nils-herrmann/clean_scirepeval huggingface dataset:
A computational intelligence technique for the effective diagnosis of diabetic patients using principal component analysis (PCA) and modified fuzzy SLIQ decision tree approach

Display Omitted This paper uses Principle Component Analysis (PCA) for the dimensionality reduction of attributes in the Pima Indian Diabetes Data set (PID).This method uses false split point calculation to eliminate false split points in FSDT approach.The best attribute is identified using gini index measure.New fuzzy membership function is used to convert crisp set into fuzzy values.This approach given 76.8% average test accuracy with PID data set which is available in the UCI machine learning repository. Knowledge inference systems are built to identify hidden and logical patterns in huge data. Decision trees play a vital role in knowledge discovery but crisp decision tree algorithms have a problem with sharp decision boundaries which may not be implicated to all knowledge inference systems. A fuzzy decision tree algorithm overcomes this drawback. Fuzzy decision trees are implemented through fuzzification of the decision boundaries without disturbing the attribute values. Data reduction also plays a crucial role in many classification problems. In this research article, it presents an approach using principal component analysis and modified Gini index based fuzzy SLIQ decision tree algorithm. The PCA is used for dimensionality reduction, and modified Gini index fuzzy SLIQ decision tree algorithm to construct decision rules. Finally, through PID data set, the method is validated in the simulation experiment in MATLAB.
A computational intelligence technique for the effective diagnosis of diabetic patients using principal component analysis (PCA) and modified fuzzy SLIQ decision tree approach
Venue: Appl. Soft Comput.

Knowledge inference systems are built to identify hidden and logical patterns in huge data. Decision trees play a vital role in knowledge discovery but crisp decision tree algorithms have a problem with sharp decision boundaries which may not be implicated to all knowledge inference systems. A fuzzy decision tree algorithm overcomes this drawback. Fuzzy decision trees are implemented through fuzzification of the decision boundaries without disturbing the attribute values. Data reduction also plays a crucial omputational intelligence technique uzzy decision tree uzzification nowledge inference systems ini index LIQ ata reduction role in many classification problems. In this research article, it presents an approach using principal component analysis and modified Gini index based fuzzy SLIQ decision tree algorithm. The PCA is used for dimensionality reduction, and modified Gini index fuzzy SLIQ decision tree algorithm to construct decision rules. Finally, through PID data set, the method is validated in the simulation experiment in MATLAB.
Computational intelligence based machine learning methods for rule based reasoning in computer vision applications
Venue: 2016 IEEE Symposium Series on Computational Intelligence (SSCI)

In robot control, rule discovery for understanding of data is of critical importance. Basically, understanding of data depends upon logical rules, similarity evaluation and graphical methods. The expert system collects training examples separately by exploring an anonymous environment by using machine learning techniques. In dynamic environments, future actions are determined by sequences of perceptions thus encoded as rule base. This paper is focused on demonstrating the extraction and application of logical rules for image understanding, using newly developed Synergistic Fibroblast Optimization (SFO) algorithm with well known existing artificial learning methods. The SFO algorithm is tested in two modes: Michigan and Pittsburgh approach. Optimal rule discovery is evaluated by describing continuous data and verifying accuracy and error level at optimization phase. In this work, Monk's problem is solved by discovering optimal rules that enhance the generalization and comprehensibility of a robot classification system in classifying the objects from extracted attributes to effectively categorize its domain.
Doxorubicin/heparin composite nanoparticles for caspase activated prodrug chemotherapy.
Venue: Biomaterials

Caspase activated prodrug chemotherapy is introduced and demonstrated using the composite nanoparticles (NPs) which deliver doxorubicin (DOX) and DEVD S DOX together to the tumor tissue. DEVD S DOX, DOX linked to a peptide moiety (DEVD) is a prodrug that is cleaved into free DOX by caspase 3 upon apoptosis. DEVD S DOX has no therapeutic efficacy, but it changes into free DOX with the expression of caspase 3. With the accumulation of the composite NPs in the tumor tissue by the enhanced permeation and retention (EPR) effect, a small exposure of DOX in the tumor cells initiated apoptosis in a localized area of the tumor tissue, which induced caspase 3 activation. Cleavage of DEVD S DOX into free DOX by caspase 3 continued with repetitive activation of caspase 3 and cleavage of DEVD S DOX at the tumor site. The composite NPs were characterized with transmittance electron microscopy (TEM) and particle size analyzer. We then evaluated the nanoparticle drug release, therapeutic efficacy, and in vivo biodistribution for tumor targeting using a non invasive live animal imaging technology and the quantification of DOX with high performance liquid chromatography. DOX induced apoptosis targeted chemotherapy (DIATC) was verified by in vitro/in vivo DEVD S DOX response to free DOX and cellular uptake behavior of the composite NPs with flow cytometry analysis. Significant antitumor efficacy with minimal cardiotoxicity was also observed, which supported DIATC for improved chemotherapy.
E Commerce Consumer Behavior Information Big Data Mining

With the Internet applications in the commercial area of rapid spread, consumer demand driven experience of becoming a leading Internet development. At the same time, e commerce as the representative of the social network of constantly new changes. In computer systems and social integration of e commerce systems are highly interactive, the consumer bears an increasingly important role in consumer behavior characteristics and potential demand has become an important driving force for technological development. A large number of enterprises through the establishment of collaborative filtering recommendation systems predict consumer model, personalized recommendations and services to address the information overload problem. Based on the above requirements, in depth study of the progress of theoretical research services and service quality management theory, according to a large data analysis and complex network, is recommended by consumer behavior.
Business model development, founders' social capital and the success of early stage internet start ups: a mixed method study
Venue: Inf. Syst. J.

Information technology (IT) and entrepreneurship are more closely related than ever. The internet, in particular, inspires the current 'generation start up' While some early stage internet start ups have quickly become major successes, others fail to secure required follow up funding and collapse. In this paper, we build on and extend the emerging business model research stream with the aim of better understanding the differences between successful and unsuccessful early stage internet start ups. In the qualitative first part of our mixed method study, 17 expert informant interviews reveal that internet start up business models are in permanent flux, continually changed and adapted by founders, who identify their professional social network (i.e. their social capital) as a critically important factor for developing the business model and ultimately making their start ups successful. In the quantitative second part of the study, we test this claim based on a social network analysis of 70 internet start ups and their 145 founders. We find strong support for the critical importance of the founders' social capital for early stage internet start up success. The findings of this study advance our understanding of the relationship between founders' social capital, the development of business models and the success of early stage internet start ups.
Bottom Up Fixation Prediction Using Unsupervised Hierarchical Models
Venue: ACCV Workshops

Fixation prediction, also known as saliency modelling, has been a subject undergoing intense study in various contexts. In the context of assistive vision technologies, saliency modelling can be used for development of simulated prosthetic vision as part of the saliency based cueing algorithms. In this paper, we present an unsupervised multi scale hierarchical saliency model, which utilizes both local and global saliency pipelines. Motivated by bio inspired vision findings, we employ features from image statistics. Contrary to previous research, which utilizes one layer equivalent networks such as independent component analysis (ICA) or principle component analysis (PCA) we adopt independent subspace analysis (ISA) which is equivalent to a two layer neural architecture. The advantage of ISA over ICA and PCA is robustness towards translation meanwhile being selective to frequency and rotation. We extended the ISA networks by stacking them together, as done in deep models, in order to obtain a hierarchical representation. Making a long story short, (1) we define a framework for unsupervised fixation prediction, exploiting local and global saliency concept which easily generalizes to a hierarchy of any depth. (2) we assess the usefulness of the hierarchical unsupervised features, (3) we adapt the framework for exploiting the features provided by pre trained deep neural networks, (4) we compare the performance of different features and existing fixation prediction models on MIT1003, (5) we provide the benchmark results of our model on MIT300.
Arrangements Of Hyperplanes

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Relative Measurement Errors among Alternative Pension Asset and Liability Measures

This study investigates the measures of pension assets and liabilities disclosed under SFAS 87 to determine which most closely reflect those that investors implicitly assess when they value the firm. Several measures considered to have conceptual merit are disclosed under SFAS 87, but no single method has been deemed most appropriate. The attributes of the three asset and five liability measurement alternatives disclosed and the controversies surrounding the FASB's deliberations on these alternatives are considered in the research design. Because the pension asset and liability issues in SFAS 87 relate to measurement and reflect a variety of unresolved questions, an approach directly comparing measurement error across alternatives is used. The research design utilizes relevance and reliability, two primary accounting choice characteristics advanced by the FASB. These two attributes are operationalized by the variances and levels of differences between alternative measures and the implied investors' assessment. In most prior studies using cross sectional valuation to address a variety of research questions, a model is posited and then tested by using book values as substitutes for unobservable variables. The measurement error is considered an econometric problem. Although the valuation equation assumed here is also based on unobservable market values, the measurement error is modeled, and the impact of the measurement error
Pension Reform in China
Venue: Journal of aging social policy

This article analyzes China's pension arrangement and notes that China has recently established a universal non contributory pension plan covering urban non employed workers and all rural residents, combined with the pension plan covering urban employees already in place. Further, in the latest reform, China has discontinued the special pension plan for civil servants and integrated this privileged welfare class into the urban old age pension insurance program. With these steps, China has achieved a degree of universalism and integration of its pension arrangement unprecedented in the non Western world. Despite this radical pension transformation strategy, we argue that the current Chinese pension arrangement represents a case of "incomplete" universalism. First, its benefit level is low. Moreover, the benefit level varies from region to region. Finally, universalism in rural China has been undermined due to the existence of the "policy bundle." Additionally, we argue that the 2015 pension reform has created a situation in which the stratification of Chinese pension arrangements has been "flattened," even though it remains stratified to some extent.
The Health Implications of Social Pensions: Evidence from China's New Rural Pension Scheme

This paper estimates the causal effect of income on health outcomes of the elderly and investigates underlying mechanisms by exploiting an income change induced by the launch of China's New Rural Pension scheme (NRPS) Using this policy experiment, we address the endogeneity of pension income by applying a fixed effect model with instrumental variable correction. The results reveal that pension enrollment and income from the NRPS both have had a beneficial impact on objective measures of physical health, cognitive function, and psychological well being of the rural elderly, and also reduced mortality over a three year horizon by 6 percentage points. Evidence further suggests that pension recipients respond to the new pension income in multiple ways: improved nutrition intake, better accessibility to health care, increased informal care, increased leisure activities, and better self perceived relative economic situation. These in turn act as channels from pension income to health of the Chinese rural elderly.
Pension Reforms in the EU since the Early 2000's: Achievements and Challenges Ahead

Most EU Member States have carried out substantial pension reforms over the last decades in order to enhance fiscal sustainability, while maintaining adequate pension income. The intensity of pension reforms has been particularly strong since 2000. These reforms have been implemented through a wide range of measures that have substantially modified the pension system rules and parameters. One of the most important elements of pension reforms, aside of whether countries engaged or not in a systemic change, has been the introduction of mechanisms aimed at automatically adjusting (indexing) the key pension parameters (pension age, benefits, financing resources) to demographic pressure (e.g. changes in life expectancy, increase in the dependency ratio) Indeed, since the mid 1990's, half of the EU Member States have adopted either automatic balancing mechanisms, sustainability factors and or automatic links between retirement age and life expectancy. All these pension reforms are projected to have a substantial impact on containing future pension expenditure trends. According to the latest long term projections in the 2015 Ageing Report, public pension expenditure is projected to be close to 11% of GDP over the long run in the EU, almost the same as in 2013. However, the fiscal impact of ageing is still projected to be substantial in many EU countries, becoming apparent already over the course of the next two decades. This is also due to the very gradual phasing in of already legislated reforms, an issue that raises questions about the intergenerational fairness of the reforms and poses some doubt on the time consistency of their implementation. Indeed, the sustainability enhancing pension reforms legislated in a majority of EU countries will lead to a reduction of generosity of public pension schemes for future generations of retirees. But to make sure that these reforms will not have to face political and social resistance and risk of reversal in the moment they start to be implemented in full, other "flanking" policy measures are likely to be necessary: for example, reforms that boost retirement incomes by effectively extending working lives and employability of older workers (also through flexible working arrangements that allow people to keep working beyond current formal retirement age and to step down gradually from full time to part time to very part time work) and provide other means of retirement incomes (e.g. private pensions) and appropriate social safety nets to avoid that low wage people follow back in poverty at old age.
The Replacement Rate: An Imperfect Indicator of Pension Adequacy in Cross Country Analyses
Venue: Social indicators research

Pension systems are usually evaluated from the perspective of two basic criteria: pension adequacy and financial sustainability. The first criterion concerns the level of pension benefits and protection of the elderly from poverty. The second criterion applies to financial liquidity. This paper is primarily of methodological nature. We discuss the problem of measuring pension adequacy, focusing mainly on the replacement rate, which, defined in a number of ways, is the most common measure of pension adequacy. However, as we argue in this paper, it covers only one of its dimensions, namely consumption smoothing. Meanwhile, an equally important dimension, often discussed in the literature and included in most definitions of pension adequacy, is protection of old age pensioners from poverty. Accordingly, we have proved the thesis that the replacement rate is not a sufficient measure of broadly understood pension adequacy in cross country studies. Consequently, we have proposed alternative (or possibly complementary) measures called the synthetic pension adequacy indicators (SPAI1 3) defined in basic form as a quotient of relative median income and the at risk of poverty rate. These indicators provide for both the above mentioned dimensions of adequacy and, according to statistical analysis, also represent them very well. Moreover, the indicators, calculated separately for men and for women, enables evaluation of the third dimension of pension adequacy, namely gender related differences in pension adequacy.
Protection of Reinforced Concrete Structures of Waste Water Treatment Reservoirs with Stainless Steel Coating Using Arc Thermal Spraying Technique in Acidified Water
Venue: Materials

Waste water treatment reservoirs are contaminated with many hazardous chemicals and acids. Reservoirs typically comprise concrete and reinforcement steel bars, and the main elements responsible for their deterioration are hazardous chemicals, acids, and ozone. Currently, a variety of techniques are being used to protect reservoirs from exposure to these elements. The most widely used techniques are stainless steel plating and polymeric coating. In this study, a technique known as arc thermal spraying was used. It is a more convenient and economical method for protecting both concrete and reinforcement steel bar from deterioration in waste water treatment reservoirs. In this study, 316L stainless steel coating was applied to a concrete surface, and different electrochemical experiments were performed to evaluate the performance of coatings in different acidic pH solutions. The coating generated from the arc thermal spraying process significantly protected the concrete surface from corrosion in acidic pH solutions, owing to the formation of a double layer capacitance a mixture of Cr3+ enriched with Cr2O3 and Cr hydroxide in inner and Fe3+ oxide on the outer layer of the coating. The formation of this passive film is defective owing to the non homogeneous 316L stainless steel coating surface. In the pH 5 solution, the growth of a passive film is adequate due to the presence of un dissociated water molecules in the aqueous sulfuric acid solution. The coated surface is sealed with alkyl epoxide, which acts as a barrier against the penetration of acidic solutions. This coating exhibits higher impedance values among the three studied acidic pH solutions.
Imaging chiral symmetry breaking from Kekule bond order in graphene

Chirality or 'handedness' is a symmetry property crucial to fields as diverse as biology, chemistry and high energy physics. In graphene, chiral symmetry emerges naturally as a consequence of the carbon honeycomb lattice. This symmetry can be broken by interactions that couple electrons with opposite momenta in graphene. Here we directly visualize the formation of Kekule bond order, one such phase of broken chiral symmetry, in an ultraflat graphene sheet grown epitaxially on a copper substrate. We show that its origin lies in the interactions between individual vacancies in the copper substrate that are mediated electronically by the graphene. We show that this interaction causes the bonds in graphene to distort, creating a phase with broken chiral symmetry. The Kekule ordering is robust at ambient temperature and atmospheric conditions, indicating that intercalated atoms may be harnessed to drive graphene and other two dimensional materials towards electronically desirable and exotic collective phases. Scanning tunnelling microscopy shows how the interaction between electrons in graphene and atomic vacancies in a copper substrate produces Kekule ordering an electronic phase that breaks chiral symmetry.
Catalysis of dynamical chiral symmetry breaking by chiral chemical potential

In this paper we study the properties of media with chiral imbalance parameterized by chiral chemical potential. It is shown that depending on the strength of interaction between constituents in the media the chiral chemical potential either creates or enhances dynamical chiral symmetry breaking. Thus the chiral chemical potential plays a role of the catalyst of dynamical chiral symmetry breaking. Physically this effect results from the appearance of the Fermi surface and additional fermion states on this surface which take part in dynamical chiral symmetry breaking. An interesting conclusion which can be drawn is that at sufficiently small temperature chiral plasma is unstable with respect to condensation of Cooper pairs and dynamical chiral symmetry breaking even for vanishingly small interactions between constituents.
Realization of chiral symmetry breaking and restoration in holographic QCD

With proper profiles of the scalar potential and the dilaton field, for the first time, the spontaneous chiral symmetry breaking in the vacuum and its restoration at finite temperature are correctly realized in the holographic QCD framework. In the chiral limit, a nonzero chiral condensate develops in the vacuum and decreases with temperature, and the phase transition is of the second order for a two flavor case and of the first order for a three flavor case. In the case of explicit chiral symmetry breaking, in the two flavor case, the second order phase transition turns into a crossover with any nonzero current quark mass, and in the three flavor case, the first order phase transition turns into a crossover at a finite current quark mass. The correct description of chiral symmetry breaking and restoration makes the holographic QCD models more powerful in dealing with nonperturbative QCD phenomena. This framework can be regarded as a general setup in an application of AdS/CFT to describe conventional Ginzburg Landau Wilson type phase transitions, e.g. in condensed matter and cosmology systems.