nils-herrmann/clean_scirepeval huggingface dataset:
Individual differences in the production of referential expressions: The effect of language proficiency, language exposure and executive function in bilingual and monolingual children
Venue: Bilingualism: Language and Cognition
Year: 2019

One hundred and seventy two English speaking 5 to 7 year olds participated in a referential communication task where we manipulated the linguistic mention and the visual presence of a competitor alongside a target referent. Eighty seven of the children were additionally exposed to a language other than English (bilinguals) We measured children's language proficiency, verbal working memory (WM) cognitive control skills, family SES, and relative amount of cumulative exposure and use of the home language for the bilinguals. Children's use of full Noun Phrases (NPs) to identify a target referent was predicted by the visual presence of a competitor more than by its linguistic mention. Verbal WM and proficiency predicted NP use, while cognitive control skills predicted both the ability to use expressions signalling discourse integration and sensitivity to the presence of a discourse competitor, but not of a visual competitor. Bilingual children were as informative as monolingual children once proficiency was controlled for.
Bireysel Zaman Baskisinin Satin Alma Sonrasi Pismanliga Etkisinde Alisveriste Zaman Baskisinin Araci Rolu Uzerine Bir Arastirma
Venue: OPUS Uluslararasi Toplum Arastirmalari Dergisi
Year: 2019

Bu calismanin amaci, zaman baskisinin satin alma sonrasi pismanlik uzerindeki etkisini, zaman baskisi turlerine (bireysel zaman baskisi, alisveriste zaman baskisi) gore belirlemektir. Zaman baskisi pazarlama literaturunde tuketiciye etkileri bakimindan arastirilan onemli konulardan biridir. Ancak arastirmalarda, konunun daha cok alisveriste yasanan zaman baskisi duzeyinde ele alindigi ve bireysel zaman baskisinin goz ardi edildigi gorulmektedir. Yerli pazarlama yazininda ise konuyla ilgili gerceklestirilen arastirma sayisi azdir. Calismada oncelikle zaman baskisi ve alisveriste zaman baskisiyla ilgili bilimsel arastirmalar incelenmektedir. Ardindan bireysel zaman baskisinin tuketicinin satin alma sonrasi pismanliga etkisinde alisveriste zaman baskisinin aracilik rolu uzerine Kirikkale ilinde bir anket calismasi gerceklestirilmektedir. Elde edilen veriler istatistiksel paket programiyla analiz edilmektedir. Arastirma neticesinde bireysel zaman baskisinin alisveriste zaman baskisini ve satin alma sonrasi pismanligi onemli duzeyde acikladigi ve alisveriste zaman baskisinin bireysel zaman baskisinin satin alma sonrasi pismanliga olan etkisinde tam aracilik rolu ustlendigi tespit edilmektedir. Bunlarin yaninda demografik ozelliklere bagli olarak bireysel ve alisveriste zaman baskisindaki farkliliklar incelenmektedir. Son olarak isletme ve arastirmacilara oneriler gelistirilmektedir.
A Dataset for Tracking Entities in Open Domain Procedural Text
Venue: EMNLP
Year: 2020

We present the first dataset for tracking state changes in procedural text from arbitrary domains by using an unrestricted (open) vocabulary. For example, in a text describing fog removal using potatoes, a car window may transition between being foggy, sticky, opaque, and clear. Previous formulations of this task provide the text and entities involved, and ask how those entities change for just a small, pre defined set of attributes (e.g. location) limiting their fidelity. Our solution is a new task formulation where given just a procedural text as input, the task is to generate a set of state change tuples (entity, attribute, before state, after state) for each step, where the entity, attribute, and state values must be predicted from an open vocabulary. Using crowdsourcing, we create OPENPI, a high quality (91.5% coverage as judged by humans and completely vetted) and large scale dataset comprising 29,928 state changes over 4,050 sentences from 810 procedural real world paragraphs from WikiHow.com. A current state of the art generation model on this task achieves 16.1% F1 based on BLEU metric, leaving enough room for novel model architectures.
Learning of Social Representations
Year: 2014

We present DeepWalk, a novel approach for learning latent representations of vertices in a network. These latent representations encode social relations in a continuous vector space, which is easily exploited by statistical models. DeepWalk generalizes recent advancements in language modeling and unsupervised feature learning (or deep learning) from sequences of words to graphs. DeepWalk uses local information obtained from truncated random walks to learn latent representations by treating walks as the equivalent of sentences. We demonstrate DeepWalk's latent representations on several multi label network classification tasks for social networks such as BlogCatalog, Flickr, and YouTube. Our results show that DeepWalk outperforms challenging baselines which are allowed a global view of the network, especially in the presence of missing information. DeepWalk's representations can provide F1 scores up to 10% higher than competing methods when labeled data is sparse. In some experiments, DeepWalk's representations are able to outperform all baseline methods while using 60% less training data. DeepWalk is also scalable. It is an online learning algorithm which builds useful incremental results, and is trivially parallelizable. These qualities make it suitable for a broad class of real world applications such as network classification, and anomaly detection.
Customer relationship management and customer satisfaction: the mediating role of relationship quality
Year: 2017

This study investigates possible associations between customer relationship management (CRM) practices, relationship quality and customer satisfaction, focusing on the possible mediation effect of relationship quality on the CRM tactics and satisfaction link. Field research was conducted by utilising a questionnaire developed by adopting relevant work reported in literature. CRM practices were conceptualised by a 14 item scale, while customer satisfaction was measured by a 4 item construct. Relationship quality was conceptualised by two dimensions, namely relationship satisfaction and trust. The questionnaire was made available over the internet and the respondents were customers of the three major mobile telephony companies in Greece. Exploratory factor analysis was conducted in order to identify latent factors among the CRM practices' items. The results revealed two CRM practices' factors, which were labelled as customer care and communication. Regression analysis was employed to examine the relationships between the emerged CRM practices' dimensions, relationship quality and customer satisfaction. Customer care was found to have a positive significant effect on customer satisfaction. Moreover, the CRM practices' dimensions were also found to have a significant positive impact on relationship quality. Finally, the full mediation role of relationship quality on the CRM practices and customer satisfaction link was also supported.
Inflammatory Breast Cancer Disease: A Literature Review
Year: 2019

Physicians, health care practitioners, and breast cancer advocacy groups have spent many decades investing in the promotion of breast cancer screening and early detection mechanisms, such as mammograms and breast self examinations. These screening modalities are extremely important in reducing breast cancer incidence, prevalence, and mortality, as breast cancer screening continues to contribute to decreasing the surging mortality rate of cancerous diseases. Without the use of these screening measures, breast cancer mortality would affect many more women and exceed current statistics. While these screenings are important for the early detection of breast cancer, a more uncommon, virulent, and fatal form of breast cancer known as Inflammatory Breast Cancer (IBC) has gone largely unreported and continues to affect women. Considering IBC is an aggressive form of breast cancer with a five year survival rate of 65% more diligent measures and strategies are needed to educate women throughout the world about IBC. The purpose of this review is to present an overview of the literature introducing IBC, address symptoms to spread awareness, concentrate on early detection, and focus on the comprehensive treatment options of IBC.  August 07, 2019  October 24, 2019    Patricia Y. Talbert, Howard University, USA.  Talbert, PY, Frazier MD. Inflammatory Breast Cancer Disease: A Literature Review. Cancer Studies. 201;
An In Vitro Comparative Evaluation of Antimicrobial Efficacy of Propolis, Morinda Citrifolia Juice, Sodium Hypochlorite and Chlorhexidine on Enterococcus faecalis and Candida albicans.
Venue: The journal of contemporary dental practice
Year: 2019

To evaluate the antimicrobial effectiveness of Propolis, Morinda citrifolia juice, Sodium hypochlorite and Chlorhexidine onEnterococcus feacalis (E. feacalis) and Candida albicans (C. albicans) as endodontic irrigants.  Four clinical isolates and one standard ATCC sample (29212) of E. feacalis and ATCC sample (90028) of C. albicans were inoculated into 5ml of peptone water each and incubated at 37deg C for 3 to 4 hours to attain the turbidity corresponding to 0.5 McFarland standard CFU. We followed Disc and well diffusion Kirby Bauer method to attain the zones of inhibition.  Overall comparison of reagents revealed a significant difference among zones of inhibition. The standard concentration of 5% sodium hypochlorite, 2% chlorhexidine, 10% Propolis and 100% Morinda citrifolia juice illustrated the maximum inhibition zone for both test organisms.  All four reagents had an antimicrobial effect on the microorganisms tested. Sodium hypochlorite and Chlorhexidine were more effectual than Propolis and Morinda citrifolia juice and there was increased antimicrobial efficacy with increasing concentrations.  A study for finding safe herbal agents that can be used as endodontic irrigants revealed that Propolis, Morinda citrifolia juice has antibiotic properties and can replace routinely used agents thereby limiting the side effects.
COMPARATIVE ANALYSIS OF SPLIT WINDOW AND SINGLE CHANNEL ALGORITHMS FOR LAND SURFACE TEMPERATURE RETRIEVAL OF A PSEUDO INVARIANT TARGET
Year: 2020

Land surface temperature (LST) acquired from remote sensing observations is essential to monitor surface energy and water exchange processes at the land atmosphere interface. Most LST retrieval methodologies are developed focusing on Northern hemisphere. Consequently, Southern hemisphere has a great need for investigating the performance of LST retrieval algorithms already consolidated in the literature. In this paper, we compared a Splitwindow (SW) and a Single channel (SC) method to retrieve LST from Landsat 8 OLI/TIRS images in a dune field, Southern Brazil. To validate the results, the Atmospheric Correction Parameter Calculator (ACPC) tool and Radiative Transfer Equation (RTE) were used. Results demonstrated that both methodologies are in accordance with the RTE, despite they overestimated the LST. Analysis of variance (ANOVA) indicated that the means are not statistically significant (0.05 level) The correlations between LST retrieved and RTE were strong, producing R2 of 0.984 and 0.973 for the SW and SC, respectively, and RMSE values of 1.18 and 1.6. SW also exhibited the best values of MSD 0.983) and Bias (0.773) thus reinforcing its superior performance. SW can be applied with an accuracy of 1.18 K in Southern Brazil, without needing complex modeling or specific radiosonde.
Accent Sandhi Estimation of Tokyo Dialect of Japanese Using Conditional Random Fields
Venue: IEICE Trans. Inf. Syst.
Year: 2017

When synthesizing speech from Japanese text, correct assignment of accent nuclei for input text with arbitrary contents is indispensable in obtaining naturally sounding synthetic speech. A phenomenon called accent sandhi occurs in utterances of Japanese; when a word is uttered in a sentence, its accent nucleus may change depending on the contexts of preceding/succeeding words. This paper describes a statistical method for automatically predicting the accent nucleus changes due to accent sandhi. First, as the basis of the research, a database of Japanese text was constructed with labels of accent phrase boundaries and accent nucleus positions when uttered in sentences. A single native speaker of Tokyo dialect Japanese annotated all the labels for 6,344 Japanese sentences. Then, using this database, a conditional random field based method was developed using this database to predict accent phrase boundaries and accent nuclei. The proposed method predicted accent nucleus positions for accent phrases with 94.66% accuracy, clearly surpassing the 87.48% accuracy obtained using our rule based method. A listening experiment was also conducted on synthetic speech obtained using the proposed method and that obtained using the rule based method. The results show that our method significantly improved the naturalness of synthetic speech. key words: Japanese text to speech, accent sandhi, accent phrase boundary estimation, accent type estimation, conditional random field
GAMBARAN KEJADIAN DISLOKASI TEMPOROMANDIBULAR JOINT PADA TINDAKAN PENCABUTAN GIGI DI RSGM UMY PADA TAHUN 2018
Year: 2019

Temporomandibular disorders (TMD) merupakan sekelompok gangguan fungsional otot pengunyah dan sendi temporomandibular (TMJ) yang sering ditemukan dalam kedokteran gigi. Salah satunya yang termasuk dalam kelompok gangguan sendi temporomandibular (TMJ) yaitu dislokasi. Dislokasi merupakan keadaan dimana posisi kondilus bergerak jauh ke depan sehingga menyebabkan tergelincir keluar dari fosa mandibula dan bergerak melebihi eminensia artikularis. Dislokasi dapat terjadi akibat adanya mekanisme traumatik dan non traumatik. Mekanisme dislokasi sendi temporomandibular bervariasi tergantung pada jenis dislokasi seperti dislokasi akut, kronis, dan rekuren. Jenis dislokasi dapat dibedakan berdasarkan letak kondilus terhadap fossa artikularis tulang temporal. Ada 4 jenis dislokasi, yaitu dislokasi anterior, dislokasi posterior, dislokasi superior, dan dislokasi lateral. Pencabutan gigi merupakan tindakan yang termasuk dalam bedah minor dikedokteran gigi dan memungkinkan terjadinya komplikasi seperti dislokasi temporomandibular joint.  Tujuan penelitian ini untuk mengetahui gambaran kejadian dislokasi temporomandibular joint khususnya pada tindakan pencabutan gigi di Rumah Sakit Gigi dan Mulut Universitas Muhammadiyah Yogyakarta pada tahun 2018. Metode: Penelitian ini menggunakan desain penelitian deskriptif. Pengambilan data dilakukan dengan cara retrospective study. Populasi pada penelitian ini yaitu rekam medis perawatan pencabutan gigi pada tahun 2018 di RSGM UMY. Teknik pengambilan sampel pada penelitian ini yaitu dengan metode total sampling. Hasil: Hasil penelitian yang diperoleh adalah tidak ditemukannya kejadian dislokasi temporomandibular joint pada tindakan pencabutan gigi di RSGM UMY tahun 2018.  Gambaran kejadian dislokasi temporomandibular joint pada tindakan pencabutan gigi di RSGM UMY pada tahun 2018 adalah (0% atau tidak ditemukan.
Marketing based on user behavior on Facebook social network through recommender system design
Year: 2015

t the influence of social networks among people and at the same time inevitable spread of commercial use of them. Accordingly, in order to sell products, recommender systems designed based on user behavior on social networks, providing a variety of commercial offers tailored to the user. The accuracy of recommender systems that make recommendations to users, and how many of the proposals are accepted by the users is important. In this paper, a recommender system is designed based on user behavior in social network Facebook in two acts and suggests that users purchase their favorite products. The first step is to examine user behavior based on user interests will be given an offer to buy products. In the second stage recommender system uses data mining techniques and suggestions to the user that is associated with their previous purchases. This is real data and the real results of it and it is valid, as well as the results show a high level of accuracy recommender system is designed to offer suggestions to users.
Self Organization Based Clustering in MANETs Using Zone Based Group Mobility
Venue: IEEE Access
Year: 2017

The dynamic network topology and mobile nature of nodes can cause challenges regarding connectivity and routing. Clustering in mobile ad hoc networks (MANETs) is one of the effective ways to organize a network according to the network topological changes. In this paper, we propose a self organization based clustering scheme in MANET using zone based group mobility to improve scalability and stability of overall network. This proposed algorithm utilizes the bio inspired behavioral study of birds flocking for the formation and maintenance of clusters in MANETs. A dynamic mechanism for cluster size management is taken into account to reduce network congestion and improve the performance of the MANETs in group mobility. For proper use of resources and to reduce extra energy consumption, an algorithm is also proposed to handle the isolated nodes. Simulation result shows that proposed algorithm reduces the energy consumption and improves the network lifetime along with more robustness.
An antinoise sparse representation method for robust face recognition via joint l1 and l2 regularization
Venue: Expert Syst. Appl.
Year: 2017

L1 or L2 regularization based representation is not antinoise enough.An antinoise sparse representation via joint L1 and L2 is proposed.The rationale of the objective function for fusion is analyzed.Recognition of noisy samples is evaluated as true positive.The Anti L1L2 outperforms some state of art sparse algorithms. Sparse representation methods based on l1 and/or l2 regularization have shown promising performance in different applications. Previous studies show that the l1 regularization based representation has more sparse property, while the l2 regularization based representation is much simpler and faster. However, when dealing with noisy data, both naive l1 and l2 regularization suffer from the issue of unsatisfactory robustness. In this paper, we explore the method to implement an antinoise sparse representation method for robust face recognition based on a joint version of l1 and l2 regularization. The contributions of this paper are mainly shown in the following aspects. First, a novel objective function combining both l1 and l2 regularization is proposed to implement an antinoise sparse representation. An iterative fitting operation via l1 regularization is integrated with l2 norm minimization, to obtain an antinoise classification. Second, the rationale how the proposed method produces promising discriminative and antinoise performance for face recognition is analyzed. The l2 regularization enhances robustness and runs fast, and l1 regularization helps cope with the noisy data. Third, the classification robustness of the proposed method is demonstrated by extensive experiments on several benchmark facial datasets. The method can be considered as an option for the expert systems for biometrics and other recognition problems facing unstable and noisy data.
Ubiquitous computing: a learning system solution in the era of industry 4.0
Year: 2020

Ubiquitous computing, which was initially advocated by Mark Weiser has become one of the keywords to express a vision of the near future of computing systems. The "ubiquitous world" is a ubiquitous computing environment with integrated networks; computer integrated manufacturing system (CIMS) and invisible computers which equipped sensor microchips and radio frequency identification systems. Anyone can access the ubiquitous computing systems anytime and anywhere broader, without individual awareness or skills. Ubiquitous computing is becoming crucial elements to organize the activities of groups of people by use of groupware under workforce mobility. The computer supported cooperative work is transforming from telework to ubiquitous work with new information and communication technologies that support people working cooperatively. Ubiquitous learning is a demand for the knowledge workforce for more multi skilled professionals. It is a new and emerging education and training system that integrating e learning of cyberspace and mobile learning of physical space with a global repository that has the potential to be accessed by anyone at any place and anytime under ubiquitous integrated computing environment. In this paper, we discuss the study of emerging trends through the implementation of work and learning that influenced ubiquitous computing technology prospects. Furthermore, the perspective of ubiquitous work and learning system, gaining quality, and hence credibility with emerging information and communication technologies in education and training systems in the area of the education system are discussed. The experimental results showed that CIMS could improve the students learned more efficiently and achieved better learning performance.
Sound Capture and Processing: Practical Approaches
Year: 2009

Provides state of the art algorithms for sound capture, processing and enhancement Sound Capture and Processing: Practical Approaches covers the digital signal processing algorithms and devices for capturing sounds, mostly human speech. It explores the devices and technologies used to capture, enhance and process sound for the needs of communication and speech recognition in modern computers and communication devices. This book gives a comprehensive introduction to basic acoustics and microphones, with coverage of algorithms for noise reduction, acoustic echo cancellation, dereverberation and microphone arrays; charting the progress of such technologies from their evolution to present day standard. Sound Capture and Processing: Practical Approaches Brings together the state of the art algorithms for sound capture, processing and enhancement in one easily accessible volume Provides invaluable implementation techniques required to process algorithms for real life applications and devices Covers a number of advanced sound processing techniques, such as multichannel acoustic echo cancellation, dereverberation and source separation Generously illustrated with figures and charts to demonstrate how sound capture and audio processing systems work An accompanying website containing Matlab code to illustrate the algorithms This invaluable guide will provide audio, R&D and software engineers in the industry of building systems or computer peripherals for speech enhancement with a comprehensive overview of the technologies, devices and algorithms required for modern computers and communication devices. Graduate students studying electrical engineering and computer science, and researchers in multimedia, cell phones, interactive systems and acousticians will also benefit from this book.
We need a measured approach to metrics
Venue: Nature
Year: 2015

Metrics evoke a mixed reaction from the research community. A commitment to using data and evidence to inform decisions makes many of us sympathetic to, even enthusiastic about, the prospect of granular, real time analysis of our own activities. Yet we only have to look at the blunt use of metrics such as journal impact factors, h indices and grant income targets to be reminded of the pitfalls. Some of the most precious qualities of academic culture resist simple quantification, and individual indicators can struggle to do justice to the richness and plurality of our research. This article gives an overview of the findings of the UK's independent review of the role of metrics in research assessment, which published its final report on 9 July 2015.