nils-herrmann/clean_scirepeval huggingface dataset:
New measures for assessing model equilibrium and prediction mismatch in species distribution models
Year: 2013

Models based on species distributions are widely used and serve important purposes in ecology, biogeography and conservation. Their continuous predictions of environmental suitability are commonly converted into a binary classification of predicted (or potential) presences and absences, whose accuracy is then evaluated through a number of measures that have been the subject of recent reviews. We propose four additional measures that analyse observation prediction mismatch from a different angle namely, from the perspective of the predicted rather than the observed area and add to the existing toolset of model evaluation methods. We explain how these measures can complete the view provided by the existing measures, allowing further insights into distribution model predictions. We also describe how they can be particularly useful when using models to forecast the spread of diseases or of invasive species and to predict modifications in species' distributions under climate and land use change.
CONTROLADOR DE VELOCIDADE PARA MOTORES BRUSHLESS DC UTILIZADO EM VEICULOS ELETRICOS
Year: 2012

A utilizacao de veiculos eletricos tem se mostrado cada vez mais apropriada frente as atuais problematicas que circundam o uso eficiente da energia. Motores CC sao largamente empregados em veiculos eletricos, dentre eles os Motores CC sem escovas, denominados Motor Brushless DC se destacam devido ao elevado rendimento e reduzida manutencao, tornando se a melhor opcao para esta aplicacao. A principal caracteristica dos motores brushless e nao possuir comutador mecanico. A comutacao e feita atraves de um circuito eletronico conversor, o qual realiza o controle de velocidade de rotacao do motor.
Approach for minimising network effect of VNF migration
Venue: IET Commun.
Year: 2018

In the software defined network (SDN) environment, network function virtualisation enables the virtual machine migration. Owing to the fact that transferring large amount of data will impede competing workflows, virtual network function (VNF) migration has brought a new perspective. Many optimised algorithms focusing on limiting migration time and migration cost have been proposed. In this study, the authors address the problem from a different perspective. They view the network topology from a global perspective and focus on the network effect of the whole network caused by VNF migration in the context of SDN. They introduce a parameter delay to formulate the network effect and an effect model is proposed to evaluate the migration effect of the network. In addition, a heuristic algorithm is proposed to minimise network effect while balancing network load and improving the service considering the migration cost and resources limit at the same time. The practicability and efficiency of the proposed model and algorithm are validated by simulation evaluation. By comparing their proposed algorithm with traditional benchmarks and closely related benchmarks, the experimental results show that their proposed algorithm largely reduces the network effect, while at the same time limiting the run time.
Seamless Support of Low Latency Mobile Applications with NFV Enabled Mobile Edge Cloud
Venue: 2016 5th IEEE International Conference on Cloud Networking (Cloudnet)
Year: 2016

Emerging mobile multimedia applications, such as augmented reality, have stringent latency requirements and high computational cost. To address this, mobile edge cloud (MEC) has been proposed as an approach to bring resources closer to users. Recently, in contrast to conventional fixed cloud locations, the advent of network function virtualization (NFV) has, with some added cost due to the necessary decentralization, enhanced MEC with new flexibility in placing MEC services to any nodes capable of virtualizing their resources. In this work, we address the question on how to optimally place resources among NFV enabled nodes to support mobile multimedia applications with low latency requirement and when to adapt the current resource placements to address workload changes. We first show that the placement optimization problem is NP hard and propose an online dynamic resource allocation scheme that consists of an adaptive greedy heuristic algorithm and a detection mechanism to identify the time when the system will no longer be able to satisfy the applications' delay requirement. Our scheme takes into account the effect of current existing techniques (i.e. auto scaling and load balancing) We design and implement a realistic NFV enabled MEC simulated framework and show through extensive simulations that our proposal always manages to allocate sufficient resources on time to guarantee continuous satisfaction of the application latency requirements under changing workload while incurring up to 40% less cost in comparison to existing overprovisioning approaches.
KoalaPhone: touchscreen mobile phone UI for active seniors
Venue: Journal on Multimodal User Interfaces
Year: 2015

We deal with a problem of designing a user interface for touchscreen phones with respect to special needs of seniors. We conducted qualitative study \hbox {n}=5$$n=5) followed by quantitative one \hbox {n}=118$$n=118) From the comparison of our study with existing studies we observed an obvious trend in more extensive usage of advanced features, which cannot be explained only by the shift of the younger seniors to older age groups. We provided a set of recommendations and we designed a new touchscreen phone user interface to support needs of active seniors. In comparison \hbox {n}=15$$n=15) with standard Android UI our solution had higher completion rate in two of four complex tasks and 6$\times $x higher completion rate of all tasks while producing 2.4$\times $x fewer errors. Our interface was subjectively perceived more comfortable, efficient and producing less errors.
Autonomous Unmanned Aerial Vehicles in Search and Rescue Missions Using Real Time Cooperative Model Predictive Control
Venue: Sensors
Year: 2019

Unmanned Aerial Vehicles (UAVs) have recently been used in a wide variety of applications due to their versatility, reduced cost, rapid deployment, among other advantages. Search and Rescue (SAR) is one of the most prominent areas for the employment of UAVs in place of a manned mission, especially because of its limitations on the costs, human resources, and mental and perception of the human operators. In this work, a real time path planning solution using multiple cooperative UAVs for SAR missions is proposed. The technique of Particle Swarm Optimization is used to solve a Model Predictive Control (MPC) problem that aims to perform search in a given area of interest, following the directive of international standards of SAR. A coordinated turn kinematic model for level flight in the presence of wind is included in the MPC. The solution is fully implemented to be embedded in the UAV on board computer with DUNE, an on board navigation software. The performance is evaluated using Ardupilot's Software In The Loop with JSBSim flight dynamics model simulations. Results show that, when employing three UAVs, the group reaches 50% Probability of Success 2.35 times faster than when a single UAV is employed.
4K Real Time Software Solution of Scalable HEVC for Broadcast Video Application
Venue: IEEE Access
Year: 2019

Scalable high efficiency video coding (SHVC) is the scalable extension of the high efficiency video coding (HEVC) standard. SHVC enables spatial, quality, bit depth, color gamut, and codec scalability. The architecture of the SHVC encoder is based on multiple instances of the HEVC encoder where each instance encodes one video layer. This architecture offers several advantages of being modular and close to the native HEVC coding block scheme. However, the close loop SHVC architecture requires the complete decoding of the reference lower layer frames to decode a higher quality layer, which considerably increases the complexity of both encoder and decoder processes. In this paper, we propose an end to end 4K real time SHVC solution, including both software encoder and decoder, for video broadcast applications. The SHVC codec relies on low level optimizations for specific Intel <inline formula> <tex math notation="LaTeX"\times 86$ /tex math>/inline formula> platform and parallel processing to speed up the encoding and decoding processes. The proposed encoder enables real time processing of 4Kp30 video in <inline formula> <tex math notation="LaTeX"$2\times /tex math>/inline formula> spatial scalabilities on the <inline formula> <tex math notation="LaTeX"$4\times10$ /tex math>/inline formula> cores Intel Xeon processor (E5 4627V3) running at 2.6 GHz. In addition, the SHVC decoder enables to decode, respectively, the lower quality layer in full HD <inline formula> <tex math notation="LaTeX"$1920\times1080$ /tex math>/inline formula>p30) resolution, an advanced RISC machine (ARM) Neon mobile platform, and the enhancement layer in UHD <inline formula> <tex math notation="LaTeX"$3840\times2160$ /tex math>/inline formula>p30) on a fitted laptop, with 4 cores Intel i7 processor running at 2.7 GHz. Finally, experimental results have shown that the proposed solution can reach a high rate distortion performance close to the reference SHVC reference software model (SHM) with a speedup of 37 and 66 in intra and inter coding configurations.
Synthesis of Curcumin Analogues Monoketone from Cinnamaldehyde and their Inhibition Assay against Alpha Glucosidase Enzyme
Year: 2017

The synthesis of curcumin analogues monoketone as target compounds from cinnamaldehyde and inhibition assay against alpha glucosidase enzyme had been performed. The stepwise of synthesis was performed by aldol condensation Claisen Schmidt reaction andused ketones variation to give curcumin analogues monoketone. The antidiabetic activity of curcumin analogues was carried out by inhibition test against alpha glucosidase enzyme isolated from rotten rice (Oryza sativa) The first step of synthesis was started by reacting cinnamaldehyde and monoketones such as acetone (curcumin analog A (1E,3E,6E,8E) 1,9 diphenyl 1,3,6,8 nanotetraen 5 one] cyclopentanone (curcumin analog B (2E,5E) 2,5 bis (E) 3 phenylallylidene) cyclopentanone] and cyclohexanone (curcumin analog C (2E,6E) 2,6 bis (E) 3 phenylallylidene] cyclohexanone] in ethanol as solvent. The synthesis was carried out in base condition (KOH) by stirring at 52 degC for 50 minutes. The structures of all products were identified by using FTIR, direct inlet MS, 1H and 13C NMR. Futhermore, the activity of curcumin analogues was tested against with alpha glucosidase enzyme inhibition. The results show that the curcumin analogues (A C) were yielded in 85.57; 72.15; and 82.97% respectively as yellow solid. The melting point of curcuminanalogues (A C) were at 116.60 122.40; 196.20 200.10; and 142.30 148.10 degC, respectively. The inhibition of alpha glucosidase enzyme indicated that the curcumin analog B was potential to inhibit alpha glucosidase enzyme with the highest activity by giving inhibition percentage of about 70.71% at 2.5 mM.
Three Dimensional Structure and Low Level Features of the North Pacific Storm Track from 1999 to 2005
Year: 2009

A storm track is a region in which synoptic eddy activities are statistically most prevalent and intense. At daily weather charts, it roughly corresponds to the mean trajectories of cyclones and anticyclones. In this paper, the recent QuikSCAT (Quick Scatterometer) satellite sea winds data with a 0.5degx0.5deg horizontal resolution, and the NCEP (National Centers for Environmental Prediction) 10 m height Gaussian grid wind data and pressure level reanalysis data, are employed to document the spatial structure of the North Pacific storm track in winter (January) and summer (July) from 1999 to 2005. The results show that in winter the North Pacific storm track is stronger, and is located in lower latitudes with a distinct zonal distribution. In summer, it is weaker, and is located in higher latitudes. Based on the horizontal distributions of geopotential height variance at various levels, three dimensional schematic diagrams of the North Pacific storm track in winter and summer are extracted and presented. Analyses of the QuikSCAT wind data indicate that this dataset can depict the low level storm track features in detail. The double storm tracks over the Southern Oceans found by Nakamura and Shimpo are confirmed. More significantly, two new pairs of low level storm tracks over the North Pacific and the North Atlantic are identified by using this high resolution dataset. The pair over the North Pacific is focused in this paper, and is named as the "subtropical storm track" and the "subpolar storm track" respectively. Moreover, statistical analyses of cyclone and anticyclone trajectories in the winters of 1999 to 2005 reveal as well the existence of the low level double storm tracks over the North Pacific.
Bureaucracy and Service Delivery
Year: 2017

This essay reviews the literature on the politics of bureaucracy in the developing world, with a focus on service delivery and bureaucratic performance. This survey classic topics and themes such as the developmental state, principal agent relations, and the ancient Greece hypothesis, and link them to new research findings in political science, sociology, and economics. This review identify the concept of embeddedness as an important yet still under explored framework that cuts across disciplines and which may be used to understand bureaucratic performance and service delivery. Looking forward, the out line a framework for conceptualizing bureaucratic action by exploiting variation across time, space, task, and client, and identify promising areas for further research on the bureaucrat citizen encounter in developing countries.
Improved Gini Index Algorithm to Correct Feature Selection Bias in Text Classification
Venue: IEICE Trans. Inf. Syst.
Year: 2011

This paper presents an improved Gini Index algorithm to correct feature selection bias in text classification. Gini Index has been used as a split measure for choosing the most appropriate splitting attribute in decision tree. Recently, an improved Gini Index algorithm for feature selection, designed for text categorization and based on Gini Index theory, was introduced, and it has proved to be better than the other methods. However, we found that the Gini Index still shows a feature selection bias in text classification, specifically for unbalanced datasets having a huge number of features. The feature selection bias of the Gini Index in feature selection is shown in three ways: 1) the Gini values of low frequency features are low (on purity measure) overall, irrespective of the distribution of features among classes, 2) for high frequency features, the Gini values are always relatively high and 3) for specific features belonging to large classes, the Gini values are relatively lower than those belonging to small classes. Therefore, to correct that bias and improve feature selection in text classification using Gini Index, we propose an improved Gini Index (I GI) algorithm with three reformulated Gini Index expressions. In the present study, we used global dimensionality reduction (DR) and local DR to measure the goodness of features in feature selections. In experimental results for the I GI algorithm, we obtained unbiased feature values and eliminated many irrelevant general features while retaining many specific features. Furthermore, we could improve the overall classification performances when we used the local DR method. The total averages of the classification performance were increased by 19.4% 15.9% 3.3% 2.8% and 2.9% (kNN) in Micro F1, 14% 9.8% 9.2% 3.5% and 4.3% (SVM) in Micro F1, 20% 16.9% 2.8% 3.6% and 3.1% (kNN) in Macro F1, 16.3% 14% 7.1% 4.4% 6.3% (SVM) in Macro F1, compared with tf*idf, kh2, Information Gain, Odds Ratio and the existing Gini Index methods according to each classifier.
Hierarchical Reinforcement Learning with MAXQ Method
Year: 2009

Reinforcement learning is an important branch of machine learning.In the system of reinforcement learning,the learning stategies increase exponentially along with the number of state variables,which is called "dimensions disaster".Here a hierarchical reinforcement learning based on the MAXQ is proposed to solve this problem,which is realized by decomposing the task to different level,thus sub tasks in every level can be solved in relatively smaller scale.This method turns out to be effective to decrease the stategies.Finally,offer the concerned algorithm MAXQ RLA.
Agree or Disagree: Predicting Judgments on Nuanced Assertions
Venue: *SEMEVAL
Year: 2018

Being able to predict whether people agree or disagree with an assertion (i.e. an explicit, self contained statement) has several applications ranging from predicting how many people will like or dislike a social media post to classifying posts based on whether they are in accordance with a particular point of view. We formalize this as two NLP tasks: predicting judgments of (i) individuals and (ii) groups based on the text of the assertion and previous judgments. We evaluate a wide range of approaches on a crowdsourced data set containing over 100,000 judgments on over 2,000 assertions. We find that predicting individual judgments is a hard task with our best results only slightly exceeding a majority baseline, but that judgments of groups can be more reliably predicted using a Siamese neural network, which outperforms all other approaches by a wide margin.
Effect of severe shot peening on corrosion behavior of AZ31 and AZ91 magnesium alloys
Year: 2019

Severe shot peening (SP) was performed on the AZ31 and AZ91 Mg alloys to obtain a nanostructured surface layer. The microstructure, micro hardness and corrosion behavior of AZ31 and AZ91 Mg alloys after SP treatment were studied using transmission electron microscopy, micro hardness tester and corrosion tests, respectively. Results showed that SP treatment produced a plastic deformation layer with a Mg grains at the nanometer scale in the surface of AZ31 and AZ91 Mg alloys. After SP treatment, the micro hardness in the near surface region displayed an obvious increase for two alloys, owing to the combination of the grain refinement and the work hardening. The corrosion resistance of AZ31 alloy was improved by SP treatment, because a relatively compact passive film formed rapidly on the nanostructured surface. Unfortunately, SP treatment played a minor role in enhancing the corrosion resistance of AZ91 alloy, because it had little effect on size and distribution of b phases.
Soil Salinity: Effect on Vegetable Crop Growth. Management Practices to Prevent and Mitigate Soil Salinization
Year: 2017

Salinity is a major problem affecting crop production all over the world: 20% of cultivated land in the world, and 33% of irrigated land, are salt affected and degraded. This process can be accentuated by climate change, excessive use of groundwater (mainly if close to the sea) increasing use of low quality water in irrigation, and massive introduction of irrigation associated with intensive farming. Excessive soil salinity reduces the productivity of many agricultural crops, including most vegetables, which are particularly sensitive throughout the ontogeny of the plant. The salinity threshold (ECt) of the majority of vegetable crops is low (ranging from 1 to 2.5 dS m 1 in saturated soil extracts) and vegetable salt tolerance decreases when saline water is used for irrigation. The objective of this review is to discuss the effects of salinity on vegetable growth and how management practices (irrigation, drainage, and fertilization) can prevent soil and water salinization and mitigate the adverse effects of salinity.
Fintech and Banks Collaboration: Does it Influence Efficiency in the Banking Sector?
Year: 2019

The efficiency of the banking sector in Sub Saharan Africa is low compared to rest of the world and Fintech is taunted to alter this scenario. Efficient banks increase financial stability, intermediation and value to the shareholders. As Fintech innovations continue to alter the landscape in the banking sector, banks in Kenya are forming collaborations that are envisioned to shape the evolution of credit allocation and delivery of services. The study investigates the influence of Fintech on a bank's efficiency in credit allocation using the data envelopment model with input orientation based on the intermediation dimension. Efficiency scores are decomposed as technical efficiency, pure technical efficiency and scale efficiency. Secondary data for the period 2009 2018 is extracted from thirteen banks sampled from the top fifteen banks in Kenya based on their market share. The banks are either locally owned or listed in Nairobi Securities Exchange, of which five have Fintech collaborations with a Pre Fintech and Post Fintech period. Panel regression model tested the effect of financial ratios on technical efficiency of the banks. Fintech collaborating banks are more technically efficient based on models M1, M2 and M3 in Pre Fintech. In Post Fintech, the Fintech banks are more efficient based on models M2, M3 and M4 but with decreasing returns to scale which is due to the banks being overly large, thus nonoptimal in their operations. The positive effect on technical efficiency is observed from the ratios, liquidity, loan intensity, return on assets and cost of income. Cost of intermediation and credit risk had a negative effect on technical efficiency. Therefore, Fintech and banks collaborations did not significantly influence efficiency in the banking sector.
A Conceptual Framework of Community Participation and Entrepreneurial Success towards the Homestay Business in Sabah, Malaysia
Year: 2019

This conceptual paper is to examine the relationships between community participation and entrepreneurial success in homestay business. The study will be conducted in Sabah, Malaysia. The main problem that the homestay entrepreneurs faced is to sustain their homestay business due to lack of visitors. This study applies quantitative approach to collect data by using purposive sampling in selecting the respondents. It examines the influence of community participation towards entrepreneurial success in the homestay business. The study uses Partial Least Squares (PLS) method to analyze the data. In addition, this study used social exchange theory (SET) to illustrate the relationship of community participation and entrepreneurial success. The findings of the study will be useful in providing the guiding principle and information for the academic, government, tourist association as well as related agencies in order to enhance Malaysian tourism industry. The novelty of the study will offer a guideline for future research, designing the most effective programme for homestay entrepreneurs, and provide empirical result for future research.
The Relationship between Adverse Childhood Experiences (ACE) and Juvenile Offending Trajectories in a Juvenile Offender Sample
Year: 2015

Adverse childhood experiences have been identified as a key risk factor for offending and victimization, respectively. At the same time, the extent to which such experiences distinguish between unique groups of offenders who vary in their longitudinal offending patterns remains an open question, one that is pertinent to both theoretical and policy related issues. This study examines the relationship between adverse childhood experiences for distinguishing offending patterns through late adolescence in a large sample of adjudicated juvenile offenders.