for Obstacle Detection Using MmWave Radar and Vision Sensor
Venue: Sensors
Year: 2020

For autonomous driving, it is important to detect obstacles in all scales accurately for safety consideration. In this paper, we propose a new spatial attention fusion (SAF) method for obstacle detection using mmWave radar and vision sensor, where the sparsity of radar points are considered in the proposed SAF. The proposed fusion method can be embedded in the feature extraction stage, which leverages the features of mmWave radar and vision sensor effectively. Based on the SAF, an attention weight matrix is generated to fuse the vision features, which is different from the concatenation fusion and element wise add fusion. Moreover, the proposed SAF can be trained by an end to end manner incorporated with the recent deep learning object detection framework. In addition, we build a generation model, which converts radar points to radar images for neural network training. Numerical results suggest that the newly developed fusion method achieves superior performance in public benchmarking. In addition, the source code will be released in the GitHub.
Base protocol for real time active random surveillance of coronavirus disease (COVID 19) Adapting veterinary methodology to public health
Venue: One Health
Year: 2020

The pandemic of new coronavirus disease COVID 19 is threatening our health, economy and life style. Collaborations across countries and sectors as a One Health World could be a milestone. We propose a general protocol, for setting timely active random surveillance of COVID 19, at the human community level, with systematic repeated detection efforts. Strengths and limitations are discussed. If considered applicable by public health, the protocol could evaluate the status of COVID 19 epidemics consistently and objectively.
La responsabilite sociale d'entreprise
Year: 2010

Le mouvement de responsabilite sociale d'entreprise (RSE) qui s'est developpe ces dernieres annees remet il en cause les approches traditionnelles de la firme Pourquoi et comment les entreprises integrent elles a leurs objectifs economiques, des objectifs environnementaux et sociaux Dans cette nouvelle edition, les auteurs presentent l'evolution des differentes approches du concept de RSE ils analysent la pression des parties prenantes, les discours, les pratiques et mettent en lumiere les dilemmes et les limites de la RSE par rapport aux enjeux du developpement durable. Ils en presentent les principaux dispositifs et notamment la nouvelle norme internationale de responsabilite societale ISO 26000. En proposant une nouvelle lecture des rapports entre les activites economiques et la societe, cet ouvrage ouvre des perspectives de reflexion utiles aussi bien aux chercheurs qu'aux acteurs concernes (milieux economiques, syndicats, ONG.
Blockchain acceptance and adoption in the tourism industry
Year: 2019

Tourism has always been characterized by extensive innovativeness (from theme parks and cultural&gourmet tours till a deeper service integration) Today, digital solutions represent an opportunity to expand and innovate the range of services offered. Focusing on blockchain as an emerging technological solution, the paper investigates how expert and practitioners perceive the potentialities and limitations of its adoption in tourism. To capture the attitudes expressed in the field, we analyze the ongoing discussions on a major social network: Twitter. Through a social network analysis of the flow of tweets conducted over three months, we map the current perceptions towards blockchain. Specifically, we contribute to the literature on technology acceptance and adoption by intercepting the current perceptions in the tourism industry. This paper shows how experts and practitioners are envisioning the possibilities that blockchain shape future services in the tourism sector. Our study is based on an extensive literature review and a social network analysis of a Twitter database. This allows us to investigate the current sentiment towards blockchain, and also to envision future directions of a promising and yet under analyzed technology.
On the Error Analysis of Fixed Gain Relay Networks over Composite Multipath/Shadowing Channels
Venue: 2013 IEEE 77th Vehicular Technology Conference (VTC Spring)
Year: 2013

In this paper, the analysis for the average bit error probability (ABEP) of a dual hop fixed gain relay network is conducted. To this end, we consider two different scenarios: 1) the second hop (relay destination link) is subject to composite multipath/shadowing and the first hop (source relay link) experiences only multipath fading; 2) the first hop is perturbed by the composite multipath/shadowing and the second hop undergoes only multipath fading. We develop new and exact closed form expressions of the ABEP for the first scenario in terms of the Meijer G and Lommel functions. Since the exact closed form expressions for the second scenario are mathematically intractable, we derive a new approximation and bounds. These approximation and bounds are shown to be tight for medium to high average signal to noise ratio (SNR) regime. In addition, we also provide new and relatively simpler asymptotic expressions of the ABEP for both the scenarios. It is shown that some physical insights (e.g. diversity order) of the system can readily be obtained by using these asymptotic expressions. All our analytical results are corroborated by the Monte Carlo simulations.
Power Trading Blockchain using Hyperledger Fabric
Venue: 2020 International Conference on Information Networking (ICOIN)
Year: 2020

Various technologies are mentioned in the 4th Industrial Revolution. One of the emerging issues in the power market is the blockchain based smart grid network. We propose the architecture of the network by incorporating blockchain technology into the existing smart grid system. The Ethereum and Hyperledger Fabrics are widely used in the blockchain technology as public blockchains and private blockchains, respectively. We describe the network architecture in the smart grid blockchain and compare the performance of transactions processing. The performance analysis shows that Hyperledger Fabric is viable approach by providing pipelined concurrent transaction among peers processing and MVCC(multi version concurrency control)
A New Word Discovery Method Based on Constrainted and DSG
Venue: 2019 Chinese Automation Congress (CAC)
Year: 2019

Accurate identification of risk places is of great significance for risk identification, risk analysis, risk response planning and other work in risk areas. Therefore, we will combine the word formation features of risk place and statistical algorithms to discover new words in this paper. Firstly, we preprocess the data based on conditional random field (CRF) and develop a professional dictionary with the help of expert. Secondly, segment the test set, and form a set of new words to be selected based on segmentations and their left right words. Finally, we make word vectors based on directional skip gram (DSG) and calculate the distance between two words to discover new words. The results show that the algorithm can accurately identify new places, and it is suitable for discovering professional vocabulary which word formation features is compound.
Femme Fatale: The Lethality of Female Suicide Bombers
Year: 2020

Are female suicide bombers deadlier than male suicide bombers? Utilizing newly coded data on the tactical attributes of suicide terrorism worldwide from 1998 to 2015, this study shows that the use of female suicide bombers is not only positively correlated with the lethality of the suicide attacks, but also accentuates the existing tactical advantages of suicide terrorism. Especially in the cases of soft targets like civilians, and easily accessible locations, the deadliest outcomes result from those attacks carried out by female suicide bombers.
Can Active Video Games Improve Physical Activity in Adolescents? A Review of RCT
Venue: International journal of environmental research and public health
Year: 2020

Children and adolescents are not meeting the required federal physical activity (PA) guidelines established by the United States Department of Health and Human Services. It is critical that a regular pattern of PA is established in their youth to ensure ongoing PA into adulthood. However, many programs implemented during adolescence have shown limited effects, stressing the need for more innovative approaches to generate more interest and maintenance of PA behavior in this age group. Active video games (AVGs) or exergaming may prove to be an innovate process to improve PA in children and adolescents. A literature review was conducted to explore if active video games or exergaming could be an effective intervention to improve physical activity in adolescents. Active video games, also called "exergames" are a category of video games that require movement or physical exertion to play the game. The methodology consisted of searching Academic Search Premier, CINAHL, The Cochrane Library, ERIC, PubMed, and Web of Science databases. Inclusion criteria involved only youth aged 12 to 19 years, randomized controlled trials (RCTs) and studies within the last 12 years. The following search terms were used: exergaming or active video games; physical activity or exercise; adolescents or youth; RCT or randomized clinical trial. The outcome indicates that exergaming or active video games can be an effective tool to improve PA in adolescents that will be more acceptable and sustainable than many conventional approaches.
Quantitative determination of magnetite and maghemite in iron oxide nanoparticles using Mossbauer spectroscopy
Year: 2019

Iron oxide nanoparticles are available in two common phases, namely magnetite (Fe3O4) and maghemite (Fe2O3) Upon exposure to oxygen atoms, the magnetite phase readily oxidizes into the maghemite phase with the partial conversion of ferrous ions into ferric ions. We report on the approach to determine the ratio of magnetite and maghemite in iron oxide nanoparticles synthesized by the wet chemical route. X ray diffraction studies and transmission electron microscopy observations confirmed the formation of highly crystalline nanoparticles of size \left(  \right) nm. The average particle size is in the magnetic single domain range suitable for the superparamagnetic behavior. The Mossbauer spectrum of the sample is composed of two six line patterns in perfect agreement with the theoretically predicted model. The extracted Mossbauer parameters show contribution of two phases accounting for 47% magnetite and 53% maghemite. The hysteresis loops of the iron nanoparticles demonstrated the "S shaped" pattern with negligible coercivity and remanence magnetization. This result reveals a promising method to synthesize and characterize magnetic nanoparticles of uniform size with a potential for biomedical applications.
Compound Sentence Segmentation and Sentence Boundary Detection in Urdu
Venue: MAICS
Year: 2017

The raw Urdu corpus comprises of irregular and large sentences which need to be properly segmented in order to make them useful in Natural Language Engineering (NLE) This makes the Compound Sentences Segmentation (CSS) timely and vital research topic. The existing online text processing tools are developed mostly for computationally developed languages such as English, Japanese and Spanish etc. where sentence segmentation is mostly done on the basis of delimiters. Our proposed approach uses special characters as sentence delimiters and computationally extracted sentence endletters and sentence end words as identifiers for segmentation of large and compound sentences. The raw and unannotated input text is passed through preprocessing and word segmentation. Urdu word segmentation itself is a complex task including knotty problems such as space insertion and space deletion etc. Main and subordinate clauses are identified and marked for subsequent processing. The resultant text is further processed in order to identify, extract and then segment large as well as compound sentences into regular Urdu sentences. Urdu computational research is in its infancy. Our work is pioneering in Urdu CSS and results achieved by our proposed approach are promising. For experimentation, we used a general genre raw Urdu corpus containing 2616 sentences and 291503 words. We achieved 34% improvement in reduction of average sentence length from 111 w/s to 38 w/s (words per sentence) This increased the number of sentences by almost three times to 7536 shorter and computationally easy to manage sentences. Resultant text reliability and coherence are verified by Urdu language experts.
The Role of Official Statistics in Measurement of the Impacts of Climate Change: Indian Experience
Year: 2008

Climate is the long term statistical expression of short term weather which can be defined qualitatively as 'Expected Weather' or quantitatively by statistical expressions such as central tendencies and variances in key parameters. Changes in climate are the differences between the average conditions in terms of key parameters over time. There is broad consensus that major or minor climate change leads to many hazards and disasters viz increased flood, land slides, avalanche and mud slide damage, increased soil erosion, increased flood run of, increased recharge floodplain aquifiers etc. It also causes displacement of people and increased deaths and serious illness in older age groups and urban poor, increased heat stress in life stock and wild life, increased risk of damage to a number of crops, decreased crop yields, decreased water resource quantity and quality, increased risk of forest fires etc. Relating such disaster like events to climate change can provide robust basis for assessing the impacts of such changes. These would require availability of sound database on the indicators of climate changes and occurrences of disaster type events. In India different Ministries/Organisations/Institutions measures and monitors some indicators of climate changes but as such there is no regular information on climate change induced events such as flashfloods. Central Statistical Organisation in collaboration of National Institute of Disaster Management initiated a joint exercise to develop a Disaster Statistics database. This database will be one which can help researchers and policy makers to assess the impact of climate changes on major or minor disaster. The database will contain data of both hazards and disasters. Some of these hazards and disasters are manmade while most of them are due to change of climate over a considerable period of time. This paper will try to highlight the progress of this endeavour and also will try to explore the possibilities of measuring the impacts of climate change on hazards and disasters.
CFD based shape optimization of steam turbine blade cascade in transonic two phase flows
Year: 2017

In this study CFD based shape optimization of a 3D nozzle and a 2D turbine blade cascade is undertaken in the presence of non equilibrium condensation within the considered flow channels. A two fluid formulation is used for the simulation of unsteady, turbulent, supersonic and compressible flow of wet steam accounting for relevant phase interaction between nucleated liquid droplets and continuous vapor phase. An in house CFD code is developed to solve the governing equations of the two phase flow and was validated against available experimental data. Optimization is carried out in respect to various objective functions. It is shown that nucleation rate and maximum droplet radius are the best suited target functions for reducing thermodynamic and aerodynamic losses caused by the spontaneous nucleation. The maximum increase of 2.1% in turbine blade efficiency is achieved through shape optimization process.
Dynamo: amazon's highly available key value store
Venue: SOSP
Year: 2007

Reliability at massive scale is one of the biggest challenges we face at Amazon.com, one of the largest e commerce operations in the world; even the slightest outage has significant financial consequences and impacts customer trust. The Amazon.com platform, which provides services for many web sites worldwide, is implemented on top of an infrastructure of tens of thousands of servers and network components located in many datacenters around the world. At this scale, small and large components fail continuously and the way persistent state is managed in the face of these failures drives the reliability and scalability of the software systems. This paper presents the design and implementation of Dynamo, a highly available key value storage system that some of Amazon's core services use to provide an "always on" experience. To achieve this level of availability, Dynamo sacrifices consistency under certain failure scenarios. It makes extensive use of object versioning and application assisted conflict resolution in a manner that provides a novel interface for developers to use.
Foreignization and Domestication Ideology in Cultural Term Translation of Novel Tuesday With Morrie: Category Household Goods and House Surroundings
Year: 2018

The research basically aims at identifying translation ideology in cultural term translation of novel Tuesday with Morrie: material culture written by (Albom, 1997) translated by (Widodo, 2009) into an Indonesian language text. Translation ideology classified into its ideology such as foreignization and domestication by (Venuti, 2004) and its techniques of translation theory composed by (Molina Hurtado Albir, 2002) The research approach is a translation approach by using Newmark's perspective. The findings show that there are 9 material cultures especially house goods and household surroundings on Tuesday with Morrie translated into an Indonesian language text. There are six techniques in the data, namely: adaptation, amplification, establish equivalent amplification adaptation, pure borrowings, establish equivalent, and equivalent description. The ideology of the translation in cultural term category material culture using in this novel is domestication and foreignization. Translation to TL (Bahasa) in this novel gives a shift in the cultural environment of cultural elements category material culture in Indonesia.
An Overview of Image Recognition and Retrieval of Clothing Items
Venue: 2018 International Conference on Research in Intelligent and Computing in Engineering (RICE)
Year: 2018

Clothing is important to daily life. As on line fashions retail industry has been growing recognition and retrieval of relevant clothing items have huge potentials, because of the highly increasing earnings of the online clothing sale. This involves acquiring relatable clothing data from a huge number of databases available online. Extracting knowledge and important insights from fashion data still presents challenges due to the essential subjectivity needed and lack of influence to effectively model the domain. There have been many researches about clothing retrieval which are assisted by automated system. In fashion industry, various techniques are suggested and implemented for the classification, recognition and extraction of relevant images from huge databases. The success rates of these techniques are judged on various parameters like their accuracy rate, time taken to generate the outputs, etc. The paper presents a brief analysis of the various retrieval techniques used for clothing retrieval in the fashion industry. Along with this a complete summary on the existing techniques of retrieval based on different scenarios is explained which is expected to be helpful to the researchers who are working in fashion domains for image retrieval.