Reviewerly/exHarmony huggingface dataset:
Optimal nonparametric estimator of the area under ROC curve based on clustered data

In diagnostic trials, clustered data are obtained when several subunits of the same patient are observed. Intracluster correlations need to be taken into account when analyzing such clustered data. A nonparametric method has been proposed by Obuchowski (1997 Obuchowski, N. A. 1997. Nonparametric analysis of clustered ROC curve data. Biometrics 53 (2):567–78.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) to estimate the Receiver Operating Characteristic curve area (AUC) for such clustered data. However, Obuchowski’s estimator is not efficient as it gives equal weight to all pairwise rankings within and between cluster. In this paper, we propose a more efficient nonparametric AUC estimator with two sets of optimal weights. Simulation results show that the loss of efficiency of Obuchowski’s estimator for a single AUC or the AUC difference can be substantial when there is a moderate intracluster test correlation and the cluster size is large. The efficiency gain of our weighted AUC estimator for a single AUC or the AUC difference is further illustrated using the data from a study of screening tests for neonatal hearing.
The Reform and Exploration of the Training Mode of Computer Applied Talents Based on Establishing Emerging Engineering Education

The development of the construction of emerging engineering education is an important task for universities and colleges to further strengthen higher engineering education and the training of engineering technical talents. Combining with the new concept, new structure, new mode, new quality and new system of the construction of emerging engineering education, the paper focused on the reform ideas and specific measures for the training of new engineering talents in computer major.
An Experimental Investigation of the Scope of Object Comparative Quantifier Phrases

Recent investigations of the constraints on the scope of Comparative Quantifier Phrases (CQPs) (Takahashi 2006; Mayr & Spector 2012; Fleisher 2015) have revealed a puzzle: while CQPs give the appearance of behaving like typical generalized quantifier phrases in some environments, they seem to have a more restricted scopal range than other quantificational phrases, apparently resisting inverse scope over indefinite subjects, except in certain discourse contexts. In this paper, we present a set of three experiments probing the scope of object CQPs relative to a singular indefinite in subject position. Based on the results, make two major contributions. First, we demonstrate that CQPs in object position can uncontroversially take wide scope over an indefinite subject, thereby revealing that they have a wider scopal range than has been assumed based on introspection, and than the current decompositional accounts on the market allow. Second, we identify two factors related to processing scopally ambiguous sentences and three specific factors that affect the accessibility availability of the inverse scope reading: the form of the subject indefinite, the form of the object CQP, and the felicity conditions supporting the use of a CQP. Our results thus underscore the features of the optimal contexts for examining the full scopal range of quantificational phrases more generally. We propose that the varied scopal behavior of object CQPs in particular are related to their post-suppositional cardinality requirements (Brasoveanu 2013), which interact with independently motivated processing preferences.
SYNTHESIS INTERFERENCE OF INDONESIAN LANGUAGE IN THE RIGHT OF GERMAN

Interference is a symptom of irregularities in language rules. It’s can be happend to someone who is learning a foreign language such as students of STIBA Bumigora grade 2015 who learn German as the second foreign language. Language Interference consists of phonological, lexical, morphological, and syntactic interference. In this study, the authors limit his research only to syntactic interference. Syntactic interference consists of two things, they are inter-language interference and intra-language interference. The method of this study is descriptive analysis. The results of the study show us there are several factors that cause errors in syntactic interference on students german essays STIBA Bumigora Mataram. They are; (1) Errors caused by inter-language interference, it's because of the influence of Indonesian language into the German sentence structure. such as; misplaced words and omission of auxilary verb (to be). (2) Errors caused by intra-language interference, it’s because lack of understanding German grammar rules to german essays. Such as; case errors (nominativ, akkusativ, dativ) and verb conjugation errors.
Improving Reading Fluency Through Videoscribe For Student with Learning Disability

This study aims to determine the effect of videoscribe for improving reading fluently ability for student with learning disability. This research uses single subject research (SSR) experiment, A-B-A design and data analysis technique using visual graph analysis. The subject of this research is student with learning disability. Target behavior in this study is the speed of reading fluently in short discourse text. Observations were conducted in three sessions. First is baseline session (A1), second, interventions through media videoscribe (B) and last session baseline (A2). Based on the results of research, we knew that the ability of children in reading fluently can be increased through videoscribe. At the baseline condition (A1), the reading fluently ability of the student increases from the duration of four point five minutes to four minutes. In intervention condition (B), the duration becomes shorter in one minute. At the baseline condition (A2) the duration becomes shorter, even without any intervention. Based on data analysis, it can be explained that direction tendency, stability tendency, data trending trend, and level change increase positively, and overlape percentage on inter-condition analysis is 0%. It can be concluded that the media videoscribe can improve reading fluently ability for student with learning disability.
vChecker: an application-level demand-based co-scheduler for improving the performance of parallel jobs in Xen

Abstract Big data analysis requires the speedup of parallel computing. However, in the virtualized systems, the power of parallel computing is not fully exploited due to the limit of current VMM schedulers. Xen, one of the most popular virtualization platforms, has been widely used by industry to host parallel job. In practice, the virtualized systems are expected to accommodate both parallel jobs and serial jobs, and resource contention between virtual machines results in severe performance degradation of the parallel jobs. Moreover, the physical resource is vastly wasted during the communication process due to the ineffective scheduling of parallel jobs. Unfortunately, the existing schedulers of Xen are initially targeting at serial jobs, which are not capable of correctly scheduling the parallel jobs. This paper presents vChecker, an application-level co-scheduler which mitigates the performance degradation of the parallel job and optimizes the utilization of the hardware resource. Our co-scheduler takes number of available CPU cores in one hand, and satisfies need of the parallel jobs in other hand, which helps the credit scheduler of Xen to appropriately schedule the parallel job. As our co-scheduler is implemented at application level, no modifications on the hypervisor is required. The experimental result shows that the vChecker optimizes the performance of the parallel job in Xen and enhances the utilization of the system.
Leachate Treatment of TPA Talang Gulo, Jambi City by Fenton method and adsorption

ABSTRAK Lindi adalah cairan yang ditimbulkan oleh sampah akibat masuknya air eksternal yang dapat melarutkan materi-materi terlarut, termasuk materi-materi organik hasil dekomposisi secara biologi. Lindi dari sebuah landfill (TPA) mengandung zat organik dan anorganik dalam konsentrasi yang tinggi. Dengan adanya gaya gravitasi maka lindi yang terbentuk akan bergerak ke dasar landfill (TPA) akan masuk ke dalam tanah dengan membawa bahan cemaran baik material tersuspensi maupun material terlarut yang dapat mencemari air tanah. Salah satu proses pengolahan lindi adalah dengan menggunakan reagen Fenton dan adsorpsi yang termasuk dalam teknologi Advanced Oxidation Processes (AOPs). AOPs didasarkan pada pembentukan spesies yang sangat reaktif seperti radikal hidroksil (OH•) yang efektif untuk menurunkan COD, BOD dan TSS. Penelitian ini bertujuan untuk mengolah lindi menggunakan reagen Fenton dan adsorpsi serta mempelajari rasio molar Reagen Fenton dan waktu pengadukan terhadap penurunan COD, BOD dan TSS. Pada penelitian ini lindi diolah selama 30-120 menit. Kondisi optimum dicapai pada rasio molar 1:200, waktu pengadukan 120 menit, dan adsorpsi menggunakan karbon aktif selama 120 menit dimana penurunan COD, BOD dan TSS maksimum yang dicapai berturut-turut 95%, 95% dan 92% dengan nilai konsentrasi akhir 96 mg/L, 25,5 mg/L% dan 90 mg/L. Kata Kunci: Lindi, Reagen Fenton, AOPs, COD, BOD, TSS ABSTRACT Leachate is a liquid generated by waste due to the entry of external water that can dissolve dissolved materials, including decomposition of organic matter biologically. Leachate from a landfill (TPA) contains organic and inorganic substances in high concentrations. by gravitational force, the leachate formed will move to the bottom of the landfill (TPA) and will enter the soil by carrying contaminated material, both suspended material and dissolved material that can pollute ground water. One of the leachate treatment processes is using Fenton reagent and adsorption. Fenton method included in Advanced Oxidation Processes (AOPs) technology. AOPs are based on the formation of highly reactive species such as hydroxyl radicals (OH•) which are effective for reducing COD and BOD. This study aims to treat leachate by using Fenton reagent and adsorption. The effect of reagent Fenton molar ratio and stirring time on degradation of COD, BOD and TSS were also investigated. In this study leachate was processed for 30-120 minutes. the optimum conditions were achieved at a molar ratio of 1: 200, stirring time of 120 minutes, and adsorption using 120 minutes of activated carbon where the maximum decrease in COD, BOD and TSS achieved was 95%, 95% and 92% with a final concentration of 96 mg/L, 25.5 mg/ L and 90 mg/ L. Keywords : Leachate, Fenton Reagent, AOPs, COD, BOD, TSS
A Smart Inertial Pattern for the SUMMIT IoT Multi-platform

The SUMMIT project funded by the Italian MISE under the PON2020 Action, aims to the development a IoT (Internet of Things) platform which should be flexible and adaptive to easily embed several smart objects such as sensors, multi-sensor architectures and mobile terminals. The main idea is to lunch an open and dynamic eco-system to support the development of IoT based services both for the private and public sectors. The concept of “pattern” will lead the overall development of the SUMMIT platform which represents each element to be integrated in the SUMMIT framework by assuring security, privacy and dependability properties. Above patterns will be also self-evolving on the basis of their behavioral analysis to be performed during the system operation. The three main cases of study addressed by the project will be smart energy, smart health and smart cities. Among patterns addressed by the project the development of a smart inertial platform is considered. Such platform will find application in several contexts with a strong priority in the Smart Living framework. As an example, the architecture developed can be adopted for the sake of Activity of Daily Living monitoring (including Falls), postural instability detection, aided navigation, physical activity assessment, just to cite mostly addressed needs. Actually, above application contexts represent serious needs to be addressed to enable Active Ageing and Well Being. The Smart Inertial Pattern (SIP) is based on an embedded architecture equipped with sensors (accelerometer, gyroscope, compass) and communication facilities. In this paper the use of the SIP device for the implementation of a ADL classifier exploiting an event correlated approach is presented.
ATM Transaction Status Feature Analysis and Anomaly Detection

In this paper, based on ATM transaction status analysis and anomaly detection problem, by analyzing the transaction statistics of a bank ATM application system, the characteristic parameters of ATM transaction status are extracted and analyzed, then a set of targets are designed. An abnormal monitoring scheme that can promptly and accurately alarm the four abnormal situations in which the trading volume is steep, the transaction failure rate is increased, the transaction processing is slow, and the transaction response time is too long. Firstly, the transaction data is divided to distinguish between working days, non-working days, trading volume troughs, and normal trading periods, to avoid data interference between different time periods and to take into account the data discontinuity. The characteristics of the anomaly data were identified by K-Means Clustering Analysis. Then the data is analyzed by B-P Neural Network method, the change rule of ATM transaction status with time is obtained. According to this rule, the ATM transaction status is judged, and the abnormal situation is alarmed in time. Finally, this paper increases the amount and type of data collected, then increases the influencing factors such as ATM popularity, holidays, transaction types into the model, uses the existing transaction data before and after the Spring Festival to verify, in order to obtain a more realistic monitoring and early warning program. The transaction status anomaly monitoring scheme designed in this paper not only can correctly judge but also timely alarm the financial aid equipment failure scenarios, so that the security of the financial self-service equipment trading system is guaranteed.
Interrelation between Cloud Computing Technology and Agriculture Fields

Cloud computing is an architecture for facilitating computing service through the internet on requirement and pay per user access to a group of shared resources namely networks, storage, servers, services and applications, without physically acquiring them Cloud DBMS is a distributed database that gives computing as a service.It is sharing of web infrastructure for resources, software and information over a network.The cloud is used as a storage location and database can be accessed and computed from anywhere.In this paper I have discussed about cloud and its use.How we can implement cloud for better performance and different benefits and drawbacks of cloud which we can improve in future Use of Cloud computing technology in agricultural areas has greater chance in the overall development of India.An effective implementation of cloud computing is encouraging in agricultural sector.Cloud Computing is emerging today as a commercial infrastructure that eliminates the need for maintaining expensive computing hardware, software, Information technology, staff, infrastructure, recourses and their maintenance.Cloud computing is a network-based environment that focuses on sharing computations, Cloud computing networks access to a shared pool of configurable networks, servers, storage, service, applications & other important computing resources.In modern era of cloud computing technology very helpful for centralized the all-agricultural related data bank (Soil-related, weather, Research, Crop, Farmers, Agriculture marketing, fertilizers and pesticide information) in the cloud.In this paper, also discuss Computing model, characteristics, deployment model, cloud service model, cloud benefits and challenge of cloud computing in agriculture field.
Cybercrime, human rights and digital politics

Crimes in relation to information and communication technology (ICT), their investigation and prosecution and their ‘shield and sword’ relation to human rights and to digital politics are discussed in this chapter. Particular focus is given to questions of jurisdiction to prescribe and jurisdiction to enforce in cyberspace, and on how internal cooperation in cybercrime matters is designed.
Multi-Stage Image Restoration in High Noise and Blur Settings

We describe a simple approach useful for improving noisy, blurred images. Our approach is based on the use of a parallel block-based low rank factorization technique for projection based reduction of matrix dimensions and on a customized iteratively reweighted CG approach followed by the use of a Fourier Wiener filter. The regularization scheme with a transform basis offers variable residual penalty and increased per-iteration performance. The outlined approach is particularly aimed at high blur and noise settings.
High-efficiency Vector Quantization Codebook Search Algorithms for Extended Adaptive Multi-ratewideband Audio Coder

inequality elimination (TIE), equal-average nearest neighbor search (ENNS)The extended adaptive multi-rate-wideband (AMR-WB+) is a standard audio codec stipulated by the 3rd Generation Partnership Project (3GPP).It has been experimentally validated by 3GPP that an AMR-WB+ audio codec well outperforms others when encoding speech or audio signals at bitrates below 24 kbps, but at the cost of high computational load, particularly when performing the vector quantization (VQ) of immittance spectral frequency (ISF) coefficients.For this sake, by no means can an AMR-WB+ audio codec implemented on mobile devices meet the energy efficiency requirement.As a solution to this problem, in this paper, we present two high-efficiency triangular inequality elimination (TIE)-based algorithms for VQ codebook search.The first is referred to as the iterative TIE (ITIE) search algorithm, and the other is substantially the combined use of ITIE and the equal-average nearest neighbor search (ENNS) algorithm, both of which are subsequently applied to quantize the vectors of ISF coefficients.Most of the codewords are ruled out herein as the candidates using one-level and two-level rejection criteria, leading to a significantly reduced number of codeword searches but still maintaining the same coding quality.With a full search algorithm as a benchmark, this work shows a reduction in the total number of operations of more than 75.21%, a figure far beyond 60.23% using the TIE algorithm with a dynamic and an intersection mechanism (DI-TIE), 60.85% using ENNS, and 64.88% using the equal-average equal-variance equal-norm nearest neighbor search (EEENNS) algorithm.Moreover, this work can be implemented on handheld devices equipped with multiple sensing components, e.g., smartphones, to provide various multimedia and audio applications, and the energy saving requirement can be achieved as well.
Estimating Multilevel Models on Data Streams

Social scientists are often faced with data that have a nested structure: pupils are nested within schools, employees are nested within companies, or repeated measurements are nested within individuals. Nested data are typically analyzed using multilevel models. However, when data sets are extremely large or when new data continuously augment the data set, estimating multilevel models can be challenging: the current algorithms used to fit multilevel models repeatedly revisit all data points and end up consuming much time and computer memory. This is especially troublesome when predictions are needed in real time and observations keep streaming in. We address this problem by introducing the Streaming Expectation Maximization Approximation (SEMA) algorithm for fitting multilevel models online (or “row-by-row”). In an extensive simulation study, we demonstrate the performance of SEMA compared to traditional methods of fitting multilevel models. Next, SEMA is used to analyze an empirical data stream. The accuracy of SEMA is competitive to current state-of-the-art methods while being orders of magnitude faster.
Language Learning and Teaching Using New Technologies

How the new technologies can be used to assist the language learning and which innovative applications are helpful to meet the continuously increasing demands of learners is the focus of this study. New technologies including overhead projectors, interactive whiteboards, computers and wireless internet have opened up the classroom to the outside world. The teaching-learning process has to adapt to changing learning contexts. Technology provides a learner independent in language learning. Thus, technology enables the learner’s efforts easier and faster. At present, there are several online services and some of them are free. It is possible that many more services will be available in future.
Research on Domain Term Dictionary Construction Based on Chinese Wikipedia

Domain terms are words or phrases that represent concepts or relationships in a specific domain. It can represent the characteristics of corresponding domains. The automatic construction of domain-specific dictionary is an important task in natural language processing, which can be adopted in domain-specific ontology construction, vertical search, text classification, information retrieval, question answering system etc. In this paper, we propose a novel method for constructing domain term dictionary based on Chinese Wikipedia web resource and deep learning technology. We for first time explore to word representation by Word2vec model integrating Wikipedia link structure. Then we use word clustering algorithm and seed word extraction method to construct an original domain dictionary. Moreover, neural network method is applied to extend domain dictionary. In experiments, different methods were employed to extract the domain-specific terms and their performances were compared in automobile field, the results reveal the effectiveness of our method for construction of domain-specific dictionary.
A cross sectional study to assess prevalence and pattern of ocular morbidity among pre-school children attending anganwadi centres of Hubballi taluk in South India

Background: About 30% of blind population of India loses their eyesight before the age of 20 years and many of them are under 5 when they become blind. Childhood blindness will have serious impact on development, education and quality of life. Therefore it is essential that ocular morbidity is detected and treated at an early stage.Methods: A cross-sectional study was conducted among 120 children aged 3-5 years attending 6 anganwadi centres of Hubballi taluk which were selected by stratified random sampling. Data was collected using pretested semi-structured questionnaire. Ocular examination was conducted to identify ocular morbidity. Test for visual acuity, colour blindness and refractive status was done using lea chart, ischihara charts and plusoptix mobile vision screener respectively. Nutrition status was assessed by clinical examination and anthropometry. Statistical analysis was done using SPSS package.Results: Out of 120 children 51.7% were male. Majority, 63.3% were residing in urban area and 40% belonged to class IV of modified B G Prasad classification of socio-economic status scale. The prevalence of ocular morbidity was found to be 20%. 15.8% of children had refractive error, 2.5% had vitamin A deficiency and 1.7% had squint. No statistically significant association was found between ocular morbidity and any risk factors.Conclusions: Refractive error was found to be the most common ocular morbidity among pre-school children. This if detected early can be corrected. Therefore it is important to screen for refractive error at the preschool age itself and to create awareness among parents and anganwadi teachers regarding common ocular symptoms.