nils-herrmann/clean_scirepeval huggingface dataset:
MoDuL: Deep Modal and Dual Landmark wise Gated Network for Facial Expression Recognition
Venue: 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020)
Year: 2020

Automatic facial expression recognition (FER) is a challenging computer vision problem that finds a number of applications in human computer interaction. Most recent FER approaches are deep learning based and involve the extraction of two types of features from face images: geometric features (e.g. distances between aligned facial landmarks) and appearance features extracted using convolutional neural networks applied on patches extracted around each landmark. In this paper, we explore the use of gating networks to learn an optimal combination of these two modalities (modal gate) Furthermore, we also design landmark wise gates to adaptively weight each landmark as well as the corresponding patch contribution. The proposed MoDuL architecture achieves state of the art results on several FER databases with negligible computational overhead.
Evaluation of the Larvicidal Potential of the Essential Oil Pogostemon cablin (Blanco) Benth in the Control of Aedes aegypti
Venue: Pharmaceuticals
Year: 2019

The objective of this work was to collect information on the chemical constituents that demonstrate the larvicidal activity against Aedes aegypti, as well as the antioxidant, microbiological, and cytotoxicity potential of the essential oil of Pogostemon cablin leaves. The chemical characterization was performed by gas chromatography coupled to mass spectrometer (GC MS) The larvicidal activity was performed according to the protocol of the World Health Organization. The antioxidant activity was evaluated through the sequestering capacity of 2,2 diphenyl 1 picryl hydrazine (DPPH) As for the microbiological evaluation, the microdilution technique was used, according to the protocol of the Clinical and Laboratory Standards Institute. The cytotoxic activity was evaluated against the larvae of Artemia salina. The species P. cablin presented the following compounds: Patchouli alcohol (33.25% Seyshellene (6.12% a bulnesene (4.11% Pogostol (6.33% and Norpatchoulenol (5.72% which was in synergy with the other substances may significantly potentiate the larvicidal action of the species with the LC50 of 28.43 mg*mL 1. There was no antioxidant activity, however, it presented antimicrobial activity against all bacteria tested with Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) of 62.5 mg*mL 1. The species demonstrated significant toxic action with LC50 of 24.25 mg*mL 1. Therefore, the P. cablin species showed significant larvicidal potential, antimicrobial activity, the absence of antioxidant action, and high toxicity.
Employees' work outcomes associated with the psychological contract within a service company
Year: 2008

During the last decade, dramatic changes have been experienced in workplaces because of technological growth, globalisation, ever increasing competitive markets, changing industrial relation laws and better management skills (Cappelli, 1999) Amidst this change, the biggest issue is for organisations to gain dedication from their employees. Maslach et al (2001) explains that the impact of the changing world of work is perhaps most evident in changes in the psychological contract. Employees are expected to give more in terms of time, effort, skills and flexibility, whereas they receive less in terms of lifetime employment and job security. In security companies, the employer obligations and employee obligations also went through a process of change. Crime has become a very serious concern in South Africa. In Gauteng, crime has increased with 69,2% (SAP Statistics, 2005) from 1994 to 2004. Because of crime, many independent security companies were formed to help prevent crime, working together with the South African Police Force. A lack of research exists regarding employees' work outcomes like job insecurity, organisational commitment and intention to quit associated with the psychological contract within a service company. The objectives of this study are to investigate the relationship between employer obligations, employee obligations, job insecurity, organisational commitment and intention to quit of employees (N=217) in a service (security) company. A cross sectional design was used. Constructs were measured by means of an employer obligations questionnaire, employee obligations questionnaire, job insecurity questionnaire, organisational commitment questionnaire and intention to quit questionnaire. The research method for each of the two articles consists of a brief literature review and an empirical study. Exploratory factor analysis, as well as Cronbach alpha coefficients are computed to access the reliability and validity of the different measurement instruments. Descriptive statistics are used to analyse data and Pearson product moment correlation coefficients, as well as regression analysis were used to examine the relationship between the constructs employed in this research. Significant differences are found between various biographical groups and the scores of the psychological contract (employer obligations scale and employee obligations scale) the job insecurity scale, the organisational commitment scale and the intention to quit scale. Conclusions are made, limitations of the current research are discussed and recommendations for future research are put forward.
The 2018 California Wildfires: Integration of Rapid DNA to Dramatically Accelerate Victim Identification+
Venue: Journal of forensic sciences
Year: 2020

In November 2018, Butte County, California, was decimated by the Camp Fire, the deadliest wildfire in state history. Over 150,000 acres were destroyed, and at its peak, the fire consumed eighty acres per minute. The speed and intensity of the oncoming flames killed scores of people, and weeks before the fire was contained, first responders began searching through the rubble of 18,804 residences and commercial buildings. As with most mass disasters, conventional identification modalities (e.g. fingerprints, odontology, hardware) were utilized to identify victims. The intensity and duration of the fire severely degraded most of the remains, and these approaches were useful in only 22 of 84 cases. In the past, the remaining cases would have been subjected to conventional DNA analysis, which may have required months to years. Instead, Rapid DNA technology was utilized (in a rented recreational vehicle outside the Sacramento morgue) in the victim identification effort. Sixty nine sets of remains were subjected to Rapid DNA Identification and, of these, 62 (89.9% generated short tandem repeat profiles that were subjected to familial searching; essentially all these profiles were produced within hours of sample receipt. Samples successfully utilized for DNA identification included blood, bone, liver, muscle, soft tissue of unknown origin, and brain. In tandem with processing of 255 family reference samples, 58 victims were identified. This work represents the first use of Rapid DNA Identification in a mass casualty event, and the results support the use of Rapid DNA as an integrated tool with conventional disaster victim identification modalities.
Revisiting Resource Management for Deep Learning Framework
Venue: Electronics
Year: 2019

The recent adoption of deep learning for diverse applications has required infrastructures to be scaled horizontally and hybrid configured vertically. As a result, efficient resource management for distributed deep learning (DDL) frameworks is becoming increasingly important. However, existing techniques for scaling DDL applications rely on general purpose resource managers originally designed for data intensive applications. In contrast, DDL applications present unique challenges for resource management as compared to traditional big data frameworks, such as a different master slave communication paradigm, deeper ML models that are more computationally and network bounded than I/O, the use of heterogeneous resources (e.g. GPUs, TPUs) and the variable memory requirement. In addition, most DDL frameworks require data scientists to manually configure the task placement and resource assignment to execute DDL models. In this paper, we present Dike, an automatic resource management framework that transparently makes scheduling decisions for placement and resource assignment to DDL workers and parameter servers, based on the unique characteristics of the DDL model (number and type of parameters and neural network layers) node heterogeneity (CPU/GPU ratios) and input dataset. We implemented Dike as a resource manager for DDL jobs in Tensorflow on top of Apache Mesos. We show that Dike significantly outperformed both manual and static assignment of resource offers to Tensorflow tasks, and achieved at least 95% of the optimal throughput for different DDL models such as ResNet and Inception.
Cross Country Comparisons of the Effects of Leverage, Intangible Assets, and Tax Havens on Corporate Income Taxes
Year: 2012

To our knowledge, this paper provides the most comprehensive analysis, to date, of the role of leverage, intangible assets, and tax havens in reducing firm level corporate income taxes. Using publicly available financial statement information for 3,926 public corporations from 62 countries from 2005 to 2009, we find evidence consistent with multinationals lowering their current income tax expense by issuing long term debt, relying disproportionately on intangibles in their production, and establishing subsidiaries in tax havens. We also find wide cross country variation in the use of debt and intangibles, but little variation in the use of tax havens. American multinationals appear to use debt more than other countries to lower their taxes. Besides enhancing our knowledge about international taxes, these findings should provide some empirical underpinning for ongoing policy debates about the taxation of multinationals.
An Improved Immune Genetic Algorithm and Its Application in Computer aided Landscape Design
Year: 2014

This paper proposes an improved immune genetic algorithm, and utilizes it in evaluating the results of com puter aided landscape design. After analyzing the related works and the flow chart of the standard immune genetic algo rithm, an improved immune genetic algorithm is designed. The main modifications of our proposed immune genetic algo rithm lie in the following aspects. 1) We modified the standard immune genetic algorithm using symbolic coding and full binary tree in the chromosomes to describe solutions. 2) The crossover operator with single point is used, and the cross point can be selected from the intermediate nodes and the root nodes. 3) The mutation operator is modified to avoid the dependence of mutation probability on the initial value. 4) The modified immune genetic algorithm not only can keep random global search ability, but also can avoid local premature convergence. Next, the landscape design evaluation re sults can be obtained by SVM, the parameters of which can be optimized by the proposed modified immune genetic algo rithm. Finally, experiments are conducted on three datasets using an index system which is including 17 indexes. Experi mental results demonstrate that the proposed scheme can effectively evaluate the quality of computer aided landscape de sign.
The Investigation of Consumers' Behavior Intention in Using Green Skincare Products: A Pro Environmental Behavior Model Approach
Year: 2018

Increasing environmental awareness among societies is motivating consumers to use green cosmetic products. Green skincare products are the fastest growing sector in the worldwide market compared with other green cosmetic products. However, compared with general cosmetic products, the market share of green cosmetic products in Indonesia is relatively low. The present research investigated consumers' purchasing intentions toward green skincare products in Indonesia using the pro environmental reasoned action (PERA) model. A total of 251 female consumers participated in this study. Structural equation modeling was conducted to reveal the relationships between the five factors in the PERA model. The results indicated that perceived authority support (PAS) has a positive effect on perceived environmental concern (PEC) PAS and PEC have positive effects on attitude (AT) and subjective norms (SN) and AT and SN have positive effects on behavioral intention (BI) to purchase green skincare products, with the key factor being attitude. The PERA model was able to describe 62.6% of the BI to purchase green skincare products. Green skincare companies are recommended to produce more green skincare products and market the products by involving public figures and emphasizing the green attributes. Furthermore, we recommend that green skincare companies produce quality and sustainable products using quality processes, and be involved in pro environmental activity to increase consumer attention to the green skincare products.
Applying Functional Equivalence in Translating Chinese Culture Specific Items into English
Year: 2009

Globalization brings in opportunities to China and challenges to the translators.A large quantity of "Chinese culture specific items" with distinct Chinese cultural features needs to be translated into English.We should take the relations of language,culture and translation into consideration since the translation of these items is influenced by many cultural factors.In this thesis,we introduce Eugene Nida's theory of "functional equivalence" in the translation of Chinese culture specific items into English,and provide detailed translation strategies and methods applied in translating such items.Then the translation will be more customary with the target readers and the idea of the source language can be more accurately and completely transmitted.
An energy efficient two stage hybrid flow shop scheduling problem in a glass production
Venue: Int. J. Prod. Res.
Year: 2020

Energy efficient scheduling is highly necessary for energy intensive industries, such as glass, mould or chemical production. Inspired by a real world glass ceramics production process, this paper investigates a bi criteria energy efficient two stage hybrid flow shop scheduling problem, in which parallel machines with eligibility are at stage 1 and a batch machine is at stage 2. The performance measures considered are makespan and total energy consumption. Time of use (TOU) electricity prices and different states of machines (working, idle and turnoff) are integrated. To tackle this problem, a mixed integer programming (MIP) is formulated, based on which an augmented e constraint (AUGMECON) method is adopted to obtain the exact Pareto front. A problem tailored constructive heuristic method with local search strategy, a bi objective tabu search algorithm and a bi objective ant colony optimisation algorithm are developed to deal with medium and large scale problems. Extensive computational experiments are conducted, and a real world case is solved. The results show effectiveness of the proposed methods, in particular the bi objective tabu search.
General theory of quantum fingerprinting network
Venue: Physical Review Research
Year: 2021

The purpose of fingerprinting is to compare long messages with low communication complexity. Compared with its classical version, the quantum fingerprinting can realize exponential reduction in communication complexity. Recently, the multi party quantum fingerprinting is studied on whether the messages from many parties are the same. However, sometimes it is not enough just to know whether these messages are the same, we usually need to know the relationship among them. We provide a general model of quantum fingerprinting network, defining the relationship function $f^R$ and giving the corresponding decision rules. In this work, we take the four party quantum fingerprinting protocol as an example for detailed analysis. We also choose the optimal parameters to minimize communication complexity in the case of asymmetric channels. Furthermore, we compare the multi party quantum fingerprinting with the protocol based on the two party quantum fingerprinting and find that the multi party protocol has obvious advantages, especially in terms of communication time. Finally, the method of encoding more than one bit on each coherent state is used to further improve the performance of the protocol.
[Remote sensing inversion of cultivated land fertility at county scale based on SWCI NDVI feature space]
Venue: Ying yong sheng tai xue bao The journal of applied ecology
Year: 2021

It is objective needs during utilization and management of regional cultivated land resource to use remote sensing to accurately and efficiently retrieve the status of cultivated land fertility at county level and realize the gradation of cultivated land rapidly. In this study, with Dongping County as a case, using Landsat TM satellite imagery and cultivated land fertility evaluation data, the moisture vegetation fertility index (MVFI) was constructed based on surface water capacity index (SWCI) and normalized difference vegetation index (NDVI) and then the optimal inversion model was optimized to obtain the best inversion model, which was further applied and verified at the county scale. The results showed that the correlation coefficient between MVFI and integrated fertility index (IFI) was 0.753, which could comprehensively reflect the growth of winter wheat, soil moisture and land fertility, and had clear biophysical significance. The best inversion model was the quadratic model, with high inversion accuracy. This model was suitable for the inversion of cultivated land fertility in the county. The spatial distribution and uniformity of the inversion results were similar to the results of soil fertility evaluation. The area differences between the high, medium and low grades were all less than 2.9% This study provided a remote sensing inversion method of cultivated land fertility based on the feature space theory, which could effectively improve the evaluation efficiency and prediction accuracy of cultivated land fertility at the county scale.
Relationships between various person environment fit types and employee withdrawal behavior: A longitudinal study
Year: 2011

This study investigated the relationships between various person environment fit types and employees' withdrawal attitudes and behaviors. I collected an initial survey data from 901 employees who had been with their organizations for 6 months at most and whose current organizations were their first employers. Of these respondents, only 297 responded to the second survey, 6 months after the first. The results showed person job, person supervisor, and person organization fits correlated significantly with turnover intention on the first survey. Logistic regression analyses showed only person organization fit correlated significantly with actual turnover at the time of Survey 2. I discuss implications and limitations of this study.
The student's choice based on consumer psychology: an analysis applied to higher education institutions of Brazil
Year: 2016

The purpose of this paper is to investigate the student's choice of a higher education institution (HEI) in Brazil, through the Consumer Cultural Influence Model (CCIM) that considers subjective aspects of consumer behavior involving human values, social axioms, judgment and meaning of product, and product attributes. Through a quantitative approach, participants were surveyed via Internet. They were Brazilian university students, from all geographic regions of Brazil, mostly attending the first year of higher education, and enrolled in either private or public HEI. The instrument was presented in Portuguese using four Likert type measurement scales (i.e. human values, social axioms, judgment and meaning, and HEI attributes) and social economic status questions. Findings reveal important results, consistent and complementary to the tools commonly used for understanding consumer behavior. They also support HEI can be clustered in three distinct categories in Brazil, and that students from each category make their HEI choice influenced by different aspects. For large HEI, student's choice showed to be related to subjective aspects. The students of this category give more importance for the social axiom of social complexity than students from other categories and, in a negative way, for the dimensions of reward for application (social axiom) and conformity (human value) For small HEI, CCIM explains 11.4 of choice related to subjective aspects. This study provides valuable information to the development of specific public policies to enhance student's enrollment in HEIs and accomplish the goals of Brazilian National Education Plan (PNE) 2014 2024. It also provides valuable managerial insights into HEI's choice and offers specific information to provide strategic positioning guides to college managers competing in Brazilian educational marketplace.
Study on robot coalition problem based on novel quantum inspired ant colony algorithm
Year: 2012

Robot coalition problem is a complicated combinatorial optimization problem. In this paper, a novel quantum ant colony algorithm for the problem is proposed, where the thought of quantum evolution algorithm is combined with ant colony algorithm. In this algorithm, the pheromone is encoded by quantum bits and a new pheromone representation is designed. To avoid the algorithm falling into local optimum, the strategy of quantum crossover is designed to improve the information structure of population. Simulation results show that the algorithm is more effective than quantum genetic algorithm and basic ant colony algorithm.
Revised definition/outline of the Kheis Terrane along the western margin of the Kaapvaal Craton and lithostratigraphy of the newly proposed Keis Supergroup
Venue: South African Journal of Geology
Year: 2019

The Kheis Province is situated between the Namaqua Natal Province and the western margin of the Kaapvaal Craton in the Northern Cape Province of South Africa. It has been described as a thin skinned fold and thrust belt formed between 1800 and 1700 Ma. The lithostratigraphic subdivision of the rock units comprising the Kheis Province has been a source of much controversy. From detailed study of aerial photography and satellite imagery, as well as field based studies, the outcrop patterns in the Kheis Province and Kaaien Terrane were reinterpreted and a new stratigraphic subdivision is outlined here. It is proposed that the structural Kaaien Terrane and Kheis Province should be combined into the Kheis Terrane and that the rocks occurring in the Kheis Terrane should be grouped together to form the new Keis supergroup, with the basal metaconglomerate of the Mapedi/Gamagara Formation recognised as the regional unconformity between the Keis supergroup and the underlying rocks of the Transvaal Supergroup in the Griqualand West area. The Keis supergroup is subdivided from the base upwards into the Elim Olifantshoek Groblershoop and Wilgenhoutsdrif groups. The basal Elim group is composed of the Mapedi/Gamagara and Lucknow formations. It is overlain with a regional erosional unconformity by the Olifantshoek group, which is made up of the Neylan Hartley Volop and Top Dog formations. The Olifantshoek group is conformably overlain by the Groblershoop group which is comprised of three upward coarsening successions:the Faanshoek and Faansgeluk formations,the Maraisdraai and Vuilnek formations andthe Opwag and Skurweberg formations. The Groblershoop group is in turn erosively overlain by the rocks of the Wilgenhoutsdrif Group, which include the basal erosive Groot Drink formation which is overlain by the Zonderhuis and Leerkrans formations. The lithologies of the Keis supergroup are in faulted contact with the rocks of the younger Areachap Group of the ~1200 Ma Namaqua Natal Metamorphic Province.