nils-herrmann/clean_scirepeval huggingface dataset:
A Comparison of Service Quality on Customer Satisfaction towards Music Product Website in Indonesia and India
Venue: 2018 International Conference on Sustainable Energy, Electronics, and Computing Systems (SEEMS)
Year: 2018

The development of information technology has opened the eyes of the world to a new world, new interactions, new market place, and an infinite business network. One proof of the development of these technologies is the Internet, which is causing information technology to make a positive impact on the people. Quite much it has changed the lifestyle of primitive Indonesian and Indian society transforming them into modern societies an evolving parabola. For instance, it has created new types of business opportunities where business transactions are increasingly being made electronically, referred to as click and mortar. There has been an increased awareness about almost everything from traditional product selling through booking orders to downloading commodities like entertainment (read music) for instant consumption. The growing popularity of such websites shows a rise in their demand but what is not clear is satisfaction customers may have with them. This research places an effort to understand the effect of service quality on customer satisfaction on music product websites with respondents from Indonesia and India, and compares are there any differences in consumer attitudes in these countries. It was observed that responsiveness, assurance, and empathy affect on customer satisfaction of music product website and tangibles, reliability and responsiveness have same impact for both countries, but assurance, empathy and customer satisfaction differ. This is an important milestone in understanding customer's intention in buying music online in both the countries.
Plastic flexible films waste management A state of art review.
Venue: Waste management
Year: 2018

Plastic flexible films are increasingly used in many applications due to their lightness and versatility. In 2014, the amount of plastic films represented 34% of total plastic packaging produced in UK. The flexible film waste generation rises according to the increase in number of applications. Currently, in developed countries, about 50% of plastics in domestic waste are films. Moreover, about 615,000 tonnes of agricultural flexible waste are generated in the EU every year. A review of plastic films recycling has been conducted in order to detect the shortcomings and establish guidelines for future research. This paper reviews plastic films waste management technologies from two different sources: post industrial and post consumer. Clean and homogeneous post industrial waste is recycled through closed loop or open loop mechanical processes. The main differences between these methods are the quality and the application of the recycled materials. Further research should be focused on closing the loops to obtain the highest environmental benefits of recycling. This could be accomplished through minimizing the material degradation during mechanical processes. Regarding post consumer waste, flexible films from agricultural and packaging sectors have been assessed. The agricultural films and commercial and industrial flexible packaging are recycled through open loop mechanical recycling due to existing selective waste collection routes. Nevertheless, the contamination from the use phase adversely affects the quality of recycled plastics. Therefore, upgrading of current washing lines is required. On the other hand, household flexible packaging shows the lowest recycling rates mainly because of inefficient sorting technologies. Delamination and compatibilization methods should be further developed to ensure the recycling of multilayer films. Finally, Life Cycle Assessment (LCA) studies on waste management have been reviewed. A lack of thorough LCA on plastic films waste management systems was identified.
Semi supervised Classification Using Feature Distribution
Year: 2012

It is crucial for semi supervised learning(SSL) to cut down the dimension of the feature space through feature selection.The popular information gain(IG) selection method,which inclines to high frequency words,always ignores similarity of classes.Thus,the classification performance of characteristics IG is unstable.This paper puts forward a feature distribution selection to help IG retain features possessing high categories discriminative information.To solve the inherent efficiency problem of the expectation maximization(EM) algorithm,unlabeled documents that possess maximum posterior category probability are transferred from unlabeled collection to labeled collection.The iteration number of the improved EM is obviously reduced.Finally,experimental evaluation on Reuter 21578 and Epinion.com with two different data sets shows that the semi supervised learning method using feature distribution obtains very effective performance for micro average F1 criterion.
Digital image security based on data hiding and cryptography
Venue: 2017 3rd International Conference on Information Management (ICIM)
Year: 2017

The implementation of a system that combines encryption standards with watermarking techniques to provide security to exchanged medical images is the main concern of this paper. The system is based on a hybrid algorithm that applies the techniques of encryption and watermarking to offer different security features to medical images transmitted between healthcare entities. Based on the proposed algorithm, the authenticity and integrity of the transmitted images can be verified either in the spatial domain or in the encrypted domain or in both domains. This is achieved by joining the watermarked image and its encrypted version after embedding two unique watermarks; one in the plain image and one in the encrypted image. The proposed algorithm makes use of the concept of bit planes where two images consists of 8 bit planes combined to form a single image having 16 bit planes. The algorithm provides high embedding capacity while keeping low computational complexity.
Sociodemographic Predictors of HIV Infection among Pregnant Women in Botswana: Cross Sectional Study at 7 Health Facilities
Venue: Journal of the International Association of Providers of AIDS Care
Year: 2020

To determine the prevalence and sociodemographic predictors of HIV among pregnant women in Botswana.  This was a cross sectional study of randomly enrolled women aged 18 to 49 years, attending 7 health facilities in Botswana. Data were gathered from November 2017 to March 2018 and analyzed using SPSS version 24.  Of the 429 women enrolled, 407 (96.4% were included in the analysis. The HIV prevalence was 17% 69 of 407 (95% CI: 13.4 21.0) Women aged 35 to 49 years had higher HIV prevalence than those 18 to 24 years (adjusted odds ratio [AOR] 6.2; 95% CI: 2.7 14.4) Illiterate and elementary school educated women had higher HIV prevalence than those with a tertiary education (AOR 8.5; 95% CI: 1.8 39.1) Those with a history of alcohol intake had a higher HIV prevalence than those without (AOR 2.6; 95% CI: 1.3 5.3)  HIV prevalence was lower than it was in 2011. Age, level of education, and history of alcohol intake were strong predictors for HIV infection calling for targeted behavioral change interventions.
A Survey on Link Prediction Problem in Social Networks
Year: 2017

Link prediction is a crucial task in analysis of online social networks. It can be used for friend recommendations in social networks. It also has applications in other areas like bioinformatics, information retrieval and e commerce. Currently, variety of techniques is available to deal with link prediction problem, ranging from local feature based approaches to global feature based approaches. Some recent techniques combine the advantages of these two approaches and comes under hybrid category. all these methods differ from each other with respect to prediction performance in terms of accuracy, efficiency, and generalization ability. In this paper, we survey some representative link prediction techniques under each category. We largely consider three types of approaches. First category is of local feature based approaches which do not exploit the whole network structure. Second category is of global feature based approaches which use the overall path structure of a network. And, finally the hybrid approaches which combine the advantages of above two approaches (local and global) in computation of similarity scores between each pair of nodes in a network. We discuss some recent existing approaches corresponding to these broad categories and analyze their strength and weaknesses. We conclude the paper with discussion on recent developments and future research direction.
Is My Network Module Preserved and Reproducible?
Venue: PLoS Comput. Biol.
Year: 2011

In many applications, one is interested in determining which of the properties of a network module change across conditions. For example, to validate the existence of a module, it is desirable to show that it is reproducible (or preserved) in an independent test network. Here we study several types of network preservation statistics that do not require a module assignment in the test network. We distinguish network preservation statistics by the type of the underlying network. Some preservation statistics are defined for a general network (defined by an adjacency matrix) while others are only defined for a correlation network (constructed on the basis of pairwise correlations between numeric variables) Our applications show that the correlation structure facilitates the definition of particularly powerful module preservation statistics. We illustrate that evaluating module preservation is in general different from evaluating cluster preservation. We find that it is advantageous to aggregate multiple preservation statistics into summary preservation statistics. We illustrate the use of these methods in six gene co expression network applications including 1) preservation of cholesterol biosynthesis pathway in mouse tissues, 2) comparison of human and chimpanzee brain networks, 3) preservation of selected KEGG pathways between human and chimpanzee brain networks, 4) sex differences in human cortical networks, 5) sex differences in mouse liver networks. While we find no evidence for sex specific modules in human cortical networks, we find that several human cortical modules are less preserved in chimpanzees. In particular, apoptosis genes are differentially co expressed between humans and chimpanzees. Our simulation studies and applications show that module preservation statistics are useful for studying differences between the modular structure of networks. Data, R software and accompanying tutorials can be downloaded from the following webpage: http:/www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/ModulePreservation.
Joint Optimization of Multi UAV Target Assignment and Path Planning Based on Multi Agent Reinforcement Learning
Venue: IEEE Access
Year: 2019

One of the major research topics in unmanned aerial vehicle (UAV) collaborative control systems is the problem of multi UAV target assignment and path planning (MUTAPP) It is a complicated optimization problem in which target assignment and path planning are solved separately. However, recalculation of the optimal results is too slow for real time operations in dynamic environments because of the large number of calculations required. In this paper, we propose an artificial intelligence method named simultaneous target assignment and path planning (STAPP) based on a multi agent deep deterministic policy gradient (MADDPG) algorithm, which is a type of multi agent reinforcement learning algorithm. In STAPP, the MUTAPP problem is first constructed as a multi agent system. Then, the MADDPG framework is used to train the system to solve target assignment and path planning simultaneously according to a corresponding reward structure. The proposed system can deal with dynamic environments effectively as its execution only requires the locations of the UAVs, targets, and threat areas. Real time performance can be guaranteed as the neural network used in the system is simple. In addition, we develop a technique to improve the training effect and use experiments to demonstrate the effectiveness of our method.
Evaluacion de la calidad de vida en pacientes con cancer terminal
Year: 2013

Assessment of quality of life in patients with terminal cancer  Research on life quality of cancer patients allows giving the attention back to the patient and his/her needs.  FACT G survey was performed to 77 terminal cancer patients on the Palliative Care and Pain Relief unit from Iquique's General Hospital.  Physical welfare was eva luated with a 21.22 out of a maximum of 28, social/familiar welfare had a 12.57 over 28, emotional welfare was 16 over 24 and functional welfare had 17.33 over 28. Final score, which represents the sum of the four prior divisions, with a scale from 0 to 108, was 67.62% of the maximum score.  Performance of life quality surveys is feasible for cancer patients, and allows us to make specific interventions on the patient and his/her close ones to improve his/her life quality.
Comparing Functional Connectivity Matrices: A Geometry Aware Approach applied to Participant Identification
Venue: NeuroImage
Year: 2020

Understanding the correlation structure associated with multiple brain measurements informs about potential "functional groupings" and network organization. The correlation structure can be conveniently captured in a matrix format that summarizes the relationships among a set of brain measurements involving two regions, for example. Such functional connectivity matrix is an important component of many types of investigation focusing on network level properties of the brain, including clustering brain states, characterizing dynamic functional states, performing participant identification (so called "fingerprinting" understanding how tasks reconfigure brain networks, and inter subject correlation analysis. In these investigations, some notion of proximity or similarity of functional connectivity matrices is employed, such as their Euclidean distance or Pearson correlation (by correlating the matrix entries) Here, we propose the use of a geodesic distance metric that reflects the underlying non Euclidean geometry of functional correlation matrices. The approach is evaluated in the context of participant identification (fingerprinting) given a participant's functional connectivity matrix based on resting state or task data, how effectively can the participant be identified? Using geodesic distance, identification accuracy was over 95% on resting state data, and exceeded the Pearson correlation approach by 20% For whole cortex regions, accuracy improved on a range of tasks by between 2% and as much as 20% We also investigated identification using pairs of subnetworks (say, dorsal attention plus default mode) and particular combinations improved accuracy over whole cortex participant identification by over 10% The geodesic distance also outperformed Pearson correlation when the former employed a fourth of the data as the latter. Finally, we suggest that low dimensional distance visualizations based on the geodesic approach help uncover the geometry of task functional connectivity in relation to that during resting state. We propose that the use of the geodesic distance is an effective way to compare the correlation structure of the brain across a broad range of studies.
Worldwide Increasing Divorce Rates: A Sociological Analysis
Year: 2020

The article explores how change in lifestyles has impacted the family relations leading to divorce worldwide more in industrial countries, and to a smaller extent in developing countries. Sociologically speaking, the main cause of such increase in divorce event is social change emerging due to modernization and industrialization, more education for them, change in women's consumption behavior etc. All such trends are affecting the family adjustability and the mutual respect and tolerance, leading to challenges and conflicts toward divorces. Divorce, though not being a huge problem in the Western world, it is problem creating in the developing countries. Being a stigma in many such countries, the divorced women face lots of social and economic issues. Many of such women cannot easily remarry, and eventually deviate from the right and regular way of life. The children of divorce also lose a lot of advantages such as socialization, family/parents' affections etc. The method of research used in the present article is of qualitative type. In conclusion, it is proved that in societies with minimum divorce, more family and social health could be maintained.
Measuring phase amplitude coupling between neuronal oscillations of different frequencies.
Venue: Journal of neurophysiology
Year: 2010

Neuronal oscillations of different frequencies can interact in several ways. There has been particular interest in the modulation of the amplitude of high frequency oscillations by the phase of low frequency oscillations, since recent evidence suggests a functional role for this type of cross frequency coupling (CFC) Phase amplitude coupling has been reported in continuous electrophysiological signals obtained from the brain at both local and macroscopic levels. In the present work, we present a new measure for assessing phase amplitude CFC. This measure is defined as an adaptation of the Kullback Leibler distance a function that is used to infer the distance between two distributions and calculates how much an empirical amplitude distribution like function over phase bins deviates from the uniform distribution. We show that a CFC measure defined this way is well suited for assessing the intensity of phase amplitude coupling. We also review seven other CFC measures; we show that, by some performance benchmarks, our measure is especially attractive for this task. We also discuss some technical aspects related to the measure, such as the length of the epochs used for these analyses and the utility of surrogate control analyses. Finally, we apply the measure and a related CFC tool to actual hippocampal recordings obtained from freely moving rats and show, for the first time, that the CA3 and CA1 regions present different CFC characteristics.
Fiber Bragg Grating Sensors Based In Situ Monitoring and Safety Assessment of Loess Tunnel
Venue: J. Sensors
Year: 2016

Compared with electrical strain gauges, fiber Bragg grating (FBG) sensing technology is a relatively novel method for tunnel structural health monitoring, which has a number of advantages including high accuracy, multiplexing, electromagnetic interference resistance, and good repeatability. In order to study the internal force of the tunnel liner and detect the potential safety hazards, series of strain monitoring tests of a loess tunnel, taking into account the complex stress and strain variation of the loess during tunnelling, were performed by employing the tandem linear FBG sensor arrays controlled by the wavelength division multiplexing (WDM) technology. The concrete strain has obvious linear characteristics over time in the early stage and then gradually tends to a stable value. Moreover, after the necessary temperature compensation, loess tunnel structure safety was assessed through the analysis of real time strain and internal force of the liner concrete, and the FBG monitoring data and safety assessment results indicate that the safety factors of various liner sections all meet the code requirements, which verify the safety and stability of the tunnel liner structure. The FBG sensors based in situ monitoring technology can be well applied in the loess tunnel structure safety assessment.
Improving ancient DNA read mapping against modern reference genomes
Venue: BMC Genomics
Year: 2011

BackgroundNext Generation Sequencing has revolutionized our approach to ancient DNA (aDNA) research, by providing complete genomic sequences of ancient individuals and extinct species. However, the recovery of genetic material from long dead organisms is still complicated by a number of issues, including post mortem DNA damage and high levels of environmental contamination. Together with error profiles specific to the type of sequencing platforms used, these specificities could limit our ability to map sequencing reads against modern reference genomes and therefore limit our ability to identify endogenous ancient reads, reducing the efficiency of shotgun sequencing aDNA.ResultsIn this study, we compare different computational methods for improving the accuracy and sensitivity of aDNA sequence identification, based on shotgun sequencing reads recovered from Pleistocene horse extracts using Illumina GAIIx and Helicos Heliscope platforms. We show that the performance of the Burrows Wheeler Aligner (BWA) that has been developed for mapping of undamaged sequencing reads using platforms with low rates of indel types of sequencing errors, can be employed at acceptable run times by modifying default parameters in a platform specific manner. We also examine if trimming likely damaged positions at read ends can increase the recovery of genuine aDNA fragments and if accurate identification of human contamination can be achieved using a strategy previously suggested based on best hit filtering. We show that combining our different mapping and filtering approaches can increase the number of high quality endogenous hits recovered by up to 33%.ConclusionsWe have shown that Illumina and Helicos sequences recovered from aDNA extracts could not be aligned to modern reference genomes with the same efficiency unless mapping parameters are optimized for the specific types of errors generated by these platforms and by post mortem DNA damage. Our findings have important implications for future aDNA research, as we define mapping guidelines that improve our ability to identify genuine aDNA sequences, which in turn could improve the genotyping accuracy of ancient specimens. Our framework provides a significant improvement to the standard procedures used for characterizing ancient genomes, which is challenged by contamination and often low amounts of DNA material.
Blockchain, adoption, and financial inclusion in India: Research opportunities
Venue: Int. J. Inf. Manag.
Year: 2020

The economic development of rural India requires connecting remote villages to local and global supply chains. Yet, high rates of financial exclusion inhibit rural Indians from participating in these supply networks. We review the literature on financial inclusion, adoption, and blockchain in India, and posit that to resolve financial exclusion, the four challenges of geographical access, high cost, inappropriate banking products, and financial illiteracy need to be overcome. Next, we argue that blockchain technologies hold the potential to overcome most of these challenges. However, for blockchain technologies to become the cornerstone of financial inclusion initiatives, an understanding of technology adoption in India is needed. To guide the development of such understanding, we develop a research agenda on the antecedents of adoption, adoption patterns, and outcomes of adoption. Answering these research questions will lead to a nuanced understanding of adoption of blockchain based technologies in rural India. The practical contribution of this paper is the discussion of how blockchain can alleviate the issue of financial exclusion in rural India, thereby providing a basis for a solution that could connect rural Indians to global supply chain networks. The theoretical contribution lies in the identification of knowledge gaps that should be answered to achieve financial inclusion of rural Indians.