nils-herrmann/clean_scirepeval huggingface dataset:
H/LQR optimal control for a supersonic air breathing missile of asymmetric configuration
Year: 2019

Robust control is challenging to achieve for air breathing missiles operating in a high Mach number regime, such as at high supersonic speeds (M 3) The challenge arises because of strong couplings, significant non linearities and large uncertainties in the aerodynamics and propulsion system. The feasibility of achieving robust control in such applications is strongly linked to the development of an appropriate control design structure. The purpose of this paper is to illustrate that in order to stabilise a highly unstable airframe and achieve the required performance, a hybrid of two control schemes may be used to achieve best results. A state feedback linear quadratic regulator is used to stabilise the plant and a forward path H optimal controller is used to achieve the required performance and robustness. We also highlight the complementary attributes of the two control schemes that together can generate a more robust controller; LQR is used since it can achieve good gain and phase margins, whereas, the H control method is better equipped to deal with uncertainties.
Model Checking PBFT Consensus Mechanism in Healthcare Blockchain Network
Venue: 2018 9th International Conference on Information Technology in Medicine and Education (ITME)
Year: 2018

Now blockchain network is used in many areas such as healthcare, energy trading and so on. However, the research about how to evaluate the performance of the blockchain network is insufficient. In some papers, the performance of blockchain is analyzed by running real blockchain applications. However, the devices and services cost is a burden. In this paper, we aim to use continuous time Markov chain (CTMC) models to simulate the time response of PBFT (Practical Byzantine Fault Tolerance) based healthcare blockchain network. Some influencing factors such as replica nodes delay and primary node delay will be analyzed. The simulation results also contribute to the optimization design of blockchain network.
ANALISIS POLA PERGESERAN JUDUL SKRIPSI DI PROGRAM PENDIDIKAN SOSIOLOGI ANTROPOLOGI FKIP UNIVERSITAS SEBELAS MARET
Year: 2016

ABSTRAK Ali Firmansyah. K8408024. ANALISIS POLA PERGESERAN JUDUL SKRIPSI DI PROGRAM PENDIDIKAN SOSIOLOGI ANTROPOLOGI FKIP UNIVERSITAS SEBELAS MARET Skripsi: Fakultas Keguruan dan Ilmu Pendidikan Universitas Sebelas Maret Surakarta. April 2016. Peneltian ini menggambarkan pola pergeseran judul skripsi oleh mahasiswa program pendidikan sosiologi antropologi FKIP UNS. Penelitian ini adalah hasil dari penelitian dari literatur atau dokumentasi, dengan menggunakan jenis penelitian deskriptif kualitatif. Hasil penelitian ini menunjukkan adanya pola pergeseran judul skripsi mahasiswa Program Pendidikan Sosiologi Antroplogi FKIP UNS, Dengan beberapa alasan sebagai berikut, Pertama, Pola pergeseran Judul skripsi dipengaruhi dengan norma hukum atau peraturan yang berlaku pada saat itu, Kedua, pergeseran yang penentuan judul skripsi, tergantung pada ruang sosial mahasiwa (pergaulan dan lingkungan mahasiwa) Ketiga, Standar kompetensi lulusan yang diharapkan oleh institusi pendidikan dimana akhirnya para lulusan akan berkerja, Keempat, akses terhadap informasi akan penelitian penelitian dan perkembangan teori teori baru yang berkembang di seluruh dunia.  Pola Pergeseran, Judul Skripsi,
Droop Free Colloidal Quantum Dot Light Emitting Diodes.
Venue: Nano letters
Year: 2018

Colloidal semiconductor quantum dots (QDs) are a highly promising materials platform for implementing solution processable light emitting diodes (LEDs) They combine high photostability of traditional inorganic semiconductors with chemical flexibility of molecular systems, which makes them well suited for large area applications such as television screens, solid state lighting, and outdoor signage. Additional beneficial features include size controlled emission wavelengths, narrow bandwidths, and nearly perfect emission efficiencies. State of the art QD LEDs exhibit high internal quantum efficiencies approaching unity. However, these peak values are observed only at low current densities J) and correspondingly low brightnesses, whereas at higher J, the efficiency usually exhibits a quick roll off. This efficiency droop limits achievable brightness levels and decreases device longevity due to excessive heat generation. Here, we demonstrate QD LEDs operating with high internal efficiencies (up to 70% virtually droop free up to unprecedented brightness of >100,000 cd m 2 (at ~500 mA cm 2) This exceptional performance is derived from specially engineered QDs that feature a compositionally graded interlayer and a final barrier layer. This QD design allows for improved balance between electron and hole injections combined with considerably suppressed Auger recombination, which helps mitigate efficiency losses due to charge imbalance at high currents. These results indicate a significant potential of newly developed QDs as enablers of future ultrabright, highly efficient devices for both indoor and outdoor applications.
Extending Linear Discriminant Analysis by Using Unlabeled Data
Venue: 2011 IEEE 11th International Conference on Computer and Information Technology
Year: 2011

Linear discriminant analysis(LDA) is a traditional dimension reduction method which finds projective directions to maximize separability between classes. However, when the number of labeled data points is small, the performance of LDA is degraded severely. In this paper, we propose two improved methods for LDA which utilizes abundant unlabeled data. Instead of using all the unlabeled data as in most of semi supervised dimension reduction methods, we select confident unlabeled data and develop extended LDA algorithms. In the first method, a graph based LDA method is developed to utilize confidence scores for chosen unlabeled data so that unlabeled data with a low confidence score contributes smaller than unlabeled data with a high confidence score. In the second method, selected unlabeled data points are used to modify the centroids of classes in an objective function of LDA. Extensive experimental results in text classification demonstrates the effectiveness of the proposed methods compared with other semi supervised dimension reduction methods.
Modelling the negative effects of landscape fragmentation on habitat selection
Venue: Ecol. Informatics
Year: 2015

Landscape fragmentation constrains movement of animals between habitat patches. Fragmentation may, therefore, limit the possibilities to explore and select the best habitat patches, and some animals may have to cope with low quality patches due to these movement constraints. If so, these individuals experience lower fitness than individuals in high quality habitat. I explored this negative effect of fragmentation on habitat selection in a modelling study. Model landscapes were generated containing different amounts of habitat with differences in the degree of connectivity. In these landscapes, the behaviour of two model species was simulated with different dispersal ranges. I found that habitat selection of the species with limited dispersal range increasingly deviates from optimal selection when fragmentation increases. This effect of fragmentation on habitat selection largely limits the spatial distribution of species with limited dispersal range because constrained habitat selection is expected to result in lower mean reproductive output when more individuals occur in low quality habitat. In addition to the often suggested causes for extinction in small, isolated patches, i.e. increased sensitivity to environmental and demographic stochasticity, constrained habitat selection may lead to an increase in extinction probability of populations when a large fraction of the individuals occur in low quality habitat.
Hydromagnetic Oscillatory Couette Flow of a Visco Elastic Fluid with Dust in a Channel with Radiative Heat
Venue: Advances in Intelligent Systems and Computing
Year: 2021

A theoretical study of the oscillatory Couette flow of visco elastic fluid with non conducting dust is under consideration. The motion of fluid along with dust particles through a porous medium is under constant pressure gradient along with radiative heat transfer in a vertical channel. In this study, second order fluid characterizes the non Newtonian fluid and also considering dusty fluid model into account. A uniform magnetic field of strength B0 is applied perpendicular to the flow region. The left wall of the channel is fixed and right wall of the channel is oscillating with time. The governing equations are solved by applying perturbation method. The impact of visco elastic parameter on velocity of fluid, dust particles and skin friction have been shown graphically along with the other non dimensional parameter involved in this study.
OBSOLETE: 6th Mass Extinction
Year: 2013

There have been five past mass extinctions during the history of Earth. We have entered a 6th mass extinction. The 6th mass extinction (also referred to as the Anthropocene extinction) is an ongoing current event where a large number of living species are threatened with extinction or are going extinct because of the environmentally destructive activities of humans. This article presents an overview of Earth's five past mass extinctions, an overview of the current 6th mass extinction, current and future rates of species extinction associated with the ongoing 6th mass extinction, and past and present human activities associated with the 6th mass extinction.
Sensitive Acetylcholinesterase Biosensor Based on Screen Printed Carbon Electrode Modified with Cerium Oxide Chitosan/Mesoporous Carbon Chitosan for Organophosphorus Pesticide Residue Detection
Year: 2018

A novel electrochemical acetylcholinesterase (AChE) biosensor modified with cerium oxide chitosan (CeO2 CS) and ordered mesoporous carbon chitosan (OMC CS) using a screen printed carbon electrode (SPCE) was fabricated to detect organophosphorus pesticides (OPs) Compared with a common electrode, SPCEs do not need to be polished, can be conveniently carried, and are suitable for on site detection. CeO2 has good redox properties and a larger electron transfer rate. In addition, OMC has good electrical conductivity and a larger specific surface area, and chitosan (CS) has a considerable number of hydroxyl and amine groups in polymer chains, which have strong complexation ability. Herein, CeO2 CS and OMC CS were modified in the SPCE layer by layer to improve the electrochemical response and increase the fixed amount of AChE. The results obtained with this biosensor revealed that its sensitivity was significantly improved. Taking into account the possible interaction between the test conditions, the experimental parameters were optimized using a quadratic orthogonal rotation combination design to achieve a high electrochemical signal. The properties of AChE/OMC CS/CeO2 CS/SPCE were characterized by differential pulse voltammetry and cyclic voltammetry techniques. Under optimum conditions, the fabricated acetylcholinesterase biosensor showed great reproducibility and high stability. In addition, the as prepared AChE biosensor was successfully utilized for analysis of OPs in vegetables.
Magneto thermoelastic response in a functionally graded rotating medium due to a periodically varying heat source
Year: 2015

This paper deals with the problem of magneto thermoelastic interactions in a functionally graded isotropic, unbounded, rotating medium due to a periodically varying heat source in the context of the linear theory of generalized thermoelasticity without energy dissipation and with energy dissipation. The governing equations of generalized thermoelasticity (GN model) for a functionally graded material under the influence of a magnetic field are established. The Laplace Fourier double transform technique has been used to get the solution. The inversion of Fourier transform is done by using residual calculus, where the poles of the integrand are obtained numerically in the complex domain by using Laguerre's method, and the inversion of the Laplace transformation is done numerically using a method based on Fourier series expansion technique. The numerical estimates for displacements, temperature and stress are obtained for a hypothetical material. The solution to the analogous problem is obtained by taking a suitable non homogeneous parameter. Finally, the results obtained are presented graphically to show the effect of rotation, non homogeneity, damping coefficient and magnetic field on displacements, temperature and stress.
Enhancing the Role of Geoconservation in Protected Area Management and Nature Conservation
Venue: Geoheritage
Year: 2017

Acknowledgement by the International Union for the Conservation of Nature (IUCN) that geodiversity is part of natural diversity and geoheritage is part of natural heritage should help to strengthen the position and delivery of geoconservation through engagement with the wider nature conservation agenda. In particular, we identify six key areas offering opportunities to enhance the standing and mainstreaming of geoconservation: (1) integrating geoconservation principles in protected area management, including the promotion of geoheritage conservation across the full range of IUCN Protected Area Management Categories; (2) supporting biodiversity conservation and adaptation to climate change through the nature based solutions approach and 'conserving nature's stage' (3) contributing to natural capital and ecosystem services valuation; (4) contributing to conservation in the marine environment; (5) enhancing the connections between people, place, and nature and contributing to human well being; and (6) promoting ecosystem stewardship and contributing to the achievement of the UN Sustainable Development Goals. Adoption of a more outward looking approach should help to progress the integration of geoconservation within nature conservation, protected area planning and management, and broader environmental strategies and policies.
Decision support models for optimal personalized marketing interventions in insurance
Year: 2015

In many important settings, subjects can show significant heterogeneity in response to a stimulus or "treatment" The notion that "one size may not fit all" is becoming increasingly recognized in a wide variety of fields, ranging from economics to medicine. This has drawn significant attention to personalize the choice of treatment, so it is optimal for each individual. An optimal personalized treatment is the one that maximizes the probability of a desirable outcome. We call the task of learning the optimal personalized treatment personalized treatment learning. From the statistical learning perspective, this problem imposes important challenges, primarily because the optimal treatment is unknown on a given training set. A number of statistical methods have been proposed recently to tackle this problem. The purpose of this paper is to show that causal conditional inference trees and its natural extension to causal conditional inference forests can provide a solution to the purpose of selecting the best targets for cross selling an insurance product. We will discuss its usefulness in insurance pricing and retention as well.
'A progress that threatens all life' Nature vs. nurture in Duncan Williamson's 'Mary and the seal'
Year: 2020

The paper first discusses two documentaries by Donna Read, Signs Out of Time (2004) and Goddess Remembered (1989) that focus on the pacific tradition of the female centered settlements on the territories of modern Eastern Europe in the Neolithic and Bronze Ages. Read depicts significant findings of a world renowned archeologist Marija Gimbutas who claims that a peaceful image of Old Europe embodied in the omnipotent Great Mother changed radically towards the end of the third millennium when violent Indo European nomads came from Russia and shattered the matriarchal utopia of equality and natural harmony. These tribes introduced the principles of hierarchy and violent male rule. Read's and Gimbutas' findings are further developed and examined in the studies by Riana Eisler and Erich Fromm who also claim that conspicuous material aggrandizement of patriarchal culture severely damaged a blissful matriarchal bond between man and nature. These theoretical insights are applied to Williamson's comprehension of nature vs. nurture issue in "Mary and the Seal" (1997) In portraying a tender relationship between Mary and the seal, as well as its tragic and totally unnecessary shooting, contemporary patriarchal culture is brought to a trial. The mere existence of the bond between Mary and the seal, an embodiment of an idyllic matriarchal unity between man and nature, testifies to the prevalent need for the return to its substantial but 1 mkostic76@gmail.com This paper was submitted on August 18th, 2020 and accepted for publication at the meeting of the Editorial Board held on September 25th, 2020.  212 MILENA M. KALICANIN long forgotten values. The theoretical insights of Graves, Althusser, Freire, Fiske and Miller will also be used in the interpretation of the story.
(Re) discovering the business purpose
Year: 2019

This study aims to focus on the purpose and legitimacy of business, notably, the organizational purpose, the conventional view that the purpose of business is to optimize the returns to shareholders, and the emerging view that organizations serve multiple purposes including economic returns.,This study applies Habermas's discourse ethics to corporate social responsibility (CSR) and stakeholder management (SHM) and argues that discourse ethics is a balanced philosophical approach, which can effectively address the limitations of CSR and SHM.,The analysis demonstrates that discourse ethics is a distinctive philosophical approach to ethical theory and has high relevance to the field of CSR and SHM.,The discursive approach to CSR and SHM is unique because it allows assimilating various ethical situations from pragmatic to normative under one theoretical framework. The potential of the proposed approach is illustrated through a thorough discussion of its application to CSR and SHM.
Speech Emotion Recognition Using Scalogram Based Deep Structure
Year: 2020

Speech Emotion Recognition (SER) is an important part of speech based Human Computer Interface (HCI) applications. Previous SER methods rely on the extraction of features and training an appropriate classifier. However, most of those features can be affected by emotionally irrelevant factors such as gender, speaking styles and environment. Here, an SER method has been proposed based on a concatenated Convolutional Neural Network (CNN) and a Recurrent Neural Network (RNN) The CNN can be used to learn local salient features from speech signals, images, and videos. Moreover, the RNNs have been used in many sequential data processing tasks in order to learn long term dependencies between the local features. A combination of these two gives us the advantage of the strengths of both networks. In the proposed method, CNN has been applied directly to a scalogram of speech signals. Then, the attention mechanism based RNN model was used to learn long term temporal relationships of the learned features. Experiments on various data such as RAVDESS, SAVEE, and Emo DB demonstrate the effectiveness of the proposed SER method.
Point Voxel CNN for Efficient 3D Deep Learning
Venue: NeurIPS
Year: 2019

We present Point Voxel CNN (PVCNN) for efficient, fast 3D deep learning. Previous work processes 3D data using either voxel based or point based NN models. However, both approaches are computationally inefficient. The computation cost and memory footprints of the voxel based models grow cubically with the input resolution, making it memory prohibitive to scale up the resolution. As for point based networks, up to 80% of the time is wasted on structuring the irregular data which have rather poor memory locality, not on the actual feature extraction. In this paper, we propose PVCNN that represents the 3D input data in points to reduce the memory consumption, while performing the convolutions in voxels to largely reduce the irregular data access and improve the locality. Our PVCNN model is both memory and computation efficient. Evaluated on semantic and part segmentation datasets, it achieves much higher accuracy than the voxel based baseline with 10x GPU memory reduction; it also outperforms the state of the art point based models with 7x measured speedup on average. Remarkably, narrower version of PVCNN achieves 2x speedup over PointNet (an extremely efficient model) on part and scene segmentation benchmarks with much higher accuracy. We validate the general effectiveness of our PVCNN on 3D object detection: by replacing the primitives in Frustrum PointNet with PVConv, it outperforms Frustrum PointNet+ by 2.4% mAP on average with 1.5x measured speedup and GPU memory reduction.
Recycling of plastic waste into tiles with reduced flammability and improved tensile strength
Venue: Process Safety and Environmental Protection
Year: 2019

This paper is focused on finding effective alternative for disposal of waste plastic bags by designing tiles with better mechanical strength, reduced flammability level, resistant against strong acids and bases and organic solvents, so that tiles can be used for designing structures for paver tiles for societal usage. In recent years the plastic consumption has increased manifolds leading to accumulation of plastic waste in large amount. Waste plastic bags being non biodegradable and its extreme durability make its disposal process difficult. Plastic solid waste (PSW) present challenges and opportunities to the societies regardless of their technological advances and sustainability awareness. Traditional technologies for waste plastic disposal have failed to cope up with the increased generation of plastic waste. Also, the disposal of fly ash, waste by product generated by combustion of coal in thermal power plants, is a serious problem both in terms of land use and environmental pollution. In this study, waste plastic matrix reinforced with fly ash (FA) and a flame retardant at different loadings (wt 5, 10, 15, 20 using twin screw extruder were molded into composite tiles and their characteristics were evaluated. Effect of different filler loading on waste plastic matrix was investigated. Composite (LFTP3) having appropriate ratios of fly ash and flame retardant showed reduced flammability with linear burning rate of 4.36 mm/minute and improved tensile strength of 9.68 MPa. Morphological and structural properties of all the composites were also investigated along with their flammability, resistance to different acids and bases and organic solvents, water absorption and mechanical strength.
Economics of Climate Adaptation (ECA) Guidebook for Practitioners
Year: 2016

There is a growing consensus that climate change impacts should be considered in the development of adaptation strategies by decision makers at all levels. This requires identifying cost efficient adaptation measures, resulting from a structured risk management approach. The Economics of Climate Adaptation (ECA) approach offers a unique contribution, which combines risk assessment, adaptation measures and risk transfer. Its results allow a flexible identification of cost effective climate adaptation measures for a variety of projects and sectors. Recently, KfW decided to implement two pilot studies in Bangladesh and El Salvador using the ECA methodology. The main objectives were to support decision makers in developing their adaptation strategy and to develop a climate adaptation measures investment portfolio. Following the evaluation of these two pilot studies, the need to develop a document for practitioners has arisen. The ECA Guidebook aims at filling this gap while complementing the already existing ECA documentation and tools. This Guidebook is tailored for practitioners of developing projects, which promote resilience in developing countries. It aims also at 1) exploring whether ECA methodology is appropriate to the project's goals and 2) offering step by step guidance while using the ECA methodology.